Surrogate Markers and its role in the Drug Development Process Aloka G. Chakravarty, Ph.D. Director, Biologics Therapeutics Statistical Staff chakravarty@cder.fda.gov The opinions expressed are those of the author and do not necessarily reflect those of the FDA

Outline Definition and motivation Biomarkers and Surrogate Endpoints – are these terms interchangeable? Regulatory Issues Case Examples Conclusion

Surrogate Marker Working Definition A laboratory or physical sign that is used in therapeutic trials as a substitute for a clinically meaningful endpoint that is a direct measure of how a patient feels, functions, or survives and that is expected to predict the effect of the therapy (Temple, 1999)

Regulatory Motivation Replace a distal endpoint with a more proximal one, can be measured earlier Can be measured more easily or frequently Can be measured with higher precision, or less subject to competing risks May be less affected by other treatment modalities Reduced sample size requirements ? Possibility of faster decision making

Surrogate Endpoints at various phases of drug development Will focus this talk on effect of Surrogate Endpoints in Phase III clinical trials – a possible FDA Critical Path Initiative Other uses: Can be used to integrate data across all phases to build an evidence base, including validation (Phase II Learn and Confirm strategy) Can be linked with external sources of information - of disease, of other treatments Can be mined for relationships of SEPs to disease, other markers, patient covariates and treatment as well as for signs of possible toxicity

Relationship: Surrogate Endpoint and Disease Need to establish strength of relationship of SEP with the disease, not just a correlation factor “A correlate does not a surrogate make” (Fleming) Need high sensitivity SE= a/(a+c) and specificity SP= d/(b+d) Attributable proportion defined as AP=SE/[1-(RR)-1] should be close to 1, where RR=a(c+d)/[c(a+b)] Suppose success is measured with respect to a distal CE as well as a proximal SE. If we can dichotomize based on both the endpoints, we get the following table. A is the number of patients that both the endpoints could pick up as success etc.

Relationship: Surrogate Endpoint and Treatment Evaluate treatment action plans on SEPs, or identify safety concerns based on SEPs Select appropriate metric to characterize treatment response, the choice depends on biological considerations as well as statistical Rank possibly useful SEPs based on AP Use SEPs to study dose response, subgroup of responders etc.

Biomarker - Definition A characteristic that is objectively measured and evaluated as an indicator of normal biologic or pathogenic processes or pharmacological responses to a therapeutic intervention Biomarkers can be measurements thought to be directly related to clinical outcomes blood pressure, blood pressure - RNA viral load total lipids, lipid fractions - CD4 count coronary artery occlusion - tumor size

Biomarker – what to consider Effects on Binding early effects such as intracellular, membrane or circulating receptor e.g. binding to ACE of ACE-Is was an early clue that the effects will be relatively prolonged than their blood level half life Effects on activity of an intrinsic or externally induced molecule Effect on an externally induced enzyme, hormone or cytokine is the effect examined e.g. inhibition of infused isoproterenol as a measure of beta blockade Effect on etiologic agents or anatomical features infectious agent pathological hallmarks of neurologic disease e.g. arteriosclerotic plaque structure

Biomarkers & Surrogate Endpoints - A Conceptual Model Clinical endpoints (for Efficacy) Surrogate Endpoints (for Efficacy) Evaluate Patient Benefit Biomarkers (for Efficacy) Conduct provisional integrated evaluation Establish linkage of biomarker with Clinical Endpoint Global Intervention Assessment Evaluate Patient Risk Surrogate Endpoints (for Toxicity) Biomarkers (for Toxicity) Clinical endpoints (for Toxicity)

Biomarkers as Surrogate Endpoints - Possible Relationships

Biomarkers as Surrogate Endpoints - Possible Relationships (contd.)

Distinction - Biomarkers and Surrogate endpoints Surrogate endpoints are a subset of biomarkers Early clue by biomarkers, validation by surrogates A biological marker is a candidate for surrogate endpoint if it is expected to predict clinical benefit (or harm, or lack of benefit or harm) based on epidemiologic, therapeutic, pathophysiologic or other scientific evidence Need to consider all possible effects COX-2 selective NSAIDs treat pain, but cardiovascular effects? TPA establishes blood flow but causes hemorrhage strokes

Distinction - Biomarkers and Surrogate endpoints (contd.) Surrogate endpoint are primarily endpoints in therapeutic intervention trials, although sometimes in natural history or epidemiologic studies For a surrogate to be useful, one must specify the clinical endpoint, class of intervention and population in which substitution of a biomarker for clinical endpoint is considered reasonable

Fast track Program To facilitate the development and expedite the review of new drugs that are intended to treat serious or life-threatening conditions demonstrate the potential to address unmet medical conditions Granted for a specific indication of a specific drug/biological product

Scheme to determine Fast Track Condition serious or life-threatening? No Yes Yes Any approved treatment for the condition? Not fast track No No Unmet Medical needs? Yes Fast track designation

Accelerated Approval 21 CFR (314 and 601) Accelerated Approval Rule, 1992 Serious or life-threatening illness Surrogate or non-ultimate clinical endpoints Post-marketing data required to “verify and describe the drug’s clinical benefit and to resolve remaining uncertainty as to the relation of the surrogate endpoint upon which approval was based to clinical benefit, or the observed clinical benefit to ultimate outcomes.”

Subpart H Special section of fast track related to surrogate endpoints Section 112 of the FDAMA of 1997, Chapter V (21 USC 351) provides for definition, designation, and request for such … has an effect either on a clinical endpoint or on a surrogate endpoint that is reasonably likely to predict clinical benefit conduct post-approval studies to validate the surrogate endpoint or otherwise confirm the effect on the clinical endpoint

Regulatory Issues Use of SEPs focus on the treatment effect mediated by a certain pathway, but in reality, multiple pathways or modalities may exist. All anti-hypertensives lower BP but could have different (better or worse) effects on endpoints (CHF, renal function, diabetes) because their mechanism of action are different and multiple They have to be comparatively evaluated as well

Four Roles of Surrogate Endpoints Efficient and improved design of trials Improved understanding of drug effects subgroup differences -dose &dose interval effects over time -withdrawal effect phramaco-dynamic effects Efficacy in new settings (e.g. pediatric) Support for results of clinical trials

Improve design of Phase II-III trials Effect (magnitude and time course) on an “etiologic SEP” can help choose dose range and regimens, titration steps for large trials give insight into tolerance, first dose effects, withdrawal effects that need study this is important for “all at once” Phase III studies, seen substantial efforts to study regimens that would have had little chance on PK/PD grounds Potential role in identifying population more or less likely to respond (as a baseline covariate)

Better understanding Subgroup differences in favorable (or not) responses sensitivity to QT effects in women or group with inherited QT abnormalities potential problems may be avoided (orthostatic effects, anti-cholinergic effects) Better labels (precautions or modified treatment plan) PD interactions

Efficacy in new settings Approval is sometimes feasible without new clinical trials where basic effectiveness is established and pathophysiology is clear ICH E-5 proposes use of PD drug response as a potential basis for “bridging study” into new regions ICH PED guidance discusses PD to bridge adult DR to pediatric population where disease is similar Depends on understanding of the SEP effect to the clinical effect

Efficacy in new setting FDA Guidance: Providing Clinical Evidence of Effectiveness for Human Drug and Biological Products Efficacy of a different dose, regimen or dosage form (e.g. post-infarction propranalol) Better the understanding of SEP relationship to the clinical outcome, the better clinical trial design

Case example I - CD4 count as SEP in HIV trials CD4 lymphocyte count widely used and accepted as a SEP for progression to AIDS ZDV approved in 1987 based on 17 weeks survival ddI approved in 1991 based on surrogate endpoint (CD4) with limited indication (in AZT failures) ddC is the first drug approved under accelerated approval regulation (1992) More than 12 other HIV drugs has been approved under this regulation since then.

Accelerated to Traditional Approval: Time and Endpoints

Endpoints used in approval of Anti-HIV Drugs CD4 Didanosine(ddI) DP or 50% drop of CD4 CD4 Dideoxycytidine (ddC) DP DAVG16 of CD4 stavudine (d4T) DP or 50% drop of CD4 CD4, HIV, p24 lamivudine (3TC) DP CD4 and HIV RNA Saquinavir mesylate DP DAVG of HIV, DP Ritonavir Change of HIV, CD4; DP DAVG CD4, DAVG HIV Indinavir sulfate Survival Change of CD4 and HIV RNA Nevirapine Time to HIV failure DAVG CD4 and HIV RNA Nelfanivir mesylate %<400 for HIV Week 48 DAVG CD4 and HIV RNA Delavirdine mesylate Time to HIV failure %<400 for HIV at Week 24 Efavirenz Time to HIV failure %<400 for HIV at Week 16 Abacavir Time to HIV failure %<400 for HIV at Week 24 Amprenavir Time to HIV failure %<400 for HIV at Week 24 Lopinavir Time to HIV failure 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Endpoints used for Anti-Viral approvals Accelerated Traditional Time Endpoint < 1995 Change in CD4 count or time-averaged change of CD4 (DAVG) < 1997 Clinical progression 1995-1998 HIV RNA load (change from baseline, DAVG, % < threshold) > 1997 HIV RNA % < 400 copies /mL or time to virologic failure > 1998 HIV RNA < 400 and/or <50 copies /ML These are the Topics proposed by PhRMA. All these questions are about non-inferiority designs. These questions are: Has DAVDP had experience with non-inferiority trials? Is DAVDP open to drug-specific proposals using this design? Are there any special considerations that would prompt FDA to think about such studies differently than the considerations described in the ICH E9 guideline?

Approaches to a better surrogate Week 16 vs. Week 24 for HIV RNA Week 24 will likely be a better predictor of clinical outcome than Week 16 FDA usually ask for Week 24 results in accelerated approval of HIV drugs. Data beyond Week 24 are also requested and reviewed Based on the predicted value of the surrogate, compute what kind of efficacy we will need to reliably predict a significant and meaningful clinical outcome at the end for traditional approval

Case Example II: CAST trial Cardiac Arrhythmia Suppression Trial (CAST) evaluated effect of encainide, flecainide and moricizine on survival of patients who had MI and had >10 premature ventricular beats per hour Reduction in ventricular ectopic contraction used as a SEP for decreased mortality Primary endpoint was death or cardiac arrest with resuscitation, either of which due to arrhythmia.

CAST trial results Unexpected results: encainide and flecainide arms stopped early : 63 patients died in encainide or flecainide arm compared to 26 in the placebo arm (p=0.0001). After continuing the trial with moricizine as the only active arm (CASTII), there was excess mortality in moricizine arm alone (17 deaths in 665 patients) as compared to no therapy or placebo group (3 deaths in 660 patients). This study had to be terminated early also. Points to the fact that surrogate markers may not always be a good predictor and have to be validated extensively before being used in a regulatory setting.

Conclusions Collection of information on the SEPs should be encouraged, it provides additional insight into the mechanism of action It can often provide supportive evidence into reliability of observed association When used as auxiliary information, can provide improvement in trial design Need to be cautious about association and inferences drawn from it