Beyond Purely Data-Driven Approaches for Efficient Knowledge Management in Process Development

Knowledge from first principles is freely available and generally valid, and when integrated along with Artificial Intelligence (data-driven) methods, it can greatly improve the understanding and applicability. The applications of such an approach, referred to as hybrid modelling, to a fermentation and controlled drug release case are presented and the learnings from the development of these models are shared.
Presented by Moritz von Stosch, PhD, Senior Manager, Technical R&D, GlaxoSmithKline Vaccines

Moritz von Stosch works as Senior Manager at Technical R&D of GSK Biologicals, Belgium. He is a process systems engineer by education with a Diplom in Chemical Engineering from the RWTH-Aachen University and PhD in Biochemical Engineering from the University of Porto. Before joining GSK, Moritz worked as a Lecturer at the School of Chemical Engineering and Advanced Materials at Newcastle University, where his research focused on the development of novel hybrid modeling methods and their application to enable more efficient process operation/design.
Followed by Klaus Mauch, CEO at Insilico Biotechnology AG

Klaus Mauch is one of Insilico’s co-founders and became managing director in 2004 and CEO in 2006. In his previous role as CTO, he was responsible for the design and development of Insilico’s modelling and simulation platform where he established novel methods for the computer-aided construction of cellular networks. Before that, he gained extensive experience in metabolic engineering and applied systems biology as a group leader at the Institute of Biochemical Engineering, University of Stuttgart. He was awarded a Master’s degree in Chemical Engineering by the Technical University of Karlsruhe, Germany. Klaus is a member of the Advisory Board of the Division Systems Biology and Synthetic Biology of DECHEMA, board member of the Industrial Association White Biotechnology (IWBio), and board member of the Association of German Biotechnology Companies (VBU).
And Shilpa Nargund Data Scientist and Business Development Manager at Insilico Biotechnology AG

Shilpa Nargund is a Data Scientist and a Business Development Manager at Insilico Biotechnology AG. As a Data Scientist, she works on optimizing cell culture processes using Insilico’s Digital Twins, whereas in the role of a Business Development Manager, she is developing Insilico’s business in the APAC region, starting with the establishment of a Singapore office. Previously, she spent 5 years in early and late-stage cell culture process development teams in Biopharma companies across USA, India and Singapore. She is a Chemical Engineer with a Bachelor’s from Institute of Chemical Technology, Mumbai, India and a PhD from the University of Maryland, College Park, USA.
Sponsored by Insilico Biotechnology AG

Insilico Biotechnology AG develops and delivers predictive Digital Twins to advance biopharmaceutical process development and manufacturing. Insilico Digital Twins of cell culture processes lead to superior productivity, product quality and process robustness. Groundbreaking predictive power is achieved by exploiting process data using machine learning and models of biochemical networks. As a result, Insilico’s unique approach substantially reduces experimental effort, costs of goods and time to market. Leading biopharmaceutical companies worldwide use Insilico Digital Twins for cell line development, media design and process control. Founded in 2001, Insilico Biotechnology AG is a privately held company based in Stuttgart, Germany.