AI and digital twins on the factory floor: how drug makers are using them in 2026
Eli Lilly credits AI with producing more medicine than it otherwise could; agentic AI is halving deviation investigations. What is real, and what it needs.
In this article
“Pharma 4.0” was a theme of the 2025 International Pharma Convention at Pharma Asia. In 2026, some of the world’s biggest drug makers are showing what it looks like in practice.
Eli Lilly: more output from the same plants
Lilly uses AI to predict batch outcomes, tune process parameters and detect deviations, and builds digital twins — virtual copies of production lines — to simulate scale-up and find bottlenecks before changing equipment, Pharma Manufacturing reported in June 2026. In one case, a digital twin’s prediction was tested in a pilot and then implemented, sharply shortening a bottleneck step. Chief Information and Digital Officer Diogo Rau said: “We literally made more product last year than we possibly could have without AI.” In October 2025 Lilly also partnered with NVIDIA on a supercomputer intended partly for manufacturing digital twins.
Lilly’s Scot Lindsey stressed that explanations matter: “We don’t want any black box.”
Agentic AI in quality
In July 2026, Megha Sinha of Kolter AI told PharmTech that agentic AI systems in validated GxP environments can cut deviation investigation time by 50% or more — detecting out-of-specification results, pulling batch records and drafting root-cause analyses. She put the market for plant-level digital twins at more than $1 billion, while describing the infrastructure as “half built.”
Research tools reaching industry
Cambridge’s research centre in Singapore (CARES) and A*STAR’s Institute for Infocomm Research have developed an AI platform that builds digital twins from real-time plant data and flags anomalies such as abnormal tank levels before they escalate.
What it needs
| Foundation | Why |
|---|---|
| Clean, connected data | AI cannot learn from paper records |
| Sensors and PAT | Real-time measurements feed the models |
| Validated systems | GMP requires explainable, controlled software |
What it means for Pakistan
The first step for most plants is digitising records and instrumenting lines — work that also supports DRAP’s documentation requirements. Automation and software suppliers exhibit at Pharma Asia 2026.
Sources
- Pharma Manufacturing, “Eli Lilly taps AI, digital twin technology to boost manufacturing capacity”, 11 June 2026
- PharmTech, “Midyear 2026 check-in: agentic AI cuts deviation investigations by 50%”, 17 July 2026
- European Pharmaceutical Review, “AI digital twin developed to boost pharma manufacturing efficiency”
