Clinical Data – Analytics Platform
Date Submitted: September 6, 2023
Idea Originator: Aastha Vij , Merck KGaA, Darmstadt, Germany
Strategic Priority: Deliver Data-Driven Value at Scale
Problem Statement
All pharmaceutical companies need a platform to do statistical analysis of their clinical data towards regulatory submissions as well as exploratory analysis for further internal insights based on their clinical data. Typically, analysts need programming environments like SAS, R & Python, with (FAIR) access to their internal and external data sources. These analyses need to have detailed audit trails to ensure traceability of every data access or data modification as part of GxP compliance for regulatory submissions. This enforces need for such platforms to be validated & qualified for GxP.
Currently, there are no platforms offered by the technology partners in the industry which offer a mature solution comprising of a flexible and strong ecosystem of IDEs for these different programming languages, coupled with code repository for version control, GxP compliance, sandbox for exploratory analysis, audit trails across interfacing system and easy access to different data sources in the company. Further, the tools for preparing, cleaning data & associated metadata not available as modular, easy-to-integrate products, forcing manual copying of data across systems and making traceability complex.
As this is a shared problem across the industry and simply lacking a good technology solution in the industry, several Pharmaceutical companies are resorting to building their own analysis platforms, spending a lot of money on building technology, taking away time, money and focus from drug development into technology development – which is not the expertise these companies typically have. The differentiating factor for each company is the medicines they produce, and the underlying software platforms ought to be commodity products.
Idea Proposal and Value Proposition
Companies who are interested in leveraging such a platform should join hands in defining the shared needs and identify strong technology partners/ software companies from the industry network to build such a platform jointly instead of each company building this in isolation.
This benefits all Data Analysts and data preparation experts who need to do exploratory or submission related analysis on clinical scientific data. In the end, it also benefits patients, as the companies developing drugs can focus their time, money, and resources on drug development instead of tool development.
Critical Success Factors
Interested companies need to be able to align on their priorities and requirements, be open to sharing their requirements, jointly put funds together to identify a strong technology/software partner to co-develop such a solution, be ready to invest time in guiding this software development process iteratively and test the platforms in their organizations. Companies who have already tried out this internal development activity should come out and openly share their lessons learnt.
