Collaborative Research: Advancing Chemical Separation Simulations: Computational Algorithms and Optimization with Implicit Adsorption Isotherms

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The unprecedented growth of biopharmaceuticals in recent years has led to better strategies for managing chronic diseases in humans including diabetes, immunodeficiencies, and cancer. These therapeutics are often produced using purified proteins extracted from biological sera, which has created a need for technologies that produce these proteins efficiently, quickly, and in sufficient quantities to meet the growing demand. The global market for biologics is the fastest growing market in the pharmaceutical industry with global revenues near $163 billion; it is expected to grow annually by 10.9%. FDA approval rates for protein therapeutics increased threefold from 2013 to 2017. There are currently over 200 approved biotherapeutic drugs on the market with over 1500 in clinical trials and more in the pipeline. The work in this project seeks to aid bio-manufacturers in expanding their production capacity in existing facilities by developing an accurate computational simulation framework for describing new methods of protein separation strategies. The simulation will be used with optimization algorithms to help engineers improve the performance of adsorption membranes which in turn will reduce bottlenecks in manufacturing.This project is motivated by the need for efficient new separation and purification processes for protein therapeutics. The emergence of biologics, for example drugs derived from biotechnology, as a leading way to manage chronic diseases in humans has created a pressing need for lower cost, faster biomanufacturing operations to make these products available and more affordable for growing patient populations. This research project will develop numerical approaches to solve the mathematical descriptions needed to simulate these processes. The mathematical descriptions will incorporate new, more complex ion-exchange relationships that define the solid phase adsorption as an implicit function of the liquid phase adsorption, a significant change from the standard explicit mathematical relationships. The goals of this project are to develop, validate, analyze, and use computational tools to inform the design of new, rapid membrane chromatography purification processes for bio-manufacturing environments. Specifically, the research team will work on four major research activities: (1) development and testing of a computational framework; (2) analysis of computational models for nonlinear and implicit models of chromatographic adsorption processes; (3) validation of the computational tools using experimental data; and (4) simulation-based optimization using the developed computational framework to understand the effects of the design parameters on desired outcomes. This project is jointly funded by the Computational Mathematics program of DMS, and the Established Program to Stimulate Competitive Research (EPSCoR).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.