Leveraging Synthetic Test Data for Automated Database Validation

1. Leveraging synthetic test data in clinical trials
2. Automation of EDC database validation
3. Robust user acceptance testing in clinical data management

ACDM members and non-members who would like to join an open discussion concerning a Hot Topic in Data Management.

1. Learning Patterns: The AI looks at data from past clinical trials to learn what real patient information looks like. It then creates fake data that follows those same patterns.
2. Creating “Discrepant” Data: The AI is then trained to create incorrect or “dirty” data. This is used to test if the database design/edit checks is smart enough to spot mistakes and follow the rules, which means the AI model will read the edit check  document and create data which can validate the DB design.

• It is faster: It automates the testing.
• It is realistic: AI can create a wider variety of “what-if” scenarios making  testing more reliable.
• Reduces go live timelines
• Regulatory compliance maintained

MEET THE PRESENTERS

Sravan Kumar Basani is a Lead Data Manager with over 14 years of hands-on experience in Clinical Data Management and Project Management. He earned his Master’s degree in Pharmaceutical Sciences from the University of Greenwich, UK, and holds certifications in Clinical Data Management from the Society for Clinical Data Management (SCDM), as well as Project Management Professional and Power BI Data Analyst credentials.

Throughout his career, he has actively managed end-to-end clinical data processes, applying CDISC standards, overseeing SDTM implementation, conducting audits, and working with Medidata Rave databases, IRT/IVRS, and safety gateway applications.

He leads projects with strategic resource planning, vendor coordination, budget management, and a focus on delivering high-quality results on schedule.

He has collaborated with top organizations like Novartis, IQVIA, Parexel, Syneos, and Tech Observer, successfully driving multiple clinical trial programs and leading cross-functional teams.

He prides himself on working closely with stakeholders at all levels to align objectives and ensure compliance. He proactively manages project risks, maintains audit readiness, and oversees financials to achieve successful outcomes.

He continuously innovates by leveraging tools such as AI and Power BI to streamline data review and automate reporting. His passion for innovation and learning drives him to engage with industry experts and collaborate in developing efficient methodologies that advance clinical data management.

Revathi Sankar is a Senior Manager at SRM Tech, where she leads Life Sciences R&D Clinical Technology initiatives and drives strategic digital transformation across the clinical research domain. With more than 16 years of experience, she has extensive expertise in clinical data management, EDC platforms, clinical study build, analytics, and technology-enabled clinical operations, supporting global pharmaceutical and life sciences organizations across complex clinical development programs.

In her current role, Revathi is focused on advancing AI-enabled clinical technologies, modern eClinical platforms, and digital innovation to accelerate the transformation of clinical research. She collaborates with pharmaceuticalcompanies, CROs, and technology partners to deliver scalable, technology-driven solutions that enhance operational efficiency, data quality, regulatory compliance, and patient-centric clinical research. Her professional interests include AI adoption in clinical trials, intelligent automation, and next-generation digital solutions for the Life Sciences industry.