In this episode of "In the Interim…", host Dr. Scott Berry undertakes a detailed, methodical critique of ICH-E20 draft guidance language as applied to adaptive clinical trial design. Focusing on an innocuous but corruptible paragraph in Section 3.1, Scott scrutinizes the logic behind regulatory reluctance to appreciate multiple or complex adaptations in confirmatory trials. Drawing on extensive experience, he highlights how such restrictive interpretations do not reflect practical development realities, instead setting up “false choices” where alternative designs desired by regulators are infeasible. Through operational scenarios—including the SEPSIS-ACT trial, an enrichment design, and sample size re-estimation examples—Scott illustrates the empirical benefits of seamless and multi-adaptive trials for sponsors, patients, and regulators. Technical discussion addresses misconceptions about complexity and bias and stresses the value of presenting realistic alternatives when engaging with regulatory authorities. The episode ultimately encourages a more nuanced dialogue to advance efficient and scientifically robust clinical trials.

Key Highlights

• Discussion of ICH-E20 section 3.1 guidance and its operational impact on adaptive designs.
• Dissection of “false choice” dilemmas in regulatory interactions, referencing real adaptive trial submissions.
• Case-based examples: SEPSIS-ACT, enrichment, and sample size adaptation trials.
• Highlighting myths regarding bias and operational burden from multiple interim analyses.
• Emphasis on practical strategies for more effective regulatory communication about adaptive trials and realistic alternatives.

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In this episode of "In the Interim…" Dr. Scott Berry is joined by Professors Victoria Cornelius, Danny McAuley, and Anthony Gordon, for a technical review of the PANTHER trial—an international, Phase 2 adaptive platform evaluating pharmacologic interventions for ARDS. The trial is open-label and does not employ blinding, as discussed in the episode. The primary endpoint is 28-day organ support-free days (death as -1, survivors 0–28 days), analyzed with a Bayesian proportional odds model. PANTHER uses  stratification by hyper- and hypoinflammatory subphenotypes, with fixed, equal randomization within each stratum. Analyses for treatments are separated by stratum, reflecting the potential of differential treatment effects. Quarterly interim analyses allow early stopping by stratum for efficacy or futility. Content includes explicit discussion of infrastructure: rapid device deployment, centralized data for trial and future biological discovery, and governance challenges in multinational collaboration. Funding is provided by NIHR (UK), US Department of Defense, CIHR (Canada), NHMRC and MRFF (Australia), HRB (Ireland), and additional support from Germany and Japan. PANTHER is positioned to streamline Phase 2 critical care drug testing and facilitate graduation to larger platforms such as REMAP-CAP, with potential to expedite pharmaceutical evaluation and accelerate ARDS therapeutic development.

Key Highlights

• Real-time phenotyping (Randox device) to stratify ARDS patients.
• Separate Bayesian analyses by phenotype stratum.
• Open-label, fixed randomization within stratum.
• 28-day organ support-free days as a composite endpoint.
• Quarterly interim analyses enable early dropping or graduation of arms by strata.
• Central data resource and biosample collection for future research.
• Operational, funding, and device logistics for global trial deployment.
• Transition of Phase 2 results to established Phase 3 platforms (e.g., REMAP-CAP).

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In this episode of "In the Interim…", Dr. Scott Berry connects with Dr. Byron Gajewski, professor of biostatistics and data science at the University of Kansas Medical Center (KUMC), for a detailed discussion on the design, simulation, and operational realities of Bayesian adaptive clinical trials in academic environments. Gajewski discusses his academic background, training at Texas A&M, and progressive adoption of Bayesian principles based on direct experiential advantages in complex data settings. The conversation highlights KUMC’s Fixed and Adaptive Clinical Trial Simulator Working Group, which utilizes FACTS for faculty, staff, and student collaboration, enabling practical simulation, trial protocol development, and in-house applied statistical training. The PAIN-CONTRoLS Trial serves as a practical example of multi-arm Bayesian adaptive design, using response-adaptive randomization for comparative effectiveness in neuropathy research. The NIH-funded HOBIT trial is examined in detail: multi-arm structure, adaptive allocation among investigational arms, fixed control randomization, group-sequential interim analyses, and sliding dichotomy methodology for the Glasgow Outcome Scale Extended. The discussion stresses a shift to probabilistic, evidence-driven interpretation and reporting, shaping operational choices and academic culture for both investigators and trainees.

Key Highlights

• Gajewski describes how practical challenges in real-world problems catalyzed his transition to Bayesian modeling.
• KUMC’s working group integrates FACTS software in collaborative simulation and operational trial planning.
• The PAIN-CONTRoLS Trial: multi-arm Bayesian adaptive design, response-adaptive randomization, real-time analysis, and endpoint-driven allocation.
• HOBIT trial: Adaptive allocation, fixed control arm proportion, group-sequential interims, ordinal endpoint modeling.
• Emphasis on probabilistic, quantitative reporting over binary outcomes in trial analysis and interpretation.
• Cultural shift observed among academic collaborators and trainees embracing Bayesian adaptive strategies.

In this episode of "In the Interim...", Dr. Scott Berry hosts Dr. Stephen Senn, award-winning statistician and author, for a discussion on advanced challenges in adaptive and platform trial methodology. Senn draws on experience in academic, pharmaceutical, and regulatory settings to address the recent draft guidance on Bayesian statistics from the FDA and multiple controversies in clinical trial design.

Key Highlights

• Emphasizes understanding data origin and regression to the mean as essential for trial interpretation, above adherence to Bayesian or frequentist frameworks.
• Details methodological considerations for time adjustments and model complexity, highlighting that model specification and parameter handling are critical regardless of statistical school.
• Identifies the limitations of non-concurrent controls in platform trials, focusing on evolving background therapy, site participation, and protocol changes that reduce validity of historical or pooled control data.
• Analyzes blinding difficulties in trials with multiple treatments and administration modes, using “veiled” blinding as a case and noting the implications for placebo response comparability.
• Clarifies that operational efficiencies are the principal advantage of adaptive and platform trials, while purported statistical efficiencies can be exaggerated.
• Stresses the importance of presenting interim analyses transparently to DSMBs when using complex models for time or covariate adjustment, to ensure oversight and interpretation remain rigorous.

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In this episode of "In the Interim…", Dr. Scott Berry is joined by statisticians Dr. Amy Crawford, Dr. Cora Allen-Savietta, and Dr. Jessica Overbey for a technical deep dive into hierarchical composite endpoints and the win ratio in clinical trial design. The group addresses clinical and statistical justifications for layered endpoint structures, demonstrates the mechanics of pairwise win ratio analysis, and explores operational and interpretive consequences in both conventional and adaptive trials. The panel scrutinizes analytic limitations, regulatory concerns, and emerging modeling strategies—all grounded in real-world trial examples.

Key Highlights

• Precise definition and use case for hierarchical composite endpoints in cardiovascular and related trials.
• Stepwise breakdown of win ratio mechanics, tie-handling, and the distinction between effect estimation (win ratio) and hypothesis testing (FS-test).
• Discussion of endpoint prevalence and dominance, risk of clinical interpretation being tied to lower-order outcomes, the role of patient exposure, and methods to parse component contributions.
• Overview of statistical power, role of simulation, and comparative advantages over other composite approaches.
• Identification of core limitations: interpretive complexity, opaque weighting, and mutable meaning of wins with maturing data.
• Review of predictive probability for adaptive interim analysis and modeling using ordinal regression.
• Opinions of US and European regulatory perspectives including support, reservations, and expectations for transparency with graphics and complementary analyses.

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In this episode of "In the Interim…", Dr. Scott Berry interviews Professors Steven Tong and Josh Davis about the SNAP platform trial for Staphylococcus aureus bacteremia. The discussion covers SNAP’s rationale, large-scale adaptive design, methodology, and operational execution at approximately 150 hospitals in 13 countries. Key statistical questions, domain results, pediatric-adult analysis, and global implementation strategy are explored in depth. Listeners will find clear examples of how adaptive platform trials can efficiently address clinically relevant questions in infectious disease, while highlighting the nuances of trial design, statistical thresholds, and network collaboration.

Key Highlights

• High and unchanging mortality for Staphylococcus aureus bacteremia—over one million deaths annually.
• SNAP leverages silo-based structure (MSSA, MRSA, PSSA) and factorial domains for simultaneous, efficient investigation of treatments.
• Cefazolin shown non-inferior to flucloxacillin for MSSA with lower related acute kidney injury.
• In PSSA, penicillin demonstrated significantly less toxicity and favorable mortality signal over flucloxacillin; mortality difference did not meet the statistical superiority threshold.
• Futility reached in the adjunctive clindamycin domain for effect on 90-day mortality.
• Both adults and children enrolled, with pediatric results using statistical borrowing from adults in line with FDA Bayesian guidance.
• Ongoing platform expansion includes bacteriophage therapy, antiplatelet domains, and evaluation of diagnostic strategies.
• Statistical leadership: Dr. Anna McGlothlin (Berry Consultants), Dr. Julie Marsh (statistics lead).

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In this episode of "In the Interim…", Dr. Scott Berry and Dr. Kert Viele examine Bayesian borrowing in Phase 3 clinical trials, focusing on statistical handling of prior information and real-world FDA interactions. The episode opens with an analogy, comparing prior probability in Bayesian analysis to interpreting a home pregnancy test, succinctly demonstrating the effect of prior knowledge on trial interpretation. The discussion addresses technical challenges—how borrowing inflates Type I errors and why this is addressed differently under Bayesian operating characteristics. Concrete examples include dynamic versus static borrowing approaches, and formal integration of prior evidence in regulatory submissions. Case studies center on the WATCHMAN device (PROTECT AF and PREVAIL trials) and REBYOTA, illustrating FDA engagement, relevant trial design tactics, and published outcomes. The episode also critiques common pitfalls such as selective data use and improper prior construction, emphasizing the FDA’s focus on comprehensive and unbiased historical sources.

Key Highlights

• Pregnancy test analogy used to clarify prior probability in trial interpretation.
• Bayesian borrowing’s effects on Type I error and statistical thresholds.
• Case studies: WATCHMAN device (PROTECT AF, PREVAIL) and REBYOTA approvals.
• Dynamic borrowing versus static borrowing strategies in regulatory settings.
• Risks of cherry-picking and importance of unbiased, relevant prior data.
• FDA guidance and review procedures for Bayesian trials.

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In Episode 51 of "In the Interim…", Dr. Scott Berry interviews writer, producer, and performer Shaun Cassidy to examine the practical elements of storytelling that matter in scientific and statistical communication. Cassidy draws on his experience in television, music, and live performance—including his role as writer and Executive Producer of New Amsterdam—to present clear parallels between audience engagement in show business and in clinical research. The conversation prioritizes improving narrative precision, emotional resonance, and authenticity when conveying complex topics to varied audiences.

Key Highlights

• Cassidy demonstrates that audiences retain emotional impact over factual content, asserting that “people don’t remember what you say, but how you made them feel.”
• Emphasis on narrative specificity: personal, concrete details foster stronger audience connection than generalized statements, countering assumptions about broad relatability.
• Effective communication relies on reactive delivery—improvised response to audience cues—rather than rigid, memorized scripts; Cassidy notes this principle applies across disciplines.
• Role of authenticity and vulnerability: openly stating discomfort or introversion facilitates greater audience trust and personal connection, especially in technical or scientific fields.
• Anecdotes from Cassidy’s work in television, music, and teaching illustrate the central role of storytelling structure and audience feedback, with parallels drawn to professional scientific presentations.
• Alan Alda’s illustration of improv for scientists is discussed as an example of bridging technical expertise with adaptive communication skills.

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In this episode of "In the Interim…", Dr. Scott Berry and Dr. Lindsay Berry investigate the statistical foundations and clinical implications of analyzing ordinal endpoints, drawing on experience from major stroke and COVID-19 trials. Discussion centers on the Modified Rankin Scale, DAWN, MR CLEAN, and REMAP-CAP, demonstrating that methods such as proportional odds, dichotomization, and utility weighting all impose explicit or implicit clinical weights on the outcome categories. The episode presents direct mathematical derivations, exposes the equivalence between proportional odds models and value-weighted analysis, and uses real trial data to explore how statistical and clinical perspectives on endpoint weighting may diverge. Emphasis remains on transparency and the need for clinically relevant weight assignment in trial endpoints.

Key Highlights

• Structural overview and clinical significance of the Modified Rankin Scale scores.
• Illustration that proportional odds models and dichotomized analyses apply hidden, prevalence-driven or threshold-based weights.
• Utility weighting in DAWN, formulated from EQ-5D patient utilities and economic studies, with observed alignment.
• MR CLEAN investigators' critique of utility weighting; empirical data demonstrated relative consistency and challenged the claim that statistical approaches resolve variation across patients.
• REMAP-CAP platform trial: Organ Support Free Days endpoint analyzed with proportional odds imposed weights on the scale from death to free of organ support .
• Extension of these arguments to win ratio/rank-based approaches, with caution that all methods encode clinical assumptions.

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In this episode of "In the Interim…", Dr. Scott Berry marks the podcast’s one-year anniversary, sharing listener metrics, watch data, and regional engagement. He then delivers a step-by-step analysis of the FDA meeting process, detailing the progression from initial sponsor meeting requests and question submission to briefing book preparation, feedback cycles, and in-person logistics for a Type C meeting at the White Oak facility. Drawing from more than 25 years of trial design and regulatory experience, Scott offers precise guidance on technical preparation, sponsor responsibilities, and common errors in sponsor-FDA dialog, emphasizing what works and what wastes time inside the one-hour meeting constraint. His practical approach focuses on clarity, respect for process, and actionable advice.

Key Highlights

• Slightly over 30,000 people tuned in during the first year across 45 episodes; about 10,000 via audio, 20,000 via video with a global worldwide reach.
• FDA meeting workflow: request, submit four to eight questions, draft briefing book, receive written feedback, strict one-hour in-person discussion controlled by sponsor.
• Advice on briefing book content, avoiding new materials at the meeting, even what not to bring through the White Oak facility.
• Sponsor pitfalls: disingenuous patient advocacy, asking impossible questions, taking adversarial stance in statistical discussion.

For more, visit us at https://www.berryconsultants.com/