Clean Batch Manufacturing with Uncertainty Management (TSE03-K)

University Of Illinois At Chicago, Chicago IL

Investigators

Abstract

This NSF/EPA TSE project addresses trade-off issues between environmental and economic impacts in the pharmaceutical industry for new drug design and approval. Key issues facing the decision-makers in drug manufacture place numerous demands upon the design process. For example, batch operating procedures should be optimized at the conceptual design phase, since later improvements require expensive, FDA re-approval. In addition, uncertainty in properties and operations must not deteriorate the purity of the stage intermediates, and stringent purity requirements make internal recycles to the next batch less customary. This project is expected to make a computer-aided batch process development methodology with two salient features, a plant-wide problem representation aimed at unifying the corporate production targets and the environmental objectives; and the generation of mathematical algorithms to quantify the impact of uncertain information about the process and the materials. Design models will make use of probabilistic methods for quantifying the impact and cost of uncertainty. A multi-period planning framework with optimal trade-off between economic and ecological targets is planned, to facilitate investment decisions over a five-year planning horizon, and to create a sustainable plant management scheme for participation in permission trading markets. This project is expected to make significant improvements in technological and ecological competency of a large group of pharmaceutical and specialty chemical manufacturers. It is also expected that the framework designed for pharmaceuticals will be found to be applicable to other industrial sectors where trade-offs between economics and the environment are considered the norm. The engineering curricula will benefit from course enhancements for batch process design with ecological considerations and through new approaches to process "design for the environment" under uncertainty, bringing probabilistic methods and the fundamentals of green engineering into design training at the undergraduate and graduate level.