AI/Automation Strategy for Clinical Content
Led the strategic scoping and documentation of an AI-driven content operations model for Tata 1MG's Clinical Content team.
Mapped the end-to-end content creation, review, audit, and publication lifecycle — identifying where AI could replace manual effort, augment clinical decision-making, or accelerate throughput.
Covered pharma drug content, diagnostics content, and OTC/VMS content streams as distinct but related AI opportunity areas.
The Challenge
- Clinical content at scale requires both clinical accuracy (which demands human expertise) and operational speed (which demands automation).
- Defining which content operations are safe to automate vs which require mandatory human review in a regulated health-tech environment.
The Approach & Solution
- Created a detailed AI strategy document and Figma whiteboard mapping AI use cases across the content lifecycle.
- Defined prompt frameworks for accuracy evaluation, comprehensiveness scoring, and FAQ generation.
- Established the governance model for AI-assisted vs AI-generated content, with mandatory human review gates for safety-critical attributes.
Key Results & Commercial Impact
Technology Stack & Tools
Have a similar project in mind?
We specialize in custom AI systems, clinical data licensing pipelines, and scalable web apps. Let's build something exceptional together.
Explore More Projects
Google Health Partnership
Packaged clinical content as LLM training data, including drug monographs, DDI data, disease content, and regulatory safety data, in a B2B monetization deal.
Samsung Health API Integration
Real-time API integration spanning 600K+ SKUs, 50+ attributes, and a 200K-interaction DDI tool, enabling in-app discovery and routing cart/checkout to Tata 1mg.
Elsevier Clinical Monograph API Partnership
Tata 1mg's first clinical content licensing deal. Delivered 1,500 structured drug monographs over 9 months and built the CMS & API infrastructure.