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

合作研究：推进化学分离模拟：计算算法和隐式吸附等温线优化

• 批准号: 2011911
• 负责人: Anastasia Wilson
• 金额: $ 14万
• 依托单位: AUGUSTA UNIVERSITY RESEARCH INSTITUTE, INC.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2011911&HistoricalAwards=false
• 关键词: Collaborative; Research; Advancing; Chemical; Separation

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, i.e., 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 aims to 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 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.

近年来，生物制药的空前增长已经为管理人类慢性疾病（包括糖尿病、免疫缺陷和癌症）带来了更好的策略。这些治疗药物通常使用从生物血清中提取的纯化蛋白质来生产，这就产生了对有效、快速和足够数量地生产这些蛋白质以满足日益增长的需求的技术的需求。全球生物制品市场是制药行业增长最快的市场，全球收入接近1630亿美元；预计年增长率为10.9%。从2013年到2017年，FDA对蛋白质疗法的批准率增加了三倍。目前市场上有超过200种已批准的生物治疗药物，超过1500种正在临床试验中，还有更多正在筹备中。该项目的工作旨在通过开发描述蛋白质分离策略新方法的精确计算模拟框架，帮助生物制造商扩大其现有设施的生产能力。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。这个项目的动机是需要有效的新的分离和纯化工艺的蛋白质治疗。生物制剂（即来自生物技术的药物）作为管理人类慢性疾病的主要方法的出现，迫切需要更低成本、更快的生物制造操作，使这些产品能够为不断增长的患者群体提供并更负担得起。该研究项目旨在开发数值方法来解决模拟这些过程所需的数学描述。数学描述将纳入新的，更复杂的离子交换关系，将固相吸附定义为液相吸附的隐式函数，这是标准显式数学关系的重大变化。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、快速的膜色谱纯化过程的设计。具体而言，研究小组将进行四项主要研究活动：(1)开发和测试计算框架；(2)色谱吸附过程的非线性和隐式模型的计算模型分析；(3)利用实验数据验证计算工具；(4)利用开发的计算框架进行基于仿真的优化，以了解设计参数对期望结果的影响。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。