DIA 2024 Global Annual Meeting

Component Type: Forum
Level: Intermediate
CE: ACPE 1.00 Knowledge UAN: 0286-0000-24-528-L04-P; CME 1.00; RN 1.00

We all want to see innovation in treatments and prevention that meets the many unmet needs of patients globally. And yet, despite this compelling goal, the complexity and uncertainty involved in delivering innovation has baffled policy makers, regulators, healthcare systems and companies at every step of the process. The response has been to establish policies and requirements to “direct” innovation to best effect. The result has been a confused environment where crosstalk of policy measures and requirements collectively and often constrain, rather than enable, innovation.

In this forum, we are going to aim to take a more holistic framing of the drive for innovation and explore three recent cases where policy crosstalk risks frustrating innovation.

Learning Objectives

Explore how various legislative and other policy-related initiatives, including some not directly targeting the industry, are threatening the climate for development of innovative products.

Chair

Virginia Acha, PhD, MSc

Speaker

Policy Cross-Talk Case Study: Clinical Research
Karen A Noonan, MA

Policy Cross-Talk Case Study: Supply Chains and Resilience
Christopher Colwell, MPA

Policy Cross-Talk Case Study: Pricing and Access Policies
Duane Schulthess, MBA

Component Type: Session
Level: Intermediate
CE: ACPE 1.00 Knowledge UAN: 0286-0000-24-542-L04-P; CME 1.00; RN 1.00

This session will explore special topics in causal inference. Presenters will describe trial design and analysis issues in drug development, related to both randomized trials and real-world data (RWD), that may benefit from statistical methodology to allow for better and more accurate generation of evidence with respect to drug treatment effects.

Learning Objectives

Describe various statistical approaches to handle complex design and analysis issues in drug development. Explain use case examples for illustration for causal inference methods.

Chair

Pallavi Mishra-Kalyani, PhD, MS

Speaker

Causal Inference in Clinical Drug Development: Industry Update
Antara Majumdar, PhD

Methodological Challenges and Potential Solutions When Conducting External Control Studies Intended for Causal Inference
Shia Kent

Regulatory Considerations and Case Studies of Externally Controlled Trials
Pallavi Mishra-Kalyani, PhD, MS

Component Type: Session
Level: Intermediate
CE: ACPE 1.00 Knowledge UAN: 0286-0000-24-555-L04-P; CME 1.00; RN 1.00

In this session, we will present various interactive graphics and new concept meetings that can be used to provide informative data insights and to enhance clinical trials execution from planning, monitoring, reporting, and regulatory submission.

Learning Objectives

Identify information of interest in an interactive way, which can greatly enhance clinical trials execution from planning, monitoring, reporting, and regulatory submission; Describe how to generate additional, broader, and deeper insights in helping accelerate the understanding of the clinical trial data, and further drive the understanding of disease development and patient journey.

Chair

Erya Huang, PhD

Speaker

Industry Update
Melvin Slaighter Munsaka, PhD, MEd, MS

Industry Update
Neetu Sangari, PhD, MEd, MS

Industry Update
Matthew Kumar, MSc

Component Type: Forum
Level: Intermediate
CE: ACPE 1.00 Knowledge UAN: 0286-0000-24-625-L04-P; CME 1.00; RN 1.00

This discussion will dive into large language models (LLMs) impact on healthcare, their integration with digital health technology, and ethical/regulatory implications.

Learning Objectives

Describe how digital health technologies (DHTs) and generative artificial intelliegence (AI), including large language models (LLMs) are applied to healthcare context; Examine the various integration points between LLMs and DHT and discover how these technologies can work synergistically to revolutionize patient care, telemedicine, remote, and disease progression.

Chair

Jagdeep Podichetty, PhD, MS

Speaker

Panelist
Qi Liu, PhD

Panelist
Jie Shen, PhD, MBA

Panelist
Sakshi Sardar, PhD

Panelist
Emily Lewis, MS

Component Type: Session
Level: Intermediate
CE: ACPE 1.00 Knowledge UAN: 0286-0000-24-668-L04-P; CME 1.00; RN 1.00

This session discusses usage of a variety of artificial intelligence (AI) solutions (knowledge-based expert systems, generative AI, machine learning) across the clinical research lifecycle from drug discovery to patient recruitment, data quality management, and submission. We will go over specific problems that lend themselves to AI and how we go about building scalable solutions with emphasis on explainability, reliability, and validity.

Learning Objectives

Discuss the use of generative artificial intelligence (AI) and machine learning in clinical research and measures taken to insure validity and reliability; Describe the role of knowledge graph (KG) in building AI systems.

Chair

Katy Ghantous, PhD, MS

Speaker

Industry Update
John Overington

Industry Update
Joe Mullen, PhD, MS

Academic Update
Ramona Lynn Walls, PhD

Component Type: Session
Level: Intermediate
CE: ACPE 1.00 Knowledge UAN: 0286-0000-24-675-L04-P; CME 1.00; RN 1.00

This session will describe key challenges in quality assessment for cell and gene therapies, focusing on challenges related to raw materials; discuss regulatory perspectives; and present best practices to control and evaluate raw materials.

Learning Objectives

Identify the key current challenges in quality control for cell and gene therapy development; Explain global regulators’ perspectives on quality control, including raw material selection, control, and qualification; Discuss best practices, including standards and reference materials, to support the development and manufacture of cell and gene therapies.

Chair

Fouad Atouf, PhD

Speaker

Qualification and Selection of Raw Materials During Early Stage of Development
Mo Heidaran, PhD

Perspective on the Selection of Raw Materials for Cell Therapy Manufacturing
Haritha Vallabhaneni, PhD

Cell and Gene Therapy Products: Global Regulatory Perspective
Michael Day, PhD