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Top Results
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Industry
Life Sciences
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Patient-centered Care Models Taking Center Stage in Life Sciences
Read how patient-centric care models and pharma innovation are ushering new trends in life sciences to improve patient outcomes and enrich lives.
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At the TCS Pace Port™, leaders explored the immense potential of AI and generative AI in the pharma industry during the Life Sciences Forum event. Learn more.
Article
02 Dec 2024
With EU MDR’s deadline extension, medtech manufacturers can leverage next-gen technologies and build on connected, collaborative, and cognitive value chains.
White Paper
29 Nov 2024
Know how regulatory teams can overcome hurdles like unclear IVD/CDx regulatory path and lengthy drug approval time to offer personalized and comprehensive care.
Blog
16 Sep 2024
Products and Platforms
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.
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This paper highlights challenges in data transfer agreement and demonstrates how the proposed e-DTA solution can transform the clinical trial industry.
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18 Dec 2024
Engage with our experts at the World Drug Safety Congress Americas 2024 to learn about AI in pharmacovigilance and our TCS ADD™ Safety platform. Join us now.
Events
09 Sep 2024
Join us at the life sciences event to learn how AI and generative AI can accelerate next-gen clinical R&D and enhance patient safety. Register now for the event.
Events
07 Aug 2024
Reimagining reporting and visualization during clinical data management
Clinical data management is an important part of clinical trials involving the monitoring of the study parameter analytics, which might include statistical analysis of the captured patient data and management data such as audit trials and queries. Reports and dashboards enable reviewers to access the required analytics from the clinical trial management system. Access to quality reporting data is the key to efficient data management and study success.
Most of the reports are predefined and offer little or no configuration options to fine tune the report fields and filters. In real-world situations, the users often run into scenarios where they need a specific type of report containing specific fields or filter conditions that may not be available in the clinical trial management system.
The answer to the problem is an AI-based solution that can understand natural language input and translate the same into database queries. The solution accepts a natural language, plain English prompt from the end user specifying the report fields and filter requirements. AI translates the requirements into database queries and executes them to generate and download the required report. Thus, the solution reimagines the reporting solution from traditional user dashboards and canned reports to user-driven, natural language-based intelligent reports along with trend analysis and recommendations.
This solution does not need the user to have low-code/no-code custom report building skills or specialized SQL/CQL skills. On an average, a person needs to grasp the low-code/no-code platform and then learn SQL/CQL along with the database schema which might take months to master whereas with this proposed solution, no upskilling is necessary.
On an average, a custom report development takes weeks to months in the existing clinical trial landscape. Our proposed solution can cut down that turnaround time to minutes by drastically reducing the time and manual effort needed to generate the reports.
To read the complete paper, please click here.
About the authors
Image of Vandita Tripathi
Vandita Tripathi
Vandita Tripathi is working as the Product and Portfolio Head for TCS ADD™, part of the Life Sciences unit at TCS.
Image of Manas Saha
Manas Saha
Manas is a .NET and Azure architect and Technical Lead with 16+ years of experience in developing and designing software solutions using Microsoft technologies.
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