Reimagining a critical R&D process through AI

A top 10 global biopharmaceutical company partnered with Baringa to address a challenge familiar across R&D: a highly regulated, overly complex and document intensive process slowing teams down, and a desire to use AI without a clear or credible route to value. 

The Trial Master File (TMF) process is central to regulatory compliance, and at our client this was heavily manual, pulling study teams away from milestone-driving activities and into administrative tasks. The business knew AI could help, but lacked clarity on ROI, technical feasibility within their IT landscape and how to move quickly without compromising GxP and ongoing study delivery.  

Over nine weeks, Baringa ran a fast-paced AI diagnostic to cut through assumptions and uncover where AI and automation would deliver meaningful value. The work secured strong executive sponsorship and cross-functional alignment, creating the momentum to move immediately into solution design and build, which is now underway as a strategic AI initiative with our continued support. 

Quickly articulating a quantitative value case 

Within a few weeks of landing into the project, the Baringa team had analysed key process documentation, metrics and held user pain point workshops which were used to summarise a clear quantitative value case. This was critical to successful early engagement with senior stakeholders across R&D and IT organisations and building momentum and support for the project right from the beginning.  

We identified that over 400,000 hours of effort (equivalent to >200 FTEs) across the organisation were spent on manual and administrative eTMF tasks that were perfect use cases for AI. We also identified the steps in the process that sucked up the most resource, and those that were duplicative or low value. Finally, we identified some key areas where TMF quality was currently a concern or raised inspection risks, where AI and automation could help to drive consistency and control.  

Leveraging deep R&D expertise 

Our team brought deep R&D, process and AI expertise together to accelerate the project and provide an outside-in challenge on how the process could be re-imagined with AI while retaining GxP compliance on a critical process.  

This was important to address typical change resistance, and to ensure that we weren’t simply automating a “bad” process but also challenging the status quo and re-designing the process where it was no longer fit for purpose or out of line with industry practice, embracing a new risk-based way of approaching R&D.  

Defining a bold AI vision, grounded in practical delivery 

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We shaped a long-term vision for an agentic AI driven TMF ecosystem that continuously scans for, checks, classifies, and prepares documents for inspection readiness, freeing study teams from repetitive tasks and document management all-together.  

But we paired that ambition with pragmatism. Together with the client, we designed a tightly scoped MVP that targets high-volume document types, embeds human-in-the-loop oversight for GxP integrity, minimises disruption to teams and platforms and demonstrates early value while laying foundations for enterprise scaling.  

The MVP will be developed and deployed with in one initial team, which will deliver ROI within 1-2 years and cost savings of up to $4M within 3 years. Once scaled and rolled out to the whole of R&D, the value could be circa $25M in cost savings over 3 years to the business.  

The outcome: sponsorship, alignment and momentum to build 

By the close of the diagnostic, the organisation had: 

• A business case in the range of $10-25M cost savings for a scaled R&D AI solution for eTMF management  
• A future-state blueprint endorsed across R&D, Clinical Systems, and IT 
• Executive sponsorship to move forward rapidly into solution design and build 
• A repeatable framework for AI diagnostics across adjacent R&D processes