A multi-level meta-heuristic algorithm for the optimisation of antibody purification processes
A multi-level meta-heuristic algorithm for the optimisation of antibody purification processes
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DOI：
10.1016/j.bej.2012.08.013
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发表时间：
2012-12-15
影响因子：
3.9
通讯作者：
Farid, Suzanne S.
中科院分区：
文献类型：
--
作者：
Simaria, Ana S.;Turner, Richard;Farid, Suzanne S.
多产品生物制药设施需要灵活的工艺配置，以适应具有不同特性和杂质负载的产品，从而避免瓶颈和延迟，同时满足最终产品规格和成本目标。为了帮助设计这样的设施，这项工作提出了一个元启发式优化方法，使用遗传算法，解决不同层次的决策（设施，产品序列和单元操作）和多个过程和业务标准被用来评估每个替代品产生。这适用于治疗性单克隆抗体（mAb）生产的案例研究，重点是最佳纯化序列和色谱柱尺寸策略，以科普上游和下游列车的不同设施配置和不同的产品杂质负荷。工业案例研究提供了新的见解，允许识别最具成本效益的纯化序列和柱尺寸策略，以满足设施中每种产品的需求和纯度目标。重点也放在提供方法来可视化的权衡在一组最佳的解决方案，具有类似的成本值，以提高决策过程。(c)2012 Elsevier B.V.保留所有权利。
Multi-product biopharmaceutical facilities need flexible process configurations that can adapt to products with diverse characteristics and impurity loads so as to avoid bottlenecks and delays, whilst meeting final product specifications and cost targets. In order to aid the design of such facilities, this work presents a meta-heuristic optimisation approach using genetic algorithms where different levels of decision are addressed (facility, product sequence and unit operation) and multiple process and business criteria are used to evaluate each alternative generated. This is applied to a case study on the production of therapeutic monoclonal antibodies (mAbs), with a focus on the optimal purification sequences and chromatography column sizing strategies to cope with different facility configurations of upstream and downstream trains and different product impurity loads. The industrial case study provides novel insights that allow the identification of the most cost-effective purification sequences and column sizing strategies that meet demand and purity targets for each product in the facility. Emphasis is placed also on providing methods to visualise the trade-offs in the set of optimal solutions with similar cost values so as to enhance the decision making process. (c) 2012 Elsevier B.V. All rights reserved.