Digital CMC Centre for Excellence in Regulatory Science and Innovation
Enabling regulatory-ready digital transformation in pharmaceutical development and manufacturing
Funding: £1 million
Duration: 14 months
Funded and supported by: Innovate UK, Medicines and Healthcare products Regulatory Agency and the Office for Life Sciences
Academic partners: De Montfort University, The Cambridge Crystallographic Data Centre
Founding Industry partners: AstraZeneca, Bristol Myers Squibb, GSK, Pfizer and Siemens
The challenge
Fewer than 15% of digital tools reach regulatory submissions.
We seek to change that through practical frameworks, shared workflows, and cross-sector collaboration.
Digital and AI-enabled tools are transforming pharmaceutical development and manufacturing. Yet adoption in regulated Chemistry, Manufacturing and Controls (CMC) activities remains uneven, held back not by technology, but by uncertainty around regulatory expectations, fragmented guidance, and capability gaps.
About
The Digital CMC Centre for Excellence in Regulatory Science and Innovation (CERSI) is a collaborative initiative led by CMAC at the University of Strathclyde and supported by the Medicines and Healthcare products Regulatory Agency (MHRA).
We provide a neutral, pre-competitive environment for industry, regulators, and academia to advance the responsible adoption of digital and AI-enabled tools in pharmaceutical CMC.
Digital CMC CERSI aims to:
- Accelerate safe and effective digital transformation in pharmaceutical CMC
- Develop practical regulatory science frameworks and workflows
- Build shared understanding between industry, regulators, and academia
- Support harmonisation, transparency, and lifecycle-based governance
- Enable sustainable and resilient medicines manufacturing
Approach
The Digital CMC CERSI has created a collaborative environment where industry, regulators and academia can work together to explore new approaches to digital regulatory innovation.
The project focused on:
Developing agile regulatory frameworks - Supporting more standardised and forward-looking approaches for digital CMC and regulatory decision-making.
Advancing digital and AI-enabled technologies - Exploring the application of AI, machine learning, hybrid models and predictive tools through collaborative case studies and engagement activities.
Building capability across the sector- Delivering training, workshops, webinars and knowledge-sharing activities to support the wider adoption of digital technologies.
Why this matters
The responsible adoption of digital predictive tools could enable:
Faster patient access to medicines
More robust and resilient manufacturing
Improved sustainability
Better process understanding
Reduced development costs and timelines
Stronger supply chain agility
Achieving these benefits requires trusted, transparent, and regulator-ready approaches that maintain patient safety and product quality.
The Digital CMC CERSI exists to help bridge the gap between innovation and implementation.
Outputs and Resources
The Digital CMC Regulatory Lifecycle (DCRL) Framework
A risk‑based structure that supports the management of digital predictive tools across the pharmaceutical CMC lifecycle, enabling confident, regulatory‑ready adoption.
The Digital CMC Regulatory Lifecycle (DCRL) Workflow
A guided sequence for the development, validation, and regulatory use of digital and AI-enabled tools across their full lifecycle.
Webinars and videos
Papers
Submitted
Digital and AI-Enabled Models in Pharmaceutical Development and Manufacturing: A Regulatory-Focused Industry Survey
A global industry survey of pharmaceutical companies exploring the use of computational models in CMC, focusing on barriers to adoption and levels of implementation in both regulated and non-regulated settings. The study includes knowledge-based, data-driven, and hybrid AI/ML-enabled models.
Coming soon
Digital Transformation in Pharmaceutical CMC: Enabling Regulatory-Ready Adoption of Computational Models
A white paper co-authored with industry and the MHRA outlining the rationale, philosophy, and proposed approach to accelerating the adoption of predictive digital tools in regulatory submissions and inspections. It sets out the case for digital tools in CMC and proposes a consistent framework for ensuring predictive models (including AI/ML) are regulatory-ready, bringing together current regulatory guidance, standards, and scientific best practice.
Exemplification of a workflow for credibility assessment on 4 predictive model types
A case study–led paper co-authored with industry that details the DCRL workflow, demonstrating its application across four representative predictive model types to illustrate practical implementation and assessment of model credibility.
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Funded and supported by the MHRA and the Office for Life Sciences (OLS) managed by Innovate UK with delivery partner Medical Research Council (MRC) the as part of the “RS&IN Implementation Phase: Human Health CERSI” Innovate UK: Project no. 10139447
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