Stratified Medicine : a New Challenge for Academia, Industry, Regulators and Patients [1 ed.] 9781780843186, 9781780843209

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Stratified Medicine A New Challenge for Academia, Industry, Regulators and Patients Thomas Bieber University of Bonn, Germany

Published by Future Medicine Ltd Future Medicine Ltd, Unitec House, 2 Albert Place, London N3 1QB, UK www.futuremedicine.com ISSN: 2047-332X ISBN: 978-1-78084-320-9 (print) ISBN: 978-1-78084-319-3 (epub) ISBN: 978-1-78084-318-6 (pdf) © 2013 Future Medicine Ltd All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without prior written permission of the copyright holder. British Library Cataloguing-in-Publication Data. A catalogue record for this book is available from the British Library. Although the author and publisher have made every effort to ensure accuracy of published drug doses and other medical information, they take no responsibility for errors, omissions, or for any outcomes related to the book contents and take no responsibility for the use of any products described within the book. No claims or endorsements are made for any marketed drug or putative therapeutic agent under clinical investigation. Any product mentioned in the book should be used in accordance with the prescribing information prepared by the manufacturers, and ultimate responsibility rests with the prescribing physician. Content Development Editor: Duc Hong Le Senior Manager, Production & Design: Karen Rowland Head of Production: Philip Chapman Managing Production Editor: Harriet Penny Production Editor: Georgia Patey Assistant Production Editors: Samantha Whitham, Abigail Baxter & Kirsty Brown Editorial Assistant: Ben Kempson Graphics & Design Manager: Hannah Morton

Contents Stratified medicine: a new challenge for academia, industry, regulators and patients Stratified medicine: a new era in the therapeutic approach Challenges for academic medicine and clinicians Challenges for diagnostics industry Challenges for the pharmaceutical industry Separate or codevelopment of biomarker and drug: the scenarios Challenges for the regulatory agencies in establishing an environment favorable for stratified medicine Challenges for the patients facing stratified medicine & personal genomics Conclusions & outlook to the future health system Stratified medicine: a challenging social experiment Index

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About the Author Thomas Bieber Thomas Bieber is Professor and Chairman at the Department of Dermatology and Allergy at the University of Bonn (Germany). He was also educated in drug regulatory affairs (master’s degree) and has special expertise in preclinical and clinical aspects of drug development. Besides clinical dermatology and allergy, his scientific focus is in the ontogeny and immunobiology of dendritic cells, their role in atopic dermatitis and in tolerance mechanisms. He has been the recipient of many awards and is a member of the German National Academy of Sciences (Leopoldina, Germany). He is author and coauthor of more than 450 papers and book chapters and is currently Chief Editor of Allergy, the official journal of the European Academy of Allergy and Clinical Immunology.

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Foreword Stratified medicine: a new challenge for academia, industry, regulators and patients Thomas Bieber “If it were not for the great variability among individuals, medicine might have well been a science and not an art.” – Sir William Osler (1849–1919), father of modern medicine Progress in prevention, diagnostic and treatment of diseases has always been dependent on a dynamic framework of our understanding of mechanisms of diseases, the ability to translate this knowledge into pharmacology and finally to evaluate the clinical outcome of therapeutic approaches. With this regard, stratified medicine (SM) is less a revolution and rather an evolution. There has not been a sudden step in our approach to diagnosing and treating diseases. Instead, SM represents the logic and expected outcome of substantial scientific progress heralded by the complete sequencing of the human genome in 2001 [1,2]. However, more than 10 years after this genetic breakthrough, which promised to revolutionize modern medicine, expectations are still far from being fulfilled. The progress made in our understanding of the genetic code as well as its regulation by epigenetic and epistatic mechanisms has added some further levels of complexity when compared with the genome published initially by C Venter and the Human Genome Project Consortium [1]. Directly or indirectly related to our increasing knowledge in genomics, modern biomedical research has also observed the further development of our understanding in protein synthesis and its regulation, as well as many aspects doi:10.2217/EBO.12.308

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Bieber of cellular biology, such as cell cycle or perturbed receptor signaling ultimately leading to cancer and other life-threatening diseases. This subtle and highly complex architecture of more or less disease-specific pathways steadily provides new targets for (at least theoretically) more efficient and tailored pharmacological approaches. Based on these new developments, provided in large parts by academic research, the pharmaceutical industry is currently challenged by two main topics: switching strategically from the paradigm of the so-called ‘one-size-fits-all’ products and other blockbuster business models to the more ‘niche buster’ paradigm aimed to treat selected patients with a given disease but with overall more efficacy and safety; and defining new strategies in a regulatory framework that is not adapted to the rapid development of SM-related products. The notion of disease-modifying treatment has emerged as a new paradigm in the context of chronic and progressing diseases as well. A major critical step for the industry and the regulators in this stratified approach will be the identification and validation of biomarkers as companion diagnostics, which will ultimately enable the clinician to select ‘the right patient at the right time’. Therefore, the ultimate goal of SM is to develop the ‘magic bullet’: to link drug response with genetics and/or a biological profile and to provide a safe and efficacious drug for a distinct patient population. These developments have to be established and supported in a given favorable and ideally globally harmonized regulatory environment. Finally, besides these issues related to drug development stricto sensu, the increasing availability of more or less validated personal genomic profiles will also deeply impact on the behavior, privacy and decisions of patients as well as their protection. This book does not aim to represent a comprehensive analysis of all aspects and challenges for all stakeholders involved in SM (Figure 1). Instead, it is aiming to highlight some of the key challenges for academia, industry, regulators and patients emerging in this highly dynamic field. As a caveat, it should be acknowledged that with regard to the rapid evolution in this complex area of biomedical and regulatory research, some of these aspects mentioned and discussed herein may be considered under new light in the near future. Financial & competing interests disclosure The author has no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in these manuscripts. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties. No writing assistance was utilized in the production of these manuscripts.

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Stratified medicine: academia, industry, regulators & patients Figure 1. Stakeholders involved and their interactions in the development of stratified medicine.

Pharmaceutical industry

Policy makers

Health technology assessment

Diagnostics industry

Bioinformatics

Stratified medicine

Regulators

Patients

Academia

Biobanks

Ethics

In the pink circles are the stakeholders considered in this book.

References 1

Venter JC, Adams MD, Myers EW et al. The sequence of the human genome. Science 291(5507), 1304–51 (2001).

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Lander ES, Linton LM, Birren B et al. Initial sequencing and analysis of the human genome. Nature 409, 860–921 (2001).

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Chapter

1 Stratified medicine: a new era in the therapeutic approach

The wide spectrum of the therapeutic continuum 7 Definition: why stratified medicine?10 Current drugs approved for SM in Europe

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Thomas Bieber The wide spectrum of the therapeutic continuum A brief look at the history of the pathophysiologic understanding of diseases (Figure  1.1) shows the shift within the paradigms providing the basics for therapeutic approaches and reveals the tremendous contribution of biomedical sciences during the last century.

doi:10.2217/EBO.12.309

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Bieber Figure 1.1. Historical evolution of the concepts and approaches in human medicine. 19th century Cellular approach (Virchow) 0

-460

1900

1600

Antique–middle age The imbalance of the four humors (Hippocrates)

21st century Genomic approach

17–18th century Organ-related medicine (Bichat)

2000 20th century Biological approach

In the second part of the 20th century, progress in medical sciences such as the discovery and use of antibiotics and glucocorticosteroids were seminal in changing the prognosis of many diseases from a lethal to a more chronic disorder. The basis of today’s classical evidence-based medicine is the statistically significant efficacy of a given drug or therapeutic approach in a large patient population. This approach represents the background for the ‘one size fits all’ paradigm, as well as the blockbuster business model for the pharmaceutical industry, the regulatory bodies providing the regulatory framework in which the development and marketing of such medicinal products are accomplished. However, the heterogeneity of diseases and therapeutic responses is best exemplified by following facts: n The overall therapeutic response is in average 50%. The highest efficacy is noticed for analgesics (80%), while only 30% is reached in oncologic diseases [1]; There is no efficient therapy available for approximately two out of three of all diseases;

n

Side effects are observed in 30–50% of drug applications;

n

Drug side effects account for up to 6% of hospitalization;

n

0.1–0.7% of drug side effects in hospitals have a lethal outcome;

n

This high variability in the drug response is due to two types of factors (Figure 1.2).

n

Thus, the heterogeneity of disease clinical phenotype (the phenome) and therapeutic response (besides the issue of compliance) is not well understood and the current paradigm in disease definition and drug development is a kind of ‘try and error without hint’.

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Stratified medicine: a new era in the therapeutic approach Figure 1.2. Intrinsic and extrinsic factors contributing to variability in drug responses and side effects. Extrinsic Nutrition

Smoking Intinsic

Others

Genetics Age Gender Race

Diseases

Drugs

Alcohol Environment

Adapted with permission from Nature Publishing Group [12].

One way to improve patient care and to avoid some of the major errors in this strategy is to establish instruments for the physicians in order to help them with their diagnostic and therapeutic decisions such as medicine, based on guidelines and evidence, issued from a number of meta-analysis of studies. We are currently adhering to a plethora of such guidelines; however, they often do not take the biological heterogeneity of the diseases into consideration, as well as the resulting variation in therapeutic response or the individual risk of serious side effects. The most effective way to improve human health is to understand normal biology as a basis for understanding disease biology, which then becomes the basis for improving health [2]. Thus, modern technologies in biomedical sciences and advances in genomic medicine provide the new foundation for understanding disease heterogeneity and therapeutic response. Since the first sequence of the human genome in 2001, many insights have been gained in the huge variation within the genome, such as the significance of individual variants such as the single-nucleotide polymorphisms (SNPs) and the way these SNPs are transmitted within haplotypes [3]. It is assumed that approximately 50,000–200,000 SNPs from more than 10 million are

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Bieber disease related. Genome-wide association studies have started to link some phenotypes and these variants but a further level of complexity is dictated by epigenetic regulation mechanisms [4], which are currently under intense investigations since they may explain, how environmental factors (e.g., food or exposition to harmful agents) may affect the genomic expression level directly. As a further result of the progress in molecular medicine, gene expression profiles and other downstream products of genetic information can be measured in a variety of different fluids, organic and cellular compartments, leading to the fast expansion of potential biomarkers issued from immunologic, metabolic and other ways, the so-called ‘-omics’ [5]. An individual disease-specific profile can thus be generated, based on a multitude of -omics-derived information and biomarkers, which will ultimately lead to a further disease stratification associated with the development of new compounds targeting distinct opportunities and operating in these disorders. Due to the reduced costs for sequencing the genome of a given person, companies have now started to offer this service directly to individuals, the so-called ‘direct to consumer strategy’ of personal genomic profiling, potentially providing information about the personal risk to develop diseases and opening the door to a more preventive kind of medicine [6]. Thus, we currently assist to a historical transition, moving away from a ‘trial-and-error without hint’ model of care towards stratified ‘try-and-error with hint’ management based on a patient-specific molecular disease profile.

Definition: why stratified medicine? When looking at the literature with regard to this new development in medicine related to genomics and other aspects, a number of different terms are used and have more or less been considered as synonymous: personalized medicine, individualized medicine, tailored medicine, genomic medicine, stratified medicine (SM) and, more recently, precision medicine [7]. Personalized or individual medicine represents the extreme of the spectrum (Figure 1.3) when it comes to design a fully personalized approach. This is the case in oncology; for example, by using the patient’s own tumor cells as a source for a cancer vaccine approach [8]. Alternatively, the future vision of an individually tailored disease management based on an extended and almost complete knowledge (and validated interpretation) of the genomic, epigenomic and environmental background of a given individual may represent the ultimate form of truly personalized medicine. Since the future of medicine described herein is more related to the possibility to consider subgroups of patients with a given disease and to

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Stratified medicine: a new era in the therapeutic approach Figure 1.3. Spectrum of the current medicine.

Empirical medicine

Evidence-based medicine

Stratified medicine

Personalized medicine

Note that personalized medicine is the extreme, since it is based on the use of single and personal tissue probes for the design of an individual and tailored therapeutic approach.

offer them a more adjusted and safe therapeutic approach based on a stratification using biomarkers, the terms personalized or individual do not seem appropriate. This stratification is based on potentially different biomarkers issued from the whole spectrum of -omics, including extrinsically influenced markers such as nutrigenomics and not genomic information alone. Furthermore, since SM is not just about reading nucleotides, the term ‘genomic medicine’ seems inadequate. Therefore in this book, the term ‘stratified medicine’ will be used, since it best describes what is meant by the current concept where a few biomarkers are used either isolated or combined to stratify the population of patients and for identifying a subpopulation of individuals sharing the same profile. Conditions & potential for SM From a scientific rationale point of view, SM needs some key fields in order to be implemented efficiently: Heterogeneity of a given target disease

n

Identification and validation of biomarkers and their development as companion diagnostic

n

Stratification of patients population with the biomarker

n

Improved genotype–phenotype relationship with information of improved computational medicine

n

Provide evidence for a better benefit to risk ratio and efficiency

n

Besides the monogenic diseases, most of the diseases, even the most common ones, can be considered as genetically complex threats and for many of them a number of unmet needs have been defined with regard to their management.

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Bieber The potential of SM can be summarized as follows: n Identification of still healthy individuals with high risk to develop a given disease and the opportunity to act preventively Opportunity for early detection of a disease possibly even before the first symptoms appear (early intervention) and to control them effectively

n

Better and more precise diagnostic of disease and stratification according to ways for a more adapted therapy

n

Prognostic information

n

Improving the selection of new chemical entities in drug discovery

n

Rescue of ‘old drugs’ for better defined indications and avoid withdrawal of marketed drugs

n

Development of more targeted therapies with more efficacies and less side effects

n

Improving the selection of new chemical entities in drug discovery

n

Reducing the time, costs and failure rate of clinical trials for new therapies

n

Stage-adapted therapy decisions and improved treatment algorithms

n

Better monitoring during therapy and more options for alternatives by nonresponders

n

Opportunity for disease-modifying strategy

n

In some instances, SM has the potential to improve established therapies further. The hyperlipidemia, as well as the TNF-a antagonists, markets are examples for fields that might seem mature for stratification into multiple targeted therapies [9,10]. When all these aspects are considered, SM could be beneficial for: The industry: by discovering new fields of activities

n

The physician: by improving his management and increasing in the success

n

The patient: by receiving the best possible therapy

n

Thus, the ultimate goal for the SM is the shift from acute and reactive medicine to a more predictive and preventive medicine, defined as P4: predictive, preventive, personalized and participatory medicine [11]; the

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Stratified medicine: a new era in the therapeutic approach Table 1.1. Drugs currently approved in Europe and for which a test is either mandatory or recommended. Compound

Disease

Biomarker

Aim

Status†

Abacavir

HIV

HLA-B*5701

Avoid side effect

02/2008 EPAR

Source

Anastrazol

Breast carcinoma

Hormone receptor

Improve efficacy

06/1996 SmPC

Arsen trioxide

Leukemia

Promyelocytic Improve efficacy leukemia protein/ retinoic acid receptor

03/2002 EPAR

Azathioprine

Immuno­suppression TPMT Var.

Avoid side effect

Recom.‡

SmPC SmPC

Carbamazepine Epilepsia

HLA-B*1502

Avoid side effect

Recom.

Cetuximab

Colon carcinoma

KRAS-Gen

Improve efficacy

07/2008 EPAR

Dasatinib

Leukemia

Philadelphia chromosome

Improve efficacy

11/2006 EPAR

Erlotimib

Lung carcinoma

EGF receptor

Improve efficacy

08/2011 SmPC

Exemestan

Breast carcinoma

Estrogen receptor

Improve efficacy

12/1999 SmPC

Fulvestrant

Breast carcinoma

Estrogen receptor

Improve efficacy

03/1994 SmPC

Gefitinib

Lung carcinoma

EGF receptor

Improve efficacy

07/2009 SmPC

Imatinib

Leukemia

Philadelphia chromosome

Improve efficacy

11/2001 EPAR

Lapatinib

Breast carcinoma

HER2

Improve efficacy

06/2008 EPAR

Letrozol

Breast carcinoma

Hormone receptor

Improve efficacy

01/1997 SmPC

Maraviroc

HIV

C–C chemokine receptor type 5

Improve efficacy

09/2007 EPAR

Mercaptopurine Oncology

TPMT Var.

Avoid side effect

Recom.‡

Natalizumab

Multiple sclerosis

Anti-JCV antibody

Avoid side effect

06/2011 SmPC

Nilotinib

Leukemia

Philadelphia chromosome

Improve efficacy

11/2007 EPAR

Panitumumab

Colon carcinoma

KRAS-Gen

Improve efficacy

12/2007 EPAR

Tamoxifen

Breast carcinoma

Hormone receptor

Improve efficacy

Recom.‡

Toremifen

Breast and stomach Hormone receptor

Improve efficacy

02/1996 SmPC

Trastazumab

Breast and stomach HER2

Improve efficacy

08/2000 EPAR

Zelboraf

Melanoma

Improve efficacy

01/2012 SmPC

BRAF

‡

SmPC

NCI

The date of the last update of the document considered. This information is mandatory/obligatory. ‡ A recommendation that is not an obligation in contrast to the above note (†). EPAR: European Public Assessment Report; HER2: Human EGF receptor 2; HLA: Human leukocyte antigen; NCI: National Cancer Institute; Recom.: Recommendation; SmPC: Summary of Product Characteristics; TPMT Var.: Thiopurin-S-methyltransferase variant. From European Medicines Agency as to December 2012. †

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Bieber modern response to the current collective, paternalistic, nonpredictive and curative medicine.

Current drugs approved for SM in Europe As mentioned above, SM is an evolutionary process and there exists a number of drugs already, which have been developed and applied prospectively on the basis of stratification (e.g., trastuzumab or the serine/ threonine–kinase inhibitor vemurafenib, positive opinion by the Committee for Medicinal Products for Human use [101], the final EC decision pending in Europe) or inversely when the recommendation has been refined retrospectively (e.g., azathioprine) (Table 1.1). Although the progress in understanding mechanisms of diseases, particularly in oncology, has been so significant during the last decade, it does not yet mirror the number of submission dossiers for new medicinal products in the EMA and US FDA. Instead, it seems as the pipeline in successful drug development is rather drying up [102]. The reasons for this declining trend, particularly in Europe, are manifold but could particularly be due to the slow translational implementation of these discoveries and to the uncertainty experienced by companies due to the lack of guidance, which should be provided by the regulators.

References 1

2

3

4

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Spear BB, Heath-Chiozzi M, Huff J. Clinical application of pharmacogenetics. Trends Mol. Med. 7(5), 201–204 (2001).

5

Green ED, Guyer MS. Charting a course for genomic medicine from base pairs to bedside. Nature 470(7333), 204–213 (2011).

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Browning SR, Browning BL. Haplotype phasing: existing methods and new developments. Nat. Rev. Genet. 12(10), 703–714 (2011). Wong KM, Hudson TJ, McPherson JD. Unraveling the genetics of cancer: genome sequencing and beyond. Annu. Rev. Genomics Hum. Genet. 12, 407–430 (2011).

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Press, Washington DC, USA (2011).

Schneider MV, Orchard S. Omics technologies, data and bioinformatics principles. Methods Mol. Biol. 719(1), 3–30 (2011). Khoury MJ, McBride CM, Schully SD et al. The scientific foundation for personal genomics: recommendations from a National Institutes of Health/Centers for Disease Control and Prevention multidisciplinary workshop. Genet. Med. 11(8), 559–567 (2009).

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Lesterhuis WJ, Haanen JB, Punt CJ. Cancer immunotherapy: revisited. Nat. Rev. Drug Discov. 10(8), 591–600 (2011).

9

Trusheim MR, Berndt ER, Douglas FL. Stratified medicine: strategic and economic implications of combining drugs and clinical biomarkers. Nat. Rev. Drug Discov. 6(4), 287–293 (2007).

10 Lacana E, Amur S,

Committee on the Framework for Developing a New Taxonomy of Disease. Toward Precision Medicine: Building a Knowledge Network for Biomedical Research and a New Taxonomy of Disease. The National Academies

Mummanneni P, Zhao H, Frueh FW. The emerging role of pharmacogenomics in biologics. Clin. Pharmacol. Ther. 82(4), 466–471 (2007).

11 Bousquet J, Anto JM, Sterk PJ

et al. Systems medicine and integrated care to combat

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Stratified medicine: a new era in the therapeutic approach chronic noncommunicable diseases. Genome Med. 3(7), 43 (2011).

Websites 101 European Medicines Agency/

12 Huang SM, Temple R. Is this

the drug or dose for you? Impact and consideration of ethnic factors in global drug development, regulatory review, and clinical practice. Clin. Pharmacol. Ther. 84(3), 287–294 (2008).

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Committee for Medicinal Products for Human Use. Zelboraf, Summary of opinion (2011). www.ema.europa.eu/docs/ en_GB/document_library/ Summary_of_opinion_-_ Initial_authorisation/

human/002409/ WC500119363.pdf 102 Krishan M. New drug

approvals FDA/EMA in 2010: declining R&D productivity? Guild (KPG), Knol Publishing. http://knolgooglecom/k/ krishan-maggon/new-drugapprovals-fda-ema2010/3fy5eowy8suq3/129

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Chapter

2 Challenges for academic medicine and clinicians Thomas Bieber

Successful basic & translational research in a collaborative effort

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Redefining diseases: from a clinical to a molecular taxonomy

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Successful basic & translational research in a collaborative effort In many instances, academia-based research provides the initiation for translational development that potentially leads to the development of a new drug. Thus, academic medicine must establish and support research in genomic and stratified medicine as well as in systems biology. Although single researchers from academia may successfully exploit some discoveries to a certain degree in the context of a small spin-off company, modern stratified medicine will certainly benefit most from large international consortia aiming to gather information on a large scale. This is particularly the case for establishing comprehensive genomic catalogues including clinical phenotypic data. Novel high-throughput technologies that are more cost effective will allow the improvement of existing catalogues of genomic data by further genomewide association studies. The SNP Consortium with the International HapMap Project [101], as well as the 1000 Genomes Project [102], are examples of such initiatives, which are further implemented by the Encyclopedia of DNA (ENCODE) [103] and ModENCODE projects [104].

doi:10.2217/EBO.12.310

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Bieber This kind of approach in the field of oncology has been started in the European ‘P-medicine’ initiative [105] with the support of the European Community’s Seventh Framework Program. ‘P-medicine’ aims at developing new tools, information technology (IT), infrastructure and virtual public health models to accelerate stratified medicine (SM) for the benefit of the patient. Within the scope of this initiative, 19 partners from nine European countries and Japan have started to create and support new knowledge and innovative technologies to overcome current problems in clinical research and pave the way for more individualized therapy. Genomic information, including noncoding variants, is not sufficient to understand normal human biology and biology of diseases. They need to be complemented by further related catalogues with phenotypic data (phenome) and those generated from epigenomics, transcriptomics, proteomics, glycomics and the recently highlighted metabolomics [1]. To this end, biobanks, established from a large and representative population of normal and pathological tissues, will represent the source for future biomarkers. Biobanks and adapted IT are the key for further development of SM [2]. Two types of biobanks can be distinguished: the populationrelated and the disease-related biobanks. Some of them, such as the Integrated Biobank of Luxembourg [106] (started in 2007), may combine both purposes. Establishing a biobank represents substantial organizational and financial challenges since it will grow with time, requiring a versatile and efficient IT environment with the possibility of audit trails. Large and representative biobanks flanked by appropriate patients registries need a multinational coordination, as exemplified by the Biobanking and Biomolecular Resources Research Infrastructure [107]. They also require a solid legal and ethical basis. As mentioned above, efficient working in the context of newly established consortia will be the key for the success of SM. These consortia should include industry-based research efforts in a fair and efficient way. Genomics catalogs, biobanks and their computational support should be shared by academia and industry, possibly with substantial support from national and international authorities or foundations. Such models of public–private partnership could represent an important asset for successful translational research aiming to develop new compounds for the stratified approach. Most important, in contrast to the current ‘regional approaches’, such as those started in the USA and in Europe, a global vision of SM based on genomic information must include catalogues from all possible ethnic

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Challenges for academic medicine & clinicians groups. This is essential in order to evaluate and adapt the potential of new stratified therapeutic approaches on a large scale of different population groups, taking into consideration particular genomic variations. Although this approach sounds obvious, this ambitious project still has to be initiated and certainly needs substantial support from international authorities such as the WHO.

Redefining diseases: from a clinical to a molecular taxonomy In history, most diseases have been classified according to a distinct clinical phenotype. In many disciplines, such as dermatology, this phenotypic classification was inspired by the binomial nomenclature of the Swedish botanist, physician and zoologist Carl von Linné (1707–1778). Any kind of therapeutic approach was tightly related to the clinical (visual) definition of the disease (e.g., malignant melanoma), and the often substantial heterogeneity within a disease’s entity was acknowledged by a further level in the taxonomic definition of the disease (e.g., nodular malignant melanoma or acrolentiginous malignant melanoma). Progress in biomedical research steadily provides new insights into the mechanisms of many diseases. One of the most striking aspects remains the heterogeneity of relevant signal transduction pathways underlying tumors of a clinical phenotype corresponding to one single entity [3]. One of the first examples is the discovery of the overexpression of some hormone receptors, such as the human EGF receptor 2 in subgroups (30%) of breast cancers, which has led to the development of a stratified approach with more adapted compounds, as mentioned in Table 1.1 in Chapter 1. Another more recent example is the BRAF mutation considered as a so-called ‘driver gene’ in a subgroup of malignant melanoma belonging to distinct types [4]. Translational research has then ultimately led to new compounds interfering with this pathway, which is, however, only active in patients suffering from tumors that carry this particular mutation, but not in other patients. This is a typical and paradigmatic example of SM. Should physicians reconsider their way of classifying diseases and leave the overhauled clinical phenotype behind for a more endophenotypeoriented view and classification of diseases? Such a consideration may bear at least two important consequences: Heterogeneous diseases that were phenotypically well defined and classically grouped into one single entity will be redefined and will split, according to insights they give, into new relevant pathways and/or biomarkers. Although the therapeutic approach will be similar for many seemingly different diseases with the same relevant pathway (e.g., breast

n

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Bieber cancer, melanoma and lung cancer), this redefinition could be questioned by the incessant progress of disease biology, leading to perpetual redefinitions of many disorders; Some rather common diseases such as chronic inflammatory disorders of the skin (e.g., atopic dermatitis) could experience a profound stratification according to genomic progress and future biomarkers, ultimately leading to the differentiation of one or several distinct diseases within this entity (Figure 2.1).

n

It is therefore not excluded that the taxonomy of a number of diseases will be re-examined under a different light, when we will have a more detailed endophenotypic profile based on -omics of such complex disorders. This aspect gains substantial importance, when it comes to considering preventive and predictive medical approaches. Moreover, it will also deeply impact on the refinement of therapeutic guidelines (see section on ‘Redefining disease guidelines & standard of care’) and ultimately on the design of future clinical trials for SM products (see Chapter 4). Finally, this Figure 2.1. Consequences of disease stratification for the definition of a phenotype and the search for new standards of care. New treatment + secondary prevention

Primary prevention + conventional treatment

?

Variant X

?

?

Variant Z

‘Orphan drug’

?

Orphan disease?

?

BM A + B

?

?

BM D + E

?

Gene X

Gene Y

?

BM Ω

Endophenotype

Pathophysiological pathways

?

Gene Z

Molecular taxonomy

Clinical phenotype

Heterogenous disease

?

‘Personalized’ management

Gene Ω

Genotype/ epigenotype

BM: Biomarker.

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Challenges for academic medicine & clinicians will ultimately have a deep impact on the International Codification of Diseases, which would need a profound and fundamental refining procedure. Redefining disease guidelines & standard of care The current paradigm governing medical activities is the so-called evidencebased medicine and disease guidelines [5,6]. Guidelines are important because they: n Support inexperienced physicians Help for codification of processes

n

Increase the quality of patient care

n

Contribute to standards in therapeutic approaches

n

Improve economic aspects, avoiding unnecessary procedures During the last few years, there have been an increasing number of disease guidelines from many national and international societies. However, in essence, most of the guidelines are based on the knowledge accumulated from several trials aiming to test the value of a given procedure within an unselected and unstratified population of patients with a given diagnosis, a kind of ‘one-guideline-fits-all’ paradigm. In other words, the clinical heterogeneity of a given disease (and pathophysiology behind it) has mostly been neglected by the current guidelines; they try to press all of the diverging aspects of a complex disorder into a kind of bottleneck (Figure 2.2).

n

As a result of refinement of the definitions Figure 2.2. Consequences of disease of diseases on the basis of endophenotypic stratification for clinical guidelines. data, most of the guidelines currently Empirical medicine accepted are obsolete and have to be either rewritten or subjected to substantial differentiation. This will ultimately lead to a Guideline ‘widening of the bottle neck’ and further Evidence-based medicine multiplication of the guidelines. This (‘one fits for all’) represents a substantial burden for most of the societies at the origin of these papers. As SM is rapidly progressing, a significant Stratified medicine delay in updating these important documents for physicians is most likely, possibly impacting on the efficiency of the Guideline 1 Guideline 2 Guideline 3 health systems. Guideline 4

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Guideline 5

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Bieber When reconsidering the therapeutic options within the new guidelines for a given disease, physicians will have to redefine the standard of care/ comparator for each subgroup of patients. This will have profound consequences for the future design of clinical trials (see later) and also be of importance for health technology assessment agencies when it comes to evaluating the efficiency of a new medicinal product and to discussing the issue of superiority versus noninferiority compared with a newly defined standard of care/comparator. Changing medical education In European countries, there exists some degree of harmonization of the curriculum of medical studies. This may even be enforced if there is a consensus as to the reorganization of the medical curriculum according to the Bologna process [108]. Although the importance of genomic medicine has been recognized, none of the countries have included elements of SM/personalized medicine in their curricula so far [7]. With regard to the fast-growing development of SM, governments and medical schools should start initiatives aimed at educating the future generations of physicians to understand genomic and molecular medicine. They must be prepared for their task and role in a future health system that is strongly influenced by SM. Students should be aware of the wide spectrum of -omics and the diagnostic tools (biomarkers) with which they will explore their patients and provide them with evidence-based recommendations. They will be asked to develop new skills and be able to perform queries in complex software linked to phenotypic, endophenotypic and genomic catalogues. Facing a better informed patient, they must be able to handle complex and multidimensional information needed for a better support of their therapeutic decisions. Furthermore, with regard to the steadily growing amount of information available, appropriate postgraduate educational programs will be needed to keep physicians and healthcare professionals informed and capable of managing their patients according to the latest developments. As an example for the USA, the American Medical Association/ US FDA Practicing Physician Training in Pharmacogenomics [109] generated an eLearning platform for physicians, providing important information with regard to basics and new developments in the field of pharmacogenomics. For students, the American College of Clinical Pharmacology provides medical and graduate student training in pharmacogenomics [110]. The future generation of physicians will need more healthcare professionals with genomic and system biological competencies. Unfortunately, since the current curricula have not yet been revised with this regard, there is an urgent need for an updating procedure.

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Challenges for academic medicine & clinicians Changing the physician–patient relationship In the paternalistic model, based on the knowledge accumulated on the site of the physician, the patient has a rather passive attitude. The rapidly and steadily growing information flow provided by the internet has revolutionized this perception since most of the patients are much more educated about their disease, the new technologies, the risk assessment and the therapeutic alternatives compared with 20 years ago. Moreover, once the patients have their own genomic profile accessible, physicians will have lost the monopoly over the medical information and the paradigm of the physician–patient relationship will definitely change. Indeed, the physician will have to learn from his patients, possibly neglecting the family or personal history and will rather tend to approach the patient and his disease in a completely different way, leaving a great part of the decision to the patient himself. Therefore, four different models of the physician–patient relationship can be considered [111]: n The paternalistic model: the physician (who considers himself as the guardian of his patient) gives the patient only limited information and decides what is best for them The informative model: the patient is informed about all aspects of their disease by the physician and decides by themself how to proceed without being influenced by the physician

n

The interpretative model: similar to the informative model but the physician guides the patient to their decision

n

The balanced model: patient and physician take a common decision based on a suggestion provided by the latter, taking into account all of the available information

n

We will assist with a shift from the first model to the other alternatives, and the new generation of physicians will have to handle a large amount of heterogeneous information provided by computational systems before being able to provide balanced recommendations to their educated patients and relatives. With this regard, we may assist with a kind of mutation from the ‘old-fashioned kind of physician’ to a modern kind of ‘personal health consultant’.

References 1

Suhre K, Shin SY, Petersen AK et al. Human metabolic individuality in biomedical and pharmaceutical research. Nature 477(7362), 54–60 (2011).

2

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Riegman PH, Morente MM, Betsou F, de Blasio P, Geary P. Biobanking for better healthcare. Mol. Oncol. 2(3), 213–222 (2008).

3

Vander Heiden MG. Targeting cancer metabolism: a therapeutic window opens. Nat. Rev. Drug Discov. 10(9), 671–684 (2011).

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5

6

7

Hong S, Han SB. Overcoming metastatic melanoma with BRAF inhibitors. Arch. Pharm. Res. 34(5), 699–701 (2011). Freddi G, Roman-Pumar JL. Evidence-based medicine: what it can and cannot do. Ann. Ist. Super Sanita. 47(1), 22–25 (2011). Kumar D. The personalised medicine. A paradigm of evidence-based medicine. Ann. Ist. Super Sanita. 47(1), 31–40 (2011). Frueh FW, Gurwitz D. From pharmacogenetics to personalized medicine: a vital need for educating health professionals and the community. Pharmacogenomics 5(5), 571–579 (2004).

Websites 101 International HapMap

Project. About the HapMap. www.accp.com/stunet/

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prncorner.aspx#ctl00_ pnlPKPDPG_title

108 World Federation for Medical

Education. Statement on the Bolognia process and medical education. www.aic.lv/bolona/Bologna/ contrib/Statem_oth/WFMEAMEE.pdf

102 1000 Genomes. A Deep

Catalog of Human Genetic Variation. www.1000genomes.org

103 National Human Genome

Research Institute. The ENCODE Project: Encyclopedia of DNA Elements. www.genome.gov/encode

104 The National Human Genome

Research Institute Model Organism Encyclopedia of DNA Elements. www.modencode.org/ publications/about/index. shtml

105 P-Medicine.

http://p-medicine.eu

106 Integrated Biobank of

Luxembourg for Next Generation Healthcare. www.ibbl.lu

107 Biobanking and Biomolecular

Resources Research Infrastructure. www.bbmri.eu

109 American Medical

Association. Practising physician training in pharmacogenomics. http://ama.learn.com

110 American College of Clinical

Pharmacology. Medical and graduate student training in pharmacogenomics. www.accp1.org/~user/index. html

111 Klemperer D. How Physicians

and Patients Will Take Decisions. Concepts in Physician–Patients Communication. The Working Party on Public Health, Berlin, Germany, 5–47 (2003). http://bibliothek.wzb.eu/ pdf/2003/i03-302.pdf

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3 Challenges for diagnostics industry

The tools for stratification: biomarkers & endophenotypes25 Development process for biomarkers

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Validation of biomarkers 28 Biobanks: the issue with the tissue

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Qualification of biomarkers29 Biomarkers as surrogate end points for clinical trials: the Holy Grail? 30 Lack of harmonization of in vitro diagnostics: a major regulatory issue 31

Thomas Bieber The tools for stratification: biomarkers & endophenotypes One of the key foundations of stratified medicine lies in the use of validated biomarkers for the identification of the right patients for the right medicinal products. By definition, a biomarker is a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes or pharmaco­ logic responses to a therapeutic intervention. According to this definition, which was provided by the US NIH Biomarkers Definition Working Group [1], every character­ istic that has a kind of predictive value can be considered as a biomarker. Consequently, the spectrum of possible biomarkers is quite wide, including anatomical, histological, genomic, proteomic, microbiomic, pharmacogenomic, nutrigenomic, metabolites and imaging technologies such as MRI.

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Bieber Among the biomarkers, one has to distinguish between the core biomarkers, which are more related to the fundamental pathophysiological events, and the downstream biomarkers, which are more considered as secondary phenomena. With regard to the natural history of a disease (Figure 3.1 illustrates the example of a chronic disease), biomarkers can be classified at least into five main categories that can include overlapping fields: n Screening biomarker that enable one to predict the risk of emergence of a disease in a given individual at phase 0 Diagnostic biomarker that confirms the clinical phenotype/diagnosis

n

Prognostic biomarker that is related to the natural course of the disease

n

Severity biomarker

n

Predictive biomarker for the therapeutic response to a given drug

n

Endophenotypes are defined as measurable components unseen by the unaided eye along the pathway between disease and distal genotype [2]. The endophenotype represents the collection of all kinds of biomarkers between clinical phenotype and genotype. Ultimately, this individual biosignature, which could also include data obtained from their environmental life, will be steadily updated so that, in contrast to the current ‘snapshot situation’ related to a particular phase in given disease Figure 3.1. Cartography of the application of biomarkers in the natural history of a chronic disease. 4

4

4 4

3 2

Clinical threshold

5 1

Subclinical disease

Clinically apparent disease

Remission

Cure

1: Screening biomarker; 2: Diagnostic biomarker; 3: Prognostic biomarker; 4: Severity biomarker; and 5: Predictive biomarker for therapeutic response.

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Challenges for diagnostics industry condition, which again corresponds to the current field of companion diagnostics, a more prospective and continuous picture will emerge for future therapeutic and most importantly for preventive purposes. For practical purposes, we will mainly consider biomarkers that are related to genomics and endophenotype in the following parts of the book.

Development process for biomarkers Similarly to drugs, the identification and development of new biomarkers undergoes several steps, starting from discovery, through validation (including clinical utility) and finally leading to the qualification step by the regulatory authorities as a possible surrogate end point for clinical trials. This development needs to be aligned to that of the drug and represents a major challenge if the developments are running separately – that is, not in the ideal context of a codevelopment exercized within a single company or in close partnership with a diagnostic company (see Chapter 5). Discovery of biomarkers: the effervescent pipeline The discovery of a new biomarker is typically either intended, as with hypothesis-driven, or the byproduct (hypothesis-free) of a disease oriented basic research program in an academic or industrial setting. This is in contrast to the validation of biomarkers, which will classically be performed in the context of a defined development program established in an industrial setting such as a spin-off company or pharmaceutical industry. For genomic markers, the availability of next-generation sequencing [3] for genome-wide genetic marker development and genotyping will further foster the importance of genomics in the extending field of biomarkers. Biomarkers can be already known genomic, biological or clinical features, for which a correlation was found to a given clinical phenotype, or a particular biological behavior of a relevant process, such as a signaling pathway or a pharmacological response to a compound. The alternative strategy is a hypothesis-driven approach based on disease mechanistic modeling, where distinct key molecules are assumed to be representative for a relevant situation such as the prognostic of a disease or the drug–drug interaction. The use of a multiplex strategy such as the array technology will be helpful for the screening of potential biomarker candidates [4] and should further supply the effervescent pipeline of candidate biomarkers, which are still in an exploratory state. However, in order to apply any biomarker for qualification as a potential surrogate biomarker in drug development studies and for its inclusion in submission dossier (Marketing Authorization Application or New Drug Application), a thorough process of validation and qualification of a biomarker’s performance is mandatory.

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Bieber Validation of biomarkers Definition The process of validation aims to get a reliable biomarker assay and determines its suitability and performance attributes (specificity, sensitivity, robustness, uninvasiveness, accessibility and clinical utility) from the report of the workshop “Stratification biomarkers in personalised medicine” (Brussels, Belgium, 2010 [101]). A work in progress along the biomarkers target product profile The validation process needs to be iterative and context specific with regard to the intended use of the biomarker within the development process. Similar to drug development, a target product profile should be generated at an early stage of biomarker development in order to define its diagnostic value, its appropriateness for efficacy or safety, as well as its sensitivity and specificity. Validation represents a major hurdle that is still to be cleared for most of the biomarkers aimed to be considered as companion diagnostics or surrogate end points for clinical trials. Therefore, for an improved validation process, diagnostic industry should seek for extended public–private partnerships. As defined by the US FDA Guidance for Industry on Voluntary Genomic Data Submissions (2005) [102], a biomarker is valid if it is measured in an analytical test system with well-established performance characteristics and for which there is an established scientific framework or body of evidence that elucidates the physiologic, toxicologic, pharmacologic, or clinical significance of the test results. Therefore, from the definitions of valid and probably valid biomarkers in this guidance, the requirement of a widespread agreement in the medical or scientific community regarding the physiologic, toxicologic, pharmacologic or clinical significance of the results is the most crucial aspect and implies a series of multidisciplinary steps of statistically critical evaluation. While in 2005, the FDA provided a drug–diagnostic codevelopment concept paper including hints to feasibility tests, validation and clinical utility [103], the EMA provided a reflection paper on codevelopment of pharmacogenomic biomarkers and assays in the context of drug development [104] , which lacks details related to the validation of biomarkers. Therefore, with regard to the validation issue, companies engaged in the (co)development of biomarkers are still working with limited advice from the regulatory agencies, but the dialogue is ongoing and will hopefully lead to a concrete regulatory guidance helping to foster the work in progress [5].

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Challenges for diagnostics industry The recent draft guidance of the EMA reflection paper on methodological issues with pharmacogenomic biomarkers in relation to clinical development and patient selection [105] provides an important tool for the design of trials, including the evaluation of pharmacogenomics biomarkers, and is of significant value for the development of other biomarkers. It includes discussions about the design of trials for the prospective validation of biomarkers.

Biobanks: the issue with the tissue In any case, the validation and the qualification of a biomarker are highly dependent on an adequate amount of representative and good-quality samples provided by patients and healthy individuals as controls. Therefore, the availability of clinical and biological material from disease-related and other biobanks is currently recognized as the major bottleneck for the rapid and efficient identification of new biomarkers [6,7]. Moreover, the quality of the collected patient’s information (the clinical and biological phenotypes) is of critical importance for the subsequent statistical evaluation (sensitivity and specificity) of the clinical utility. The advent of high-throughput sequencing technologies applied to genomic material obtained from such biobanks bears a substantial potential for the discovery of new genomic markers. The situation of limited samples available is even more challenging with regard to biobanks related to rare diseases that are potentially classified as orphan diseases (Reg. 141/2000/EC) [106]. With this regard, unbiased samples collected by academia are of critical importance. Therefore, the collection of sufficient clinically relevant material of good quality in biobanks as well as their handling supported by efficient information technology for sharing information and tracing and other procedures, will only be practicable in the context of large cohorts collected within national or international consortia and involving academia, industry and patients or patient organizations.

Qualification of biomarkers Definition & procedure Qualification is a conclusion that means that, within the stated context of use, the results of assessment with a biomarker can be relied upon to adequately reflect on a biologic process, response or event and support the use of biomarker during drug or biotechnology development (report of the workshop “Stratification biomarkers in personalized medicine”[101]). Qualification of a biomarker refers to the extent of information needed to understand its clinical utility and relates to a specific intended use that informs a regulatory and/or medical decision. The process of qualification

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Bieber (‘fitness for use’) has been the focus of the regulators (Guide to applicants: qualification of novel methodologies for drug development [107]). The guideline aims to link the biomarker with biological and clinical end points, based upon mechanistic and statistical consistency.

Biomarkers as surrogate end points for clinical trials: the Holy Grail? Definition According to Temple: “a surrogate end point of a clinical trial is a laboratory measurement or a physical sign used as a substitute for a clinically meaningful end point that measures directly how a patient feels, functions or survives. Changes induced by a therapy on a surrogate end point are expected to reflect changes in a clinically meaningful end point” [8]. The validation of a biomarker as a surrogate end point for efficacy can potentially provide a seductive and interesting tool for the analysis of the outcome of clinical trials performed in diseases where clinical end points are difficult to appreciate or in the context of a disease-modifying strategy such as in Alzheimer disease, when it makes sense to attack the disease at an early, presymptomatic phase (P0 phase) [9]. Although the availability of a biomarker as a surrogate end point is very attractive, its validity is, however, questioned by the following aspects according to the International Conference on Harmonization guidance E9 (statistical principles for clinical trials [108]): first, it may not be a true end point; and, second, the proposed surrogate end point may not yield a quantitative measure of clinical benefit that can be weighed directly against adverse effects. In practice, the strength of the evidence for surrogacy depends upon: n The biological plausibility of the relationship The demonstration in epidemiological studies of the prognostic value of the surrogate for the clinical outcome

n

Evidence from clinical trials that treatment effects on the surrogate correspond to effects on the clinical outcome

n

Therefore, when validating a biomarker as a surrogate end point, one should be aware of the fact that there is no clear demarcation when a biomarker becomes validated, and the process of validation (which is a progressively increasing degree of certainty) is highly dependent on subjectivity. Among others, one possible approach could be the concept of using a surrogate threshold effect methodology [10] – that is, use a certain level of change in a biomarker that enables the conclusion of, for example, a 70–80%

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Challenges for diagnostics industry probability that it will translate into clinical benefit. Importantly, the validation as a surrogate end point must consider risk to benefit balance and needs a collaborative effort between industry, academia and regulators [101]. Large clinical trials are necessary to prove surrogacy but induce substantial costs. On the other hand, once available, a surrogate end point can minimize unnecessary drug exposure and, in the long term, can be cost saving and potentially useful for accelerated marketing authorization for certain drugs indicated in life-threatening diseases such as for conditional approval (according to Art. 14/7 of the Reg. EC 726/2004 [109]).

Lack of harmonization of in vitro diagnostics: a major regulatory issue The analytic validity of a new biomarker test is the prerequisite for its approval/registration according to the Dir. 98/79/EC on in vitro diagnostics [110]. In Germany, it is regulated by the Medizinproduktegesetz (Medical Devices Act). As for any other medical device, the potential risk of a biomarker test is evaluated and classified into two main product classes by the so-called conformity assessment procedure (Art. 9, Dir 98/79/EC [110]). The conformity assessment procedure is a condition sine qua none for obtaining the CE conformity marking and its marketing in the EU. So far, this procedure can be performed either by the manufacturer himself or by a third party, the so-called notified body, depending on the classification. In Europe, most of the new biomarkers do not belong to the tests mentioned on Annex II of the in vitro diagnostics so that the conformity assessment procedure can be done by the manufacturer himself, without any control by a third party. This is in contrast to the situation in the USA, where most of the genetic tests are classified in a higher risk class and a clinical validity must be provided before approval/registration of the test. While for biomarker tests of diagnostic and prognostic value (class II), the clinical validity can be provided retrospectively (e.g., on the basis of samples and data from biobanks), those biomarker tests involved in therapeutic decisions (class III) must be validated in the context of prospective clinical trials [10,11]. With regard to the potential harm that could be caused by biomarker tests for which the clinical validity has not been proven, the current regulatory situation in Europe needs to be further improved, and the question of the evaluation of the requirements in terms of clinical validity to provide for biomarker tests with a higher risk potential has to be addressed. Besides the aspect of technical quality, the issue of interpretation is another field that requires further clarification. This could be solved similarly to the new German law on genetic diagnostics, which requires that the interpretation is provided by a qualified physician, for example a geneticist [111].

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Bieber These discrepancies between the European and the North American situation represent a major problem in the context of global development of biomarker tests as companion diagnostics for new drugs in stratified medicine. It could be solved by implementing the guidance proposed by the Global Harmonization Task Force on a global regulatory model for in vitro diagnostics [112,113]. In particular, the smaller diagnostic companies will face substantial regulatory problems and have to get more expertise into the complex field of registration of in vitro diagnostics within a more global approach.

References 1

Group Biomarkers Definitions Working Group. Biomarkers and surrogate end points: preferred definitions and conceptual framework Clin. Pharmacol. Ther. 69(3), 89–95 (2001).

2

Gottesman II, Gould TD. The endophenotype concept in psychiatry: etymology and strategic intentions. Am. J. Psychiatry 160(4), 636–645 (2003).

7

3

Zhao J, Grant SF. Advances in whole genome sequencing technology. Curr. Pharm. Biotechnol. 12(2), 293–305 (2011).

8

4

Valentin MA, Ma S, Zhao A, Legay F, Avrameas A. Validation of immunoassay for protein biomarkers: bioanalytical study plan implementation to support preclinical and clinical studies. J. Pharm. Biomed. Anal. 55(5), 869–877 (2011).

5

Hinman LM, Carl KM, Spear BB et al. Development and regulatory strategies for drug and diagnostic codevelopment. Pharmacogenomics 11(12) 1669–1675 (2010).

6

Miossec P, Verweij CL, Klareskog L et al. Biomarkers

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and personalised medicine in rheumatoid arthritis: a proposal for interactions between academia, industry and regulatory bodies. Ann. Rheum. Dis. 70(10), 1713–1718 (2011).

9

Phillips KA, Van Bebber S, Issa AM. Diagnostics and biomarker development: priming the pipeline. Nat. Rev. Drug Discov. 5(6), 463–469 (2006). Temple RJ. A regulatory authority’s opinion about surrogate end points. In: Clinical Measurement in Drug Evaluation. Nimmo WS, Tucker GT (Eds). J Wiley, NY, USA (1995). Hampel H, Frank R, Broich K et al. Biomarkers for Alzheimer’s disease: academic, industry and regulatory perspectives. Nat. Rev. Drug Discov. 9(7), 560–574 (2010).

10 Burzykowski T, Buyse M.

Surrogate threshold effect: an alternative measure for meta-analytic surrogate end point validation. Pharm. Stat. 5(3), 173–186 (2006).

11 Gewin V. Crunch time for

multiple-gene tests. Nature 445(7126), 354–355 (2007).

12 Melzer D, Hogarth S,

Liddell K, Ling T, Sanderson S, Zimmern RL. Genetic tests for common diseases: new insights, old concerns. BMJ 336(7644), 590–593 (2008).

Websites 101 EMA. Report on the EMEA/

Committee for Medicinal Products for Human Use biomarkers workshop. www.ema.europa.eu/docs/ en_GB/document_library/ Report/2009/11/ WC500012540.pdf

102 US Department of Health and

Human Services/FDA. Guidance for industry. Pharmacogenomics submissions. www.fda.gov/downloads/ RegulatoryInformation/ Guidances/ucm126957.pdf

103 US Department of Health and

Human Services/FDA. Draft drug–diagnostic codevelopment concept paper. www.fda.gov/downloads/ drugs/scienceresearch/ researchareas/ pharmacogenetics/ ucm116689.pdf

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Challenges for diagnostics industry 104 EMA/Committee for

Medicinal Products for Human Use. Draft reflection paper on codevelopment of pharmacogenomic biomarkers and assays in the context of drug development. www.ema.europa.eu/docs/ en_GB/document_library/ Scientific_guideline/2010/07/ WC500094445.pdf

105 EMA. Draft reflection paper

on methodological issues with pharmacogenomic biomarkers in relation to clinical development and patient selection. www.ema.europa.eu/docs/ en_GB/document_library/ Scientific_guideline/2011/07/ WC500108672.pdf

106 Official Journal of European

Communities. Regulation (EC) No 141/2000 of the European Parliament and of the Council of 16 December 1999 on orphan medicinal products. http://ec.europa.eu/health/ files/eudralex/vol-1/ reg_2000_141/ reg_2000_141_en.pdf

107 EMA/Committee for

Medicinal Products for Human Use. Qualification of novel methodologies for drug development: guide to applicants. www.emea.europa.eu/docs/ en_GB/document_library/ Regulatory_and_ procedural_ guideline/2009/10/ WC500004201.pdf

108 European Medicines Agency.

ICH topic E 9 statistical principles for clinical trials (1998). www.emea.europa.eu/docs/ en_GB/document_library/ Scientific_ guideline/2009/09/ WC500002928.pdf

109 Official Journal of European

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Communities. Regulation (EC) no. 726/2004 of the European Parliament and of the Council of 31 March 2004. http://eur-lex.europa.eu/ LexUriServ/LexUriServ.do? uri=OJ:L:2004:136:0001:0001 :en:pdf

110 Official Journal of European

Communities. Directive 98/79/EC of the European Parliament and of the Council of 27 October 1998 on in vitro diagnostic medical devices. http://eur-lex.europa.eu/Lex UriServ/LexUriServ.do?uri= CELEX:31998L0079:en:HTML

111 Bundesministerium der Justiz.

Gesetz über genetische Untersuchungen bei Menschen (Gendiagnostikgesetz GenDG) (2009). www.gesetze-im-internet.de /bundesrecht/gendg/gesamt. pdf

112 Global Harmonization Task

Force. Principles of conformity assessment for in vitro diagnostic medical devices (2008). www.ghtf.org/documents /sg1/sg1final_n046.pdf

113 Global Harmonization Task

Force. Principles of in vitro diagnostic medical devices classification (2008). www.ghtf.org/documents/ sg1/sg1final_n045.pdf

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Chapter

4 Challenges for the pharmaceutical industry Thomas Bieber

Considerations to the economic challenges

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Development process

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Clinical development: redesigning the design of clinical trials

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Regulatory strategies: the fictive case of Utopica41

Considerations to the economic challenges Stratified medicine approaches will not emerge in diseases for which the current therapies are more or less uniformly efficacious and beneficial for a large population. By contrast, there is a substantial unmet medical need in oncology, autoimmune disorders (including arthritis) as well as in neurologic disorders. Thus, as shown by drugs in the field of oncology, such as trastuzumab and imatinib, although the target population is reduced in size, an efficacious and well-accepted but more expensive medicine witnesses the success of this new economic model of the ‘mini-blockbuster’ or ‘niche-buster’ for the pharmaceutical industry. The way to a clinically and economically successful drug is rather stony but recent analyses raise hope for the economical success of stratified medicine [1].

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Bieber The economic challenge at the beginning of a drug’s development is different when the industrial background is considered. While big pharmaceutical companies may afford to invest a significant amount of their budget in a new project, the situation is more difficult for spin-offs or small- and mid-size enterprises, which often experience the typical ‘valley of death’ phenomenon [2,101] between the promising discovery of a putative therapeutic target and the point of time at which investors are convinced of the strategy. Thus, small- or mid-sized enterprises should seek for collaboration with either medical research foundations or with established pharmaceutical companies in a fair partnership. According to Trusheim et al., three criteria must be satisfied for the development of a viable stratified medicine (SM) [3]: n Technical feasibility of identifying a patient subpopulation: this parameter is the key for the development of SM and has been discussed in Chapter 3; Attractive economics: on average, the pharmaceutical industry invests 15–20% of their revenue in research and development. It has been forecast that the complexity of clinical trials for SM will be more expensive than in the past. However, the use of a more targeted strategy by stratification and identification of responsive populations could accelerate the development procedure, for example, by reducing the number of clinical trials thereby reducing the costs and allowing a faster marketing authorization. The faster and wider adoption of the therapy would compensate for the investment in research and development. Moreover, if the new compound efficiently addresses an important unmet medical need and, therefore, represents a real progress, negotiations with the Health Technology Assessment Agency can potentially lead to a premium pricing;

n

A sustainable franchise: this could be achieved ideally, if the product is either the first on the market for this particular stratified indication or is able to displace competitors in this segment of the market, which could be reached by an increased adoption and compliance from patients. Similarly, since the targeted population is even smaller due to stratification, the product could acquire the status of an orphan drug by the Committee on Orphan Medical Products more easily and thereby a regulatory market protection according to regulation (EC) 141/2000 in Europe.

n

With regard to the global development strategy, the ‘one-fits-for-all’ model is further challenged by the significant genetic variation among populations worldwide. Thus, although it is expected that this will generate a new level of complexity and increasing costs, some pharmaceutical companies have started to invest into the development of drugs designed for Asian

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Challenges for the pharmaceutical industry countries, taking into account the genomic challenge but attracted by an enormous market in these developing countries [4]. However, there remains a degree of uncertainty with regard to the cost explosion related to the drug development in the recent past and the putative limited market for a given drug targeting a small subpopulation of patients.

Development process Preclinical development Safety and efficacy aspects are critical in the development of a new drug and the relevance of genetic variants has been recognized by the EMA and the US FDA in the past in providing guidance, such as the 1999 FDA Guidance to Industry on in vivo Drug Metabolism/Drug Interaction Studies [102], and the 2001 CHMP Note for Guidance on the Investigation of Bioavailability and Bioequivalence [103]. Since depending on the type of active compound, genetic polymorphisms may have a substantial impact on the metabolism of the drug, whether they are small molecular compounds or biologics [5], pharmacogenomics (PGx) should be an integral part and involved as early as possible in the development process, as with before Phase I, as it may be of importance for the outcome of the therapy response. This may exclude the scenario when PGx data are available late in the development process or even after approval. Crucial points to evaluate will be: n The impact and relative contribution of polymorphisms on the metabolism and the metabolites of the drug The impact on the transport

n

A physiologically based pharmacokinetic (PBPK) modeling for the guidance of the design of clinical trials

n

The frequency and the distribution of the relevant polymorphisms among different populations worldwide since this may be crucial for the strategic decision of global development

n

Acknowledging the primary importance of the issue for drug development, the EMA and FDA have prioritized the PGx issue in providing guidance and reflection papers for the industry (see later), which should stimulate the companies to have PGx data incorporated in the label already at the time of submission. Thereby, an early and active partnership between the diagnostics industry and drug companies should be implemented to reach this goal.

Clinical development: redesigning the design of clinical trials Since on one hand the overall increasing costs for clinical development belong to the most important budget position in the investment for a new

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Bieber drug and on the other hand, due to the selection by stratification, the targeted population expected to have the benefit for the medicinal product is expected to be reduced, the issue of the clinical development plan will be even more critical than in the past. Some of the most important points will be discussed below. Phase I As mentioned earlier, the design of Phase I studies is strongly dependent on whether the PK/pharmacodynamic (PD) of the investigational medicinal product/investigational new drug is influenced by genetic variants and whether PGx data are available at this time point. If PGx is of relevance, the frequency and distribution of the polymorphisms have to be taken into consideration for the design of the Phase I ‘first-in-man’ studies, the aim is to avoid safety issues due to genetic differences. Thus, the focus of the study should be PK/PD studies with either preliminary selection on a PGx-based stratification or unbiased recruitment with a retrospective analysis of the data based on PGx information. The exposure level should be appreciated in each genetic subpopulation, since this information is key to the decision of whether Phase II/III studies will be performed with different doses based on a stratification or whether an adjusted dose could be applied, taking into consideration the spectrum of polymorphisms. In any case, as already suggested in the EMA Reflection Paper on the use of Pharmacogenomics in the Pharmacokinetic Evaluation of Medicinal Products [104], the collection of samples in early Phase I studies for retrospective analysis becomes unavoidable, provided that the ethical issues have been solved. This would particularly make sense for the retrospective evaluation of rare polymorphisms or those not yet known at the time point of the study. Phase II/III in the traditional approach Phase II/III studies should answer following important questions and thereby confirm the initial hypothesis: n Is the drug effective in all or only a subpopulation of patients? Is the therapeutic response linked to a particular biomarker profile?

n

Can the dose be optimized according to the stratification?

n

Is the safety linked to a particular biomarker profile?

n

What is the informative or predictive value of the biomarker?

n

Obviously, the design of Phase II (and Phase III) clinical trials in a stratified approach aims to establish the proof of concept and to optimize the dose

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Challenges for the pharmaceutical industry selection for subsequent clinical studies, which is a more complex task compared with the traditional ‘one-fits-for-all’ approach. Lee et al. have proposed and discussed four distinct types of study design (Figure 4.1) [6]. This is in agreement with the Reflection Paper on Methodological Issues with Pharmacogenomic Biomarkers in Relation to Clinical Development and Patient Selection [105]. Interestingly, in the absence of a validated biomarker, the most frequent strategy currently used is the prospective–retrospective randomized clinical trial with a number of biomarkers evaluated after the study and trying to identify responders from non-responders. Such studies are cumbersome and costly since they require a large number of patients in order to allow sufficient power for the statistical analysis. They also imply the use of subgroup analysis, an issue recently discussed by the EMA [106]. The upcoming alternative: adaptive trial design With regard to the rapid accumulation of new knowledge in the field of biomarkers, it is not surprising that the traditional Phase II/III trials with their fixed and rigid protocols provide only (if any) limited flexibility. This hampers the implementation of new findings which could be of critical importance for an ongoing trial. Therefore, companies should consider altering their clinical development plans in some cases by introducing adaptive design tools to increase flexibility, and optimizing the use of accumulated knowledge could have an important role in achieving these goals [7]. The I-SPY study is a typical example of successful implementation of this approach in SM [8]. As defined by the FDA in the 2010 draft guidance [107], “an adaptive design clinical study is defined as a study that includes a prospectively planned opportunity for modification of one or more specified aspects of the study design and hypotheses based on analysis of data (usually interim data) from subjects in the study. Analyses of the accumulating study data are performed at prospectively planned time points within the study, can be performed in a fully blinded manner or in an unblinded manner, and can occur with or without formal statistical hypothesis testing”. Compared with the classical approach, “adaptive design may more efficiently provide the same information, increases the likelihood of success on the study objective, or yields improved understanding of the treatment’s effect (e.g., better estimates of the dose– response relationship or subgroup effects, which may also lead to more efficient subsequent studies)”. Adaptive trial design also includes those protocols addressing objectives normally achieved through separate Phase II and III trials, the so-called seamless adaptive Phase II/III design. Interestingly, the FDA is avoiding this wording as it considers the seamless design as a variant of adaptive design.

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Bieber Figure 4.1. The four main randomized clinical trial designs for the drug and biomarker development in stratified medicine. Population

A

Population

B

R

Conventional tests only

Biomarker test ± conventional tests

Biomarker positive

Biomarker negative

R Treatment

Control

Treatment

Outcomes

Control

Treated according to standard of care

Control

Outcomes

Outcomes Population

C

Treatment

Population

D

R Biomarker positive

Biomarker negative

Treatment

Control

Biomarker analysis R

Treatment

R

Control

Outcomes

Treatment

Control

Outcomes

Biomarker positive

Biomarker negative

Outcomes

Biomarker positive

Biomarker negative

Outcomes

(A) Classical randomized clinical trial (RCT); (B) targeted RCT; (C) nontargeted RCT (stratified by biomarker); and (D) biomarker analysis within existing RCT. For this kind of approach, the research hypotheses may be prespecified in the trial protocol (prior to study unblinding) or defined retrospectively.

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Challenges for the pharmaceutical industry It is well accepted that the costs for the clinical development of a new drug represent a substantial part of the overall R&D investment. Unfortunately, these costs can be increased when, for example, the initial hypothesis and/or the selection of the biomarker were inadequate. More recently, Beckmann et al. have suggested alternative ways to further improve the design of stratified randomized clinical trial with an emphasis on the efficiency aspect in the Phase II development [9].

Regulatory strategies: the fictive case of Utopica The pharmaceutical industry will face a number of regulatory issues while establishing a clinical development plan for an investigational medicinal product for SM. In order to illustrate this situation, the fictive case of the pharmaceutical company ‘Dermutopix’ that has developed a new chemical entity, referred to as ‘Utopica’ for the treatment of atopic dermatitis (AD), a common chronic inflammatory skin disease [10], is presented and some key questions will be briefly addressed in this context. Scientific rationale Recently, mutations of the gene encoding for filaggrin (FLG), an important component of the epidermal barrier, have been identified as underlying the most frequent monogenetic skin disorder, the ichthyosis vulgaris (OMIM: 146700) [11]. Loss-of-function variants of the same gene (FLG) have also been shown in patients affected by AD [12]. There is a great variety of reported variants among the different ethnic populations worldwide [13]. The investigational medicinal product is addressing this genetic defect by inducing mechanisms able to override the mutated sequences of FLG und thus to restore the impaired epidermal barrier function in patients with AD. The company will apply for a marketing authorization for Utopica as an orphan drug according to Reg. 141/2000 and Reg. 507/2006 with the indication ‘ichthyosis vulgaris’. However, it also has realized the potentially interesting market for using Utopica in the management of AD and the strategic aspects are exposed briefly below. What are the unmet medical needs in AD & for which patients could Utopica be of interest? AD is the most common chronic inflammatory skin disease (10% of children and 5% of adults are affected) and has a substantial socioeconomic burden [14]. Clinically, AD is divided in three severity states: mild, moderate and severe. While mild and moderate forms are the most frequent ones (85–90% of AD patients) and are controlled by classical topical treatment, including steroids and/or calcineurin inhibitors combined with a basic

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Bieber therapy, such as emollients, the more severe forms (10–15% of AD patients) remain therapeutically resistant. Severe forms also have the longest history with an early onset and are often associated with allergic asthma. None of the topical treatments are able to improve the disease substantially on a long-term basis and systemic cyclosporine A (CyA) is the only approved medicinal product for this indication but does not work in monotherapy. Moreover, the well known side effects of CyA are limiting its use in the long term. Is the stratification of AD a feasible approach for the identification of patients responding to Utopica? What would be the best biomarker & what could be the outcome in terms of target population? According to the aforementioned information, a stratification of AD patients based on the FLG genotype appears an important strategy since these patients would be those who could have a benefit of Utopica as this product is aimed to improve the FLG-related skin barrier function and sensitization processes. At a first glance, genotyping FLG would be the most obvious approach and assessing the known FLG variants could represent an ideal diagnostic and prognostic marker. Alternatively, the technology of Raman spectroscopy, which can detect the FLG metabolites in situ in the skin [15], has provided the possibility of assessing FLG variants in a more convenient and noninvasive manner. Thus the company considered to explore both opportunities of biomarkers for the detection of FLG variants in AD with severe forms of AD and made some first attempts to evaluate the proportion of patients which may benefit from this new product. FLG variants are found in approximately 30% of all AD patients but patients with severe AD represent a major subpopulation. These variants lead to a dramatic impairment of their skin barrier function promoting sensitization and other allergies, it was finally estimated that approximately 10% of all AD patients may represent an adequate target population for Utopica as they may combine the clinical phenotype of severe AD and the genotype of loss-of-function variants of FLG. Is it worth starting an in-house development & clinical validation program for the biomarker? While assessing FLG variants by Raman spectroscopy is a rather young technology on the one hand, it is only applicable in vivo and needs the presence of the patient. Moreover, the device is still cumbersome and must be used by an expert. In any case, this technology does not allow a retrospective and high-throughput assessment, such as a biochemical or genetic marker.

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Challenges for the pharmaceutical industry On the other hand, the FLG genotyping must rely on blood samples obtained from patients or from biobanks and can be performed in absence of the patients. With regard to the complexity of the issue and the lack of own expertise in genotyping, the company sealed a partnership with a company in the diagnostics industry for the development of the biomarker program. While the technical and analytical aspect of genotyping is not an issue, the diagnostics company has to rely on good quality DNA material flanked by high-quality clinical and biological phenotyping from a large population of AD and control individuals, a challenge that can only be mastered in collaboration with academia and patients organizations. To optimize the process, the diagnostics company contacted the FP-7funded Patient Partner project [108] and the recently started European Patient’s Academy on Therapeutic Innovation (EUPATI) for advice and help in this matter. Moreover, since the company is rather new on the market, it was decided to seek for regulatory advice with regard to the future steps for the development of the new companion diagnostic within different regulatory frameworks such as Europe, USA and later in Asian countries. The regulatory consultant advised the diagnostics and the pharmaceutical company to have either a briefing meeting [109] with the Pharmacogenomics working party (PGx WP) of the EMA [110] or alternatively to have a briefing meeting with the Innovation Task Force of the EMA [111]. What problems may be faced in the context of a global development of Utopica? Preclinical development of Utopica was based on in vitro experiments using epidermal cell cultures from AD patients from European countries which carried the typical R501X and 2282del4 variants. However, further genetic studies have shown a large number of other variants, which all may have functional consequences. Thus, it is not clear whether Utopica will be able to correct the skin barrier function if the responsible FLG variants are from a different genotype. This is of special importance since the company is aiming for a global development and AD patients in Asian countries such as China, South Korea and Japan, also carry FLG variants but of a different genotype. Furthermore, epidemiologic studies have shown that in China, the incidence of AD seems much lower than in Europe (in children 5% instead of 15% in Europe and USA/Canada). However, the disease seems underdiagnosed in this country due to cultural reasons.

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Bieber What could be the best approach for clinical trials of Utopica? Phase I

Since Utopica is a topical therapy, PK/PD issues are less critical than with a product applied systemically. Although, according to the current knowledge, FLG is almost only expressed in the skin, the question of absorption and possible safety issues must be addressed adequately in Phase I trials with AD patients suffering from a severe form and carrying the appropriate genotype. A Phase I approach including only healthy volunteers was excluded by the company for two reasons: healthy volunteers do not have an impaired skin barrier function and the measurements would not provide adequate information, and due to its molecular weight (800 Da), which is above the cut-off of penetration into normal skin (500 Da), Utopica will probably not penetrate the upper layer of the epidermal barrier. Phase II/III

Based on the figures mentioned above, the company realized that the recruitment of patients for the clinical trials would be more difficult than initially speculated. Thus for purposes of stratification and recruitment of appropriate patients in the clinical trials, the company was seeking for dermatological centers of excellence in Europe, the USA and Asian countries with strong expertise in AD and partnership with patients organizations. With regard to the Phase II and Phase III trials, since the diagnostic partner would not be able to complete the validation of the biomarker test, it was decided to prefer clinical trials with a nontargeted prospective–retrospective design (see ‘Phase II/III in the traditional approach’ section and Figure 4.1). Has Utopica the potential of a disease-modifying therapy? The regulatory definition of disease modification can be found in the guideline of the EMA for medical products for the treatment of Alzheimer disease and other dementias [112]: “For regulatory purposes a disease modifying effect will be considered when the pharmacologic treatment delays the underlying pathological or physiopathological disease processes and when this is accompanied by an improvement of clinical signs and symptoms of the dementing condition. Consequently a true disease modifying effect cannot be established conclusively based on clinical outcome data alone, such a clinical effect must be accompanied by strong supportive evidence from a biomarker program.” From this definition, we can extract three main aspects: the treatment acts directly on the pathophysiological process; there must be an obvious improvement of the clinical signs; and disease modification must be substantiated by various validated biomarkers tightly related to the pathophysiological progress of the disease.

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Challenges for the pharmaceutical industry In the case of AD, studies have shown that individuals carrying the FLG loss-of-function variants (i.e., 30% of all AD patients) have the highest risk to develop an early and severe form of AD and to become sensitized to environmental allergens. Thus, FLG variants seem to represent a risk factor for the so-called atopic march, as with AD patients developing allergic rhinitis and severe allergic asthma in the course of the disease. Therefore, during the clinical development of Utopica, the company also thought to include a series of studies aimed to demonstrate that an early intervention with the product could potentially hamper the emergence of sensitization in patients with early-onset AD. However, although the potential of this strategy would be significant and would represent a real breakthrough in the management of AD, as with a real disease-modifying strategy, the lack of available and validated markers witnessing the pathophysiologic process of the disease at that time point of the clinical development has hampered this promising approach. Indeed, due to the extended natural history of AD, large prospective epidemiological cohorts would be needed to identify and appreciate the value of such a biomarker. Should the company look for a conditional approval strategy? Fortunately, the company was able to demonstrate the safety and clinical efficacy of Utopica in the treatment of the severe form of AD but due to delays in the development program of the biomarker and other problems related to suboptimal recruitment of patients, Dermutopix was not able to complete more than two pivotal studies. Nevertheless, although the indication does not belong to the mandatory scope of the Reg. EC/726/2004, they decided to submit the marketing authorization application in a centralized procedure. However, with regard on one hand to the high unmet medical need and the severity of the disease in this particular subpopulation as defined by the biomarker but on the other hand the lack of comprehensive clinical data due to the limited number of clinical trials, the company decided to submit the dossier for conditional approval, according to Art. 14(7) of the Reg. EC/726/2004 and Art. 4 of the Reg. EC/507/2006. In the case of a conditional approval, which represents an interesting strategy for many of the new products developed for SM, the company has the obligation to deliver comprehensive data for Utopica following the marketing authorization. According to the new pharmacovigilance Reg. EC/1235/2010, amending Reg. EC/726/2004, the company has to include a detailed post-marketing risk management plan that will be of special value for products conditionally approved because of the limited amount of information provided in a premature application.

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Bieber References 1

2

3

4

5

9

Ballantyne C. In tough times, personalized medicine needs specific partners. Nat. Med. 14(12), 1294 (2008).

10 Bieber T. Atopic dermatitis.

Trusheim MR, Berndt ER, Douglas FL. Stratified medicine: strategic and economic implications of combining drugs and clinical biomarkers. Nat. Rev. Drug Discov. 6(4), 287–293 (2007). Hughes B. Evolving R&D for emerging markets. Nat. Rev. Drug Discov. 9, 417–420 (2010). Lacana E, Amur S, Mummanneni P, Zhao H, Frueh FW. The emerging role of pharmacogenomics in biologics. Clin. Pharmacol. Ther. 82(4), ~466–471 (2007).

6

Lee CK, Lord SJ, Coates AS, Simes RJ. Molecular biomarkers to individualise treatment: assessing the evidence. Med. J. Aust. 190(11), 631–636 (2009).

7

Orloff J, Douglas F, Pinheiro J et al. The future of drug development: advancing clinical trial design. Nat. Rev. Drug Discov. 8(12), 949–957 (2009).

8

Beckman RA, Clark J, Chen C. Integrating predictive biomarkers and classifiers into oncology clinical development programmes. Nat. Rev. Drug Discov. 10(10), 735–748 (2011).

Trusheim MR, Burgess B, Hu SX et al. Quantifying factors for the success of stratified medicine. Nat. Rev. Drug Discov. 10(11), 817–833 (2011).

Barker AD, Sigman CC, Kelloff GJ, Hylton NM, Berry DA, Esserman LJ. I-SPY 2: an adaptive breast cancer trial design in the setting of neoadjuvant chemotherapy. Clin. Pharmacol. Ther. 86(1), 97–100 (2009).

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N. Engl. J. Med. 358, 1483–1494 (2008).

101 Foundation EK. Assessing

risk and return: Personalized medicine development and new innovation paradigm (2008). kauffman.org/uploadedFiles/ HHS_White_Paper_1008.pdf

102 US FDA. In vivo drug

11 Smith FJ, Irvine AD, Terron-

metabolism/drug interaction studies: study design, data analysis, and recommendations for dosing and labeling (1999). www.fda.gov/downloads/ drugs/guidancecompliance regulatoryinformation/ guidances/ucm072119.pdf

Kwiatkowski A et al. Loss-offunction mutations in the gene encoding filaggrin cause ichthyosis vulgaris. Nat. Genet. 38(14), 337–342 (2006).

12 Palmer CN, Irvine AD,

Terron-Kwiatkowski A et al. Common loss-of-function variants of the epidermal barrier protein filaggrin are a major predisposing factor for atopic dermatitis. Nat. Genet. 38(4), 441–446 (2006).

103 CPMP/EWP/QWP/1401/98.

13 Irvine AD, McLean WH,

Leung DY. Filaggrin mutations associated with skin and allergic diseases. N. Engl. J. Med. 365(14), 1315–1327 (2011). 14 Bieber T, Leung DY, Ivancevich JC, Gamal YE. Atopic eczema and contact dermatitis. In: White Book of Allergy. Pawankar R, Canonica W, Holgate S, Lockey R (Eds). World Allergy Organization WI, USA 39–42 (2011). 15 O’Regan GM, Kemperman

Websites

PM, Sandilands A et al. Raman profiles of the stratum corneum define 3 filaggrin genotypedetermined atopic dermatitis endophenotypes. J. Allergy Clin. Immunol. 126(3), 574–580 (2010).

Note for guidance on the investigation of bioavailability and bioequivalence. www.emeaeuropa.eu/docs/ en_GB/document_library/ Scientific_ guideline/2009/09/ WC500003519.pdf

104 EMEA/128517/2006.

Reflection paper on the use of pharmacogenomics in the pharmacokinetic evaluation of medicinal products. www.emeaeuropa.eu/docs/ en_GB/document_library/ Scientific_guideline/2009/ 09/WC500003890.pdf

105 EMA/446337/2011.

Reflection paper on methodological issues associated with pharmacogenomic biomarkers in relation to clinical development and patient selection. www.emaeuropa.eu/docs/ en_GB/document_library/ Scientific_ guideline/2011/07/ WC500108672.pdf

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Challenges for the pharmaceutical industry 106 EMA/907825/2011. Report of

the first workshop on subgroup analysis. www.emaeuropa.eu/docs/ en_GB/document_library/ Press_release/2011/11/ WC500118013.pdf

109 EMEA/CHMP/

PGxWP/20227/2004. Guideline on pharmacogenetics briefing meetings. www.emaeuropa.eu/docs/ enGB/documentlibrary/ Scientificguideline/2009/09/ WC500003886.pdf

107 US FDA. Adaptive design

clinical trials for drugs and biologics. www.fda.gov/downloads/ Drugs/GuidanceCompliance RegulatoryInformation/ Guidances/UCM201790.pdf 108 Patientpartner. Identifying the needs of patients partnering in clinical research. www.patientpartnereurope.eu

110 EMA/CHMP/

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PGxWP/250429/2010. Work plan for the Pharmacogenomics Working Party 2011. www.emaeuropa.eu/docs/ en_GB/document_library/ Work_programme/2010/01/ WC500069713.pdf

111 EMA/ITF. Organisation of

briefing meetings. www.emaeuropa.eu/docs/ enGB/documentlibrary/ StandardOperatingProcedureSOP/2009/09/ WC500002943.pdf

112 CPMP/EWP/553/95.

Guideline on medicinal products for the treatment of Alzheimer’s disease and other dementia. www.emeaeuropa.eu/docs/ en_GB/document_library/ Scientific_ guideline/2009/09/ WC500003562.pdf

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Chapter

5 Separate or codevelopment of biomarker and drug: the scenarios

Two companies develop the drug & biomarkers separately or subsequently50 Two companies develop the drug & the related biomarkers separately but concomitantly

50

Two companies develop drug & biomarkers separately but concomitantly in partnership 

50

Thomas Bieber Since biomarker-based stratification represents the ground for the development of future medicinal products, the development of both diagnostics and drug must be aligned. The main current hurdle for this optimal codevelopment lies in the limited access to biosamples necessary for a prosper validation and qualification of biomarkers. The strategy followed by companies will depend on the situation and several scenarios can be envisaged, as briefly discussed.

Codevelopment in one company51

doi:10.2217/EBO.12.313

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Bieber Two companies develop the drug & biomarkers separately or subsequently This is the classical situation of the past when drugs, such as trastazumab, came on the market with therapeutic responses, limited to a population that has to be identified subsequently based on retrospective biomarker-based analyses. Besides the significant delay in adapting the approval labeling by the regulatory agencies (see Chapter 6 on regulators), the initial concern among the patients and the physicians about the efficacy of the drug, as well as the costs generated in the absence of identification of nonresponders (typical try and error strategy), can generate a substantial socioeconomic burden. Drugs with an interesting therapeutic potential in a limited subgroup of patients undergo the risk to lack marketing authorization and for that are not available for these patients. It is expected that this type of situation will remain quite limited in the future because of economic and regulatory hurdles, the scenarios mentioned below will become most likely. Two companies develop the drug & the related biomarkers separately but concomitantly It is assumed that this is currently the most frequent situation leading to the development of diagnostic platforms independent of the drug because there has not been any possible agreement between both stakeholders. For the diagnostic provided, this may imply a couple of opportunities, such as the wide and unrestricted use of the biomarker for the development of drugs in other companies, but also the threats related to the possible increasing costs and lack of early evaluation of the validity and utility of the biomarker in the context of an associated drug development, that is, the lack of or at least deferred qualification by the regulatory agencies. Similarly, the pharmaceutical company may have the chance to select the best available biomarker on the market but this implies a delayed and costly development of the product since it has to rely on a forehanded validated and possibly qualified biomarker for the clinical development. Two companies develop drug & biomarkers separately but concomitantly in partnership This model of an efficient collaboration aimed to maintain optimal adjustments between both projects, potentially leading to a joint approval of the drug and its companion diagnostic, may be the most likely with regard to the current increase in diagnostic companies offering high-end technologies to identify and validate biomarkers. Small- and mid-size drug companies usually cannot afford to provide this level of expertise and the joint venture model could be the most promising.

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Separate or codevelopment of biomarker & drug: the scenarios Codevelopment in one company Only larger pharmaceutical companies will have the required resources to codevelop both drug and biomarkers simultaneously; thereby, bridging the drug–diagnostic divide [1]. Interestingly, despite progress in understanding the mechanisms of diseases and in the translational discovery of new biomarker, the incorporation of stratified medicine strategy into the development of new drugs remains rather slow, partially due to the lack of software tools to analyze the numerous variables [2]. This aspect has been addressed by a consortium gathering researchers from the Massachusetts Institute of Technology, US FDA, IMS Heath, Adaptive Pharmacogenomics and a number of pharmaceutical companies, which developed a tool to model clinical studies (Phase I–III) and allows the estimation of how different decisions would impact global complexity and the costs of therapeutics developments. Preliminary results seem to confirm that this modeling may help companies in their strategic decisions related to the codevelopment of a drug and its companion diagnostic [101]. References 1

2

Opar A. Bridging the drug–diagnostic divide. Nat. Rev. Drug Discov. 10, 323–324 (2011). Reichert JM. Letter from the Editor: stratified medicine. MAbs 2(2), 107 (2010).

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Website 101 Massachusetts Institute of Technology.

Economics of Stratified Medicine (2011). http://cbi.mit.edu/research-overview/ other-research-programs/strat_med

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6 Challenges for the regulatory agencies in establishing an environment favorable for stratified medicine

Initiatives by regulatory agencies54 Development of drugs & biomarkers

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Thomas Bieber The aim of regulatory agencies is to evaluate the risk/ benefit balance of new drugs and to accelerate and improve the drug development process. The approach and commitment that the regulatory agencies (EMA and the US FDA) have chosen in the area of stratified medicine, is much related to their overall philosophy in the context of drug development.

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Bieber Initiatives by regulatory agencies US FDA The US FDA has always tried, besides its role in protecting the public’s health, to speed up innovations by playing the role of ‘companion’ in the process of drug development. The approval of the first device for rapid characterization of cytochrome P450 genes in 2005 and the collaboration with other federal agencies to improve cancer therapies by biomarker development and evaluation are two from several early activities initiated by the FDA in the emerging era of stratified medicine (SM). Some examples of guidance from the FDA with regard to SM: Guidance for Industry: Pharmacogenomic Data Submissions: clarifying what type of genomic data needs to be submitted to the agency and when, and encouraging the voluntary submission of exploratory genomic data (March 2005) [101]

n

Drug and Diagnostic Codevelopment concept paper (April 2005) [102]

n

Adaptive Design Clinical Trials for Drugs and Biologics (February 2010) [103]

n

In a common effort with the US NIH, a ‘national highway system for personalized medicine’ was created to pave the way for the development of genomic-based SM. Since 2004, Critical Path Initiative [1] helps to improve the identification and validation of new biomarkers and diagnostic tools. This is implemented by the Voluntary Genomic Data Submission program [2] which allows direct information exchange and discussion through a separate forum between the agency and companies. It is meant to be used as a bedrock for creating relevant policies and useful guidance. More recently, the US Department of Health and Human Services (HHS) has launched the Personal Health Care program [104]. By using genomics, or the identification of genes and how they relate to drug treatment, personalized healthcare will enable medicine to be tailored to each person’s needs. The Genetic Testing Registry, initiated by the NIH with advice from the FDA and the HHS, establishes a voluntary registry aimed to collect individual genetic information in order to address information gaps [105]. Recently, the FDA has posted a request for public comments on a new draft guidance to facilitate the development and review of companion diagnostics [106]. The proposed policy states that personalized treatments (targeted drugs or therapies) would gain approval only after their accompanying diagnostic devices also receive approval. There is an exception for treatments of serious or life-threatening conditions. The draft was open for comments until 10 September 2011.

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Challenges for the regulatory agencies Actions by the FDA, NIH and other US authorities, partly in public–private partnerships, provide a beneficial regulatory environment that should further accelerate the development of new biomarkers and drugs, allowing their rapid availability for the public health. EMA While at the beginning of SM, the EMA (possibly due to its ‘youth’) did not react in the same proactive way as the FDA, this attitude has been rapidly adopted by the agency by launching a series of initiatives and guidance aimed to optimize the regulatory environment for the development of drugs and biomarkers for SM. Some examples of guidance from the EMA with regard to SM: Position paper on terminology in pharmacogenetics [107]

n

ICH Topic E 15: definitions for genomic biomarkers, pharmacogenomics (PGx), pharmacogenetics, genomic data and sample coding categories [108]

n

Reflection paper on PGx in oncology [109]

n

Reflection paper on the use of genomics on cardiovascular clinical trials [110]

n

Qualification of novel methodologies for drug development: guidance to applicants [111]

n

ICH Topic E 16: genomic biomarkers related to drug response: context, structure and format of qualification submissions [112]

n

PGx biomarker qualification: format and data standards [113]

n

Consultation on the Qualification Opinion ILSI/HESI Submission of novel renal biomarkers for toxicity [114]

n

In 2005 and 2006, the EMA/European Federation of Pharmaceutical Industries and Associations (EFPIA) hosted two workshops on biomarkers that were kind of starting points for the contribution of the EMA to the Innovative Medicines Initiative, a public–private partnership involving the pharmaceutical industry represented by the EFPIA and the European Commission in the context of the seventh framework program. This project is a model of collaboration collecting most of the stakeholders, such as pharmaceutical companies as well as small- and medium-sized enterprises, regulators, academia, imaging companies, patient organizations and charities. Innovative Medicines Initiative supports, for example, the development of new methodologies for the evaluation of medicinal products, development of biomarkers and surrogate markers, record

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Bieber systems for clinical research, bioinformatics, pharmacovigilance projects as well as educational and training programs [3]. Recently, the EMA has released a draft guideline and a series of reflection papers for which the end of consultation was reached and the comments had been collected by the agency: Draft guideline: use of pharmacogenetic methodologies in the pharmacokinetic evaluation of medicinal products [115]

n

Reflection paper on pharmacogenomic samples and data handling [116]

n

Reflection paper on methodological issues with pharmacogenomic biomarkers in relation to clinical development and patient selection [117]

n

Reflection paper on codevelopment of pharmacogenomic biomarkers and assays in the context of drug development [118]

n

When the comments provided by the stakeholders have been implemented for these reflection papers as well as the guidance for the use of pharmacogenetics in drug development has been finalized, these papers will be of seminal value for the industry in the development and approval of drug and companion diagnostics. FDA/EMA joint initiative The voluntary genomic data submission initiative leads to two common guidelines from FDA and EMA: processing joint FDA and EMA voluntary genomic data submissions within the framework of the confidentiality arrangement [119]; and final conclusions on the pilot joint EMA/FDA voluntary genomic data submission initiative experience on qualification of nephrotoxicity biomarkers [120]. These joint initiatives illustrate that both agencies realize the necessity for common efforts in PGx-related fields because of the genetic variety among the populations and the need for a more comprehensive data catalog. On the one hand the industry seems rather reluctant to discuss biomarker issues at an early stage with FDA and EMA because they may expect discrepancies which could jeopardize a global development, On the other hand, the agencies may be reluctant to commit themselves at an early time point since they may lack expertise. Therefore, in order to avoid an early threat in the global development of SM, further joint initiatives are mandatory. Challenges for regulatory agencies Among the numerous challenges currently facing the regulatory bodies in the context of the research and development of drugs for SM and their companion diagnostics and the growing market of personal genomics (PsG)

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Challenges for the regulatory agencies by direct-to-consumer, a few key aspects will be discussed below. For purposes of simplification, both areas will be considered separately, although they actually form a continuum.

Development of drugs & biomarkers Qualification of biomarkers With regard to the biomarkers, a rigorous validation and qualification procedure by the regulators is mandatory in order to minimize the rates of false-positive and false-negative results. Qualification of biomarkers goes one step beyond validation. Through a qualification program established by the regulators, the biomarker is linked with biological processes and clinical or disease end points. An official regulatory qualification ensures that data generated with biomarkers in drug development studies, is later accepted by regulatory agencies. Therefore, the EMA and FDA recently established new processes to allow a regulatory qualification of biomarkers that are intended to be applied in drug registration trials. This is a clue to the use of such markers in the selection of the patient populations as well as for the selection of an optimal initial and/or maintenance dose of a given drug. Many of the yet-to-be-validated ‘home brew’ (in-house) biomarker tests need clinical validity and the regulatory environment must address this increasing issue, which bears both some beneficial and harmful potential. Retrospective data analysis for regulatory purposes Biobanks and data collection will be key to the development of biomarkers and new drugs. However, there is a current lack in biosamples for the validation and testing of biomarkers [4], which will impact on the further development of SM. Thus, retrospective analyses and models will be of increasing value and the agencies should acknowledge the potential of this approach and propose solutions for the efficient use of these data. Interaction between agencies & notified bodies for approval of drug & its companion diagnostic One key question for regulators will be to evaluate the situation of a tandem trial associating an investigational medicinal product with its companion diagnostic. While in some countries such as the USA, in vitro diagnostic approval is regulated by the same agency (such as the FDA), this is in sharp contrast to European countries, where in vitro diagnostics are regulated by the European Dir. 98/79/EC (recently modified by the Dir. 2007/47/EC) and for which the registration is provided by different institutions, the so-called notified bodies (see Chapter 3). This difference

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Bieber is most relevant for the regulatory rules to apply for a codevelopment from one single sponsor as well as when distinct companies are involved (see Chapter 5). Besides the increasing number of guidance already issued by the EMA and the FDA in the field of biomarkers (see above), the question arises, whether a joint approval/registration in one single package is feasible, either submitted by the same sponsor or alternatively by cooperating partners. In the most frequent situation of a separate origin, adapted procedures have to be proposed by the regulators in order to avoid complicated and frustrating processes. Most importantly there is an urgent need for a global harmonization on the classification and conformity assessment procedures for in vitro diagnostics and, ideally, for the approval processes since a lack of unified procedure will doubtlessly represent a substantial hurdle for a rapid and efficient approval of drugs and their companion diagnostics. This harmonization should also provide a regulatory framework more specifically adapted to SM and facilitate the evaluation of safety and efficacy aspects for this new generation of drugs in a risk-averse society [5]. With regard to this, regulators could learn some lessons from the field of orphan disease where agencies such as the FDA and EMA work in close collaboration for the evaluation and administration of orphan drugs [6,7]. Extend appropriate expertise for scientific advice & regulatory decisions As mentioned above, the development of drugs for SM will imply the implementation of new study designs and there is a great need of expertise in this rapidly expanding field for all actors, including regulators when it comes to providing scientific advice at all stages of the clinical development. Will the national agencies still be able to provide an adequate scientific advice or must this be provided on a more global level? Similarly, with regard to the increasing importance of the fourth hurdle for the marketing of medicinal product in Europe, where Health Technology Asessment Agencies request to be involved in the discussions for the design of Phase III trials, this expertise should also be provided by representatives of that agency. The discussions about the need and design of clinical trials for SM will be critical to answer the questions about what kind of data are necessary to document the value of a diagnostic test to predict benefit (include patients) or harm (excludes patients). Also, the question which clinical study designs are acceptable (prospective randomized clinical trials [RCT], observational cohort, retrospective) to provide such evidence, especially for safety predictor tests, has to be addressed and more adapted guidelines should

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Challenges for the regulatory agencies be proposed for clinical trials with smaller samples. It remains to be clarified to what extent qualified biomarkers could potentially be used for modeling and clinical trial simulation. Also the agencies should accompany the pharmaceutical companies in their efforts to implement trials with adaptive design as these are expected to be of increased importance for the clinical development in SM. While the FDA seems open to the concept and has provided a draft guidance for adaptive design trials for drugs and biologics [121], such a guideline is still lacking for European countries, although a reflection paper was released in 2007 [122] and two EMA–EFPIA workshops have been organized [123,124] Proactive regulatory approach in labeling change The regulatory bodies must accompany (that is, provide qualified advice for) the design of clinical trials associated with biomarkers, and clarify the process that industry should follow with regard to the development of a companion biomarker in order to optimize the approval procedures and avoid discrepancies and the waste of resources while trying to harmonize the decisions when deferred processes are concerned. The delayed approval of label changes for recommending biomarkers such as for the EGFR inhibitor panatimumab by the FDA 5  years after the initial drug approval is a typical example for this situation. Overall, regulators will need to adapt to the new knowledge [6] and an early, ongoing and possibly informal scientific dialog between the agencies and the industry [125,126] is mandatory allowing the definition of the validation milestones, as well as a consensus and final agreement on the validation status of particular biomarker. In some cases, however, in analogy to medicinal products, according to Art. 14 (7), Reg. EC 726/2004, the agencies should also consider the option of a kind of ‘conditional approval’ for biomarkers. Clearly, in order to stimulate the development of SM, regulatory incentives should be provided in the following key fields [6]: n To build infrastructures which would also stimulate work on saving failed drugs and encourage stratification work on existing drugs [1] To work on older drugs for additional therapeutic indications within a context of regulatory data protection

n

To stimulate the establishment of biobanks and initiatives, such as the Innovative Medicines Initiative

n

To require PGx data and diagnostic tests to be part of the submission package for regulatory approval where relevant

n

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Bieber Personal genomics for consumers High-throughput DNA sequencing technologies have strongly improved the liability of the data and contributed to a dramatic reduction of the costs for a single genomic analysis. This has lead to the appearance of a new kind of industry on the market: the direct-to-consumer [8] gene test kits that claim to be able to provide a personal risk profile for a limited number of diseases for less than US$1000. There are currently more than 30 providers on this growing market such as Navigenics [127] Pathway Genomics [128], deCODE [129], Illumina and 23andMe. The latter two have teamed up for this business [130]. However, it has been recognized that such PsG tests rise a series of concerns and questions with regard to their clinical validity and clinical utility [9–11]. These concerns should be addressed in the context of further investigations along four overlapping fields of research (from T1 to T4): n T1: Scientific evaluation of PsG tests, including discovery and replication T2: Evaluation of the clinical validity and utility

n

T3: Evaluation of diffusion, dissemination and implementation of the tests

n

T4: Assessment of the population impact, including effectiveness

n

In the USA, the Evaluation of Genomic Applications in Practice and Prevention initiative established in 2005 from the US CDC office of public health genomics was founded to support the development of a systematic process for assessing the available evidence regarding the validity and utility of genetic tests. Besides the issue of quality of the tests themselves, the overall interpretation is another critical point to consider. Indeed, it is well accepted that most of the complex diseases develop on the genetic background, which is on one hand strongly modulated by epigenetic regulatory mechanisms and on the other hand completed by complex environmental factors (gene– environment interaction). Thus, in contrast to monogenetic diseases, the single PsG without complementary information about intrinsic or extrinsic risk factors cannot provide the expected value. Clearly, with regard to the serious concerns because of the potential benefit and harm (e.g., limitation due to ethnicity or for complex diseases) they may represent, PsG should be submitted to a regulatory legislation and PsG/direct-to-consumer must be considered by the agencies under same rigorous standards as we expect for any similar product in the field of diagnostic for SM.

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Challenges for the regulatory agencies References 1

Hamburg MA, Collins FS. The path to personalized medicine. N. Engl. J. Med. 363, 301–304 (2010).

9

2

Goodsaid FM, Amur S, Aubrecht J et al. Voluntary exploratory data submissions to the US FDA and the EMA: experience and impact. Nat. Rev. Drug Discov. 9(6), 435–445 (2010).

10 Khoury MJ, Coates RJ, Evans

3

Goldman M. Reflections on the innovative medicines initiative. Nat. Rev. Drug Discov. 10, 321–322 (2011).

4

Phillips KA, Van Bebber S, Issa AM. Diagnostics and biomarker development: priming the pipeline. Nat. Rev. Drug Discov. 5, 463–469 (2006).

5

Eichler HG, Abadie E, Raine JM, Salmonson T. Safe drugs and the cost of good intentions. N. Engl. J. Med. 360, 1378–1380 (2009).

6

Tambuyzer E. Rare diseases, orphan drugs and their regulation: questions and misconceptions. Nat. Rev. Drug Discov. 9, 921–929 (2010).

7

8

Tambuyzer E. Towards a framework for personalized healthcare: lessons learned from the field of rare diseases Pers. Med. 7, 569–586 (2010). Khoury MJ, McBride CM, Schully SD et al. The scientific foundation for personal genomics: recommendations from a National Institutes of Health–Centers for Disease Control and Prevention multidisciplinary workshop. Genet. Med. 11(8), 559–567 (2009).

Ng PC, Murray SS, Levy S, Venter JC. An agenda for personalized medicine. Nature 461, 724–726 (2009). JP. Evidence-based classification of recommendations on use of genomic tests in clinical practice: dealing with insufficient evidence. Genet. Med. 12(11), 680–683 (2010).

11 Khoury MJ, Feero WG, Reyes

M et al. The genomic applications in practice and prevention network. Genet. Med. 11(7), 488–494 (2009).

Medicine. GTR: genetic testing registry. www.ncbi.nlm.nih.gov/gtr 106 US FDA. In vitro companion

diagnostic devices. www.fda.gov/downloads/ MedicalDevices/Device RegulationandGuidance/ GuidanceDocuments/ UCM262327.pdf

107 EMA. Position paper on the

terminology in pharmacogenetics. www.emaeuropa.eu/docs/ en_GB/document_library/ Scientific_ guideline/2009/09/ WC500003889.pdf

108 CHMP/ICH. Note for guidance

Websites 101 US FDA. Pharmacogenomic

data submission. www.fda.gov/downloads/ RegulatoryInformation/ Guidances/ucm126957.pdf

102 US FDA. Drug-diagnostic

co-development concept paper. www.fda.gov/downloads/ drugs/scienceresearch/ researchareas/ pharmacogenetics/ ucm116689.pdf

103 US FDA. Adaptive design

clinical trials for drugs and biologics. www.fda.gov/downloads/ Drugs/Guidance ComplianceRegulatory Information/Guidances/ UCM201790.pdf

104 US Department of Health

and Human Services. Personalized healthcare. www.hhs.gov/myhealthcare 105 National Center for

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Biotechnology Information, US National Library of

on definitions for genomic biomarkers, pharmacogenomics, pharmacogenetics, genomic data and sample coding categories. www.emeaeuropa.eu/docs/ en_GB/document_library/ Scientific_ guideline/2009/09/ WC500002880.pdf

109 EMEA/CHMP. Reflection

paper on pharmacogenomics in oncology. www.emeaeuropa.eu/docs/ en_GB/document_library/ Scientific_ guideline/2009/09/ WC500003866.pdf

110 EMEA/CHMP. Reflection

paper on the use of genomics in cardiovascular clinical intervention trials. www.emeaeuropa.eu/docs/ en_GB/document_library/ Scientific_ guideline/2009/09/ WC500003865.pdf

111 EMEA/CHMP/SAWP.

Qualification of novel methodologies for drug

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Bieber development: guidance to applicants. www.emeaeuropa.eu/docs/ en_GB/document_library/ Regulatory_and_procedural_ guideline/2009/10/ WC500004201.pdf 112 EMA. Genomic biomarkers

related to drug response: context, structure and format of qualification submissions. www.emeaeuropa.eu/docs/ en_GB/document_library/ Scientific_guideline/2010/09/ WC500097060.pdf

113 EMEA/CHMP.

Pharmacogenomic (PG) Biomarker Qualification: Format and Data Standards. www.emeaeuropa.eu/docs/ en_GB/document_library/ Scientific_ guideline/2009/09/ WC500003863.pdf

114 EMA. Consultation on the

qualification opinion ILSI/ HESI submission of novel renal biomarkers for toxicity. www.emeaeuropa.eu/docs/ en_GB/document_library/ Regulatory_and_procedural_ guideline/2010/05/ WC500090466pdf

115 EMA/CHMP. Draft guideline:

use of pharmacogenetic methodologies in the pharmacokinetic evaluation of medicinal products. www.emeaeuropa.eu/docs/ en_GB/document_library/ Scientific_guideline/2010/05/ WC500090323.pdf

116 EMEA/CHMP. Reflection

paper on pharmacogenomic samples and data handling. www.emeaeuropa.eu/docs/ en_GB/document_library/ Scientific_ guideline/2009/09/ WC500003864.pdf

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117 EMA. Reflection paper on

methodological issues associated with pharmacogenomic biomarkers in relation to clinical development and patient selection. www.emeaeuropa.eu/docs/ en_GB/document_library/ Scientific_guideline/2011/07/ WC500108672.pdf

118 EMA/CHMP. Reflection paper

on co-development of pharmacogenomic biomarkers and assays in the context of drug development. www.emeaeuropa.eu/docs/ en_GB/document_library/ Scientific_guideline/2010/07/ WC500094445.pdf

119 US FDA/EMA. General

principles: processing joint FDA/EMEA voluntary genomic data submissions within the framework of the confidentiality arrangement. www.emeaeuropa.eu/docs/ en_GB/document_library/ Scientific_ guideline/2009/09/ WC500003887.pdf

120 EMEA/FDA. Final conclusions

on the pilot joint EMEA/FDA VXDS experience on qualification of nephrotoxicity biomarkers. www.emeaeuropa.eu/docs/ en_GB/document_library/ Regulatory_and_ procedural_ guideline/2009/10/ WC500004205.pdf

121 US FDA. Adaptive design

clinical trials for drugs and biologics. www.fda.gov/downloads/ Drugs/Guidance ComplianceRegulatory Information/Guidances/ UCM201790.pdf

122 CHMP/EWP. Reflection paper

on methodological issues in confirmatory clinical trials with flexible design and analysis plan. www.emeaeuropa.eu/docs/ en_GB/document_library/ Scientific_ guideline/2009/09/ WC500003617.pdf

123 EMEA Report on the EMEA-

EFPIA Workshop on adaptive designs in confirmatory clinical trials. www.emeaeuropa.eu/docs/ en_GB/document_library/ Report/2009/11/ WC500011842.pdf

124 EMA/EFPIA 2nd workshop.

Adaptive design in confirmatory trials. www.emeaeuropa.eu/docs/ en_GB/document_library/ Minutes/2010/04/ WC500089206.pdf

125 EMEA/CHMP. Guideline on

pharmacogenetics briefing meetings. www.emeaeuropa.eu/docs/ enGB/documentlibrary/ Scientificguideline/2009/09/ WC500003886.pdf

126 EMA/ITF. Organisation of

briefing meetings. www.emeaeuropa.eu/docs/ enGB/documentlibrary/ StandardOperating Procedure-SOP/2009/09/ WC500002943.pdf

127 Navigenics.

www.navigenics.com

128 Pathway Genomics. Personal

genetic reports. www.pathway.com

129 deCODE Genetics.

www.decode.com

130 23andme. Genotyping

technology. www.23andme.com/more/ genotyping

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Chapter

7 Challenges for the patients facing stratified medicine & personal genomics

Patients as partners in the development process for biomarkers & drugs for stratified medicine 63 Individuals & patients as consumers of personal genomics64 A first step into a patient’s involvement in diagnostics & drug development: the European Patient’s Academy on Therapeutic Innovation 66

Thomas Bieber Patients as partners in the development process for biomarkers & drugs for stratified medicine One of the major bottlenecks in the development of biomarkers and targeted therapy is the current lack of samples in the biobanks of patients and volunteers. As a consequence, data catalogs that are mandatory for the identification and validation of biomarkers are often incomplete. Thus, further efforts in the context of research consortia are needed to gain an increased willingness of patients to contribute to the extension of disease-related biobanks, which are the key to the success of stratified medicine. Therefore, nondiscrimination legal protections for genetic purposes will help to increase the contribution of patients in the studies, and benefit the genetic screening and counseling.

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Bieber When it comes to being partners in the development, and later, in the use of new therapies, the patients should be ready to understand the significance of the new developments. They must be able to critically evaluate the large amount of information provided by sources, such as the internet, and to seek for the advice of healthcare professionals trained for counseling in stratified medicine (SM). A balanced decision for the management of their own disease situation must act as a base for their understanding of the risks and opportunities provided by different types of targeted therapies. Patient organizations and foundations dedicated to support the progress in biomedical research should be instrumental in the information of affected individuals by providing adapted educational programs (see later section on ‘A first step into a patient’s involvement in diagnostics & drug development: the European Patient’s Academy on Therapeutic Innovation’). Therefore, they could substantially contribute to the health literacy of the patients, which is a key element for their autonomy of choice and decision. An effective protection of anonymity and privacy is crucial, not only from an ethical and legal point of view, but also with regard to the risk of decreased support from the patients for the overall development of SM.

Individuals & patients as consumers of personal genomics Progress in genetic technologies leads to a considerable reduction of the costs for sequencing the human genome. Almost complete individual exonomes are now provided by some companies. However, with the increase in the number of genetic variants detectable in a single approach, there is an increase in the challenge of the interpretation of the data. Thus, while the costs of sequencing are now affordable, the costs related to the data interpretation of one single genome may reach more than US$100,000. With regard to the rapidly progressing field of biomarkers for the identification of individuals at risk of developing diseases, these tools will help to tag potential patients (and their relatives) at an early time point before the outbreak of the disease. Ultimately, complex genomic, endophenotypic and environmental information, collected for each individual in data warehouses, should provide sufficiently precise risk profiles, offering the opportunity for more effective preventive measurements. A critical point is that society might expect from these individuals the readiness to implement prevention measures linked to their own risk profile and according to ‘advice packages’, which could be provided in a stratified manner. However, this is a rather oversimplified view of the quite important potential of the new diagnostic and therapeutic

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Patients facing stratified medicine & personal genomics technologies, since it does not consider the high variability of the individual perception of genomic information and the potentially dominant role of the epigenetic regulation due to environmental factors. It is usually assumed that the knowledge about an increased risk to develop a disease will increase the awareness of this condition and represents a strong incentive for the patient to modify their behavior and lifestyle. However, the key questions remain: are individuals willing to undergo genetic tests and will they handle the genetic information adequately? Will the knowledge about their personal risk to develop one or several diseases lead to a change in their behavior towards more prevention? Although this is an important and fascinating field for social research, only a few studies, such as the REVEAL study [1], the Multiplex initiative [101] and the clinENCODE study [102] are addressing these crucial questions and the possible consequences of genomic information for the behavior of patients to date. The key results can be summarized as follows: n The overall readiness to perform genetic testing is widely accepted but is increased in individuals with higher social classes and disease-related burden in the own family. However, individuals must have the right to decline a predictive genetic test; The way the individual will react to the prognostic information provided by the genetic test is dependent on the overall severity of the disease considered and the therapeutic possibilities;

n

The behavior will be influenced by the availability and practicability of preventive measurements, as well as the opportunities to control these measurements. There is a risk to induce a false sense of safety, when the disease forecasted by the genetic test is of low severity;

n

However, the division between the exigencies and individual wishes on one hand and the skills to translation on the other hand, has still not been clearly addressed but it is expected that the degree of education of patients will be of importance in the outcome of the behavior.

n

The increasing health literacy and the freedom of decision and privacy aspects seem to be key with regard to the practicability of biomarkerbased strategies. Thus, educational programs and campaigns for healthcare professionals are mandatory for a better information of patients and consumers with regard to the translation of the scientific information in terms of prevention. Whether the patients and consumers will adhere to these educational opportunities should be investigated in

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Bieber large socioepidemiologic studies. In any case, a legal framework should contribute to their preserved autonomy and self-determination when it comes to deciding the implementation of preventive measurements or the therapeutic decision [103].

A first step into a patient’s involvement in diagnostics & drug development: the European Patient’s Academy on Therapeutic Innovation Since it has been recognized that the progress in a better development and implementation of SM is tightly related to the cooperation with patients at different levels, the third call of the Innovative Medicines Initiative supported by the 7th Framework Programme and the European Federation of Pharmaceutical Industries and Associations was aimed to foster patients’ awareness on pharmaceutical innovation. Therefore, the European Patient’s Academy on therapeutic innovation application has been selected and was started in 2012. This initiative coordinated by the European Patients Forum “will build competencies among well-informed patients and will establish a widely used, sustainable infrastructure for objective, credible, correct and up-to-date, ongoing knowledge building for patient advocates and the broader patients community including hard to reach patients” [104]. This project, which includes seven work packages, will address the following issues: n Medicines development process from research to approval; Personalized and predictive medicine;

n

Drug safety and risk/benefit assessment of (novel and existing) medicines;

n

Pharmacoeconomics and health technology assessment;

n

Design and objectives of clinical trials (and involved stakeholders);

n

Patients’ roles and responsibilities in innovative medicines development, delivery and increasing health literacy. Modern communication tools such as Wikimedia-type technologies will be used “to utilize the collaborative knowledge of a widely distributed network of experts, patient advocates and other knowledgeable persons worldwide, to create the leading public library of public information on therapeutic innovation”. This innovative approach in educational program for patients will be supervised by an expert panel, as well as by representatives of regulatory agencies such as the European Medicines Agency and the Bundesinstitut für Arzneimittel und Medizinprodukte (BfArM).

n

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Patients facing stratified medicine & personal genomics References 1

Green RC, Roberts JS, Cupples LA et al. Disclosure of APOE genotype for risk of Alzheimer’s disease. N. Engl. J. Med. 361, 245–254 (2009).

Websites 101 National Human Genome

make use of genetic tests. www.genome.gov/25521052 102 The Personal Genome:

Clinencode. http://thepersonalgenome. com/2005/05/clinencode

103 Hüsing B, Hartig J, Bührlen B,

Research Institute. NIH news: how healthy younger adults

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Reiß T, Gaisser S. Individualisierte Medizin und Gesundheitssystem.

www.tab-beim-bundestag. de/de/pdf/publikationen/ berichte/TAB-Arbeitsberichtab126.pdf 104 European Patient’s Academy

on Therapeutic Innovation. www.eu-patient.eu/ Initatives-Policy/Projects/ EPF-led-EU-Projects/EUPATI

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Chapter

8 Conclusions & outlook to the future health system Thomas Bieber After empirical and evidence-based medicine, stratified medicine represents a further evolutionary step towards a future truly personalized medicine approach. As a consequence of tremendous progress in biomedical research and diagnostic technologies, resulting from increased partnerships between the academic and industrial stakeholders, a biomarker-based stratification allows to better address the patient population that will have the highest benefit of targeted therapy with a significantly improved safety profile. While the industry of diagnostics experiences a dramatic expansion in providing increasing numbers of new biomarkers, most of them are still waiting for their validation; this new paradigm also implies substantial strategic changes for pharmaceutical companies, switching from the ‘blockbuster model’ (which may still be valid for diseases with a broad therapeutic response) to the ‘niche-buster model’, applying mainly to life-threatening conditions with high unmet medical need.

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Bieber For a rapid and qualified implementation of stratified medicine and faster but safe availability for the patients, regulatory agencies need to proactively accompany this process in a steady dialog, focusing on providing tools and guidance for the approval of new drugs and their companion diagnostics. In the near future, a more complex approach combining several biomarkers, which is able to predict the significant risk of tumor escape will be applied. Thus, a kind of refinement with increasingly complex biomarker profiles will emerge, ultimately reaching the level of truly personalized medicine. Patients are important partners at all steps of the development of new diagnostics and drugs but they may also benefit from some particular aspects of the new technologies, such as genomics, providing opportunities for early identification of individuals at risk to develop diseases for which the genes have been tagged. As an obvious consequence of a modern biomarker-based strategy, it will be possible to intervene in a pathologic process before the symptoms become apparent or before it has caused irreversible damages, that is, disease-modifying strategies will become reality. While stratified medicine has experienced its innovative start in the field of life-threatening diseases with significant unmet medical needs, such as oncology and neurological diseases, it is expected that this trend will extend progressively to other fields such as autoinflammatory and autoimmune diseases. The further reduction of the costs for sequencing and overall genomics-based diagnostics will lead to its implementation to more and more fields less related to the unmet medical need but rather to, for example, aging-related issues and ultimately to lifestyle aspects (Figure 8.1). The wider acceptance and application of validated and qualified genomic markers may initiate a new medical evolutionary process, progressively shifting away from the traditional curative medicine. This putative future health system involves a transition to predictive, preventive, personalized and participatory medicine and will require a systems biologic approach including the collection of tremendous amounts of data from genomics, endophenotypic information, as well as those related to individual interactions with the environment. Thus, a virtual cloud of billions of data points is forecasted to surround each patient and will help to develop efficient and integrated workflows that predict the most suitable therapeutic strategy for each patient [1]. At a final (futuristic) stage of the evolution of medicine, the physicians will slowly mutate from therapists to health consultants or navigators, counseling the individuals on the basis of their individual biologic profile

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Conclusions & outlook to the future health system Figure 8.1. Possible extension of stratified approaches in medicine and in further fields. Unmet medical needs

Market Oncology

Autoimmune diseases

Chronic inflammatory diseases

Aging ?

Lifestyle

and helping them to choose the optimal strategy to avoid diseases by tailored preventive measurements. However, legal and ethical considerations in the context of an increasing risk of transparency should guarantee the privacy and autonomy of choice and decision of all individuals and patients. Otherwise, an uncontrolled overemphasizing of the significance of individual genomic information could lead the society into temptation to decide on an obligation of prevention for each individual. This is the kind of scenario has been depicted by the German author Julie Zeh in her novel ‘Corpus delicti, Ein Prozess’ [2]. She depicts a future society where the medical progress has reached its apotheosis. Genomic, biologic and exposome data of all citizens are the basis of the so-called ‘Methode’, which replaces the democratic constitution. In this thrilling novel, this system dictates the behavior of each citizen in a society based on an excessive prevention policy. All citizens are healthy but legally obliged to keep themselves in healthy conditions. Illness becomes a crime.

References 1

Bousquet J, Anto JM, Sterk PJ et al. Systems medicine and integrated care to combat

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chronic noncommunicable diseases. Genome. Med. 3(7), 43 (2011).

2

Zeh J. Corpus Delicti, Ein Prozess. Schöffling & Co., Frankfurt, Germany (2009).

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Conclusion Stratified medicine: a challenging social experiment Thomas Bieber Stratified medicine (SM) is the natural outcome of the progress in biomedical sciences and particularly in genomics, which is about to generate a tectonic paradigm shift in our view to approach healthcare. It bears great expectations and hopes with regard to the availability of better medicinal products, especially for life-threatening diseases but also for other diseases with unmet medical needs. However, before reaching this aim, the stakeholders will face various challenges and the pressure for collaborative partnerships is substantial with regard to the increasing costs for research and development. Thus, public–private partnerships, such as translational medicine hubs, are expected to become of increasing value for the mandatory cross-talk between academia, national governments through their organizations, the pharmaceutical industry, the diagnostics industry and patient organizations or foundations. With regard to new insights into the mechanisms of diseases, clinicians may have to switch from a purely clinical pathophenotypic classification to a molecular taxonomy of the diseases and to redefine the guidelines and standards of care for their management. The medical education for the new generation of physicians who will face SM should include more programs that aim to inform the students about biomarkers and SM, enabling them to acquire and provide the necessary information for the therapeutic decision. This will happen in a new kind of a more collaborative rather than paternalistic kind of physician–patient relationship. doi:10.2217/EBO.12.317

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Bieber Stratification of patient populations requires the use of biomarkers that have undergone a thorough clinical validation and qualification process before being ‘fit-for-use’ and have been included in clinical trials, eventually as surrogate end points. However, these processes need the availability of biosamples of high quality, handled under standardized conditions and flanked by appropriate clinical phenotypic information. The codevelopment of a drug with its companion diagnostic needs not only a strong and efficient partnership between diagnostics and pharmaceutical companies but also needs to be supported proactively by the regulators and by the release of appropriate guidelines. For the pharmaceutical industry, SM signifies a shift from the ‘blockbuster’ model to a ‘niche-buster’ model. However, current analyses suggest that all stakeholders, including the industry, regulators, patients and payers, could benefit in the long term if patients have timely access to the correct medicines. The use of new strategies and tools for the clinical development such as adaptive trial design are expected to increase its efficiency and to foster the approval of more targeted and safe drugs. The complex (co)development process of diagnostic and drugs requires a proactive involvement of the regulatory bodies. Guidelines must be generated in an early and ongoing dialogue between regulators, academia and industry in order to optimize the development process and the way to marketing authorization for more efficient and safe drugs. Regulators will also have to establish guidance and new regulatory framework for the direct-to-consumer industry of personal genomics for which the clinical utility remains to be established. Finally, the collection of the material for biobanks will be dependent on the patients and patient organizations. Foundations and initiatives such as EUPATI should be instrumental in the information of affected individuals by providing adapted educational programs. Thereby, they could substantially contribute to their health literacy, a key element for their privacy, autonomy of choice and decision with regard to SM and personal genomics Overall, the success of SM is tightly linked to an intensive and fruitful crosstalk and interaction between numerous stakeholders, all driven by different interests. Thus, SM represents a new and fascinating social experiment ultimately leading to a more efficient, safe and hopefully affordable healthcare.

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Index A

O

B

P

atopic dermatitis, 2, 20, 41, 46, 75 Bieber, Thomas, 3, 7, 17, 25, 35, 49, 53, 63, 69, 73 biomarker, 5, 11, 25, 26, 27, 28, 29, 30, 31, 32, 38, 39, 40, 41, 42, 43, 44, 45, 49, 50, 51, 54, 55, 56, 57, 59, 61, 65, 69, 70, 75

C

clinical development, 29, 33, 37, 38, 39, 41, 45, 46, 50, 56, 58, 59, 62, 74, 75 clinical trial, 30, 39, 40, 41, 46, 59, 75 consumer, 10, 57, 60, 74, 75

G

genome-wide association study, 75 genomics, 5, 3, 10, 14, 27, 54, 55, 56, 60, 61, 63, 64, 70, 73, 74, 75

I

orphan drug, 36, 41, 75 personal genomics, 5, 14, 56, 61, 63, 64, 74, 75 personalized medicine, 10, 11, 22, 24, 29, 46, 54, 61, 69, 70, 75 pharmacogenomics, 14, 22, 24, 29, 37, 46, 55, 61, 75

R

regulatory, 5, 2, 4, 8, 15, 25, 27, 28, 29, 31, 32, 36, 41, 43, 44, 50, 53, 54, 55, 56, 57, 58, 59, 60, 66, 70, 74, 75 research and development, 36, 56, 73, 75

S

single nucleotide polymorphism, 75 stratified medicine, 5, 3, 7, 10, 11, 17, 18, 25, 32, 35, 36, 40, 46, 51, 53, 54, 63, 64, 69, 70, 75

in vitro diagnostics, 75

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