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Analysis of regulatory guidance, research on drug development, and technical perspectives on AI in life sciences.

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The Hidden Cost of AI Hallucinations in Critical Document Creation

It's 11 PM on a Friday. The FDA just flagged your CTD submission—somewhere in those 10,000 pages, your AI invented a clinical trial that doesn't exist. Here's what happens next, and how to make sure it never happens to you.

Gunin Gupta

Gunin Gupta

Founder & COO

Latest Posts

ResearchJan 17

Why Drug Name Confusion Breaks RAG Systems — And How to Fix It

Standard retrieval fails on 50% of queries involving similar drug names. Context-enriched retrieval cuts that failure rate by 80%. Here's what we learned building a benchmark to test it.

Nirmit Arora
Nirmit Arora
10 min read
IndustryJan 15

JPM26: Where Pharma & Biotech Are Headed — By the Numbers

A data-driven analysis of the 2026 J.P. Morgan Healthcare Conference. $116B in M&A, $180B at risk from patent cliffs, and the trends reshaping drug development.

Pavan Kalyan
Pavan Kalyan
12 min read
ResearchJan 14

Clinical Trial Success Rates: An Analysis of 450,000+ Trials

Examining the latest published data on clinical trial success rates by phase, therapeutic area, and development timeline. What the numbers tell us about where drugs succeed and fail.

Pavan Kalyan
Pavan Kalyan
10 min read
RegulatoryJan 14

The EMA-FDA Guiding Principles for AI in Drug Development: A Reference Guide

A detailed breakdown of the 10 joint EMA-FDA principles for AI in drug development. Includes definitions of key technical terms like GxP, data drift, and model validation.

Pavan Kalyan
Pavan Kalyan
15 min read

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