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In the Interim...
Berry
33 episodes
6 days ago
A podcast on statistical science and clinical trials. Explore the intricacies of Bayesian statistics and adaptive clinical trials. Uncover methods that push beyond conventional paradigms, ushering in data-driven insights that enhance trial outcomes while ensuring safety and efficacy. Join us as we dive into complex medical challenges and regulatory landscapes, offering innovative solutions tailored for pharma pioneers. Featuring expertise from industry leaders, each episode is crafted to provide clarity, foster debate, and challenge mainstream perspectives, ensuring you remain at the forefront of clinical trial excellence.
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Mathematics
Health & Fitness,
Medicine,
Science
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All content for In the Interim... is the property of Berry and is served directly from their servers with no modification, redirects, or rehosting. The podcast is not affiliated with or endorsed by Podjoint in any way.
A podcast on statistical science and clinical trials. Explore the intricacies of Bayesian statistics and adaptive clinical trials. Uncover methods that push beyond conventional paradigms, ushering in data-driven insights that enhance trial outcomes while ensuring safety and efficacy. Join us as we dive into complex medical challenges and regulatory landscapes, offering innovative solutions tailored for pharma pioneers. Featuring expertise from industry leaders, each episode is crafted to provide clarity, foster debate, and challenge mainstream perspectives, ensuring you remain at the forefront of clinical trial excellence.
Show more...
Mathematics
Health & Fitness,
Medicine,
Science
Episodes (20/33)
In the Interim...
A Visit with Andrew Thomson

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.

Key Highlights

  • Academic and professional pathway: Cambridge, Southampton, Imperial College, London School of Hygiene and Tropical Medicine
  • Roles as a statistical assessor: analysis, collaborative review, expert panel presentations
  • EMA vs. FDA: consensus-driven versus centralized approaches, harmonization challenges
  • Trial complexity, Interim analyses, and diversity in regulatory interpretations
  • Adoption and practicalities of platform trials during the COVID-19 response
  • Consulting goals: integrating regulatory perspective and broad expertise for drug development decisions

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

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6 days ago
43 minutes

In the Interim...
Moving Clinical Trial Goalposts

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.

Key Highlights:

  • Oncology combination therapy trial with Bayesian borrowing facing heightened regulatory caution versus single-arm historical controls.
  • Hierarchical versus pooled analysis in enrichment/basket trials, with focus on error definitions and subgroup effects that have always existed.
  • ICH E20 guidance potentially discourages use of enrichment by imposing new subgroup comparison burdens absent from standard trials.
  • Platform trial multiplicity rules contrasted with parallel single-arm trials; regulatory stance continues to evolve.
  • Ethical debate on adaptive allocation: questioning rationale behind adaptive randomizing may be ethically challenging, but fixed allocation is okay despite same interim data.
  • Critical review of explicit utility weighting in the DAWN trial, despite alternative methods having the same issues

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

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1 week ago
37 minutes

In the Interim...
The Not So Promising Zone Design

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.

Key Highlights

  • Explanation of the promising zone’s conditional power mechanism and alpha control.
  • Simulation-based comparison of power and average sample size across design types.
  • Direct comparison of group sequential vs. promising zone designs.
  • Discussion of futility rules and their impact on design choice.
  • Commentary on Goldilocks designs for incomplete data.

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

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3 weeks ago
39 minutes

In the Interim...
A Visit with Dr. Janet Wittes

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.

Key Highlights

  • Early academic transition from biochemistry to statistics.
  • Serendipitous transition from academic career at Hunter College to Branch Chief of biostatistics at NIH/NHLBI.
  • Founding Statistics Collaborative, business growth with children, and specialization in orphan disease trials.
  • Consulting expertise in adaptive design, small-sample challenges, tropical and vaccine studies.
  • Continued advocacy for vaccines, scientific rigor, and ethical public health practice.
  • Importance of representation and context in science, demonstrated by real-world consulting examples.
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1 month ago
40 minutes

In the Interim...
Bayesian Clinical Trials with Frank Harrell

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.

Key Highlights

  • Harrell credits Don Berry’s direct influence for converting him to Bayesian methods during his early career at Duke, despite entrenched academic resistance.
  • Discusses early cardiovascular research at Duke, experiences with large multicenter trials, and later founding Vanderbilt’s Biostatistics department.
  • Details the compromise of using Bayesian interim monitoring and frequentist primary analyses under NIH and regulatory mandates.
  • Outlines design and publication of the ORBITA cardiovascular trial (Imperial College London), using all-Bayesian longitudinal ordinal methodology—Lancet reviewers required all analyses remain Bayesian, rejecting inclusion of a mixing frequentist and Bayesian analyses.
  • Critiques simulation of Type 1 error within Bayesian trial designs.
  • Addresses deficiencies in eliciting utilities for clinical endpoints, underscoring operational challenges in longitudinal ordinal modeling and ethical imperatives for efficient early stopping.
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1 month ago
47 minutes

In the Interim...
A Visit with Dr. Derek Angus

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.

Key Highlights

  • Historical evolution of clinical trials studying steroid regimens for CAP/sepsis
  • Review of CAPE COD, REMAP-CAP, ADRENAL, and Annane-led French trials showing conflicting signals.
  • Discussion of persistent heterogeneity in trial populations, interventions, and endpoints.
  • Identification of methodological limitations—control contamination, endpoint definitions, varying inclusion criteria.
  • Exploration of Bayesian and adaptive trial design, and operationalization of learning health systems to resolve evidence gaps.

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

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1 month ago
41 minutes

In the Interim...
The Mystery of Clinical Trial Simulation

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.

Key Highlights

  • Simulation contrasted as a predictive tool versus engine for iterative design evaluation.
  • Emphasizes design process as team-driven and iterative, not prescriptive.
  • Use of concrete example trials enhances communication across multidisciplinary teams.
  • FACTS software enables design flexibility, in silico iteration, and comparative scenario analysis.
  • ICECAP trial as an instance of simulation-informed design adaptation.

For more visit: https://www.berryconsultants.com/

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1 month ago
41 minutes

In the Interim...
Discussions on the ICH E20 Draft Guidance

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.

Key Highlights

  • ICH E20 as a global regulatory framework for adaptive designs
  • Tone and caution in guidance may shape sponsor interpretation
  • Seamless, Bayesian, and enrichment all confirmatory trials
  • Operational guidance: reporting, simulation, interim, and blinding requirements
  • Emphasis on justification and transparent communication with regulators

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

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2 months ago
38 minutes

In the Interim...
A Discussion with Michael Proschan on Response-Adaptive Randomization

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.

Key Highlights

  • Potential issues of using RAR: Potential temporal trends, unblinding, reduction in statistical efficiency in 2-arm trials
  • Potential benefits include improved statistical efficiency in multi-arm trials  depending on the goals (e.g. dose-finding trials).
  • Potential unblinding of results in non-blinded trials and the need for operational excellence.
  • Ethical and Bayesian perspectives are considered, but emphasis remains empirical.

For more visit: https://www.berryconsultants.com/

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2 months ago
44 minutes

In the Interim...
STEP Statistical Modeling

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.

Key Highlights

  • STEP platform master protocol and the NIH StrokeNet collaborative infrastructure
  • Clinical rationale for Bayesian change point modeling of the effect of EVT across the patients
  • Shift from single to dual change point models to reflect regions of equivalence
  • Development of custom C code and MCMC samplers due to limits of standard tools
  • Interim analyses direct adaptive enrollment and define actionable conclusions
  • Future extensions to multidimensional change point curves modeling 
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2 months ago
33 minutes

In the Interim...
Bayesian Approach in Clinical Trials

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.

Key Highlights

  • Clear explanation and real-world examples of Bayesian analysis in clinical trials.
  • Theoretical and practical distinctions from frequentist methods
  • Practical breakdown of control sharing, endpoint integration, and subgroup borrowing.
  • Regulatory position and the increasing acceptance of Bayesian trial designs and analyses.
  • Case examples: REBYOTA, GNE myopathy, HEALY ALS Platform Trial, ROAR basket trial.
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2 months ago
43 minutes

In the Interim...
The Time Machine

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.

Key Highlights

  • Sports analytics as foundation: Early work of modelling athlete comparisons across eras using bridging methodologies.
  • Platform trial application: The time machine model in I-SPY 2 enabled efficient control allocation through overlapping arms over extended trial periods.
  • Core modeling principles: Additive treatment effect assumptions and the necessity of sufficient temporal overlap for reliable era comparisons.
  • Statistical implementation: Approaches include categorical era adjustment and Bayesian smoothing splines for modeling change over time.
  • Limitations and disease specificity: In conditions with rapid clinical or epidemiologic change, such as COVID-19, non-concurrent controls are avoided due to high risk of era by treatment interaction.
  • Regulatory and methodological distinction: The model leverages within-trial overlapping data collected under a unified protocol, contrasting sharply with external or historical controls.
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3 months ago
39 minutes

In the Interim...
The Legend of I-SPY 2 - Part B

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.

Key Highlights

  • Introduction of the “time machine” concept, enabling valid comparison between experimental and control arms even when enrollment periods differ—a pragmatic solution originally utilized in sports examples for evolving platform trials as treatments and control arms change.
  • Ongoing trial conduct driven by a Bayesian adaptive algorithm, developed and maintained by Berry Consultants statisticians, which computes predictive probabilities to guide arm graduation, futility, and real-time adjustment of randomization probabilities.
  • Neratinib serves as a case study in subtype-specific adaptive randomization: the platform set randomization probability to zero in subtypes without signal, while effective subtypes increased randomization and advanced to graduation.
  • I-SPY 2’s methodologies shaped subsequent adaptive platform trials (GBM AGILE, Precision Promise, COVID-19 ACTIV networks), with regulatory acceptance reflected in FDA guidance and Janet Woodcock’s public recognition of adaptive randomization as “adequate and well controlled” for registration studies.
  • Specific recognition: Laura Esserman (trial leadership), Anna Barker (funding and strategic input), Janet Woodcock (FDA guidance and adaptive methods support), Meredith Buxton (logistics; GCAR leadership), and Ashish Sanil (Berry Consultants; ongoing algorithm implementation).
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3 months ago
25 minutes

In the Interim...
The Legend of I-SPY 2 - Part A

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.

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3 months ago
40 minutes

In the Interim...
The STEP Platform with Dr. Eva Mistry and Dr. Jordan Elm

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.

Key Highlights:

  • STEP utilizes a master protocol within NIH StrokeNet, unifying eligibility, procedures, and data collection across all study domains.
  • The platform supports multiple research questions.
  • In an initial domain STEP applies a statistical change-point model to empirically estimate the thresholds where EVT is effective, neutral, or potentially deleterious based on medium vessel occlusions and baseline clinical status. 
  • Protocols may be adapted in response to new external data, including pausing and revising enrollment in specific subpopulations when emerging science warrants.
  • Shared control groups are used wherever applicable, improving trial efficiency by reducing the number of patients allocated to control arms and allowing eligible patients to contribute to multiple domains when protocol and scientific rationale permit.
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3 months ago
40 minutes

In the Interim...
A Statistician reads JAMA

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.

Key Highlights

  • FAIR-HF2 randomized 1,105 patients with heart failure and iron deficiency to intravenous ferric carboxymaltose or placebo across 70 sites, with three pre-specified co-primary analyses.
  • The study relied on the Hochberg procedure to control family-wise error across analyses: (1) time to first cardiovascular death or heart failure hospitalization; (2) total heart failure hospitalizations; (3) time to first event in a highly iron-deficient subgroup.
  • Results showed a favorable hazard ratio (0.79) and a p-value below 0.05 for primary composite 1, but statistical significance was nullified under Hochberg multiplicity criteria as other endpoints failed threshold requirements.
  • Berry challenges the reduction of trial outcomes to discrete “significant” or “not significant” designations—critiquing the scientific and statistical culture that ignores gradient evidence in favor of only black-and-white outcomes.
  • He details the likelihood principle and Bayesian analysis as superior frameworks, quantifying a 98% posterior probability of benefit; he contextualizes findings with prior evidence from the HEART-FID, IRONMAN, and AFFIRM-AHF trials and published meta-analyses—arguing that isolated, negative conclusions defy cumulative data.
  • The discussion extends to the inefficiency of fixed trial designs, the missed value in adaptive methodologies, and the inefficacy of requiring full-scale repeat trials all analyzed in isolation, when evidence already points strongly to a beneficial effect.
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3 months ago
39 minutes

In the Interim...
Seamless 2/3 Trial Designs

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.

Key Highlights:

  • Systematic definition of seamless phase 2/3 trial designs, contrasting fixed, separate-phase models with integrated, inferentially seamless approaches.
  • Detailed explanation of the required alpha adjustment when selecting doses partway through—leveraging group sequential theory, normal approximations, and quadrature for explicit formula derivation; R code and calculation procedure are made available for practitioners.
  • Exploration of the information fraction curve for adjusted alpha, emphasizing that initial adjustment is numerically significant but does not inherently reduce statistical power.
  • Findings indicate that power is always higher when including stage 1 data – and outperforms a closed testing procedure.
  • Discussion of when seamless trials may not be advantageous: operational and statistical limitations: insufficient endpoint/regulatory understanding for phase 3, differences in manufacturing readiness, need for public phase 2 results for funding, and proof of concept hurdles; identifies real scenarios where seamless 2/3 designs are challenging.
  • Considerations for operational bias and blinding, with technical commentary on the boundaries of unblinding within company roles.
  • Provision of practical R code and explicit analytic guidance for calculating adjusted alpha in seamless design protocols.
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4 months ago
45 minutes

In the Interim...
Spending Alpha

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.

Key Highlights

  • Explains the basics of hypothesis testing in superiority trials, highlighting why a one-sided 2.5% alpha is the operational standard despite persistent use of two-sided 5% language in clinical protocols.
  • Refutes the widespread belief that reviewing interim data costs available alpha, making clear that statistical error is not “penalized”—it is allocated, with potential efficiencies in average sample size and, in thoughtfully extended designs, gains in operating characteristics such as power.
  • Describes real-world examples, including the SEPSIS-ACT (selepressin) trial sponsored by Ferring Pharmaceuticals, which incorporated more than 20 interim analyses while maintaining a pre-specified final alpha of 0.025; underscores the necessity of transparent, prospective design and explicit documentation for regulatory acceptance.
  • Distinguishes between interim actions—such as futility analyses or response-adaptive randomization, which require no alpha adjustment, and early efficacy analyses, which must be precisely modeled to preserve type I error.
  • Challenges terminology like “penalty” and “spending alpha,” asserting that imprecise language fosters misunderstanding and leads to missed opportunities in adaptive trial efficiency.
  • Emphasizes the crucial role of prospective, simulation-based planning and clear protocol definition at every interim, anchoring statistical practice in measured evidence, not historical convention.
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4 months ago
37 minutes

In the Interim...
Prof Craig Ritchie: Looking Back at EPAD, moving forward in Alzheimer's Disease

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. 

Key Highlights
• 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

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4 months ago
37 minutes

In the Interim...
Drug Developers' Lessons from Sports: Regression-to-the-Mean

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.

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5 months ago
41 minutes

In the Interim...
A podcast on statistical science and clinical trials. Explore the intricacies of Bayesian statistics and adaptive clinical trials. Uncover methods that push beyond conventional paradigms, ushering in data-driven insights that enhance trial outcomes while ensuring safety and efficacy. Join us as we dive into complex medical challenges and regulatory landscapes, offering innovative solutions tailored for pharma pioneers. Featuring expertise from industry leaders, each episode is crafted to provide clarity, foster debate, and challenge mainstream perspectives, ensuring you remain at the forefront of clinical trial excellence.