Cytel has designed and defended more adaptive trials for sponsors than any other service provider. These innovative trials have helped pharmaceutical, biotech and device companies increase their clinical success rates while reducing development time and costs.

Our experts have mastered the statistical methodologies of adaptive trials and regularly train industry and FDA biostatisticians in the latest adaptive trial designs. The methods employed are published, acceptable to regulators and validated in practice.

Cytel thought-leaders are regularly invited speakers on a range of trial innovation topics including:

• advances in Bayesian and frequentist trial design methods
• utilizing trial simulations to guide trial planning
• key operational areas, including flexible randomization and IVRS integration
• drug supply forecast and management

We omit sponsor and product information to preserve client confidentiality.

Adaptive Trial Case Study #1
Sample size re-estimation in phase 3 confirmatory trial

Disease Areas: Schizophrenia, Psoriasis, Influenza

Situation: Initial sample size computation based on crucial, but very limited delta and sigma statistical information

Procedural Milestones

• Designed several trials with a mid-course correction to the initial sample size based on interim results
• Inserted detailed statistical methodology for valid inference into SAP
• Addressed follow-up questions from FDA and EMEA
• Chaired an Independent Interim Analysis Committee to create interim report from unblinded data and make a recommendation to sponsor concerning the adaptive changes

Adaptive Trial Case Study #2
Seamless phase 2/3 design

Disease Area: CNS

Situation: Start study with several doses. Make pairwise comparisons to placebo at interim. Drop poorer performing doses and increase sample size for remaining doses.

Procedural Milestones

• Developed criteria based on conditional power for dropping doses and increasing sample size
• Wrote detailed statistical methods, for inclusion in protocol, demonstrating validity of the adaptive procedure
• Created a simulation tool used by sponsor and FDA to verify the trial's likely operating characteristics (type-1 error, power, expected sample size, number of arms carried forward after interim analysis)
• Together wih sponsor, successfully defended the trial design before FDA review

Adaptive Trial Case Study #3
Seamless phase 2/3 trial revisal for orphan drug

Disease Area: Neurological Disease

Situation: An Orphan Drug indication for a HIV-associated neurological disease. The sponsor’s phase 2 study identified three possible effective doses.

The sponsor company submitted a combined phase 2/3 “seamless” design of their own, but it was rejected by the FDA. At this point the company engaged Cytel to analyze and redesign the trial.

Procedural Milestones

• Investigated several options for the study design:
• Single Four-Arm Trial: Run a single phase 3 four-arm trial; three dose groups, plus placebo
• Two Separate Trials: Run a four-arm phase 2 trial to select the best dose; then run a second independent phase 3 two-arm trial
• Seamless phase 2/3 approach: start with four arms; select best dose at interim; continue with two-arm trial
• Created application-specific simulation software and evaluated operating characteristics of different designs
• Recommended an implementation of the seamless phase 2/3 design based on the recent publication (Posch et al, 2005)
• The recommended seamless design was accepted by FDA review board

Adaptive Trial Case Study #4
Monitoring accruals and events in a phase 3 survival endpoint trial

Disease Area: Multiple Sclerosis

Situation: Trial must be completed within 21 months for business reasons. Goal is to monitor events, recommend termination when target number of events have arrived, and estimate when that will happen in regular reports.

Procedural Milestones

• Designed 21-month trial based on initial assumptions about hazard rates and accrual rates
• Accessing data on a regular basis through remote log-in to electronic case report forms and interfacing with the sponsor’s IVRS vendor
• Producing monthly reports on projected accrual and quarterly reports on projected study duration using Bayesian forecasting tools
• Unblinding individual patient data if requested by event adjudication committee

Adaptive Trial Case Study #5
Longitudinal trial with several interim looks to drop doses and potentially trigger secondary study

Disease Area: Osteo arthritis of the knee

Situation: Radiologic measurements of joint space narrowing at baseline, month 12 and month 24. Up to six interim analyses.

Procedural Milestones

• Second pair of eyes for trial design. (Evaluate criteria for dropping a dose, terminating for futility, adding one additional measurement at 36 months, and starting a second trial based on interim results.)
• Serve as member of DMC (the independent data monitoring committee) with responsibility for making adaptive change recommendations to sponsor
• Cytel also acts independent statistical center and produced the unblinded interim reports for the DMC

Adaptive Trial Case Study #6
Pain relief study

Disease Area: Rheumatoid and osteo arthritis

Situation: Endpoint is improvement at week 12 relative to baseline, measured on a visual analog scale. Large number of drop-outs are expected. Drop-out rates might be related to treatment. FDA insists on BOCF method for handling drop-outs.

Procedure Milestones

• Developed numerous simulations with various alternative patterns of informative drop-outs for the two arms
• BOCF implied large number of ties.
• Compared t-test and Smirnov test, adjusted for ties, in the simulations (only available in StatXact!)
• Sponsor decided to use Smirnov test and amended the protocol

Adaptive Trial Case Study #7
Rare disease orphan drugs opportunity using two trial types: survival and longitudinal

Disease Area: Nephrology and metabolic disease

Situation: Two studies involving orphan drugs in a rare disease population. Sample size determined by availability of patients. Robust results can only be produced by increasing duration of follow-up.

Procedural Milestones

• Designed both trials; one with survival endpoint and other with longitudinal endpoint (6MWT)
• Survival: based on number of events observed at interim, specify when the trial should be terminated
• Longitudinal: based on between and within subject variance estimates at interim, specify how many additional repeated measurement should be taken
• Addressed FDA questions on trial design
• Addressed questions from medical, regulatory members of study team at the sponsor’s site
• Produced unblinded interim report for DMC for longitudinal trial
• Served on DMC for the longitudinal trial

Adaptive Trial Case Study #8
Group sequential and adaptive designs for a cardiac ultrasound device study

Disease Area: Cardiac arrhythmia

Situation: Dual uncertainty in the endpoint: treatment effect δ = 30, 45 or 60 secs and std dev σ = 90 or 100 secs.

Procedural Milestones

• Conducted protocol review with sponsor
• Verified and reproduced the sponsor’s sample size calculations for the fixed single-look designs with all six combinations of (δ, σ)
• Obtained sample sizes for a different randomization ratio (1:1 rather than 3:1)
• Total sample sizes were roughly 350, 160 or 80 depending on δ = 30, 45 or 60 secs
• Designed group sequential trials with early stopping for efficacy
• Designed for maximum sample size of roughly 350 with looks at 80 and 160 patients
• Investigated the likely impact of three possible spending functions
• Produced tables to illustrate sample size inflation and final testing p-value penalty
• Simulated the trial under various (mis)specifications of (δ, σ)
• Reported the trial’s probability of success at each interim look and also overall
• Reported the distribution of sample sizes that stopped the trial
• Designed an adaptive two-stage designs using the Cui, Hung and Wang (1999) method to control the type I error rate
• Designed for minimum 80 patient sample size w/ option to increase sample size at interim look using an O’Brien Fleming spending function
• Investigated two filters for the estimated treatment effect at the interim look (only adapt only if estimate is within interval defined by the filter)
• Simulated the trial under various (mis)specifications of (δ, σ)
• Reported the trial’s probability of success (concluding in favor of the treatment) for both the overall trial and for each interim look
• Reported the expected sample size of the trial and the probability of enacting an adaptation

Conclusion: Produced and submitted report demonstrating that group sequential design would be simpler to implement, however for financial reasons the adaptive design was most attractive to the sponsor

Adaptive Trial Case Study #9
Trial simulations reveal best design option;
subsequent trial interim analysis

Disease Area: CNS rare disease

Situation: Study data outcomes: normal, binomial, longitudinal data; Two arms: control and experimental therapy

Procedure Milestones

• Used extensive simulations to compare operating characteristics of potentially attractive adaptive designs with the simpler information-based, group-sequential and single-look designs of these trials
• Showed that in this case, simpler designs are substantially more efficient and that more sophisticated designs may face unanticipated difficulties
• Recommendation to use well-established versions of flexible designs was accepted by the sponsor
• Analyzed data at interim look

Adaptive Trial Case Study #10
Phase 2 trial design with Bayesian methods

Disease Area: cardiovascular drug

Procedure milestones of original design:

• Double blind, randomized, parallel group
• Placebo + four doses (2.5, 5, 10, 20 mg)
• Fixed sample size: 400 subjects, 80/arm
• Accrual time = 24 weeks
• Primary endpoint (binary) at week 12
• Target dose is ED80

Alternative adaptive design:

• Randomize equally to each dose up to interim look.
• Interim look at week 18 (100 observations of end-point)
• Compute the Bayesian predictive probability of at least 80% response rate for each dose,
• Drop arms using predetermined rules

Illustrative rules:

• Drop dose if predictive probability is less than 0.4
• If two doses have predictive probabilities greater than 0.8 of at least 80% response rate drop the higher dose

Statistical analysis:

• Standard frequentist hypothesis testing methods used to determine which doses differ from placebo (FDA - guidance) Specifically:
• The p-values from the two stages can be combined (using Bauer and Keiser method)
• Adjustments for multiple comparisons are available (Hochberg and Tamhane)
• Simulations with different scenarios were used to obtain power and number of subjects on effective doses
• Results showed superiority of adaptive design over the original design

Drug supply considerations:

• Adaptive designs lead to uncertainty in the quantity of doses required
• Calculated the units of each dose required under different scenarios, determining only a modest increase in drug requirement would be required

Adaptive Trial Case Study #11
Bayesian-based adaptive phase 2 dose-finding trial design simulation

Disease Area: Dental pain

Adaptive Design Parameters

• Primary endpoint is average pain relief from 0-8 hours after single dose treatment after surgical removal of molars
• Placebo + seven dose candidates
• Adaptive allocation of doses to subjects based on responses of earlier subjects
• Allocation rules designed to assign doses in the rising part of the dose response curve to improve response estimation at “interesting” doses

Procedure Milestones

• Simulations used to investigate operating characteristics of different sample sizes for several dose-response scenarios
• Data from previous dental pain trials used to develop simulation scenarios.
• Simulations showed that one adaptive trial can replace two standard PoC and dose-finding trials and has greater power than PoC while requiring 50% smaller sample size for the same Mean Square Error in response estimation at each dose
• A response-adaptive randomizer program developed for real-time deployment during trial