DIA 2025 Global Annual Meeting

Component Type: Social Event

Component Type: Session
Level: Intermediate
CE: ACPE 1.00 Knowledge UAN: 0286-0000-25-668-L04-P; CME 1.00; RN 1.00

Planning safety reviews for a compound developed for multiple diseases is complex, requiring consistency across studies and analyses. A compound-level Data Monitoring Committee ensures unblinded safety review consistency, while an Aggregate Safety Assessment Plan (ASAP) supports post-study assessments. This presentation explores how an ASAP was implemented across a program to enable ongoing safety profile development as studies complete. It also introduces an interactive R Markdown application for real-time aggregate reviews, aligning with new draft regulatory guidance. This approach provides reviewers with access to program-level and individual study data during development, improving safety oversight. Key topics include the importance of coordination, teamwork, and standards to maintain a reliable safety database. A "year in review" will highlight lessons learned and enhancements made, concluding with an example of the application’s interactive capabilities.

Learning Objectives

Recognize and apply the Aggregate Safety Assessment Planning (ASAP) concept to drug development and aggregate safety analysis; Discuss implementing the ASAP effectively within an organization; Identify and utilize the importance of an interactive application for performing ongoing aggregate safety reviews.

Chair

Robert (Mac) Gordon, MS

Speaker

An Industry Perspective
Lisa Kammerman, PhD, MS

Overview of the ASAP Process
Greg Ball, PhD

Perspective on the ASAP Process
Y. Veronica Pei, MD, MEd, MPH

Component Type: Forum
Level: Intermediate
CE: ACPE 1.00 Knowledge UAN: 0286-0000-25-669-L04-P; CME 1.00; RN 1.00

A cross-functional panel of experts will role-play a risk review meeting discussion to identify, assess, categorize, and prioritize risks of a mock protocol decentralized clinical trial (DCT) and outline potential mitigation activities.

Learning Objectives

Outline why risk identification is a fundamental consideration when planning a Decentralized/Hybrid Clinical trial; Define roles and responsibilities for key stakeholders to identify risks for Decentralized/Hybrid Clinical Trial; Identify who are the key stakeholders for a decentralized/Hybrid Clinical trial; Discuss developing fit-for-purpose Oversight Plans.

Chair

Paula Horowitz

Speaker

Panelist
Gina Lisette Williamson, BSN, MBA

Quality Risk Management for a Decentralized/Hybrid Clinical Trial: A Role Play by Representatives of Key Stakeholders
Maryrose Petrizzo, MS

Panelist
Terry Katz, MS

Component Type: Session
Level: Intermediate
CE: ACPE 1.00 Knowledge UAN: 0286-0000-25-670-L04-P; CME 1.00; RN 1.00

The use of generative AI (genAI) is already shown to be useful in content generation. The use of genAI to accelerate development and maintainance of data standards and data transformation is rapidly evolving as it will be shown in this session.

Learning Objectives

Describe the current landscape of AI applications for developing, maintaining, and utilizing data standards to accelerate access to source data in electronic health records (EHRs) and registries; Evaluate how AI is currently shaping data standardization and transformation and anticipate its future impact on the landscape.

Chair

Jesper Kjær, MS

Speaker

Industry Feedback to AI in Data Standards
Robert DiCicco, PharmD

OHDSI OMOP AI and open science
Patrick Ryan

CDISC and AI
Chris Decker, MS

HL7 and the AI Train
Charles Jaffe, MD, PhD, FACMI, FACP

Component Type: Session
Level: Intermediate
CE: ACPE 1.00 Knowledge UAN: 0286-0000-25-671-L04-P; CME 1.00; RN 1.00

This session explores the transformative potential of AI in pharma quality and compliance, sharing use cases, strategies, and regulatory insights. Attendees will learn how AI can transform quality and compliance in pharmaceutical companies.

Learning Objectives

Describe AI use cases in pharmaceutical quality management and compliance processes; Recognize the role, benefits, and risks of using AI in quality management; Discuss strategies for integrating AI technologies into existing pharmaceutical quality and compliance frameworks.

Chair

Hangyu (cedric) Liu, MS

Speaker

AI and the Quality Professional
Michael Pelosi, MA, MBA, MSc

AI in Pharma Quality and Compliance
Roshan D'Souza

Explainable Natural Language Processing: Why you see What you see
Meera Nagaria, MS

Component Type: Forum
Level: Intermediate
CE: ACPE 1.00 Knowledge UAN: 0286-0000-25-672-L04-P; CME 1.00; RN 1.00

In this interactive forum experts from EMA and FDA will address questions from the audience and share their experiences of collaboration in specific areas as well as on how both Agencies collaborate in addressing current regulatory, scientific, and communication challenges.

Learning Objectives

Identify an overall understanding of the regulatory and scientific collaboration between EMA and FDA; Describe experience and explore specific areas of collaboration between the two Agencies; Examine how EMA and FDA are addressing regulatory and scientific challenges in new areas.

Chair

Anabela Marcal, PharmD

Speaker

Advanved Manufacturing
Evdokia Korakianiti, PhD, MSc

Artificial Intelligence
Luis Pinheiro, PharmD, MSc

Advanced Manufacturing
Manuel Osorio, PhD

GCP
Kassa Ayalew, MD, MPH

GCP
Peter Twomey, MA, MPharm

Artificial Intelligence
Tala Fakhouri, PhD, MPH

Component Type: Session
Level: Intermediate
CE: ACPE 1.00 Knowledge UAN: 0286-0000-25-673-L04-P; CME 1.00; RN 1.00

Alternative methods to a frequentist approach, such as Bayesian, may be superior in certain situations; particularly, when analyzing trial data to support approvals in small populations. Regulators are increasingly considering novel methods.

Learning Objectives

Examine global considerations for leveraging Bayesian approaches in pivotal trials to support marketing authorization; State and debate the situations and circumstances where the Bayesian approach may be the most appropriate method of analysis; Discuss health authority considerations that could facilitate the use of alternative analytical methods beyond the frequentist approach; Identify ways to bridge existing gaps in applying Bayesian methods in clinical research.

Chair

Philip Hougaard, DrSc, PhD

Speaker

FDA perspective
Yun Wang, PhD

EMA Perspective
Andrew Thomson, PhD, MA, MS

Industry Perspective
Scott Berry, PhD

Component Type: Forum
Level: Intermediate
CE: ACPE 1.00 Knowledge UAN: 0286-0000-25-674-L04-P; CME 1.00; RN 1.00

This session empowers pharmaceutical scientists and researchers with essential business skills, strategies for commercialization, and solutions for industry challenges, enabling a successful transition from lab innovation to entrepreneurial leadership.

Learning Objectives

Identify essential business and entrepreneurial skills to navigate the transition; Discuss the intersection of scientific innovation and business strategy, helping professionals identify and develop viable commercial opportunities from their research; Recognize the unique challenges in the pharmaceutical industry, from regulatory complexities to funding obstacles, and provide strategies for overcoming them.

Chair

Angela Men, MD, PhD

Speaker

Panelist
Bei Ma

Panelist
Matthew Chervenak

Panelist
Shou-Bai Chao

Component Type: Social Event

Component Type: Forum
Level: Intermediate
CE: ACPE 1.50 Knowledge UAN: 0286-0000-25-675-L04-P; CME 1.50; RN 1.50

The FDA Town Hall is the forum to hear from FDA leadership about Center priorities. The audience will be invited to submit questions of general interest.

Learning Objectives

Discuss FDA Center priorities.

Chair

Amy Bertha