October 13-14, 2025 | Loews Nashville at Vanderbilt Plaza, Tennessee, United States
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Our expert, committed team put our shared values into action – every day. With the best talent and the latest technology we help customers turn complexity into opportunities and create meaningful change.
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October 13-14, 2025 | Loews Nashville at Vanderbilt Plaza, Tennessee, United States
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The 2025 CDISC + TMF US Interchange is a premier industry event bringing together global sciences professionals, including leading pharmaceutical companies, regulatory agencies, and technology providers.
TCS is participating as a Ruby sponsor at the 2025 CDISC + TMF US Interchange. You can explore 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.
Expert sessions:
Session 1 – AI Innovation showcase | Oct 13 | 13:30 – 13:45 ET
Title: AI Empowered Metadata Governance
AI/ML-driven platform that advances the digitization and automation of clinical research using CDISC standards.
In this session we explore the current Metadata Repository uses AI/ML and in enriching metadata management. Highlights the ease of maintenance of standards, generation of traceability and transformation specifications, identifying redundancies along with the flexibility of including new standards with dynamic data model builder.
Session 2 – Digital Study Design | Oct 13 | 16:00 – 16:30 ET
Title: Accelerating digital data flow through connected standards-driven automation and AI
Diving into the vital role of metadata governance for seamless, and digitally empowered clinical trials and unveiling how AI and ML redefine metadata management. This is accomplished by automating standards creation, enabling precise traceability, and preserving lineage across clinical data standards transforming the complexities of data into a manageable, streamlined flow.
Poster presentation | Oct 14 | 12.30 – 13:30 ET
Title: Automation of Trial Design Dataset Generation – A USDM Use case
This Poster explores how Artificial Intelligence (AI) and Machine Learning (ML) techniques can be leveraged to automate and streamline the generation of Trial Design datasets. By extracting relevant data from protocols, Case Report Forms (CRFs), and other Study Data Tabulation Model (SDTM) domains, AI/ML models can significantly reduce manual effort and improve accuracy.
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.
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.
What’s in store
This year’s program will feature critical discussions on AI-driven automation, regulatory compliance, the evolving landscape of clinical data standards in the European clinical research landscape, digital data flow, ADaM dataset optimization, ARS, and advancements in trial master file (TMF) management.
To schedule a meeting with our product experts, write to us @add.platform@tcs.com or meet us at our booth 15 at the 2025 CDISC + TMF US Interchange.
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.