Predictive modelling for cell culture processes in biotherapeutic manufacturing

Interviewer: Dr. Shyam Panjwani, you and your colleagues published a paper earlier this year presenting a new predictive model for optimizing cell culture processes in biotherapeutic manufacturing and we would like to discuss this paper with you in this short interview. To kick things off, can you describe the objective of the project described in your paper and what was the unmet need behind it? Dr. Panjwani: Sure! First of all, thank you Ail for inviting me and I'll be happy to share my research with your readers and audience. The objective of our research was to enhance the efficiency and the predictability of the cell culture process, specifically in the production of biotherapeutics. Our research specifically aimed at addressing the unmet need of a data-driven predictive model in application that could predict bioreactor potency using at-line process parameters, days in advance. There is a reason why we picked potency because potency is an attribute which is not typically measured on the production floor. The samples are sent to a laboratory and so there is a delay in getting the potency measurement value. If we have predictive models like what we developed, then we can use those models to predict potency in the absence of the measured value. These kinds of models actually do not only support the business objective but also fulfills the regulatory requirement that