DIA 2025 Global Annual Meeting

Component Type: Workshop
Level: Intermediate

Imagine a future where AI measures patient burden from provided inputs. In this interactive workshop, participants will design input logic for AI using mock data and protocols, then present their rationale to foster collaborative learning.

Learning Objectives

Define and categorize key factors affecting patient burden in clinical trials; Analyze patient-related data to design effective AI inputs; Evaluate and justify the role of human insight in enhancing AI-driven patient burden assessments for patient-centric trial outcomes.

Chair

Maya Zlatanova

Component Type: Workshop
Level: Basic

Turnover in the clinical research industry hovers at 27%. Given the high stress, high turnover nature of the industry, the need for stress reduction tools is critical. In this session you will learn techniques to implement for yourself and teams.

Learning Objectives

Identify a simple way to immediately reduce stress in less than 2 minutes; Practice a technique to increase energy, clarity and decision making; Complete a guided non-sleep deep rest practice to calm, soothe and restore.

Chair

Leanne Woehlke, MA

Component Type: Workshop
Level: Intermediate

The healthcare industry is rapidly transforming with AI, necessitating new regulations for its use in drug development. This session proposes collaboration between pharma, biotech, and regulators to co-create a framework ensuring AI-driven innovation

Learning Objectives

Understand the key challenges and regulatory considerations in scaling AI-driven solutions for drug development in healthcare. Explore strategies for effective collaboration between pharma, biotech, and regulatory bodies to create a unified AI framework. Identify actionable steps to ensure AI integration in healthcare is safe, transparent, and compliant with evolving regulations.

Chair

Sridevi Nagarajan, PhD, MS, MSc