LAPSE:2024.1536
Published Article

LAPSE:2024.1536
Hybrid Rule-based and Optimization-driven Decision Framework for the Rapid Synthesis of End-to-End Optimal (E2EO) and Sustainable Pharmaceutical Manufacturing Flowsheets
August 16, 2024. Originally submitted on July 9, 2024
Abstract
In this paper, a hybrid heuristic rule-based and deterministic optimization-driven process decision framework is presented for the analysis and optimization of process flowsheets for end-to-end optimal (E2E0) pharmaceutical manufacturing. The framework accommodates various operating modes, such as batch, semi-batch and continuous, for the different unit operations that implement each manufacturing step. To address the challenges associated with solving process synthesis problems using a simulation-optimization approach, heuristic-based process synthesis rules are employed to facilitate the reduction of the superstructure into smaller sub-structures that can be more readily optimized. The practical application of the framework is demonstrated through a case study involving the end-to-end continuous manufacturing of an anti-cancer drug, lomustine. Alternative flowsheet structures are evaluated in terms of the sustainability metric, E-factor while ensuring compliance with the required production targets and critical product quality attributes.
In this paper, a hybrid heuristic rule-based and deterministic optimization-driven process decision framework is presented for the analysis and optimization of process flowsheets for end-to-end optimal (E2E0) pharmaceutical manufacturing. The framework accommodates various operating modes, such as batch, semi-batch and continuous, for the different unit operations that implement each manufacturing step. To address the challenges associated with solving process synthesis problems using a simulation-optimization approach, heuristic-based process synthesis rules are employed to facilitate the reduction of the superstructure into smaller sub-structures that can be more readily optimized. The practical application of the framework is demonstrated through a case study involving the end-to-end continuous manufacturing of an anti-cancer drug, lomustine. Alternative flowsheet structures are evaluated in terms of the sustainability metric, E-factor while ensuring compliance with the required production targets and critical product quality attributes.
Record ID
Keywords
Derivative-Free Optimization, Industry 40, Modelling and Simulations, Optimization, Process Synthesis
Subject
Suggested Citation
Barhate Y, Casas-Orozco D, Laky DJ, Reklaitis GV, Nagy ZK. Hybrid Rule-based and Optimization-driven Decision Framework for the Rapid Synthesis of End-to-End Optimal (E2EO) and Sustainable Pharmaceutical Manufacturing Flowsheets. Systems and Control Transactions 3:261-266 (2024) https://doi.org/10.69997/sct.115998
Author Affiliations
Barhate Y: Davidson School of Chemical Engineering, Purdue University, West Lafayette, IN, United States
Casas-Orozco D: Davidson School of Chemical Engineering, Purdue University, West Lafayette, IN, United States
Laky DJ: Davidson School of Chemical Engineering, Purdue University, West Lafayette, IN, United States
Reklaitis GV: Davidson School of Chemical Engineering, Purdue University, West Lafayette, IN, United States
Nagy ZK: Davidson School of Chemical Engineering, Purdue University, West Lafayette, IN, United States
Casas-Orozco D: Davidson School of Chemical Engineering, Purdue University, West Lafayette, IN, United States
Laky DJ: Davidson School of Chemical Engineering, Purdue University, West Lafayette, IN, United States
Reklaitis GV: Davidson School of Chemical Engineering, Purdue University, West Lafayette, IN, United States
Nagy ZK: Davidson School of Chemical Engineering, Purdue University, West Lafayette, IN, United States
Journal Name
Systems and Control Transactions
Volume
3
First Page
261
Last Page
266
Year
2024
Publication Date
2024-07-10
Version Comments
DOI Assigned
Other Meta
PII: 0261-0266-676179-SCT-3-2024, Publication Type: Journal Article
Record Map
Published Article

LAPSE:2024.1536
This Record
External Link

https://doi.org/10.69997/sct.115998
Article DOI
Download
Meta
Links to Related Works
(0.08 seconds)
[0.08 s]


