TCS Launches AI Platform to Oversee Clinical Trial Oversight

TCS  has rolled out a new AI-powered upgrade to its TCS ADD Risk-Based Quality Management (RBQM) platform, designed to give drugmakers and research organisations sharper, real-time oversight of clinical trials. The platform aims to help teams spot risks earlier, improve data quality, and manage increasingly complex trial setups.

The new version introduces four AI-driven modules focused on risk assessment, quality tolerance limits, trial analytics, and subject-level data monitoring. Together, these tools allow researchers to detect problems much sooner than traditional monitoring methods. 

TCS says these modules are among the few globally that are fully interoperable and can be customised to suit different trial designs. This feature can shorten deployment time for sponsors.

“In today’s rapidly evolving clinical research environment, traditional approaches to quality management are no longer sufficient,” said Rachna Malik, Global Head of TCS ADD. She said the upgraded platform supports faster, data-backed decisions and can help bring new therapies to patients more quickly.

Industry trends support TCS’s push toward AI-driven oversight. Adoption of AI in India’s healthcare GCCs has risen sharply from 65% in 2019 to 86% in 2024, Zinnov managing partner Karthik Padmanabhan told AIM, noting that AI tools are now central to improving patient recruitment, monitoring risks, and ensuring regulatory compliance.

The update comes as the life sciences industry increasingly relies on AI and analytics to navigate stricter regulations and the challenges of decentralised, adaptive trials. TCS notes that the platform is aligned with international guidelines ICH E6(R2) and the upcoming E6(R3), and incorporates Quality by Design principles from the start of a study through execution.

TCS says the platform has been used in more than 1,300 studies across 32,000 sites, a sign that AI-driven oversight is fast becoming a standard part of modern clinical research.