SAWP GTWP BMWP Other WPs SWP BWP CHMP QWP BPWP PhVWP VWP EWP CTWP 1
Objetivos de las guías Armonización Orientación Transparencia Biomarker A characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. Biomarkers for: Drug development: Drug activity in non-clinical and early clinical studies Proof of concept Dose-response relationship Efficacy Toxicity Identification of target populations 2
VECTIVIX Efficacy- PFS Effect Influenced by Unscheduled Assessments PFS Primary Analysis PFS Sensitivity Analysis HR=0.54 (95%CI: 0.44-0.66) p<0.0001 HR=0.60 (95%CI: 0.49-0.74) p<0.0001 Inability to Identify Patients Most Likely to Benefit From Panitumumab Ligand Ligand EGFR dimer Shc Grb-2 SOS Signal Adapters and Enzymes STAT Grb-2 P13K SOS Ras PTEN Akt Raf mtor FKHR GSK-3 BAD MEK 1/2 Signal Cascade Transcription Factors p27 Jun FOS Myc Cyclin D-1 MAPK Effect size depending on the K-ras stratum 100% Mutant Events / N (%) Median in Weeks 100% Wild-type Events / N (%) Median in Weeks Proportion Event-Free 90% 80% 70% 60% 50% 40% 30% 20% Panit.+BSC 76 / 90 ) 7.4 BSC Alone 95 / 100 ( 95 ) 7.3 Proportion Event-Free 90% 80% 70% 60% 50% 40% 30% 20% Panit.+BSC 115 / 124 ) 12.3 BSC Alone 114 / 119 ( 96 ) 7.3 10% 10% 0% 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 Weeks 0% 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 Weeks HR=1.00 (95%CI: 0.74-1.37) HR=0.45 (95%CI: 0.34-0.59) Stratified Log Rank Test p < 0.0001 3
Developing reliable biomarkers Optimising drug-development Decrease late attrition rate Save costs SURROGATE A biomarker that is intended to be substitute for a clinically meaningful endpoint Attractiveness of surrogate endpoints Intellectually attractive (Pathophysiologically aimed) Shorter drug development Minimise unnecessary drug exposure Cost saving 4
SURROGATES ICH E9 Statistical Principles for Clinical Trials Biological plausibility Epidemiological data Quali-quantitative relationship How much of the treatment effect on the outcome could be considered as explained by the intended surrogate variable? Let discuss an example: Biomarkers in CV disease Many drugs for the treatment and/or prevention of CV diseases are currently approved based on their effect on biomarkers and/or symptoms HARD OUTCOMES IN CASE OF: No suitable biomarker available Entirely new target Specific regulatory claims for the labeling Problems with surrogates in CV disease Multifactorial disease Can the treatment effect be explained by one single parameter? How much of the expected treatment effect could be considered as accounted for by the intended surrogate variable? 5
Problems with surrogates in CV disease Heterogeneous population To what extent the surrogate value of a particular variable is applicable to populations with different risk profile/level Problems with surrogates in CV disease Polytherapy To what extent the observed effect is explained by the background therapy and what is the interaction with the new treatment? Problems with surrogates in CV disease Extrapolability to other drugs To what extent the surrogate allows to make reliable comparative benefit/risk assessments with other drugs: With the same mechanism of action With a different mechanism of action 6
Problems with surrogates in CV disease Historical failures Should they play a role?! Phase 3 Torcetrapib/atorvastatin Imaging Program Carotid IMT Subject Populations: Heterozygous FH Mixed dyslipidemia, TG > 150 Eligible for statin treatment Coronary IVUS Coronary IVUS Subject Population: Angio. proven CAD (> 20% stenosis) Eligible for statin treatment B-mode US Coronary IVUS B-mode US / 6 months S C R E E N I N G atorvastatin dose titration 10, 20, 40, or 80 mg/d Target: LDL-C to CV risk goal Run-in period of variable duration Target population Mechnology Number of subjects torcetrapib 60 mg-atorvastatin (T/A)* Randomization atorvastatin alone* 24 months D-B/ randomized Tx Same as atorvastatin dose at the end of the titration period. Endpoint Atorvastatin dose Heterozygous FH Carotid ultrasound 904 Δ IMT (mm)/year 56 mg Mixed dyslipidemia Carotid ultrasound 752 Δ IMT (mm)/year 13 mg CHD IVUS 1188 Nominal Δ PAV 23 mg 7
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T/A Imaging Trials: Deaths and CV Safety T/A Subjects 450 454 Deaths 2 (0.4%) 2 (0.4%) Subjects with CV SAEs* A 24 (5.0%) 11 (2.4%) T/A Subjects 377 375 Deaths 1 (0.3%) 1 (0.3%) Subjects with CV SAEs* A 17 (4.5%) 13 (3.5%) T/A Subjects 591 597 Deaths 8 (1.4%) 6 (1.0%) Subjects with Adj. CV Events 62 (10.5%) 57 (9.6%) *investigator reported SAEs- not adjudicated as per protocol CHD death, non-fatal MI, stroke (fatal or non-fatal), hospitalization for unstable angina. A Carotid U/S HeFH Carotid U/S Type IIb IVUS CHD Atorvastatin titrated to reach a target of LDL < 100 mg/dl 9
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Torcetrapib Large differences in HDL and LDL Small increase in SBP No effect on progression of AT INCREASED MORTALITY Approving drugs based on surrogates is approving them based on logic rather than on proof Thank goodness! Now I understand everything! 11
Control Group Allows differentiating between real treatment effects and other changes attributable to a number of factors: 1. Natural course of the disease 2. Patient's and observer's expectations 3. Other treatments. TYPES of CONTROLS Placebo Active control Dose-response control The control group influences the inferences that can be drawn from the CT Type of enroled population. Type of endpoint. Credibility of the study results. Regulatory acceptance. 12
TYPES of CONTROLS ADVANTAGES Credibility of the observed efect Allows the estimation of the net treatment effect Efficient studies Minimisation of both patients' and observers' expectations COMPONETS OF TREATMENT EFFECT PD effect Unspecific drug effect Unspecific physician effect Absolute placebo effect Global placebo effect Overall treatment effec Regression to the mean Notreatment effect A B 13
A B TYPES of CONTROLS DISADVANTAGES Ethical problems Practical problems Extrapolability Absence of comparative information TYPES of CONTROLS ACTIVE CONTROL ADVANTAGES No ethical nor practical concerns Provides information on: Comparative efficacy Superiority over available treatments? Comparative safety 14
TYPES of CONTROLS ACTIVE CONTROL DISADVANTAGES Non-Inferiority studies (almost always!) Higher sample size A P A B? RE GU LA TO RY AP PR OV AL TYPES of CONTROL NON-INFERIORITY TRIALS The control arm has an effect Sensitivity to the treatment effects Differences between both treatments are inferior to a prespecified limit Non-inferiority margin If the difference was higher than the pre-specified margin it would be detected Assay sensitivity 15
TYPES of CONTROL POSITIONING OF DIFFERENT REGULATORY BODIES USA Placebo-controlled trials EU Relative benefit/risk evaluation in front of avalable alternatives. Clinically relevant effect. Japan Active-comparator trials. EJEMPLO A Resultados de estudios fase III en DM. Fase aguda Estudio Tratamientos N Hamilton basal Cambio Media DE LS media EC 1 A - Dosis 1 A. Dosis 2 90 81 87 17.47 17.44 17.97 5.20 5.16 5.87-5.30-5.59-5.96 EC 2 EC 3 EC 4 A - Dosis 1 A - Dosis 2 A - Dosis 2 A - Dosis 3 A - Dosis 2 A - Dosis 3 86 85 100 97 18.63 18.06 17.65 19.88 20.17 20.26 21.30 21.38 21.03 5.85 4.52 5.13 3.54 3.41 4.14 2.96 4.46 3.38-6.08-6.77-5.18-10.22-10.83-11.64-10.61 EJEMPLO A Resultados de estudios fase III en DM. Fase aguda Estudio Tratamientos N Hamilton basal Cambio Media DE LS media EC 1 A - Dosis 1 A. Dosis 2 89 90 81 87 17.79 17.47 17.44 17.97 4.73 5.20 5.16 5.87-4.14-5.30-5.59-5.96 EC 2 EC 3 EC 4 A - Dosis 1 A - Dosis 2 A - Dosis 2 A - Dosis 3 A Dosis 3 86 85 99 10 97 18.63 18.06 17.65 19.88 20.17 20.26 20.58 21.30 21.38 21.03 5.85 4.52 5.13 3.54 3.41 4.14 3.73 2.96 4.46 3.38-6.08-6.77-5.18-10.22-10.83-10.13-11.64-10.61 16
EJEMPLO A Estudio EC 1 Resultados de estudios fase III en DM. Fase aguda Tratamientos N Hamilton basal Cambio IC 95% Valor de p. Comparación con Media DE LS media Placebo 89 17.79 4.73-4.14 A Dosis 1 90 17.47 5.20-5.30 (-3.05, 0.71).222 81 17.44 5.16-5.59 (-3.38, 0.47).138 87 17.97 5.87-5.96 (-3.72, 0.06).058 EC 2 EC 3 EC 4 A Dosis 1 A Dosis 3 A Dosis 3 86 85 99 10 97 18.63 18.06 17.65 19.88 20.17 20.26 20.58 21.30 21.38 21.03 5.85 4.52 5.13 3.54 3.41 4.14 3.73 2.96 4.46 3.38-6.08-6.77-5.18-10.22-10.83-10.13-11.64-10.61 (-4.47, -0.35) (-5.15, -1.06) (-3.56, 0.55) (-3.73, -0.58) (-4.56, -1.41) (-4.37, -1.15) (-2.53, 0.67) (-3.06, 0.02) (-2.07, 1.11).253.054.552 EJEMPLO A Estudio EC 1 Resultados de estudios fase III en DM. Fase aguda Tratamientos N Hamilton basal Cambio IC 95% Valor de p. Comparación con Media DE LS media Placebo 89 17.79 4.73-4.14 A Dosis 1 90 17.47 5.20-5.30 (-3.05, 0.71).222 81 17.44 5.16-5.59 (-3.38, 0.47).138 87 17.97 5.87-5.96 (-3.72, 0.06).058 EC 2 A Dosis 1 88 86 17.19 18.63 18.06 17.65 5.11 5.85 4.52 5.13-3.67-6.08-6.77-5.18 (-4.47, -0.35) (-5.15, -1.06) (-3.56, 0.55).022.003.150 EC 3 A Dosis 3 85 19.86 19.88 20.17 20.26 3.58 3.54 3.41 4.14-8.07-10.22-10.83 (-3.73, -0.58) (-4.56, -1.41) (-4.37, -1.15).007 <.001.001 EC 4 A Dosis 3 99 100 97 20.58 21.30 21.38 21.03 3.73 2.96 4.46 3.38-10.13-11.64-10.61 (-2.53, 0.67) (-3.06, 0.02) (-2.07, 1.11).253.054.552 EJEMPLO A Estudio EC 1 Resultados de estudios fase III en DM. Fase aguda Tratamientos N Hamilton basal Cambio IC 95% Valor de p. Comparación con Media DE LS media Placebo 89 17.79 4.73-4.14 A Dosis 1 90 17.47 5.20-5.30 (-3.05, 0.71).222 81 17.44 5.16-5.59 (-3.38, 0.47).138 87 17.97 5.87-5.96 (-3.72, 0.06).058 EC 2 A Dosis 1 88 86 17.19 18.63 18.06 17.65 5.11 5.85 4.52 5.13-3.67-6.08-6.77-5.18 (-4.47, -0.35) (-5.15, -1.06) (-3.56, 0.55).022.003.150 EC 3 A Dosis 3 85 19.86 19.88 20.17 20.26 3.58 3.54 3.41 4.14-8.07-10.22-10.83 (-3.73, -0.58) (-4.56, -1.41) (-4.37, -1.15).007 <.001.001 EC 4 A Dosis 3 99 100 97 20.58 21.30 21.38 21.03 3.73 2.96 4.46 3.38-10.13-11.64-10.61 (-2.53, 0.67) (-3.06, 0.02) (-2.07, 1.11).253.054.552 EC 5 A Dosis 3 115 121 21.09 21.50 3.71 4.10-5.67-9.47 (-5.55, -2.05) <.001 EC 6 A Dosis 3 136 123 20.49 20.28 3.42 3.32-7.02-8.75 (-3.45, -0.02).048 17
Moltes mercès Gonzalo Calvo 18