Les Biomarqueurs: une composante essentielle de la Recherche Translationnelle

Transcription

1 Les Biomarqueurs: une composante essentielle de la Recherche Translationnelle Jesús Benavides Ancien Directeur de la Recherche Maladies Neurologiques. Sanofi Ecole Doctorale Biosigne. Université Paris Sud, Hôpital Bicêtre Escuela Doctoral Ciencias de la Salud. Universidad de Granada Consultant CNS drug R&D. Oteci and BIC Granada 1

2 From Aspirin to genomics 1897: Synthesis of Aspirin 1997: Sequencing of human genome has led to Identification of new potential targets Better understanding of factors involved in drug efficacy and side effects Pharmacogenomic Pharmacogenetic 2

3 And now. The postgenomic era Sequencing of human and model organisms genome has not yet led to the expected therapeutic innovation due to Poor druggability of new targets Innovation cycle longer than previewed Lack of innovative paradigms Poor translation to human 3

4 Neurological diseases: Lack of therapeutic innovation 4

5 Attrition in drug development Can the pharmaceutical industry reduce attrition rates? Kola and Landis, Nature Reviews Drug Discovery 2004; 3: Total attrition from target to market >98% 5

6 How to accelerate innovation? Multifactorial approach Target validation Candidate selection Clinical trials 6

7 Need to reduce the gap between drug discovery and clinical development (the 2002 NIH view) Translational research is concerned with moving basic discoveries from concept into clinical evaluation and is often focused on specific disease entities or therapeutic concepts G Finkelstein R,T Miller, and R Baughman,"The Challenge of Translational Research A Perspective from the NINDS," Nature neuroscience supplement,vol.5,

8 Translational research: Promoting innovation while mitigating risk Innovation New disease hypothesis New pharmacological approaches Validation of endpoints Risk mitigation Identification of candidates Dose prediction Dosing Regimen prediction Biomarker identification 8

9 Two major components of translational research Predictive experimental animal models Model construction Clinically relevant endpoints Biomarkers for clinical research Population enrichment Proof of mechanism Proof of concept Drug Safety Surrogate endpoints of efficacy 9

10 Definition of biomarkers A biomarker is defined by the Biomarker Definitions Working Group as "a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathologic processes, or pharmacologic responses to therapeutic intervention." Biomarkers can provide information about the effects of a drug on its target and/or the disease. Markers of drug effect or response (laboratory, physiological, or other) are a subset of the general class of biomarkers Other biomarkers may include diagnostic, prognostic or physiologic status information not linked to drug response 10

11 BM are a peephole or (hopefully) a window

12 Application of Biomarkers for clinical trials Patient selection Target engagement Pharmacodynamic activity Drug safety Disease progression Surrogate endpoints Some Biomarkers may have several applications 12

13 Use of biomarkers in early drug development and decision making Bridge pharmacological activity from animal to human via proof-ofmechanism or other observations Bridge safety from animal models to human safety early in development Evaluate dose-response and optimal regimen for desired pharmacologic effect Use safety markers to determine dose-response for toxicity Dose and secondary endpoints selection in pivotal trials Select patients that may benefit the most from the treatment based on Rolan. Br J Phamacol 44: 219,

14 Biomarkers can be categorized into several distinct categories on the basis of their contribution to the logic of a clinical plan. Although they seem to parallel the three phases of drug development, the objective is to deploy them as early as possible to confirm The hitting of the target That hitting the target alters the pathophysiological mechanism That altering this mechanism affects clinical status. 14

15 Clinical Endpoint A characteristic or variable that reflects how a patient feels, functions or survives Except for survival, assessing these involves some sort of intermediary measurement Clinical endpoints are usually accepted as evidence of efficacy for regulatory purposes 15

16 Clinical endpoints vs. Biomarkers Clinical endpoints Long term High variability Many patients Biomarkers Shorter term Lower vatiability Fewer patients

17 Surrogate endpoint (Marker*) A biomarker intended to substitute for a clinical meaningful endpoint. A surrogate endpoint is expected to predict clinical benefit (or harm, or lack of benefit) based on epidemiologic, therapeutic, pathophysiologic or other scientific evidence. Changes induced by a therapy on a surrogate endpoint are expected to reflect changes in a clinically meaningful endpoint. Robert J. Temple *Use of this term is discouraged because it suggests that the substitution is for a marker rather than for a clinical endpoint 17

18 Use of surrogate endpoints in late drug development Efficacy: Use to assess whether drug has clinically significant efficacy Surrogate endpoints may be used to support accelerated approval of a drug if the surrogate is deemed reasonably likely to predict a clinical endpoint of interest A few surrogate endpoints (e.g., blood pressure) are (were) acceptable for full approval 18

19 The most widely used biomarker* BLOOD LEVELS USED AS A SURROGATE FOR CLINICAL EFFICACY AND TOXICITY IN THE EVALUATION OF GENERIC DRUGS * Comment by Carl Peck: CDDS WORKSHOP, McLean, VA, May 13,

20 Examples of laboratory markers THERAPEUTIC BIOMARKER/ CLINICAL CLASS SURROGATE_ OUTCOME ANTI-HIV DRUGS CD4; VIRAL RNA DELAY AIDS PROGRESSION LIPID LOWERING DRUGS CHOLESTEROL CAD * ANTI-DIABETIC DRUGS BLOOD GLUCOSE MORBIDITY ANTIBIOTICS NEG. CULTURE CLINICAL CURE DRUGS FOR PROSTATE CA PSA TUMOR RESPONSE *Coronary artery disease 20

21 Examples of physiological biomarkers THERAPEUTIC BIOMARKER/ CLINICAL CLASS SURROGATE OUTCOME ANTIHYPERTENSIVE B.P. STROKE DRUGS FOR GLAUCOMA I.O.P. LOSS OF VISION OSTEOPOROSIS DRUGS BONE DENSITY FRACTURE RATE ANTIARRHYTHMIC ARRHYTHMIAS SURVIVAL 21

22 Hierarchy of biomarkers Qualified Biomarkers Surrogate Endpoints VALIDITY BIOMARKERS 22

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24 Biomarker identification strategy Drug effect related Often based on experimental model research Specific for each MOA Pathology progression related Based on clinical research Need of large consortia Specific for each disease 24

25 Biomarker identification strategy Preclinical Research Improve animal models Identify and characterize potential BM in animal models Phase 1-2 Translational Biomarkers Target occupancy Dose selection Dose regimen POM/POC Safety Phase 3 Patient Selection Drug efficacy Safety Identify biomarkers that can be measured in both preclinical models and in man for each drug candidate Strengthen BM research through the value chain Translational Research Translational Medicine 25

26 Questions? 26

27 Two major components of translational research Predictive experimental animal models Model construction Clinically relevant endpoints Biomarkers for clinical research Population enrichment Proof of mechanism Proof of concept Drug Safety Surrogate endpoints of efficacy 27

28 Discovery and preclinical characterization 0 Discovery Pharmacological target Screening (HTS, MTS, rational) Lead optimization in vitro and in vivo Characterization Specific pharmacology Pharmacokinetic and metabolism Safety >6 years 28

29 Clinical development 0 >10 years Phase 1: Healthy volunteers Safety Pharmacokinetics and metabolism Clinical pharmacology (Proof of Mechanism) Phase 2 : Patients Safety in patients Pilot trial (Proof of concept) Dose selection Phase 3: Patients Pivotal trials: Blind, multicentric, controlled Phase 4: Patients After registration, other therapeutic indications or uses 29

30 Value Chain Pre prog. PROGRAMME PRECLINIC Phase I Phase II/III Market After >15 years >10 9 >3000 patients 30

31 Biomarker classification 31

32 Endophenotypes: a subtype of biomarkers The endophenotype is associated with illness in the population The endophenotype is heritable The endophenotype is primarily state independent (manifests in an individual whether or not illness is active) Within families, endophenotype and illness co-segregate The endophenotype found in affected family members is also found in nonaffected family members at a higher rate than in the general population Their main application are genetic association studies from Gottesman and Gould 32

33 Endophenotypes: a subtype of biomarkers Endophenotype: a conceptual analysis K S Kendler and M C Neale Gottesman and Gould 2 1. The endophenotype is associated with illness in the population. 2. The endophenotype is heritable. 3. The endophenotype is primarily state independent (manifests in an individual whether or not illness is active). 4. Within families, endophenotype and illness co-segregate 5. The endophenotype found in affected family members is found in nonaffected family members at a higher rate than in the general population. Preston and Weinberger 3 An intermediate phenotype (often referred to as an endophenotype) is a quantitative biological trait that is reliable and reasonably heritable, i.e., shows greater prevalence in unaffected relatives of patients than in the general population. If a candidate intermediate phenotype is to provide meaningful information about a disorder, it should be associated with variant alleles that distinguish patients and their unaffected siblings from healthy controls on quantitative measures The intensive search for such candidates is based in part on (the) assumption that intermediate phenotypes in schizophrenia (reflect) a less complex genetic architecture than the disorder as a whole. Cannon and Keller 1 1. Endophenotypes should be heritable. 2. Endophenotypes should be associated with causes rather than effects of disorders. 3. Numerous endophenotypes should affect a given complex disorder. 4. Endophenotypes should vary continuously in the general population. 5. Endophenotypes should optimally be measured across several levels of analysis. 6. Endophenotypes that affect multiple disorders should be found for genetically related disorders. 33

34 What is proof of concept? An opperational definition The definition of POC varies by person, project, company, and industry. POC is reached when the cumulative weight of evidence supports the belief that a prototype (drug or others) is sufficiently likely to reach the project objective justify the resources required for the next major cycle of investment. Paul Rolan (professor of clinical pharmacology at the University of Adelaide) 34

35 POC and POM in drug development: definitions POC: Demonstrate that at well tolerated doses the drug is inducing changes in BM that are considered to be related to or to mediate a therapeutic effect POM: demonstrate that at well tolerated doses the drug is interacting with its expected target and/or inducing the expected pharmacological effects* *POM could be considered as a type of POC 35

36 POM and POC vs therapeutic efficacy POM/POC are not a demonstration of therapeutic efficacy but are helpful for Go NoGo decision to pivotal trials Dose selection Dose regimen selection Population enrichment Target validation POM/POC are based on Biomarkers 36

37 Oncology is showing the way for translational research: example of Trastuzumab, a treatment of HER2- positive metastatic breast cancer (MBC) 37

38 3 important concepts Target product profile: define what we are looking for in terms of Efficacy Safety Use Minimal target profile: what is the minimun profile we can accept withouth terminating the project Comptetitive advantage: how our approach will do better than existing approaches These 3 concepts are based on our knowledge of the unmet medical needs and competitive environement 38

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41 Summary Attrition in drug development How to reduce attrition Target validation Candidate selection Translational Research Experimental models Biomarkers Proof of Concept and Proof of Mechanism Translational Research Strategy 41

42 Value Chain Pre prog. PROGRAMME PRECLINIC Phase I Phase II Phase III Biomarker identification Biomarker validation POM/POC Secondary endpoints 42

43 Establishing a translational research strategy Select and validate targets for therapeutic intervention based on a better understanding of human pathology. Improving animal models. Adapt clinical endpoints/technologies to animal models. Identify Biomarkers in animal models and define a strategy for their use in Clinical Development. Application of Biomarkers as diagnostic tools to enrich population for clinical trials: personalized medicine strategy 43

44 Identification and validation of biomarkers In some cases these Biomarkers are MOA specific and need to be characterized in suitable experimental models. In other cases they are related to disease progression and can benefit from academic research, in particular from the collaborative consortia established for the different pathologies. These Biomarkers are expected to help to provide a POM/POC at an earlier stage and to refine dose and dose regimen prediction. 44

45 Adapt clinical endpoints/technologies to animal models Priority should be given to the evaluation of endophenotypes, such as imaging and biochemical markers in fluids or plasma (eg. proteins, mrna). In particular, the same markers should be used in both animal models and in human clinical trials. It should avoid making decisions based only on clinical phenotypes due to the differences between human and animal physiopathology. 45

46 How in vivo experimental models can improve the therapeutic innovation process Adapt clinical endpoints/technologies to animal models. Identify Biomarkers in animal models and define a strategy for their use in Clinical Development. THINK TRANSLATIONAL! 46

47 Use of Biomarkers Experimental model endpoints Behavior Histology (in vivo imaging) Patient Biomarkers Clinical scores Brain Imaging Brain Biochemistry and «Omics» CSF and plasma Biochemistry and «Omics» Selecting more relevant endpoints may overcome some of the experimental models limitations 47

48 Defining the translational strategy component of a development project A back-engineering process: from targeted product profile (TPP)* to experimental models TPP Pivotal trials POC (dose selection) POM Experimental models: identification and selection of Development candidates Biomarkers * Based on unmet medical needs 48

49 Conclusion A suitable Translational Research strategy is expected to deliver Target validation in human MOA validation in human POM and POC in early clinical development Candidate prioritization and dose and regimen selection for pivotal trials Ancillary endpoints of therapeutic efficacy Preparing personalized medecine: drug + BM diagnostic package Deliver innovative therapies to unmet medical needs 49