Dynamic plantwide modeling, uncertainty and sensitivity analysis of a pharmaceutical upstream synthesis: Ibuprofen case study

Frederico C. C. Montes, Krist Gernaey, Gürkan Sin*

*Corresponding author for this work

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Abstract

A dynamic plantwide model was developed for the synthesis of the Active pharmaceutical Ingredient (API) ibuprofen, following the Hoescht synthesis process. The kinetic parameters, reagents, products and by-products of the different reactions were adapted from literature, and the different process operations integrated until the end process, crystallization and isolation of the ibuprofen crystals. The dynamic model simulations were validated against available measurements from literature and then used as enabling tool to analyze the robustness of design space. To this end, sensitivity of the design space towards input disturbances and process uncertainties (from physical and model parameters) is studied using Monte Carlo simulations. The results quantify the uncertainty of the quality of product attributes, with particular focus on crystal size distribution and ibuprofen crystalized. The ranking of the most influential parameters on the chosen quality attributes is presented, with crystal growth and water concentration being the most influential ones. The total amount of saturated solvent, which propagates from upstream processes, has been shown to highly influence the total mass of crystal produced, and the target specifications for the API as well. This dynamic plantwide modeling coupled with Monte Carlo simulations is valuable to improve design and optimization of pharmaceutical processes at early stages, especially to bottleneck the design space against a range of uncertainties and disturbances.
Original languageEnglish
JournalIndustrial and Engineering Chemistry Research
Volume57
Issue number30
Pages (from-to)10026-10037
ISSN0888-5885
DOIs
Publication statusPublished - 2018

Cite this

@article{a1ab30eb77fa4e9fae940412192fb3fb,
title = "Dynamic plantwide modeling, uncertainty and sensitivity analysis of a pharmaceutical upstream synthesis: Ibuprofen case study",
abstract = "A dynamic plantwide model was developed for the synthesis of the Active pharmaceutical Ingredient (API) ibuprofen, following the Hoescht synthesis process. The kinetic parameters, reagents, products and by-products of the different reactions were adapted from literature, and the different process operations integrated until the end process, crystallization and isolation of the ibuprofen crystals. The dynamic model simulations were validated against available measurements from literature and then used as enabling tool to analyze the robustness of design space. To this end, sensitivity of the design space towards input disturbances and process uncertainties (from physical and model parameters) is studied using Monte Carlo simulations. The results quantify the uncertainty of the quality of product attributes, with particular focus on crystal size distribution and ibuprofen crystalized. The ranking of the most influential parameters on the chosen quality attributes is presented, with crystal growth and water concentration being the most influential ones. The total amount of saturated solvent, which propagates from upstream processes, has been shown to highly influence the total mass of crystal produced, and the target specifications for the API as well. This dynamic plantwide modeling coupled with Monte Carlo simulations is valuable to improve design and optimization of pharmaceutical processes at early stages, especially to bottleneck the design space against a range of uncertainties and disturbances.",
author = "Montes, {Frederico C. C.} and Krist Gernaey and G{\"u}rkan Sin",
year = "2018",
doi = "10.1021/acs.iecr.8b00465",
language = "English",
volume = "57",
pages = "10026--10037",
journal = "Industrial & Engineering Chemistry Research",
issn = "0888-5885",
publisher = "American Chemical Society",
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TY - JOUR

T1 - Dynamic plantwide modeling, uncertainty and sensitivity analysis of a pharmaceutical upstream synthesis: Ibuprofen case study

AU - Montes, Frederico C. C.

AU - Gernaey, Krist

AU - Sin, Gürkan

PY - 2018

Y1 - 2018

N2 - A dynamic plantwide model was developed for the synthesis of the Active pharmaceutical Ingredient (API) ibuprofen, following the Hoescht synthesis process. The kinetic parameters, reagents, products and by-products of the different reactions were adapted from literature, and the different process operations integrated until the end process, crystallization and isolation of the ibuprofen crystals. The dynamic model simulations were validated against available measurements from literature and then used as enabling tool to analyze the robustness of design space. To this end, sensitivity of the design space towards input disturbances and process uncertainties (from physical and model parameters) is studied using Monte Carlo simulations. The results quantify the uncertainty of the quality of product attributes, with particular focus on crystal size distribution and ibuprofen crystalized. The ranking of the most influential parameters on the chosen quality attributes is presented, with crystal growth and water concentration being the most influential ones. The total amount of saturated solvent, which propagates from upstream processes, has been shown to highly influence the total mass of crystal produced, and the target specifications for the API as well. This dynamic plantwide modeling coupled with Monte Carlo simulations is valuable to improve design and optimization of pharmaceutical processes at early stages, especially to bottleneck the design space against a range of uncertainties and disturbances.

AB - A dynamic plantwide model was developed for the synthesis of the Active pharmaceutical Ingredient (API) ibuprofen, following the Hoescht synthesis process. The kinetic parameters, reagents, products and by-products of the different reactions were adapted from literature, and the different process operations integrated until the end process, crystallization and isolation of the ibuprofen crystals. The dynamic model simulations were validated against available measurements from literature and then used as enabling tool to analyze the robustness of design space. To this end, sensitivity of the design space towards input disturbances and process uncertainties (from physical and model parameters) is studied using Monte Carlo simulations. The results quantify the uncertainty of the quality of product attributes, with particular focus on crystal size distribution and ibuprofen crystalized. The ranking of the most influential parameters on the chosen quality attributes is presented, with crystal growth and water concentration being the most influential ones. The total amount of saturated solvent, which propagates from upstream processes, has been shown to highly influence the total mass of crystal produced, and the target specifications for the API as well. This dynamic plantwide modeling coupled with Monte Carlo simulations is valuable to improve design and optimization of pharmaceutical processes at early stages, especially to bottleneck the design space against a range of uncertainties and disturbances.

U2 - 10.1021/acs.iecr.8b00465

DO - 10.1021/acs.iecr.8b00465

M3 - Journal article

VL - 57

SP - 10026

EP - 10037

JO - Industrial & Engineering Chemistry Research

JF - Industrial & Engineering Chemistry Research

SN - 0888-5885

IS - 30

ER -