Digital Tools in CMC Survey

Digital CMC CERSI Home
Framework
Workflow
VERA
Case studies
Sandbox
SkillsFactory

This study presents the findings from a cross-sector industry survey exploring the adoption, use, and regulatory challenges of digital and AI-enabled tools in pharmaceutical Chemistry, Manufacturing and Controls (CMC).

Aims of the study

  • Assess current adoption of digital and AI-enabled tools across pharmaceutical development and manufacturing

  • Understand how tools are used (internal decision-making vs regulatory submissions)

  • Identify key barriers to wider implementation, particularly in regulated environments

  • Capture industry perspectives on regulatory expectations and future support needs

  • Inform regulatory science priorities to enable responsible and scalable adoption

Various blister packs of pills and capsules in different colors including white, blue, orange, and brown, scattered on a white surface.

Key findings

An infographic titled 'Digital and AI-Enabled Models in Pharmaceutical Development and Manufacturing: A Regulatory-Focused Industry Survey'. It contains sections on current practice, adoption gap, and challenges. The current practice shows usage percentages for digital and AI tools in various processes, with digital tools being more prevalent. The adoption gap explains the low regulatory filings of digital tools. Challenges include model lifecycle management, regulatory expectations, skills gaps, and company culture change. The bottom section discusses how to accelerate adoption with regulatory clarity, training, case studies, and cross-sector collaboration.

    • Digital tools are commonly used across CMC activities, particularly in process development, monitoring, and control

    • AI-enabled tools are increasingly adopted, though at lower levels than traditional digital approaches

    • Adoption is higher in small molecule and drug product applications

    • Fewer than 15% of tools are included in regulatory submissions

    • Most tools are used internally to support decision-making, rather than as formal regulatory evidence

    This highlights a critical “adoption-to-regulation gap”

    • Improved process robustness and product quality

    • Increased efficiency and reduced development time

    • Cost savings and accelerated time to market

  • The main challenges are not technical, but systemic:

    • Uncertainty in regulatory expectations, especially for AI

    • Skills and expertise gaps in digital and data science

    • Organisational and cultural barriers to change

    • Lack of clear frameworks for validation, governance, and lifecycle management

  • Respondents highlighted the need for:

    • Clear, harmonised international guidance

    • Regulatory training and upskilling

    • Case studies and practical workflows

    • Cross-sector collaboration between industry, academia, and regulators

Implications for regulatory science

The findings show that while digital transformation in CMC is advancing, regulatory implementation is lagging.

This creates a need for:

  • Risk-based, proportionate frameworks

  • Clear definitions of context of use

  • Robust approaches to model credibility and lifecycle management

These are central to the mission of the Digital CMC CERSI in enabling regulator-ready adoption of digital and AI tools.

Join our mailing list

Envelope icon inside a light purple circle.

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

We respect your privacy.

Funded and supported by

UKRI logo with the text 'Innovate UK' beside it.

Stay up to date with news and events from Digital CMC CERSI and the wider CMAC network — including webinars, workshops, and community updates.

Official document header with a crest at the top left and the title 'Medicines & Healthcare products Regulatory Agency' in large black text.