Digital CMC Centre for Excellence in Regulatory Science and Innovation (CERSI)
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
Aims
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
Developing agile regulatory frameworks
Supporting standardised, 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 and knowledge-sharing to support wider adoption of digital technologies.
The challenge
<15%
of developed digital tools reach regulatory submissions.
Why this matters
About
Digital CMC 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 have provided 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 and AI-enabled tools are transforming how pharmaceuticals are developed and made. 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 gaps in capabilities.
We are changing that through practical frameworks, shared workflows and cross-sector collaboration.
The adoption of digital predictive tools will 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 is helping supporting this transition to 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.
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SkillsFactory
Hosting training resources including interactive courses, webinars, and discussion forums for the digital medicines manufacturing community.
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Virtual Expert for Regulatory Assistance
VERA is an AI-enabled support platform designed to assist with interpretation of regulatory expectations and framework implementation.
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Digital CMC Sandbox
A collaborative environment for testing, evaluation, and demonstration of digital regulatory science approaches.
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Case studies
Demonstrating how the DCRL framework can be applied in real-world CMC scenarios to support innovation, product quality, and patient safety through practical, regulator-ready examples.
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
Funded and supported by
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