How to optimise DSP with AI simulations and achieve 50% unit cost reduction
Downstream processing (DSP) is a critical cost driver in industrial biotechnology, often making up a substantial portion of overall production costs. Optimising the purification and recovery steps can significantly impact yield, scalability, and economic viability.
In this webinar, we will discuss:
DSP challenges and optimisation approaches – Key cost drivers, traditional purification, and recovery methods.
Design of Experiments (DoE) in DSP – Conventional approach to process optimisation.
AI-driven simulations for process improvement – Using in silico modelling and iterative experimentation.
Case Study: Helping Multus Biotechnology achieving 8.6x recovery increase and 55% cost reduction with AI-powered Bioprocess Foresight.
Join us to gain technical insights and understand how they translate into real-world application, as we walk you through a case study on leveraging AI for smarter, cost-effective DSP.