A roadmap to AI-driven in silico process development: bioprocessing 4.0 in practice

In silico process development constitutes a viable option for accelerating CMC development timelines and can be achieved through either a hybrid-modeling-driven or an Artificial Intelligence (AI)-driven avenue. Each pathway has its own pros and cons but the biggest difference is that the former can be developed in-house whereas the latter requires inter corporation collaboration. Motivated by the precedence of inter-corporation data ecosystems targeting drug discovery, in this paper we bring forward the case of the AI-driven approach to in silico process development in terms of both technical feasibility and scientific soundness. Our analysis asserts that methodologically, AI is now mature to be employed for the task at hand, provided that the overall exercise is driven by multidisciplinary experts. Further, in silico process development should be understood as a collection of models, with each process unit being endowed with its own model.

Automated summary

In silico process development can be accelerated through hybrid-modeling-driven or Artificial Intelligence-driven approaches, with the former allowing for in-house development and the latter requiring inter corporation collaboration. The paper focuses on the AI-driven approach, emphasizing the importance of multidisciplinary experts in the overall process.