The potential offered by digital twins - whose use is now standard practice in the manufacturing industry- is also emerging in the realm of pharmaceuticals. Simulation offers range of benefits, including speeding up the development of new drugs, testing their potential on different kinds of patients, acquiring statistical data on effectiveness, identifying limits, and guaranteeing quality with a view to optimising production along the entire process.

In addition to digital simulation - which forms the underlying basis of the digital twin concept and has been part of the production process for years now - AI, machine learning, and IIoT are now also paving the way for production processes to go beyond simulation and build predictive models with which to identify pain points and strengths. The next phase in this continuous technological evolution is the metaverse, which - while already trialled in many industrial environments - has yet to be fully exploited in manufacturing.

Its applications in the pharmaceutical world are far-ranging and include research into innovative drugs, with trialling ranging from molecular level up to patient simulation tests. In this case, characteristics such as physiology, gender, and organs are all simulated in order to understand the actual effect of a new drug before moving on to real tests on volunteers.

Finally, use of cellular digital twins in conjunction with AI, the pharmaceutical industry aims to reduce time to market for innovative drugs based on the study and simulation of these drugs at molecule level and their effects at cellular level.

Pharma Almanac discussed the issue at length in. Click here and discover more.