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

近年来，生物制药的空前增长导致了更好的策略来管理人类慢性疾病，包括糖尿病，免疫缺陷和癌症。 这些治疗剂通常使用从生物血清中提取的纯化蛋白质生产，这产生了对有效、快速和足量生产这些蛋白质以满足不断增长的需求的技术的需求。全球生物制剂市场是制药行业增长最快的市场，全球收入接近1630亿美元;预计每年增长10.9%。 从2013年到2017年，FDA对蛋白质治疗的批准率增加了三倍。 目前市场上有超过200种批准的生物素药物，其中超过1500种正在进行临床试验，更多的药物正在筹备中。 该项目旨在通过开发一个精确的计算模拟框架来描述蛋白质分离策略的新方法，帮助生物制造商扩大现有设施的生产能力。 该模拟将与优化算法一起使用，以帮助工程师提高吸附膜的性能，从而减少制造中的瓶颈。该项目的动机是需要高效的新分离和纯化过程的蛋白质治疗。生物制剂的出现，例如来自生物技术的药物，作为管理人类慢性疾病的主要方式，已经产生了对更低成本、更快的生物制造操作的迫切需求，以使这些产品对于不断增长的患者群体来说是可获得的并且是更可负担的。本研究项目将开发数值方法来解决模拟这些过程所需的数学描述。数学描述将包括新的、更复杂的离子交换关系，其将固相吸附定义为液相吸附的隐式函数，这与标准的显式数学关系相比是显著的变化。 该项目的目标是开发，验证，分析和使用计算工具，为生物制造环境提供新的快速膜色谱纯化过程的设计。 具体而言，研究小组将开展四项主要研究活动：（1）开发和测试计算框架;（2）分析色谱吸附过程的非线性和隐式模型的计算模型;（3）使用实验数据验证计算工具;（4）分析色谱吸附过程的非线性和隐式模型。以及（4）使用所开发的计算框架来理解设计参数对期望结果的影响的基于仿真的优化。该项目由DMS的计算数学计划和刺激竞争研究的既定计划（EPSCoR）共同资助。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.