Description
Francesco Destro discusses development of computational methods for improving AAV (adeno-associated virus) gene therapy manufacturing, addressing critical challenges of high costs ($100,000-$300,000 per dose) and limited production capacity. Francesco presents three modeling approaches: first, an intracellular mechanistic model that identified therapeutic gene underproduction as the bottleneck causing empty viral capsids and suggested protein overexpression to increase full-to-empty ratios; second, a population balance model that enabled design of a three-tank continuous manufacturing system achieving stable production for four weeks by managing baculovirus genetic instability through infection-age tracking; and third, a machine learning model combined with suspended microchannel resonator technology that provides near real-time AAV titer predictions, replacing expensive offline assays and enabling faster process optimization.