White Paper

Biotech's Mirrored Universe: Predictive Engineering and Digital Twinning

By Barzin Gavtash, Kindeva Drug Delivery

The biotechnology industry is cautious about innovation: change does not take place for its own sake, and it does not happen overnight. Indeed, some therapies remain on the market after 20 years because they have established safety and efficacy, and change could conceivably put patients at risk. 

It is with this wary eye that pharmaceutical companies may view digital twinning and predictive engineering – modern engineering tools considered disruptive techniques and technologies in healthcare.

However, Kindeva already is successfully applying these methods to complex drug delivery device development and is among the only companies in this industry to completely integrate these tools into its product development stream.

Our approach offers product developers a greater understanding of product performance variables based on fundamental science. It also enables organizations to be more agile in their decision-making – versus following a specific, lengthy product development process – saving money, de-risking cutting-edge design innovations, and expediting product market launch timelines. Whether you need to test a design's physical integrity (i.e., drop test) or predict its therapeutic performance, Kindeva has established techniques for every product development step.

This article defines and examines digital twinning as well as techniques that support it, like predictive engineering and predictive analytics. We also look at real-world examples of these techniques benefiting pharmaceutical organizations and detail Kindeva's expertise in this arena.

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