DIA 2025 Global Annual Meeting

Component Type: Forum
Level: Intermediate
CE: ACPE 1.00 Application UAN: 0286-0000-25-621-L04-P; CME 1.00; RN 1.00

Signal detection remains central to Pharmacovigilance activities. Better access and use of data, ever improving methods to maximise the utility of data, and better processes and governance to optimise signal detection activities are key focus areas as we continuously strive to do ever earlier and more effective safety signal detection. This session will discuss the current status of signal detection from all these aspects as well as how we anticipate the field evolving moving forwards.

Learning Objectives

Demonstrate and discuss how Generative AI can facilitate the future approach in augmenting PV systems in a trusted, compliant, and transparent manner; Summarize the opportunities and challenges with such an approach.

Chair

Andrew Bate, PhD, MA

Speaker

Industry Perspective
Mariette Boerstoel-Streefland, MD, MBA, MS

Component Type: Session
Level: Intermediate
CE: ACPE 1.00 Application UAN: 0286-0000-25-626-L04-P; CME 1.00; RN 1.00

Artificial Intelligence (AI) and Structured Content Authoring (SCA) tools are here. The challenge of seamlessly integrating these technologies into compliant and efficient workflows is reshaping the regulatory document development process. This session will delve into the balance and interdependence of four pillars (technology, process, people, and organization) to drive the business value of these tools. The interplay of these elements stokes an environment of thriving innovation, leading to enhanced efficiency, quality, and value proposition for the underlying business. AI/SCA have been thoroughly discussed in the regulatory writing process. Now there is focus on evolving technologies, the challenge lies in integrating these advancements into our workflows and processes, or implementing change management processes to allow for their use. Utilizing these tools coupled with organizational and process driven acceleration levers will condense the time to document approval and decrease the number of resources need to produce these documents. Moreover, the concerted and collaborative efforts across various functions, ranging from clinical sciences to biostatistics programming to review and approval pathways, ensures a thorough and compliant documentation process. It is time to focus and clearly define, emphasize, and promote the importance of the human element in the utilization of these tools, the people and the processes, at the heart of transformative authoring. Attendees will gain insights into the strategic integration of the four pillars in medical writing, drawing real-world use cases of these technologies in industry. These strategies, while transformative, do not necessitate a radical shift when applied independently. Instead, their true power lies in their harmonious application, which collectively refines traditional authoring paradigms.

Learning Objectives

Analyze the business value of AI and Structured Content Authoring tools in Regulatory Medical Writing to enhance efficiency and compliance; Evaluate process modifications in document development resulting from technology innovations to optimize workflow; Develop strategies to implement change management and organizational shifts that support technology-driven solutions.

Chair

David Meats, II

Speaker

Industry Perspective
James Best, MBA

Speakers
Louise Lind Skov, PhD

Component Type: Session
Level: Intermediate
CE: ACPE 1.00 Knowledge UAN: 0286-0000-25-634-L04-P; CME 1.00; RN 1.00

Aftificial Intelligence (AI) is being adopted across the medicine lifecycle to increase insights into data and improve efficiency of processes, for the benefit of public and animal health. This session will address key elements to enable the safe and responsible use of AI.

Learning Objectives

Identify AI opportunities across the medicine lifecycle; Examine the legal ecosystem of AI across jurisdictions and identify opportunities for convergence; Discuss how regulators worldwide are developing guidance to support AI innovation in the medicine lifecycle; State other strategic AI initiatives, including approaches to leveraging AI with healthcare data.

Chair

Luis Pinheiro, PharmD, MSc

Speaker

Panelist
Timothe Menard, PharmD, MSc

Panelist
Tala Fakhouri, PhD, MPH

Component Type: Session
Level: Intermediate
CE: ACPE 1.00 Knowledge UAN: 0286-0000-25-637-L04-P; CME 1.00; RN 1.00

This session will review the 3Rs (replacement, refinement, reduction) of animal use in non-clinical drug development research, and how new technologies including AI, Victorian Clinical Genetics Services (VCGs) and organoids are introducing innovative ways to meet these ethical principles.

Learning Objectives

Discuss the “3Rs” (replacement, refinement, reduction) of ethical animal use in non-clinical drug development research; Recognize how new technologies including AI, VCGs and organoids are being explored to follow these ethical principles as part of the overall drug development program.

Chair

Lindsay McNair, MD, MPH, MS

Speaker

How New Technologies are Being Developed to Align With Ethical Principles in Animal Research
Julie Frearson, PhD

Panelist
Szczepan Baran

Component Type: Session
Level: Intermediate
CE: ACPE 1.00 Knowledge UAN: 0286-0000-25-641-L04-P; CME 1.00; RN 1.00

Industry leaders explore how biopharma is leveraging data foundations and technological advancements, including AI/ML, to improve access and representation in clinical trials, moving from DEI planning to tangible progress in clinical research.

Learning Objectives

Identify key areas where tech and analytics facilitate health equity advancement, focusing on achievable, tech-enabled outcomes; Illustrate concrete use cases where tech and data can support equitable clinical research, such as community outreach, recruitment, and measurement against diversity action plans; Discuss non-technical success factors needed to wholly support data-driven tech

Chair

Katrina Rice, MS

Speaker

From Data to Action: Driving Inclusive Clinical Trials
Del Smith, PhD, MS

Placing Patients First in the Era of Advanced Tech and AI
Patrick Gee, SR, PhD, MS

Responsible AI and Diversity in Clinical Trials
Nicole Ward, MBA, MS, PMP

Component Type: Session
Level: Intermediate
CE: ACPE 1.00 Knowledge UAN: 0286-0000-25-652-L04-P; CME 1.00; RN 1.00

This session aims to explore the application of AI to drug labeling to enhance pharmacovigilance, reduce medication errors, and improve patient safety. Presenters will discuss the complexities and share real examples from both end-user and technology perspectives.

Learning Objectives

Discuss opportunities to apply artificial intelligence (AI) to drug labeling to enhance labeling review, surveillance activities, and medication error reduction; Identify the complexities and barriers to applying AI techniques to modernize labeling-related activities.

Chair

Daniele Sartori, MPharm

Speaker

Regulatory Perspective
Brett Howard, JD, PhD

From Text to Intelligence: Architecting AI Systems for Drug Labeling and Pharmacovigilance
Fatima Sabar, MSc

AI in Drug Labelling: Toward Harmonized, Globally Aligned Product Information
Daniele Sartori, MPharm

Computerized Labeling Assessment Using AI
Suranjan De, MBA, MS

Component Type: Forum
Level: Intermediate
CE: ACPE 1.00 Knowledge UAN: 0286-0000-25-655-L04-P; CME 1.00; RN 1.00

We’ve all heard the hype around emerging technologies and what it means for our industry, but when it comes down to adding value on the ground today, what advancements are actually making a difference in drug discovery, development, and distribution?

Learning Objectives

Describe and explain the advancements in data analytics and emerging technologies that are adding value to biopharma companies today.

Chair

Jessica Federer, MPH

Speaker

Panelist
Leo Barella

Panelist
Diogo Rao

Component Type: Forum
Level: Intermediate
CE: ACPE 1.00 Knowledge UAN: 0286-0000-25-666-L04-P; CME 1.00; RN 1.00

Regulatory, industry, and academic organizations discuss modern approaches to clinical drug development by describing novel methods and use cases integrating real-world data and AI to generate real-world evidence, with focus on oncology and rare diseases.

Learning Objectives

Discuss global regulatory guidance and frameworks supporting innovative designs using real-world data as well as approaches to inclusion of artificial intelligence (AI); Describe innovative approaches and methods through examples of applied AI use in drug development; Discuss areas of research interest and promote community collaboration.

Chair

Donna Rivera, PharmD, MSc, FISPE

Speaker

Applying Artificial Intelligence in Drug Development
Sid Jain, MBA

Use of Artificial Intelligence Approaches for Rare Diseases
Christina Mack, PhD, MPH