A Strategic Framework for Evaluating Next-Generation Technologies in Biocatalysis

Abstract

The emergence of a new wave of biocatalysis innovation is rapidly transforming the pharmaceutical industry. This next generation of techniques, characterized by metagenomics, artificial intelligence, and computational modeling, is reshaping approaches to process development for companies operating in this space. However, significant challenges exist in fully harnessing the potential of this new technology due to limitations in internal capabilities, including time constraints and knowledge gaps. To overcome these obstacles and unlock the true growth potential of biocatalysis, pharmaceutical companies must strategically leverage external supply organizations to tap into the next wave of biocatalysis innovation and bridge its existing capability gaps. This thesis proposes a comprehensive framework for the site selection of a next-generation technology contract development and manufacturing organization (CDMO) in biocatalysis. This framework adopts a tiered approach, with a primary focus on the use of real options analysis to facilitate quantitative decision-making in emerging technology site selection. Following the framework establishment, its application challenges the initial high-cost assumptions associated with emerging technology CDMOs, revealing a significant 20% reduction in expected costs. Overall, this de-risks the emerging technology investment and drives the implementation of novel and innovative processes in early-phase biocatalysis.