> ## Content Index
> Fetch the complete content index at: https://www.theleftshift.com/llms.txt
> Use this file to discover other available public pages before exploring further.

# TCS Launches Next-Generation AI-Powered RBQM Platform for Smarter, Faster Clinical Trials
- URL: https://www.theleftshift.com/tcs-launches-next-generation-ai-powered-rbqm-platform-for-smarter-faster-clinical-trials/
- Published: 2025-11-24T06:43:50.000Z
- Updated: 2025-11-24T06:43:50.000Z
- Description: The enhanced platform introduces four new interoperable modules: risk assessment and categorisation, quality tolerance limits, clinical trial analytics, and subject data analytics.
- Author: The Left Shift Bureau
- Tags: Indian IT

Tata Consultancy Services (TCS) has unveiled the next generation of its TCS ADD™ Risk-Based Quality Management (RBQM) Platform. The upgraded end-to-end platform introduces a comprehensive suite of AI-driven modules designed to provide pharmaceutical companies, MedTech firms, personal care sponsors, CROs, and research institutes with proactive, intelligent, and regulatory-compliant oversight across the clinical trial lifecycle.

 *“The platform’s AI and advanced analytics capabilities enable our clients to make data-driven decisions, optimise resource allocation, and ultimately bring life-changing therapies to patients faster and more efficiently. This version represents our most comprehensive vision yet for RBQM,”* [*Rachna Malik*](https://www.linkedin.com/in/rachna-malik-53911316/?ref=theleftshift.com)*, Global Head, TCS ADD™, said.*

The enhanced platform introduces four new interoperable modules: risk assessment and categorisation, quality tolerance limits, clinical trial analytics, and subject data analytics. These modules allow user-driven configuration to support diverse trial designs and monitoring models, ensuring faster deployment.

The RACT module offers smart workflows for streamlined documentation and approvals, while the QTL module provides AI-led statistical tolerance analytics through an extendable library. 

The Clinical Trial Analytics module uses proprietary AI algorithms to monitor site performance and identify issues in real-time. Meanwhile, the Subject Data Analytics module centralises statistical monitoring with AI-based risk scoring, outlier detection, and automated alerts.

Aligned with ICH E6(R2)/E6(R3) guidelines and Quality by Design (QbD) principles, the platform enables predictive insights, automated workflows, and continuous risk monitoring. 

Early adopters have reported up to 30% improvement in trial monitoring efficiency and 20% reductions in site monitoring costs. With more than 30,000 users and 1,300 studies supported, the latest release reinforces TCS ADD™ as a leader in AI-powered clinical research transformation.