Overview
The DIA Artificial Intelligence Consortium is a global, multi-stakeholder initiative uniting regulators, industry, academia, and technology innovators to tackle the practical challenges of AI in drug development. Organized into three working groups—Use Case Definition & Classification, Model Validation, and Regulatory Frameworks, Governance & Terminology Alignment—the consortium develops actionable frameworks, tools, and guidance.
In its first year, the consortium is focused on:
- Defining a structured AI use case definition and classification framework
- Creating practical AI/ML model validation guidance to evaluate quality, reliability, and fitness-for-purpose
- Harmonizing regulatory terminology and frameworks to support cross-jurisdictional alignment
Quick Facts
Launch Year: 2025
Members: 44 individuals across 27 organizations
Working Groups: Use Case Definition & Classification; Model Validation; Regulatory Frameworks, Governance & Terminology Alignment
Project Lead: Stephanie Rosner, Scientific Program Manager for Artificial Intelligence
Co-Chairs: Christina Mack (IQVIA), Leon Rozenblit (Beth Israel Deaconess Medical Center-Yale School of Medicine; Yale Ventures), Sridevi Nagarajan (Ayusarogya Ltd)
Why It Matters
This work benefits the life sciences community by:
- Supporting evidence-based regulatory and organizational decision-making
- Promoting harmonized global practices for AI in life sciences
- Driving collaboration among regulators, industry, and academia to advance innovation
By establishing shared frameworks and standards, the consortium ensures that AI can be implemented safely, effectively, and responsibly—ultimately improving scientific rigor, operational efficiency, and patient outcomes.
Partners & Collaborators
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Ayusarogya Ltd.
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BeOne Medicines
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Beth Israel Deaconess Medical Center-Yale School of Medicine; Yale Ventures
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CDSCO
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Clintegrity
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FDA
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Gilead
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Harvard Business School
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Health Canada
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HealthAI
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Healthcare Innovation Catalysts
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HSA
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Insight Global
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IQVIA
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Israel Ministry of Health
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LeapAhead Solutions
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MHRA
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Otsuka
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PMDA
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Queen Mary University of London
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Stanford University
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University of Modena and Reggio Emilia
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University of Ottawa
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VB Insights
Governance & Leadership
Steering Committee Co-Chairs
Christina Mack, IQVIA
Leon Rozenblit, Beth Israel Deaconess Medical Center-Yale School of Medicine; Yale Ventures
Sridevi Nagarajan, Ayusarogya Ltd.
Project Leads
Stephanie Rosner, Scientific Program Manager for Artificial Intelligence, DIA
Working Groups
AI Use Case Definition & Classification
Develops a structured, stage-based framework that categorizes AI use cases across the biopharma R&D-Manufacturing-Regulatory lifecycle.
Led by Leon Rozenblit (Beth Israel Deaconess Medical Center-Yale School of Medicine; Yale Ventures), Carrie Nielson (Gilead), Cary Smithson (LeapAhead Solutions). and Li Tan (BeOne Medicines)
Model Validation
Develops a practical checklist and reference framework covering performance metrics, data quality, reproducibility, and regulatory expectations to evaluate AI systems.
Led by: Christina Mack (IQVIA), Sridevi Nagarajan (Ayusarogya Ltd.), and Michael Lingzhi Li (Harvard Business School)
Regulatory Frameworks, Governance & Terminology Alignment
Harmonizes key definitions, terminology, and frameworks used by global regulators to improve clarity in regulatory submissions and collaboration across regions and disciplines.
Led by: Sridevi Nagarajan (Ayusarogya Ltd.) and Venkatraman Balasubramanian (VB Insights)
Key Activities & Status
Q1 2025: Consortium Formation & Framework Scoping
Q2 2025: Development of Foundational Deliverables
Q3 2026: Integration, Refinement, & Public Preparation
Q4 2026: Presentation & Publication of Outputs
Impact & Outputs
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AI Use Case Definition and Classification Framework
AI use case classification resources that organize and clearly describe how AI is applied across research, development, manufacturing, and regulatory domains
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Model Validation Checklist
Model validation and evaluation guidance to support consistent approaches for assessing reliability, appropriateness, and fit-for-purpose
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Global Terminology and Regulatory Alignment Guide
Terminology and framework alignment tools that harmonize key concepts across regions, disciplines, and regulatory authorities
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Multi-Stakeholder White Papers and Publications
Cross-stakeholder publications and summaries that synthesize insights and recommendations
How to Participate
Participation is open to partner organizations dedicated to advancing trustworthy AI in the life sciences.
Benefits
- Early access to frameworks and validation tools.
- Direct collaboration with regulators, academics, and industry peers.
- Opportunity to influence emerging standards and policy approaches.
- Recognition in DIA publications and events, including the 2026 Global Annual Meeting.
To learn more or express interest in joining, please contact Stephanie.Rosner@DIAglobal.org.
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Learn More About Our Work
If you or your organization want to learn more about DIA’s Research projects or Think Tanks please contact Science@DIAglobal.org.