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White Paper – Making Gen-AI Work in Pharma and Biotech
Holisticon Connect

makinG gen-ai wORK iN pHARMA aND bIOTECH

HOW DATA VALIDATION AI AGENTS ENABLE SAFE AND SCALABLE AI ADOPTION


White Paper

Pharmaceutical and biotech companies are rapidly investing in Generative AI to accelerate research, clinical development, and regulatory processes. Yet, fragmented data and missing governance frameworks often block progress. This white paper shows how Data Validation AI Agents close that gap – turning GenAI from an experimental tool into a trusted, compliant technology ready for scale.

Inside The White Paper

The State of AI in Pharma: Growth, Regulation, and Opportunity
  • How AI investment in pharma is expected to rise sixfold by 2030 — and why tightening regulations make data validation essential for safe, scalable adoption.
Four Key Barriers to AI Adoption
  • What prevents GenAI from scaling in pharma: inconsistent data, domain-specific language issues, and limited predictive capability.
The Five-Component Data Validation Framework
  • How governance, data architecture, machine learning, GenAI integration, and validation agents work together to ensure trust and compliance.
The Role of the Validation AI-Agents
  • How automated validation gates and feedback loops reduce manual checks and improve output quality.
From Raw Data to Reliable Decisions
  • How validated pipelines connect data, models, and AI outputs into a traceable, compliant lifecycle.

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