Previous Webinar
The distance learning committee is excited to announce the upcoming event:
BIOP Webinar Series -
Real-World Evidence HHSU01 FDA grantees series Part 2
Speakers: Xiaofei Wang, Duke
Shu Yang, NCSU
Matthew Secrest, Genentech
Date and Time: Aug 30 2024
10.00 – 11.00am Eastern Time
Registration link:
asabiop.ticketleap.com/...
[Note: this is a new free ticketing system, if you have any feedback that you would like to share with us, please send an email to asabiopwebinar@gmail.com ]
Below are the titles and abstracts of the two talks by Wang & Yang, and Secrest.
Title: Methods to Improve Efficiency and Robustness of Clinical Trials Using Information from Real-World Data with Hidden Bias (Wang & Yang)
Abstract: The use of external controls (ECs) from real-world data to supplement clinical trials has the potential to expedite the development of therapies for patients. The majority of the existing methods are unable to address unmeasured differences between the external control subjects and the trial population which can lead to biased treatment effect estimates. Our U01 project aims to develop innovative statistical methods to address hidden biases when integrating real-world data (RWD) to improve the efficiency and robustness of clinical trials.
The first part of the presentation will review the research aims of the project: (a) develop a novel sensitivity analysis framework for the use of ECs from RWD sources to assess the robustness of results regarding hidden biases, b) develop efficient analytic methods that selectively borrow and adjust for data discrepancies to mitigate the impact of hidden biases, and (c) disseminate these methods through representative applications, software, website, and workshops and tutorial sessions. We will also briefly introduce the project team and summarize progress to date.
The second part of the presentation will be more technically focused. We will present a data-driven integrative framework capable of addressing unknown biases associated with the use of ECs. The adaptive nature is achieved by dynamically sorting out a set of comparable ECs via bias penalization. The proposed method can simultaneously achieve (a) the semiparametric efficiency bound when the ECs are comparable and (b) selective borrowing that mitigates the impact of the existence of noncomparable ECs. Furthermore, we establish statistical guarantees, including consistency, asymptotic distribution, and inference, providing type-I error control and good power. Extensive simulations and two real-data applications show that the proposed method leads to improved performance over the trial-only estimator across various bias-generating scenarios.
Title: Bayesian dynamic borrowing and an R package for the design and analysis of hybrid control studies (Secrest)
Abstract: While randomized controlled trials (RCTs) remain the gold standard for evaluating novel therapies, integrating external control data can enhance study power, reduce trial duration, and allow more subjects to receive the experimental therapy. However, external data can introduce bias if the RCT control and external control arms are not comparable. Bayesian dynamic borrowing (BDB) offers a solution by incorporating external data while mitigating bias.
In this webinar, we will provide a high-level overview of BDB, focusing on priors such as the power prior, commensurate prior, and robust Meta-Analytic-Predictive (rMAP) prior. These methods aim to reduce type I error and increase the power of hybrid control studies.
We will also introduce the R package {psborrow2}, designed to simplify the simulation and analysis of hybrid control data. This open-source tool eliminates the need for users to create their own MCMC samplers, lowering the technical barriers to adopting BDB methods. The package, available on GitHub (github.com/Genentech/psborrow2), provides a user-friendly interface for conducting BDB analyses and facilitates simulation studies to evaluate various trial parameters' impact on study power, type I error, and other operating characteristics.
This effort is also one of the U01 project aims and is relevant to biostatisticians in the biopharmaceutical industry and academia. By leveraging dynamic borrowing techniques and tools like {psborrow2}, stakeholders can expedite the delivery of efficacious medicines to patients while maintaining the integrity of the evidence generation process.
Previous Webinars
The distance learning committee is excited to announce the upcoming event:
Overview of HTA framework and commonly used statistical methods
Date and Time: Jun 21 2024 10.00 – 11.00am Eastern Time
Speakers: Min-Hua Jen, Eli Lilly
Weili He, Abbvie
Registration link:
https://asabiop.ticketleap.com/overview-of-hta-framework-and-commonly-used-statistical-methods/
Title: Overview of HTA framework and commonly used statistical methods
Abstract: Health Technology Assessment (HTA) is a systematic evaluation process that examines health technologies, including medications, medical devices, and prevention methods. It considers various factors such as medical, economic, social, and ethical aspects. The primary goal of HTA is to provide evidence-based information to national health authorities for decision-making on reimbursement and pricing in comparison to other available therapies. Notable advancements in HTA include mandatory joint clinical assessments (JCA) of new oncology and advanced therapies by the European Network for Health Technology Assessment (EUnetHTA) in 2025. In the United States, the US Inflation Reduction Act (IRA) will allow Medicare to negotiate drug prices directly with manufacturers starting in 2026. While HTA requirements may differ by region, the fundamental principles remain consistent. However, in the US, where there is no single payer for HTA, the evaluation process and its components are not broadly understood by drug developers, including statisticians. To address this knowledge gap, the American Statistical Association (ASA) Biopharmaceutical Section (BIOP) Health Technology Assessment (HTA) Scientific Working Group (SWG) has conducted an assessment of the HTA landscape in major markets worldwide. This webinar, hosted by the ASA BIOP HTA SWG and facilitated by the BIOP Section Distance Learning Committee, introduces the conceptual framework of HTA evaluations and commonly used statistical methodologies. Statisticians play a critical role in the reimbursement strategy for patient access and HTA submissions, making this webinar essential for statisticians in the US and worldwide.
The distance learning committee is excited to announce the upcoming event:
Backfilling Patients in Phase I Dose Escalation Trials
Date and Time: May 31 2024 11.00am – 12.00 pm Eastern Time
Speaker: Ying Yuan, MD Anderson
Registration link:
https://asabiop.ticketleap.com/backfilling-patients-in-phase-i-dose-escalation-trials/
Title: Backfilling Patients in Phase I Dose Escalation Trials
Abstract: In recent years there has been increased interest in incorporation of backfilling into dose escalation clinical trials, which involves concurrently assigning patients to doses that has been previously cleared for safety by the dose escalation design. Backfilling generates additional information on safety, tolerability, and preliminary activity on a range of doses below the maximum tolerated dose, which is relevant for selection of the recommended phase 2 dose and dose optimization. However, in practice, backfilling may not be rigorously defined in trial protocols and implemented consistently. Furthermore, backfilling designs require careful planning to minimize the probability of treating additional patients with potentially inactive agents (and/or subtherapeutic doses).
In this talk, I will propose a simple and principled approach to incorporate backfilling into the Bayesian optimal interval design (BOIN). The design integrates data from the dose escalation and backfilling components of the design and ensures that the additional patients are treated at doses where some activity has been seen. Simulation studies demonstrated that the proposed backfilling BOIN design (BF-BOIN) generates additional data for future dose optimization, maintains the accuracy of the maximum tolerated dose identification, and improves patient safety without prolonging the trial duration. The application of the design will be illustrated using an FDA-accepted trial.
LATEST BIOPHARMACEUTICAL REPORT
Previous Webinar
The distance learning committee is excited to announce the upcoming event:
Real-World Evidence HHSU01 FDA grantees series Part 1
Date and Time: March 8 2024 10.00am – 11.00 am Eastern Time
Speakers:
Marie Bradley, FDA
Tianxi Cai, Harvard
Ashita Batavia & Benjamin Ackerman, Janssen
Registration link:
https://asabiop.ticketleap.com/real-world-evidence-nihu01-fda-grantees-series-part-1/
Below are the titles and abstracts of the talks by Marie, Tianxi, and Ashita/Ben, respectively.
Title: Overview of CDER’s Real-World Evidence Demonstration Projects
Abstract: Aligned with the U.S. 21st Century Cures Act, FDA established a program to evaluate the potential use of real-world evidence (RWE) in regulatory decision-making. The program is multifaceted and supports activities such as demonstration (research) projects, guidance development, internal Agency processes, external stakeholder engagement, and the Advancing Real-World Evidence initiative. This talk will present an overview of several RWE demonstration projects and will describe, for select projects, how learnings directly or indirectly serve to support FDA regulatory decision-making in evaluating the effectiveness and safety of medical products.
Title: Deriving reliable Real world evidence with electronic health records data
Abstract: Real-world clinical data hold tremendous potential to advance our understanding on the efficacy and safety of therapeutic interventions in broader populations, including disease modifying therapies for chronic diseases. However, these data remain underutilized due to methodological constraints and the inability to efficiently link and integrate data sources across study types and healthcare settings. This talk will discuss opportunities and challenges in leveraging electronic health records data to derive reliable real world evidence.
Title: Novel methods for aligning real-world progression-free survival (rwPFS) and clinical trial PFS endpoints in Multiple Myeloma
Abstract: Randomized clinical trials remain the gold standard for evaluating treatment efficacy because of their rigorous design and data collection parameters, which reduce bias and allow for valid inference of causal relationships. In Multiple Myeloma (MM), the brisk pace of drug development has seen twelve new therapies approved in the past decade - many of these were accelerated approvals based on single arm trials. Robust Real World Evidence (RWE) can enhance the interpretation of single arm studies, however comparisons between real world and clinical trial endpoints are limited by measurement bias.
J&J Innovative Medicine has established a consortium that includes leading academic RWE methodology experts, MM clinician scientists and Flatiron Health to develop novel treatment-agnostic methods for aligning rwPFS and clinical trial PFS. We will discuss our research approach, inclusion of under-represented minorities, and potential future applications of this work in this ASA Biopharma webinar.
Previous Webinar
Open-Source Software for Regulatory Submissions/Environments & Introducing openstatsware BIOP working group
Date and Time: February 23 2024 11.00am – 12.00 pm Eastern Time
Speakers:
Paul Scheutte, FDA
Ya Wang, Gilead
Registration link:
https://www.eventbrite.com/e/webinar-open-source-software-tickets-802097293597
Title: Open-Source Software for Regulatory Submissions and Regulatory Environments
Abstracts: Regulatory submissions and regulatory computing environments have traditionally been associated with the use of proprietary software packages. While academic institutions have embraced open-source software, both industry and government have been slower to adopt open-source alternatives. I will discuss some of the challenges and issues with using open-source software in a regulatory environment, followed by some of the lessons learned in the ongoing R Consortium R Submission Pilot, as well as emerging issues.
Title: Introducing openstatsware: Who we are and what we build together
Abstracts: In this talk, we would like to introduce openstatsware, an official working group of the American Statistical Association (ASA) Biopharmaceutical Section. The working group has a primary objective to engineer R packages that implement important statistical methods, and a secondary objective to develop and disseminate best practices for engineering high-quality open-source statistical software. We will talk about what R packages we have been developing and what we have done to disseminate the best practices, as well as our long-term perspective and next steps.
We would also like to give an overview of our three active workstreams. The MMRM R package development workstream aims to develop a comprehensive R package for mixed models for repeated measures (MMRM) that is robust, well documented, and thoroughly tested. The Bayesian MMRM R package development workstream aims to develop an R package for Bayesian MMRM to support robust analysis of longitudinal clinical data. The HTA-R workstream aims to develop open-source R tools of good quality to support crucial analytic topics in Health Technology Assessment (HTA) dossier submission across various countries.
LATEST PODCAST
Episode 112: Preparing Future Statisticians to Succeed in the Era of AI
Date: 2025-04-04
Description: John McGready discusses how to prepare future statisticians to succeed in the era of AI.
A message for 2021 ASA Fellow Candidates
This message is intended for BIOP members who plan to submit their ASA Fellows dossiers in 2021. Effective October 1, 2020, as approved by the Biopharmaceutical Section Executive Committee, an anonymous BIOP section working panel of dossier reviewers has been formed. The reviewers serving on the panel are experienced statisticians including former and present members of the ASA Committee on Fellows. Nominators from BIOP are encouraged to send completed dossiers for review to a current chair of the BIOP Fellows Committee (Ilya Lipkovich, ilya.lipkovich@lilly.com). All dossiers will be treated in strictest confidence. Nominators may anonymize the dossier before sending. The reviewing committee chair will send it to one of the available reviewers and provide feedback regarding potential gaps and improvements within approximately two weeks. Please submit for review well in advance of the ASA submission deadline, in order to receive feedback in time to make adjustments to the dossier. The committee will not share any personalized information about the reviewed dossiers with the BIOP Section Executive Committee, or any other committee beyond the reviewers.
You can see more details at BIOP page
We encourage you to take advantage of this service offered to the members of BIOP, and give our members the best opportunity to achieve the honor of ASA Fellow.