In this episode of "In the Interim…", Dr. Scott Berry interviews Dr. Andrew Thomson, owner and lead consultant of Regnitio. Thomson discusses his academic progression from mathematics at Cambridge to a Master’s at Southampton and advanced study with Prof. Sylvia Richardson at Imperial College, followed by doctoral work in cluster randomized trials at the London School of Hygiene and Tropical Medicine. He recounts the realities of regulatory roles, including contemplative study of data, working within multidisciplinary teams, and delivering regulatory assessments to senior committees. The episode contrasts EMA’s collaborative cross-country structure against the more centralized FDA process and explores methodological challenges faced by both. Scott and Andrew discuss regulatory expectations for interim analyses, the definition and metrics of trial complexity, and differing approaches to Type I error control across agencies. The conversation also covers the rapid adoption and adaptation of platform trials during COVID-19, and the impact on trial evaluation frameworks. Concluding, Thomson explains the motivation for launching Regnitio, emphasizing how regulatory perspective and multidisciplinary insight can support informed decision-making throughout clinical development.
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In this episode of "In the Interim…", Dr. Scott Berry and Dr. Kert Viele analyze how regulatory, editorial, and science community standards often impose additional, inconsistent requirements for novel methods in clinical trial design, rarely applied to standard approaches. Examples from oncology, enrichment trials, platform studies, and endpoint analysis illustrate how adaptive and Bayesian designs are frequently subject to higher scrutiny, shifting metrics, or distinct evidentiary demands. The episode covers technical and regulatory issues, such as the selective application of Type 1 error controls, evolving multiplicity guidance, and challenges in ethical reasoning with adaptive allocation. Scott and Kert frame the discussion with empirical comparisons and advocate for the use of clinical trial simulation to ensure fair, metric-driven evaluation of both novel and legacy designs.
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In this episode of "In the Interim…", Dr. Scott Berry examines the mathematical foundations and efficiency claims of the promising zone design for adaptive sample size in clinical trials. Scott unpacks the conditional power thresholds that trigger sample size increases without the need to adjust alpha, as originally presented by Mehta & Pocock. He systematically demonstrates, via simulation, that the promising zone rarely provides meaningful efficiency gains over fixed designs and is consistently outperformed by group sequential designs that allocate alpha across multiple analyses. Using a driving-route analogy, Scott highlights the practical flaw in making pivotal trial decisions earlier than necessary due to arbitrary statistical rules rather than observing current data. He underlines that at Berry; simulation efforts have yet to reveal a scenario where the promising zone design is more efficient than a thoughtfully constructed group sequential or Goldilocks trial. The episode urges trialists to simulate, compare, and optimize—not to accept appealing mathematical tricks without rigorous evaluation.
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Episode 30 of “In the Interim…” features Dr. Janet Wittes, Fellow of the American Statistical Association, past president of the Society of Clinical Trials, and founder of Statistics Collaborative, in discussion with Dr. Scott Berry. Dr. Wittes details her progression from Radcliffe biochemistry to Harvard statistics, shaped by targeted mentorship and her family’s insistence on advanced scientific training. She describes teaching at Hunter College, her NIH/NHLBI tenure overseeing extensive DSMB work, and the launch of Statistics Collaborative 32 years ago, building the business with her children and their peers. The episode explores her consulting on clinical trial design for orphan and neglected diseases—malaria, dengue, leishmania, ALS—and vaccine development, with technical commentary on adaptive trial methods, operational issues in low-resource contexts, and decision-making for small-sample trials. Dr. Wittes reflects on statistical leadership, ongoing DSMB involvement, and the importance of evidence-driven public health. She underscores the need for contextual and cultural awareness in trial design, illustrated by her Lilith magazine story on kosher certification and challenges in stakeholder understanding. Discussion covers career obstacles, the evolution of clinical science, vaccine advocacy, and the critical role of diversity and practical on-site knowledge in advancing statistical research.
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In this episode of "In the Interim…", Dr. Scott Berry chats with Frank Harrell, a professor of Biostatistics at Vanderbilt University and W.J. Dixon Award winner. Harrell describes his transition from frequentist to Bayesian clinical trial design, prompted by a decisive meeting with Dr. Don Berry, informed by David Spiegelhalter’s published work. The dialogue addresses persistent academic opposition to Bayesian methods, operational constraints in trial implementation, regulatory work at FDA, and technical Bayesian modeling details.
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In this episode of “In the Interim…”, Dr. Scott Berry interviews Dr. Derek Angus, Distinguished Professor and Chair of Critical Care Medicine at the University of Pittsburgh and Senior Editor at JAMA. The discussion addresses the decades-long controversy surrounding steroid use in community-acquired pneumonia (CAP) and sepsis. The episode delivers a chronological assessment of the evidence base—summarizing trial results from pivotal studies, including CAPE COD, REMAP-CAP, ADRENAL, and multiple French trials led by Dr. Djillali Annane. Dr. Angus analyzes why discrepancies persist in outcomes, clinical recommendations, and international guidelines, and underscores the challenge of heterogeneous treatment effects. The episode closes with an argument for adaptive trial designs, Bayesian inference, and embedded randomization within learning health systems as critical tools for clarifying complex response patterns and improving patient care.
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Dr. Scott Berry hosts this episode of "In the Interim…", opening with statistical analysis of elite athletes before focusing on the misunderstood role of clinical trial simulation. He distinguishes simulation as a predictive tool from its use as an in-silico process that enables trial design exploration, iteration, and optimization. Clinical trial simulation provides a mechanism for iterative comparison of multiple designs, driven by ongoing team feedback and evolving trial objectives. Scott stresses that rigid simulation plans are “not productive,” since the most effective designs typically emerge when stakeholders view real trial examples and suggest new design options in real time. The ICECAP trial serves as a key illustration, where the final design was shaped by simulation-informed team input across multiple iterations, from three tested durations to ten with response adaptive randomization. Scott also discusses the creation of the FACTS software, highlighting its ability to test alternative designs rapidly, present side-by-side comparisons, and conduct counterfactual analyses—revealing what different trial configurations would have produced using the same simulated datasets.
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In this episode of "In the Interim…", Dr. Scott Berry and Dr. Kert Viele review the ICH E20 draft guidance on adaptive clinical trial designs, offering a technical yet accessible breakdown for trial sponsors, practitioners, and those interested in clinical development. Drawing on their practical experience in creating and presenting adaptive trial designs to regulators, they discuss the document’s strengths, areas of consensus, and where cautionary or restrictive language appears. Listeners are guided through the evolving regulatory landscape, distinctions between Bayesian and frequentist approaches, and what new harmonization efforts mean for planning adaptive confirmatory trials. The episode conveys hands-on examples, such as the Sepsis ACT seamless trial and the ROAR pan-tumor trial, illustrating technical points with real-world context. Key operational topics—blinding, operational bias, adaptive design reports, and clinical trial simulations—are addressed. The discussion includes practical advice on navigating regulatory dialogue, limitations of ICH E20 in early-phase or nontraditional designs, and the necessity of clear, justification for adaptive (complex) trial features.
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In this episode of "In the Interim…", Dr. Scott Berry and NIH’s Dr. Michael Proschan conduct a detailed discussion from opposing viewpoints on response-adaptive randomization (RAR) in clinical trials. The discussion focuses on where they agree – on the positives and negatives of RAR, and where they disagree on its scientific use.
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In this episode of "In the Interim…", Dr. Scott Berry, Dr. Elizabeth Lorenzi, and Dr. Amy Crawford discuss the STEP platform trial’s statistical methodology for evaluating which acute stroke patients benefit and which do not from endovascular therapy (EVT). The discussion critiques the inadequacy of traditional clinical trials powered for a single population to show benefit, as the goal of the trial is to identify who benefits, not if the entire population has a net benefit. The team walks through the development and simulation of a Bayesian change point model, addressing heterogeneous treatment responses across the NIH Stroke Scale. The adaptive platform design leverages scheduled interim analyses to draw timely, data-driven conclusions about patient subgroups, improving trial efficiency and relevance. The episode also previews scaling to two-dimensional modeling, incorporating both stroke severity and time since last known well, and emphasizes ongoing clinical trial simulation and close integration between clinicians and statisticians throughout trial design and execution.
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This episode of "In the Interim…" features Dr. Scott Berry, Dr. Kert Viele, and Dr. Melanie Quintana of Berry Consultants dissecting the technical and operational landscape of Bayesian statistics in clinical trial design. The episode discussed what is Bayesian statistics, the impact of informative and non-informative priors, and clarifies when and why Bayesian approaches surpass frequentist analyses—especially in adaptive, platform, and rare disease trial settings. The discussion directly challenges the misconception that Bayesian methods “lower the bar," presenting evidence that they often require broader data synthesis and can raise evidentiary standards.
Key regulatory developments at FDA and EMA are reviewed, with attention to updated guidance and increased adoption. Case studies illustrate Bayesian methods in practice, including the prospectively combined phase 2 and 3 analysis for REBYOTA approval; hierarchical modeling in GNE myopathy; shared controls and endpoint integration in the HEALEY ALS Platform Trial; and robust subgroup borrowing in the ROAR basket trial. The team also addresses technical challenges such as multiplicity, subgroup analysis, complexity in endpoint modeling, and appropriate strategies for blending Bayesian and frequentist approaches for maximum regulatory and scientific clarity.
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Dr. Scott Berry and Dr. Kert Viele discuss the origins and implementation of the “time machine” modeling approach, beginning with sports analytics and progressing to adaptive platform clinical trials. The episode focuses on how techniques for comparing athletes across eras translate into methodology for platform trials.
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In this episode, Dr. Don Berry and Dr. Scott Berry provide an in-depth account of I-SPY 2, focusing on the trial’s use of the “time machine” methodology—a Bayesian solution allowing bridging across arms to inform ongoing analyses. The discussion details how predictive probabilities and adaptive randomization shaped pivotal decisions, including the handling of Pertuzumab’s approval and Neratinib’s subtype-specific performance. This episode also documents the technical and operational contributions of Laura Esserman, Anna Barker, Janet Woodcock, Meredith Buxton, and Ashish Sanil, clarifying the roles that enabled the platform’s success and broader impact on subsequent adaptive trials.
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In Episode 20 of Berry’s "In the Interim..." Podcast, The Legend of I-SPY 2 - Part A, Dr. Don Berry and Dr. Scott Berry discuss the origins and design of the I-SPY trials. Their conversation explains the inefficiency of traditional adjuvant breast cancer trials and details the shift to the neoadjuvant approach, where tumor response can be observed prior to surgery.
I-SPY 1 served as a proof-of-concept using MRI for probabilistic prediction of pathologic complete response (pCR). I-SPY 2 represents a major advancement in clinical trial science, introducing a multi-arm bandit methodology, integration of biomarker-driven subtypes and signatures, and a structured funding model that transitioned from philanthropy to “pay to play” industry support.
This episode of "In the Interim..." features an in-depth discussion of the StrokeNet Thrombectomy Endovascular Platform (STEP), a multi-domain, multi-factorial, adaptive platform trial for acute stroke, anchored in the NIH StrokeNet network. Guests Dr. Eva Mistry (University of Cincinnati) and Dr. Jordan Elm (Medical University of South Carolina) join us to explain how STEP enables simultaneous investigation of multiple treatment strategies in patients with acute ischemic stroke. The conversation details the use of a master protocol, the integration of industry partners through the Other Transactional Authority (OTA) NIH mechanism, and innovative statistical designs to efficiently identify improved treatment strategies.
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Dr. Scott Berry applies a statistician’s review of a random trial result published in JAMA – the FAIR-HF2 clinical trial. Interrogating the frequentist paradigm and the focus on the binary outcome of the primary hypothesis test. He scrutinizes the Hochberg multiplicity adjustment, challenges the prevailing disregard for accumulated scientific evidence, and contrasts the limitations of black/white view of clinical trial of over 1000 patients and 6 years of enrollment. A contrast is made to what a potential Bayesian approach, grounded in practical trial interpretation and evidence integration would look like. The episode argues how current norms, created by dogmatic statistical views, in clinical trial analysis can obscure or perhaps mislead from meaningful findings and limit the utility of costly, complex studies.
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Scott Berry convenes co-authors Kert Viele, Joe Marion, and Lindsay Berry to discuss the statistical and developmental nuances of inferentially seamless phase 2/3 clinical trial designs. The group dissects the simple method for distributing alpha when including stage 1 data, whether it is a good idea to distribute alpha, and the optimal allocation of sample size when Stage 1 data are carried forward, all referencing their recently published work in Pharmaceutical Statistics.
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In this solo episode of "In the Interim...", Scott Berry, President and Senior Statistical Scientist at Berry Consultants, addresses deep-rooted confusion in the field of adaptive clinical trial design surrounding the concept of “spending alpha.” Drawing on practical experience and rigorous statistical foundations, Berry addresses the prevailing language and myths that conflate interim analysis with loss of type I error. He clarifies that, with planned and transparent allocation of alpha, interim analyses enable more power with more efficient design, and robust clinical trials—without sacrificing statistical validity. This is a precise and fact-driven examination for those demanding technical clarity, not marketing gloss.
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Scott Berry, Founder of Berry Consultants, interviews Professor Craig Ritchie—specialist in brain health and neurodegenerative diseases, Chief Investigator of EPAD (European Prevention of Alzheimer Dementia), and CEO of Scottish Brain Sciences—for a broad discussion of platform trial methodology in Alzheimer’s Disease research as well as looking towards the future of drug development. The conversation dissects the origins and ambitions of the EPAD initiative, the conception and scientific function of the readiness cohort, and the pragmatic obstacles to deploying innovative trial models within rigid institutional frameworks. Professor Ritchie details why the EPAD platform trial failed to initiate any therapies, explores the fallout and industry shifts following COVID-19, and maps how Scottish Brain Sciences is directly applying these lessons—establishing the IONA readiness cohort to drive integration between clinical research and clinical practice.
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• Systematic review of EPAD’s objectives, specifically the platform trial and the development of a readiness cohort to streamline patient recruitment
• Detailed account of practical barriers that prevented EPAD from launching interventional arms, including pharmaceutical sponsor reluctance, inflexible IMI funding mechanisms, and the inherent risk aversion surrounding novel platform structures
• Discussion of participant contribution to research design and delivery—an early demonstration of patient involvement models now broadly recognized as best practice
• Analysis of COVID-19's dual impact—derailing EPAD's momentum while catalyzing a change in industry and regulatory acceptance of platform trials in drug development
• Tracing the origins and operationalization of the IONA readiness cohort at Scottish Brain Sciences, including direct integration of recruitment, biobanking, and engagement systems to address the translational gap in dementia medicine
• Evidence-based critique of persistent use of conventional clinical trial formats in Alzheimer’s disease, dissecting operational, financial, and data limitations that stall progress
In this engaging episode of "In the Interim...", host Dr. Scott Berry is joined by Dr. Nick Berry to explore the intriguing statistical parallels between sports and drug development, focusing on the concept of "regression-to-the-mean." Presenting examples that seem clear in sports, they discuss how these insights can illuminate the challenges faced in clinical trials and scientific inferences in medical decision making. Whether you're a statistician, drug developer, or sports enthusiast, this episode offers valuable perspectives on data interpretation and statistical phenomena.
Key Highlights:
• Discussion on how lessons from sports can benefit drug developers, emphasizing the concept of regression-to-the-mean.
• Personal anecdotes from Scott and Nick's experiences, illustrating statistical learning through sports.
• Examination of the regression-to-the-mean phenomenon through examples from baseball and golf.
• Exploration of how misunderstanding the regression-to-the-mean can lead to poor decision-making in clinical trials.
• Insights into placebo effects and how they are often confused with natural statistical phenomena.
• How regression-to-the-mean impacts expectations in financial markets and personal finance decision-making.