A Benchmark Simulator for Quality-by-design and Quality-by-control Studies in Continuous Pharmaceutical Manufacturing - Intensified Filtration-drying of Crystallization Slurries

Overview

Journal Comput Chem Eng

Date 2024 Jan 5

PMID 38178942

Authors

Francesco Destro

Zoltan K Nagy

Massimiliano Barolo

Affiliations

Soon will be listed here.

Abstract

This article introduces ContCarSim, a benchmark simulator for the development and testing of quality-by-design and quality-by-control strategies in the continuous intensified filtration-drying of paracetamol/ethanol slurries on a novel carousel technology, developed by Alconbury Weston Ltd (United Kingdom). The simulator is based on a detailed mechanistic mathematical modeling framework, and has been validated with filtration and drying experiments on a prototype equipment. A set of design- and control-relevant challenges to be addressed through ContCarSim are proposed. A case study is developed, to demonstrate the features of the simulator and its suitability to design, test and optimize the unit operation. ContCarSim is expected to promote the transition to end-to-end continuous pharmaceutical manufacturing and the adoption of closed-loop quality control by the pharmaceutical industry. The simulator can also be employed as a benchmark for data analytics and process monitoring studies.

Citing Articles

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Hur I, Casas-Orozco D, Laky D, Destro F, Nagy Z Chem Eng Sci. 2024; 285.

PMID: 38975615 PMC: 11225065. DOI: 10.1016/j.ces.2023.119534.

Quality-by-control of intensified continuous filtration-drying of active pharmaceutical ingredients.

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PMID: 38633424 PMC: 11022276. DOI: 10.1002/aic.17926.

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References

Bamberger J, Greenwood M . Using ultrasonic attenuation to monitor slurry mixing in real time. Ultrasonics. 2004; 42(1-9):145-8. DOI: 10.1016/j.ultras.2004.02.016. View

Goldrick S, Stefan A, Lovett D, Montague G, Lennox B . The development of an industrial-scale fed-batch fermentation simulation. J Biotechnol. 2014; 193:70-82. DOI: 10.1016/j.jbiotec.2014.10.029. View

Su Q, Ganesh S, Moreno M, Bommireddy Y, Gonzalez M, Reklaitis G . A perspective on Quality-by-Control (QbC) in pharmaceutical continuous manufacturing. Comput Chem Eng. 2023; 125:216-231. PMC: 9948678. DOI: 10.1016/j.compchemeng.2019.03.001. View

Fisher A, Kamga M, Agarabi C, Brorson K, Lee S, Yoon S . The Current Scientific and Regulatory Landscape in Advancing Integrated Continuous Biopharmaceutical Manufacturing. Trends Biotechnol. 2018; 37(3):253-267. DOI: 10.1016/j.tibtech.2018.08.008. View

Ottoboni S, Shahid M, Steven C, Coleman S, Meehan E, Barton A . Developing a Batch Isolation Procedure and Running It in an Automated Semicontinuous Unit: AWL CFD25 Case Study. Org Process Res Dev. 2020; 24(4):520-539. PMC: 7171873. DOI: 10.1021/acs.oprd.9b00512. View

Tomba E, Facco P, Bezzo F, Barolo M . Latent variable modeling to assist the implementation of Quality-by-Design paradigms in pharmaceutical development and manufacturing: a review. Int J Pharm. 2013; 457(1):283-97. DOI: 10.1016/j.ijpharm.2013.08.074. View

Su Q, Bommireddy Y, Shah Y, Ganesh S, Moreno M, Liu J . Data reconciliation in the Quality-by-Design (QbD) implementation of pharmaceutical continuous tablet manufacturing. Int J Pharm. 2019; 563:259-272. PMC: 9976296. DOI: 10.1016/j.ijpharm.2019.04.003. View

Jeppsson U, Pons M, Nopens I, Alex J, Copp J, Gernaey K . Benchmark simulation model no 2: general protocol and exploratory case studies. Water Sci Technol. 2007; 56(8):67-78. DOI: 10.2166/wst.2007.604. View

Fisher A, Lee S, Harris D, Buhse L, Kozlowski S, Yu L . Advancing pharmaceutical quality: An overview of science and research in the U.S. FDA's Office of Pharmaceutical Quality. Int J Pharm. 2016; 515(1-2):390-402. DOI: 10.1016/j.ijpharm.2016.10.038. View

10.

Yu L, Amidon G, Khan M, Hoag S, Polli J, Raju G . Understanding pharmaceutical quality by design. AAPS J. 2014; 16(4):771-83. PMC: 4070262. DOI: 10.1208/s12248-014-9598-3. View

11.

Bana P, Orkenyi R, Lovei K, Lako A, Turos G, Eles J . The route from problem to solution in multistep continuous flow synthesis of pharmaceutical compounds. Bioorg Med Chem. 2017; 25(23):6180-6189. DOI: 10.1016/j.bmc.2016.12.046. View

12.

Bamberger J, Greenwood M . Measuring fluid and slurry density and solids concentration non-invasively. Ultrasonics. 2004; 42(1-9):563-7. DOI: 10.1016/j.ultras.2004.01.032. View

13.

Harada T, Kawakami K, Yoshihashi Y, Yonemochi E, Terada K, Moriyama H . Practical approach for measuring heat capacity of pharmaceutical crystals/glasses by modulated-temperature differential scanning calorimetry. Chem Pharm Bull (Tokyo). 2013; 61(3):315-9. DOI: 10.1248/cpb.c12-00928. View

14.

Yu L, Woodcock J . FDA pharmaceutical quality oversight. Int J Pharm. 2015; 491(1-2):2-7. DOI: 10.1016/j.ijpharm.2015.05.066. View

15.

Destro F, Hur I, Wang V, Abdi M, Feng X, Wood E . Mathematical modeling and digital design of an intensified filtration-washing-drying unit for pharmaceutical continuous manufacturing. Chem Eng Sci. 2024; 244. PMC: 10790184. DOI: 10.1016/j.ces.2021.116803. View

16.

OConnor T, Yu L, Lee S . Emerging technology: A key enabler for modernizing pharmaceutical manufacturing and advancing product quality. Int J Pharm. 2016; 509(1-2):492-498. DOI: 10.1016/j.ijpharm.2016.05.058. View

17.

Yu L, Kopcha M . The future of pharmaceutical quality and the path to get there. Int J Pharm. 2017; 528(1-2):354-359. DOI: 10.1016/j.ijpharm.2017.06.039. View