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C Chamberlain F. Hoffmann-La Roche Ltd, Welwyn Garden City, UK

The Diapason How to Tailor Optimal Treatment for RA Patients – New Diagnostic Tools and Emerging Biomarkers in RA. C Chamberlain F. Hoffmann-La Roche Ltd, Welwyn Garden City, UK.

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C Chamberlain F. Hoffmann-La Roche Ltd, Welwyn Garden City, UK

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  1. The DiapasonHow to Tailor Optimal Treatment for RA Patients – New Diagnostic Tools and Emerging Biomarkers in RA C Chamberlain F. Hoffmann-La Roche Ltd, Welwyn Garden City, UK

  2. “For every single pharma product… the biomarker research and the development of potentially companion diagnostics is a standard part of the development process”Dr Severin SchwanRoche CEOJune 2007

  3. Contents • Introduction • Applying biomarkers to drug development • Translating biomarkers into clinical practice • Tailoring optimal treatment for RA patients • Steps towards personalised healthcare for RA

  4. Drug development is about answering questions…And so reducing clinical uncertainty Value of information Safety 2 yrs post-launch Launch Definitive clinical efficacy and safety in large Phase III trials Efficacy and safety inPhase II trials Drug–drug interactions Shows clinical efficacy in small ‘enriched’ patient population (Phase IIa) Works in human pharmacology model No safety signal Shows PD response Expected PK Enduring utility from applying biomarkers Hits target Reachessite of action PK=pharmacokinetic PD=pharmacodynamic

  5. Biomarkers can deliver helpful insight in several ways… There are different uses for biomarkers… industry has traditionally focused on using biomarkers for PK/PD analysis, but this is changing Pharmacodiagnostic biomarkers • Treatment eligibility • Response prediction Biomarkers Disease biomarkers Pharmacological biomarkers • Predisposition • Early detection • Prognosis • Monitoring/ recurrence • PD markers • PK markers

  6. Introduction Applying biomarkers to drug development Translating biomarkers into clinical practice Tailoring optimal treatment for RA patients Steps towards personalised healthcare for RA Contents

  7. Biomarkers can help understand response… Deconstructing drug action Therapeutic action Drug dosing

  8. Biomarkers can help understand response… We can use molecular pathology as a framework for understanding Clinical disease Environment Biological change Environment Molecular aetiology

  9. Biomarkers can help understand response… We can use molecular pathology as a framework for understanding Clinical biomarkers Clinical disease Biological change Biochemical biomarkers Genomic biomarkers Molecular aetiology

  10. Biomarkers can help understand response… We can use molecular pathology as a framework for understanding Clinical biomarkers Clinicalresearch andexploratorydevelopment Biochemical biomarkers Genomic biomarkers

  11. Contents • Introduction • Applying biomarkers to drug development • Translating biomarkers into clinical practice • Tailoring optimal treatment for RA patients • Steps towards personalised healthcare for RA

  12. Personalised healthcare is achievableAll the pieces are in place for translation to ‘real-world’ practice Scientific understanding Available diagnostic platforms Regulatory acceptance

  13. New technologies are growing in maturity… Availability of novel genomic data is enabling • At least 99% of the human genome is in the public domain • Sequencing capacity has been redirected to SNP discovery • 28 February 2000: dbSNP had 26,397 submissions • 25 October 2007: dbSNP had 34,434,159 human submissions! • HapMap 3.8 million genotyped SNPs (1 SNP genomarker every 700 bp) Adapted from: International HapMap Consortium. Nature 2007; 449:851–861. dbSNP=database of single nucleotide polymorphisms

  14. Diagnostic options are increasing… There has been a strong clinical dissemination of new technologies

  15. 1990: $300 million (Human Genome Project) New diagnostic technologies are getting cheaper… New technologies are getting more accessible to practice • The cost of sequencing a human genome fell from $300 million in 1990, to $60,000 by 2008 • Costs are falling by ~50% every 2 years, raising the possibility of a $1,000 genome by 2016 Falling cost of sequencing human genome $ Cost of sequencinghuman genome 1,000,000,000 100,000,000 2016: $1,000 predicted cost 10,000,000 1,000,000 100,000 2008: $60,000 10,000 1,000 100 1990 1994 1998 2002 2006 2010 2014 2018

  16. Regulatory environment is primed for progress… Regulatory support for personalised healthcare is evident “I can't tell you how important it is for medicine that we move into this paradigm”1 “FDA's efforts will bring us one step closer to 'personalizing' medical treatment”2 “Development of test and therapy combinations must be facilitated because they have the potential to maximize drug benefits while minimizing toxicity”4 2005 Janet Woodcock Deputy Commissioner for Operations, US FDA 2003 Mark McClellan Commissioner, US FDA “All of us who are part of this change process...have no choice. The metamorphosis [to personalized healthcare] is underway... it is an opportunity that is within our grasp, an opportunity that we must seize”3 “Pharmacogenetics will play an important role in the development of better medicines for populations and targeted therapies with improved benefit/risk ratios for individuals”5 2006 Andrew C von Eschenbach Acting Commissioner, US FDA 2006 Lawrence Lesko Chair, Pharmacogenetics Group, US FDA 1. New York Times, 23 March 2005. 2. Upon publishing Guidance on Pharmacogenomic Data Submissions. 3. Keynote FDA speech, April 2006. 4. Washington Drug Letter, 13 April 2003. 5. Pharmacogenomics, Personalized Medicine and the role of the FDA, Bio-IT World Conference, 18 May 2004.

  17. Contents • Introduction • Applying biomarkers to drug development • Translating biomarkers into clinical practice • Tailoring optimal treatment for RA patients • Steps towards personalised healthcare for RA

  18. The utility of personalised healthcare can be defined… Simple algorithms help capture the feasibility of PHC Yes No No No PHC 2 1 1. Disease heterogeneity 2. Treatment diversity Yes Clinical opportunities are not sufficient to justify strategy seeking to deliver PHC 3. Drug response heterogeneity No PHC 3 No Yes 4. Establish clinical utility of response prediction 4 5. Can prognostics work in clinical practice and within cost boundaries No 5 Clinical value from stratification may be sufficient to justify strategy seeking to deliver PHC … Yes PHC PHC=personalised healthcare

  19. Questions to establish PHC feasibility…Is there disease heterogeneity? • RA presentation is highly heterogeneous1,2 • Genetic epidemiology studies reveal multiple aetiologies Results of genome-wide association study3 Genetics tell us that the aetiology of RA has severaldistinct contributory factors… 1. Eyre S, et al. Arthritis Rheum 2004; 50:729–735.2. Criswell L, et al. Arthritis Rheum 2007; 56:58–68.3. Plenge RM, et al. N Engl J Med 2007; 357:1199–1209.

  20. Anti-TNF therapies represent predominant biologic RA therapy Multiple new targets for RA therapy have been identified Improving treatment is heavily reliant on differentiating such new therapeutic strategies Diverse biologic treatments can target a variety of aetiologies Questions to establish PHC feasibility…Is there treatment diversity? Tarner IH, et al. Nat Clin Pract Rheumatol2007; 3:336–345.

  21. Anti-TNF therapies demonstrate variable response New therapies for RA are seen as demonstrating responses of similar polymorphism Baseline disease characteristic may not define such responses1 Diverse biologic treatments predicated on diverse aetiologies mean that optimal therapy will depend on complex prescription Questions to establish PHC feasibility…Is there response heterogeneity? 1. Hyrich K, et al. Rheum 2006; 45:1558–1565.

  22. PHC can help ensure optimal RA prescription…Diagnostics will impact the epidemiology of RA treatment RA patients 90% of RA patients RA diagnosed US and major EU data DMARD=disease-modifying anti-rheumatic drug

  23. PHC can help ensure optimal RA prescription…Diagnostics will impact the epidemiology of RA treatment RA patients 90% of RA patients RA diagnosed Methotrexate 60% of RAdiagnosed patients Other DMARD US and major EU data DMARD=disease-modifying anti-rheumatic drug

  24. Biologics 1st line PHC Biologics Biologics Biologics Biologics 2nd line PHC can help ensure optimal RA prescription…Diagnostics will impact the epidemiology of RA treatment RA patients 90% of RA patients RA diagnosed Methotrexate 60% of RAdiagnosed patients Other DMARD 12% of RAdiagnosed patients 30–40%poor response US and major EU data DMARD=disease-modifying anti-rheumatic drug

  25. Contents • Introduction • Applying biomarkers to drug development • Translating biomarkers into clinical practice • Tailoring optimal treatment for RA patients • Steps towards personalised healthcare for RA

  26. Several biomarkers can predict response… Some biomaterials and analyses are more tractable for clinical use Synovial fluid Synovial cells Pannus Blood Whole body Biomaterials foranalysis IA=immunoassay; FACS=fluorescence-activated cell sorting PET=positron emission tomography: IVD=invitro diagnostic

  27. Several biomarkers can predict response… Some biomaterials and analyses are more tractable for clinical use Rheumatoid arthritis Genetics Synovial fluid Genomics Synovial cells Proteomics Pannus Metabonomics Blood Imaging Whole body Immunometrics Biomaterials foranalysis Dry-lab approaches IA=immunoassay; FACS=fluorescence-activated cell sorting PET=positron emission tomography: IVD=invitro diagnostic

  28. Several biomarkers can predict response… Some biomaterials and analyses are more tractable for clinical use Feasible for transfer to IVD platform? Rheumatoid arthritis Uniplex IA Personalised healthcare Genetics Synovial fluid Genotyping Genomics Epi-genotyping Synovial cells Proteomics Expression studies Pannus Metabonomics Protein arrays Blood Imaging FACS Whole body PET Immunometrics Biomaterials foranalysis Dry-lab approaches Wet-lab/clinical analyses IA=immunoassay; FACS=fluorescence-activated cell sorting PET=positron emission tomography: IVD=invitro diagnostic

  29. Response-predictive diagnostics Several biomarkers can predict response… Contributions from diverse technologies and biomarker paradigms can help achieve the required clinical informativeness Uniplex IA Pharmacodiagnostic biomarkers Genotyping Epi-genotyping Expression studies Protein arrays Disease biomarkers FACS Pharmacological biomarkers PET Clinical analyses Biomarker applications

  30. RA has high heritability 45–75%1 Many genetic factors may be important Several candidate loci/genes have been identified… some confirmed independently2–4 Exploratory pharmacogenetic data for anti-TNF therapies demonstrate proof of concept5–7 Both pharmacodynamic and pharmacokinetic parameters must be considered in the search for stratifying diagnostics for RA biologic therapy Response prediction for RA therapies… Pharmacodynamic… 1. McGregor AJ, et al. Arthritis Rheum 2000; 43:30–37.2. Tamiya G, et al. Hum Mol Genet 2005; 14:2305–2232.3. Steer S, et al. Genes Immun 2007; 8:57–68.4. Plenge RM, et al. N Engl J Med 2007;357:1199–1209. 5. Lee YH, et al. Rheumatol Int 2006; 27:157–161.6. Kang C, et al. Rheumatology (Oxford) 2005; 44:547–552.7. Kooloos WM, et al. Drug Disc Today 2007; 12:125–131.

  31. Association of TNF-α promoter polymorphism (–308 A/G) and response is well described Response prediction for RA therapies… Lee YH, et al. Rheumatol Int 2006; 27:157–161.

  32. Many other candidate genes predictive of anti-TNF response in RA have also been studied Response prediction for RA therapies… Kooloos WM, et al. Drug Disc Today 2007; 12:125–131.

  33. Ab-neg Ab-pos Response prediction for RA therapies… • Specific and neutralising anti-product antibodies develop in RA patients treated with TNF antagonists such as infliximab • Low trough levels of drug have been shown to be associated with the presence of such antibodies Pharmacokinetic parameters may also be predictive of anti-TNF response in RA Pharmacokinetic… * * * 20 15 Serum infliximab (µg/ml) 10 5 0 1.5 3 6 Months of treatment *p<0.0001 Svenson M, et al. Rheumatology (Oxford) 2007; 46:1828–1834.

  34. Response prediction for RA therapies… Disease markers may also be predictive of anti-TNF response in RA • Response to anti-TNFs may decline with increasing anti-CCP titre1 Disease markers… • Response to anti-TNFs may decline with RF titre2 EULAR – no response EULAR – response 90 100 p=0.001 80 N=236 etanercept patients 80 70 60 60 50 Patients (%) Responders (%) 40 40 30 20 20 10 0 0 CCP –ve CCP +ve CCP high +ve IgA RF –ve/low(n=83) IgA RF high (>100 U/ml) (n=43) anti-CCP –ve = <50 U/mlanti-CCP +ve = >50 U/ml – <1600 U/mlanti-CCP high +ve = >1600 U/ml 1. Drynda S, et al. ACR, 24–29 October 2008. Poster 118.2. Bobbio-Pallavicini F, et al. Ann NY Acad Sci 2007; 1109:287295. RF=rheumatoid factorCCP=cyclic citrullinated peptide

  35. Response prediction for RA therapies…Scientific studies will require a variety of clinical resources • Biobanked samples from patients with RA treated with a range of biologic therapies • DNA • Whole blood RNA • Serum • PK-timed samples • Clinical data as to response of these patients to therapy • These can be acquired through registry collections and collections in parallel to clinical trials

  36. Phase III studies leveraged to support biomarker studies through collection of a range of biomaterials into the Roche Sample Repository Roche has biobanked extensively in TCZ trialing

  37. Whole genome analysis has been started…Over a thousand patients have already been genotyped • Genotyping using Illumina 550K chip generated 473 million data points • Population structure has been addressed • These data are now available for analysis • Initial analysis will be focused on response and safety – but this data set allows ongoing interrogation for other informative but more speculative analyses

  38. Old expectations/models Descriptive pathology Simple differential diagnoses Homogeneous therapeutic response Clinical diagnosis Universal treatments New expectations/models Mechanistic pathology Complex differential diagnoses Heterogeneous therapeutic response Molecular diagnosis Targeted therapies Better informed therapeutic choice Advantageous clinical differentiation Biomarkers and selection of response… Extending traditional expectations/models

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