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TCS ADD™
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TCS ADD™: A Suite of Modern and Open Technology Platforms
TCS ADD™ is a suite of modern and open technology platforms for clinical research and drug development that helps make clinical trials more agile and safe.
Related Insights
This article focuses on a blockchain-based eTMF system that improves clinical trial documentation efficiency & addresses clinical trial data challenges.
White Paper
14 Dec 2022
Meet our leadership team to learn about PV transformation expertise and experience our TCS ADD™ Safety -- An AI Platform for Pharmacovigilance. Join us now.
Events
29 Aug 2023
Learn how NLP and generative AI can address edit check configuration challenges, reducing time to minutes or hours and transforming clinical data management.
White Paper
28 Aug 2024
The 2025 CDISC + TMF US Interchange is a premier industry event bought together global sciences professionals, including leading pharmaceutical companies, regulatory agencies, and technology providers.
TCS has participated as a Ruby sponsor at the 2025 CDISC + TMF US Interchange. Explored how we automate the clinical value chain from protocol and data collection to submission with the TCS ADD™ Metadata Repository platform at the booth #15.
Know more about the TCS ADD™ Metadata Repository platform.
Key takeaway from the session “Accelerating Digital Data Flow using Connected standards and AI”
- AI can be used in every aspect of clincial standard management - Curation, Maintenance, Lineage and Upversioning
- Protocol metadata can be maintained in unstructured and structured approach both with one format convertible to another. Hybrid approach is best for managing Protocol metadata efficiently.
- Main Benefits of Connected Standarda and AI approach include increased Quality, reduced Effort and Regulatory Compliance made much easier.
Key takeaway from the session “Revolutionalizing Digital Data Flow with standards - Are we ready?”
- USDM is going to be one of key foundation standards and has multiple Use Cases which can be targeted through this
- Flexibility and Agility in defining these standards is going to be key for Adoption
- Universal Data Model Builder can enable this agility.
Key takeaway from the poster presentation on “Automation of trial design datasets -a USDM use case”
- How trial design components can be stored from protocol document using AI
- How study definition repository (SDR) can be used to generate trial design data sets with traceability
- Advantages of using USDM aligned digital protocol to automate trial design datasets.
Speakers:
Mayank Bhatia
Head, Digital Data Flow & Metadata Repository, TCS ADD™, TCS
Mayank Bhatia has over 22 years of clinical experience and is the Head of Product Strategy and Management in the TCS ADD™ Metadata Repository. His expertise spans building products and platforms, leading cross-functional teams, achieving operational excellence, and driving change for transformational programs. He has successfully led and delivered many large-scale and critical transformational programs. He holds a bachelor’s degree in computer science and is PMP-certified.
Prasoon Sangwan
Delivery Manager, Lifesciences, TCS
Prasoon Sangwan is a Business consultant for the TCS ADD™ Life Sciences Platform. She has over 18 years of experience and leads major clinical transformation programs, including risk-based dynamic monitoring, central lab modernization, MDR implementation, SDTM automation, and protocol digitization initiatives. Prasoon has authored a book on SAS Grid and published multiple papers in the clinical and SAS space. She also holds a patent on a high-performance computing environment.
About us
TCS ADD™ Metadata Repository is a groundbreaking platform, a first for the industry to address challenges in metadata management and clinical study setup for the pharmaceutical domain. The platform optimizes workflows, enhances data quality, ensures compliance with industry standards, and accelerates study timelines. Key elements encompass end-to-end clinical metadata management (from data collection to tables, listings, and figures (TLF), intuitive mappings, real-time data accessibility, and AI-driven automation for generating submission-ready SDTM (study data tabulation model) and ADaM (analysis data model) datasets.
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