Tangential flow filtration of biotechnological products: Dimensionless modeling to rationalize resources in research while supporting translation to industry

In silico methods are strategic when difficulties prevent analytical solutions from being deduced or obtaining experimental (real-operation) data becomes awkward – perhaps unfeasible – due to safety, technological, environmental, economic, and ethical issues. At the Laboratory of Renewable Resources Engineering (Purdue University, USA), tangential flow filtration (TFF) has been researched to separate biotechnological products. Given the costs of physical testing, in silico TFF can save valuable energetic, material, or human resources in translation to industry, thus supporting Sustainable Development Goals. All-inclusive models can improve TFF performance and enhance the reproducibility of extant bioproducts as well as accelerate process design and development of future ones. In primitive formulation, comprehensive models invoke several variables and influential parameters, which jeopardizes sensitivity analysis and scale-up. This project will cast TFF models into dimensionless form for thinking-enhancement purposes. As primitive variables and parameters are lumped into fewer dimensionless ratios, in silico research will be rationalized. Deterministic modeling will be combined with data-driven simulation (e.g., machine learning) for realistic virtualization and industrial applicability. As the biomanufacturing process is expensive and hard to scale, producers will unravel reliable and sustainable bioproducts. In terms of societal benefits, patients will gain faster and better access to drugs and therapies.