Per Pharma’s Almanac, digital twins (DT) have many potential applications in the pharma industry, from accelerating drug discovery/development to optimizing manufacturing processes and clinical trials and potentially facilitating development of personalized medicines.
One application is the use of DT to improve manufacturing processes and enhance production. GlaxoSmithKline (GSK) and Sanofi are two examples. GSK worked with French firm Atos and Siemens to pilot a DT of one of its vaccine manufacturing processes. They expect to leverage DT for other vaccine manufacturing processes, potentially as simulators for operator training, and ultimately see them used as routine tools. Sanofi is working with Dassault Systemes to explore use of DT for vaccine manufacturing, the goal being to establish optimal processes before actual deployment and create virtual manufacturing systems that mimic processes Sanofi has under development.
Clinical trials are also a big opportunity. They account for a large portion of drug development costs and are often inefficient. They typically also do not represent the true patient population or real-life experiences of patients. DT can help overcome key issues by simulating diverse patient characteristics, accelerating patient selection and predicting patient responses. They can also cut the number of actual patients subjected to real-world testing, raising the efficiency/effectiveness/safety of clinical trials while reducing cost.
Other benefits include more efficiently tracking processes to ensure compliance with regulatory requirements, improving data integrity, facilitating the move to continuous processing and reduced infrastructure costs. DT can also be used to track maintenance /operational issues to identify equipment that must be repaired or replaced before it fails and reduce the need for skilled labor, which is in short supply in the pharma industry. McKinsey estimates the savings for pharma companies that leverage DT could improve productivity as much as 150-200%.
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