Digital twin deployments in pharmaceutical manufacturing are shifting from experimental pilots to compliance-critical infrastructure as regulatory authorities impose stricter expectations on model validation, data integrity, and audit readiness. In 2026, digital twins are no longer emerging-they are a strategic imperative, with regulators like the FDA and EMA increasingly supporting model-based evidence through risk-based validation, computer software assurance (CSA), and agency-led initiatives.1Advanced Applications for Digital Twins in Pharma | Pharmaceutical Engineering Industry projections place the digital twins market in pharmaceutical manufacturing at approximately $1.3 billion in 2025, growing to $8.5 billion by 2032 at a compound annual growth rate of roughly 30%. Yet implementation in pharmaceutical and biopharmaceutical sectors remains in its early stages, with strict regulatory compliance, the complexity of integrating diverse data sources, and the inherent variability of biological systems impeding widespread adoption.
Regulatory Framework Intensifies
The FDA's September 2025 finalization of its Computer Software Assurance (CSA) guidance has reshaped the validation landscape for digital technologies in regulated manufacturing. The CSA guidance, published on September 24, 2025, supersedes Section 6 of the FDA's earlier "General Principles of Software Validation" and introduces a risk-based framework for software used in production and quality systems. The guidance offers manufacturers a modernized framework, shifting from a rigid, documentation-heavy approach to one emphasizing intended use, process risk, and patient safety impact.
For digital twin implementations, the shift carries direct implications. ISPE has advised quality leaders to treat twins as controlled systems-subject to the same rigor as laboratory or manufacturing software-and has urged engineering teams to document model assumptions while QA ensures validation evidence remains reviewable and audit-ready. A peer-reviewed study published in Computers & Chemical Engineering identified regulatory alignment as the most significant barrier, citing a 9-month validation period required to meet FDA 21 CFR requirements for data integrity, traceability, and audit readiness in manufacturing records.
Meanwhile, FDA researchers from the Center for Drug Evaluation and Research (CDER) have proposed an AI-based digital twin model enabling a simplified continuous direct compression line process.2AI, Robotics & Digital Twins: Accelerating Drug Manufacturing Obstacles remain, however: the industry lacks "standardised mechanisms for neural network model verification and validation," making regulatory submissions challenging, according to the researchers.3Sanofi harnesses Dassault's digital twin tech to optimize production at future vaccine plants
Adoption Data and Industry Moves
Hexagon's 2025 Transforming Pharmaceutical Manufacturing Survey found that only 17% of pharma manufacturing decision-makers currently operate a facility-level digital twin, while 79% use twins in new projects, particularly for design and collaboration. Respondents reported persistent obstacles including data silos, audit burdens, and IoT cybersecurity requirements.
The FDA supports the adoption of advanced manufacturing technologies, but AI in biopharma manufacturing introduces a "validation paradox"-traditional validation proves a process is static and unchanging, while AI models, by definition, improve and evolve as they ingest new data. Regulators and industry consortia are working to define "Continuous Model Verification" frameworks that establish guardrails allowing AI models to learn within a safe, pre-validated design space without requiring a full regulatory filing for every algorithmic update.
Sanofi is among the pharma companies advancing digital twin-driven manufacturing at scale. The company's "Modulus" facilities in Neuville, France and Singapore are expected to be fully operational in 2026, equipped with digital twins, automation, and robotic technologies. Brendan O'Callaghan, Sanofi's Executive VP of Manufacturing and Supply, stated that the new Digital Accelerator "is a major strategic lever for integrating digital agility into every link of our manufacturing value chain."
What Comes Next
Harmonized standards are likely to emerge around digital twin governance, model validation, and cybersecurity. The FDA recently published a draft guidance document on the use of AI models in drug and biological product submissions, underscoring the growing importance of clear regulatory pathways. For manufacturers in pharma and adjacent regulated sectors-biotech, medical devices, and food and beverage-the path from pilot to validated production now runs squarely through compliance readiness, data governance, and cybersecurity planning.
