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Nair A, Loveday KA, Kenyon C, Qu J, Kis Z. Quality by Digital Design for Developing Platform RNA Vaccine and Therapeutic Manufacturing Processes. Methods Mol Biol 2024; 2786:339-364. [PMID: 38814403 DOI: 10.1007/978-1-0716-3770-8_16] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/31/2024]
Abstract
Quality by digital design (QbDD) utilizes data-driven, mechanistic, or hybrid models to define and optimize a manufacturing design space. It improves upon the QbD approach used extensively in the pharmaceutical industry. The computational models developed in this approach identify and quantify the relationship between the product's critical quality attributes (CQAs) and the critical process parameters (CPPs) of unit operations within the manufacturing process. This chapter discusses the QbDD approach in developing and optimizing unit operations such as in vitro transcription, tangential flow filtration, affinity chromatography, and lipid nanoparticle (LNP) formulation in mRNA vaccine manufacturing. QbDD can be an efficient framework for developing a production process for a disease-agnostic product that requires extensive experimental and model-based process-product interaction characterization during the early process development phase.
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Affiliation(s)
- Adithya Nair
- Department of Biological and Chemical Engineering, University of Sheffield, Sheffield, UK
| | - Kate A Loveday
- Department of Biological and Chemical Engineering, University of Sheffield, Sheffield, UK
| | - Charlotte Kenyon
- Department of Biological and Chemical Engineering, University of Sheffield, Sheffield, UK
| | - Jixin Qu
- Department of Biological and Chemical Engineering, University of Sheffield, Sheffield, UK
| | - Zoltán Kis
- Department of Biological and Chemical Engineering, University of Sheffield, Sheffield, UK.
- Department of Chemical Engineering, Imperial College London, London, UK.
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Abstract
The development and adoption of digital twins (DT) for Quality-by-Design (QbD)-based processes with flexible operating points within a proven acceptable range (PAR) and automation through Advanced Process Control (APC) with Process Analytical Technology (PAT) instead of conventional process execution based on offline analytics and inflexible process set points is one of the great challenges in modern biotechnology. Virus-like particles (VLPs) are part of a line of innovative drug substances (DS). VLPs, especially those based on human immunodeficiency virus (HIV), HIV-1 Gag VLPs, have very high potential as a versatile vaccination platform, allowing for pseudotyping with heterologous envelope proteins, e.g., the S protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As enveloped VLPs, optimal process control with minimal hold times is essential. This study demonstrates, for the first time, the use of a digital twin for the overall production process of HIV-1 Gag VLPs from cultivation, clarification, and purification to lyophilization. The accuracy of the digital twins is in the range of 0.8 to 1.4% in depth filtration (DF) and 4.6 to 5.2% in ultrafiltration/diafiltration (UFDF). The uncertainty due to variability in the model parameter determination is less than 4.5% (DF) and less than 3.8% (UFDF). In the DF, a prediction of the final filter capacity was demonstrated from as low as 5.8% (9mbar) of the final transmembrane pressure (TMP). The scale-up based on DT in chromatography shows optimization potential in productivity up to a factor of 2. The schedule based on DT and PAT for APC has been compared to conventional process control, and hold-time and process duration reductions by a factor of 2 have been achieved. This work lays the foundation for the short-term validation of the DT and PAT for APC in an automated S7 process environment and the conversion from batch to continuous production.
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Abstract
Quality-by-Design (QbD) is demanded by regulatory authorities in biopharmaceutical production. Within the QbD frame advanced process control (APC), facilitated through process analytical technology (PAT) and digital twins (DT), plays an increasingly important role as it can help to assure to stay within the predefined proven acceptable range (PAR).This ensures high product quality, minimizes failure and is an important step towards a real-time-release testing (RTRT) that could help to accelerate time-to-market of drug substances, which is becoming even more important in light of dynamical pandemic situations. The approach is exemplified on scFv manufacturing in Escherichia coli. Simulation results from digital twins are compared to experimental data and found to be accurate and precise. Harvest is achieved by tangential flow filtration followed by product release through high pressure homogenization and subsequent clarification by tangential flow filtration. Digital twins of the membrane processes show that shear rate and transmembrane pressure are significant process parameters, which is in line with experimental data. Optimized settings were applied to 0.3 bar and a shear rate of 11,000 s−1. Productivity of chromatography steps were 5.3 g/L/d (Protein L) and 2167 g/L/d (CEX) and the final product concentration was 8 g/L. Based on digital twin results, an optimized process schedule was developed that decreased purification time to one working day, which is a factor-two reduction compared to the conventional process schedule. This work presents the basis for future studies on advanced process control and automation for biologics production in microbials in regulated industries.
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Abstract
The global coronavirus pandemic continues to restrict public life worldwide. An effective means of limiting the pandemic is vaccination. Messenger ribonucleic acid (mRNA) vaccines currently available on the market have proven to be a well-tolerated and effective class of vaccine against coronavirus type 2 (CoV2). Accordingly, demand is presently outstripping mRNA vaccine production. One way to increase productivity is to switch from the currently performed batch to continuous in vitro transcription, which has proven to be a crucial material-consuming step. In this article, a physico-chemical model of in vitro mRNA transcription in a tubular reactor is presented and compared to classical batch and continuous in vitro transcription in a stirred tank. The three models are validated based on a distinct and quantitative validation workflow. Statistically significant parameters are identified as part of the parameter determination concept. Monte Carlo simulations showed that the model is precise, with a deviation of less than 1%. The advantages of continuous production are pointed out compared to batchwise in vitro transcription by optimization of the space–time yield. Improvements of a factor of 56 (0.011 µM/min) in the case of the continuously stirred tank reactor (CSTR) and 68 (0.013 µM/min) in the case of the plug flow reactor (PFR) were found.
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Digital Twin in biomanufacturing: challenges and opportunities towards its implementation. ACTA ACUST UNITED AC 2021. [DOI: 10.1007/s43393-021-00024-0] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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Jankauskas K, Farid SS. Multi-objective biopharma capacity planning under uncertainty using a flexible genetic algorithm approach. Comput Chem Eng 2019. [DOI: 10.1016/j.compchemeng.2019.05.023] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Zhou L, Liao Z, Wang L, Zhang L, Ji X, Jiao H, Wang J, Yang Y, Dang Y. Simulation-Based Multiobjective Optimization of the Product Separation Process within an MTP Plant. Ind Eng Chem Res 2019. [DOI: 10.1021/acs.iecr.9b02033] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Li Zhou
- School of Chemical Engineering, Sichuan University, Chengdu 610065, PR China
| | - Zuwei Liao
- State Key Laboratory of Chemical Engineering, Department of Chemical and Biological Engineering, Zhejiang University, Hangzhou, Zhejiang 310027, PR China
| | - Lin Wang
- Coal to Liquids Chemical R&D Center, Shenhua Ningxia Coal Industry Group, Yinchuan 750001, PR China
| | - Lingling Zhang
- State Key Laboratory of Chemical Engineering, Department of Chemical and Biological Engineering, Zhejiang University, Hangzhou, Zhejiang 310027, PR China
| | - Xu Ji
- School of Chemical Engineering, Sichuan University, Chengdu 610065, PR China
| | - Hongqiao Jiao
- Coal to Liquids Chemical R&D Center, Shenhua Ningxia Coal Industry Group, Yinchuan 750001, PR China
| | - Jingdai Wang
- State Key Laboratory of Chemical Engineering, Department of Chemical and Biological Engineering, Zhejiang University, Hangzhou, Zhejiang 310027, PR China
| | - Yongrong Yang
- State Key Laboratory of Chemical Engineering, Department of Chemical and Biological Engineering, Zhejiang University, Hangzhou, Zhejiang 310027, PR China
| | - Yagu Dang
- School of Chemical Engineering, Sichuan University, Chengdu 610065, PR China
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Lorenzo D, Santos A, Perez-Galvan C, Triana C, Romero A, Bogle IDL. Optimization-Based Design of a Reactive Distillation Column for the Purification Process of Cyclohexanone Using Rigorous Simulation Model and Validated Using an Experimental Packed Column. Ind Eng Chem Res 2018. [DOI: 10.1021/acs.iecr.8b03560] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- David Lorenzo
- Dpto. Ingeniería Química, Facultad CC. Químicas. Universidad Complutense de Madrid. Avda. Complutense s/n 28040 Madrid, Spain
| | - Aurora Santos
- Dpto. Ingeniería Química, Facultad CC. Químicas. Universidad Complutense de Madrid. Avda. Complutense s/n 28040 Madrid, Spain
| | - Carlos Perez-Galvan
- Department of Chemical Engineering. University College London, Torrington Place. London WC1E 7JE, U.K
| | - Cristian Triana
- Department of Chemical Engineering. University College London, Torrington Place. London WC1E 7JE, U.K
| | - Arturo Romero
- Dpto. Ingeniería Química, Facultad CC. Químicas. Universidad Complutense de Madrid. Avda. Complutense s/n 28040 Madrid, Spain
| | - Ian David Lockhart Bogle
- Department of Chemical Engineering. University College London, Torrington Place. London WC1E 7JE, U.K
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Abstract
Abstract
Process intensification (PI) is a rapidly growing field of research and industrial development that has already created many innovations in chemical process industry. PI is directed toward substantially smaller, cleaner, more energy-efficient technology. Furthermore, PI aims at safer and sustainable technological developments. Its tools are reduction of the number of devices (integration of several functionalities in one apparatus), improving heat and mass transfer by advanced mixing technologies and shorter diffusion pathways, miniaturization, novel energy techniques, new separation approaches, integrated optimization and control strategies. This review discusses many of the recent developments in PI. Starting from fundamental definitions, microfluidic technology, mixing, modern distillation techniques, membrane separation, continuous chromatography, and application of gravitational, electric, and magnetic fields will be described.
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Affiliation(s)
- Frerich J. Keil
- Institute of Chemical Reaction Engineering , Hamburg University of Technology , 21073 Hamburg , Germany
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Ibrahim D, Jobson M, Guillén-Gosálbez G. Optimization-Based Design of Crude Oil Distillation Units Using Rigorous Simulation Models. Ind Eng Chem Res 2017. [DOI: 10.1021/acs.iecr.7b01014] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Dauda Ibrahim
- Centre
for Process Integration, School of Chemical Engineering and Analytical
Science, University of Manchester, Manchester M13 9PL, U.K
| | - Megan Jobson
- Centre
for Process Integration, School of Chemical Engineering and Analytical
Science, University of Manchester, Manchester M13 9PL, U.K
| | - Gonzalo Guillén-Gosálbez
- Department
of Chemical Engineering, Centre for Process Systems Engineering, Imperial College, South Kensington Campus, London SW7 2AZ, U.K
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12
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Comprehensive assessment of the l-lysine production process from fermentation of sugarcane molasses. Bioprocess Biosyst Eng 2017; 40:1033-1048. [DOI: 10.1007/s00449-017-1766-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2016] [Accepted: 04/05/2017] [Indexed: 10/19/2022]
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13
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Optimal planning and campaign scheduling of biopharmaceutical processes using a continuous-time formulation. Comput Chem Eng 2016. [DOI: 10.1016/j.compchemeng.2016.04.009] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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Liu S, Farid SS, Papageorgiou LG. Integrated Optimization of Upstream and Downstream Processing in Biopharmaceutical Manufacturing under Uncertainty: A Chance Constrained Programming Approach. Ind Eng Chem Res 2016. [DOI: 10.1021/acs.iecr.5b04403] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Songsong Liu
- Centre
for Process Systems Engineering, Department of Chemical Engineering, UCL (University College London), Torrington Place, London WC1E 7JE, United Kingdom
| | - Suzanne S. Farid
- The
Advanced Centre for Biochemical Engineering, Department of Biochemical
Engineering, UCL (University College London), Torrington Place, London WC1E 7JE, United Kingdom
| | - Lazaros G. Papageorgiou
- Centre
for Process Systems Engineering, Department of Chemical Engineering, UCL (University College London), Torrington Place, London WC1E 7JE, United Kingdom
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15
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A hybrid CPU-Graphics Processing Unit (GPU) approach for computationally efficient simulation-optimization. Comput Chem Eng 2016. [DOI: 10.1016/j.compchemeng.2016.01.001] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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16
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Banimostafa A, Papadokonstantakis S, Hungerbühler K. Retrofit design of a pharmaceutical batch process considering “green chemistry and engineering” principles. AIChE J 2015. [DOI: 10.1002/aic.14966] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Affiliation(s)
- Alireza Banimostafa
- Swiss Federal Institute of Technology (ETH); Vladimir-Prelog-Weg 1 Zurich Switzerland 8093
| | | | - Konrad Hungerbühler
- Swiss Federal Institute of Technology (ETH); Vladimir-Prelog-Weg 1 Zurich Switzerland 8093
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Lorenz HM, Otte D, Staak D, Repke JU. Increasing the efficiency of existing complex downstream processes by plant-wide retrofit. Chem Eng Res Des 2015. [DOI: 10.1016/j.cherd.2015.02.018] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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Shaik MA, Dhakre A, Rathore AS, Patil N. Capacity optimization and scheduling of a multiproduct manufacturing facility for biotech products. Biotechnol Prog 2014; 30:1221-30. [DOI: 10.1002/btpr.1959] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2014] [Revised: 07/09/2014] [Indexed: 11/09/2022]
Affiliation(s)
- Munawar A. Shaik
- Dept. of Chemical Engineering; Indian Institute of Technology (IIT) Delhi; Hauz Khas New Delhi India
| | - Ankita Dhakre
- Dept. of Chemical Engineering; Indian Institute of Technology (IIT) Delhi; Hauz Khas New Delhi India
| | - Anurag S. Rathore
- Dept. of Chemical Engineering; Indian Institute of Technology (IIT) Delhi; Hauz Khas New Delhi India
| | - Nitin Patil
- Research and Development, Biocon Limited; 20th KM Hosur Road, Electronic City Bangalore India
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Ríos SD, Torres CM, Torras C, Salvadó J, Mateo-Sanz JM, Jiménez L. Microalgae-based biodiesel: economic analysis of downstream process realistic scenarios. BIORESOURCE TECHNOLOGY 2013; 136:617-625. [PMID: 23567739 DOI: 10.1016/j.biortech.2013.03.046] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/17/2013] [Revised: 03/07/2013] [Accepted: 03/08/2013] [Indexed: 06/02/2023]
Abstract
Microalgae oil has been identified as a reliable resource for biodiesel production due to its high lipid productivity and potential cultivation in non-fertile locations. However, high scale production of microalgae based biodiesel depends on the optimization of the entire process to be economically feasible. The selected strain, medium, harvesting methods, etc., sorely affects the ash content in the dry biomass which have a direct effect in the lipid content. Moreover, the suitable lipids for biodiesel production, some of the neutral/saponifiable, are only a fraction of the total ones (around 30% dry base biomass in the best case). The present work uses computational tools for the modeling of different scenarios of the harvesting, oil extraction and transesterification. This rigorous modeling approach detects process bottlenecks that could have led to an overestimation of the potentiality of the microalgae lipids as a resource for the biodiesel production.
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Affiliation(s)
- Sergio D Ríos
- Departament d'Enginyeria Química, Universitat Rovira i Virgili, Av. Països Catalans 26, Tarragona 43007, Spain.
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Brunet R, Reyes-Labarta JA, Guillén-Gosálbez G, Jiménez L, Boer D. Combined simulation–optimization methodology for the design of environmental conscious absorption systems. Comput Chem Eng 2012. [DOI: 10.1016/j.compchemeng.2012.06.030] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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Brunet R, Guillén-Gosálbez G, Jiménez L. Cleaner Design of Single-Product Biotechnological Facilities through the Integration of Process Simulation, Multiobjective Optimization, Life Cycle Assessment, and Principal Component Analysis. Ind Eng Chem Res 2011. [DOI: 10.1021/ie2011577] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Robert Brunet
- Departament d’Enginyeria Quimica, Escola Tecnica Superior d’Enginyeria Quimica, Universitat Rovira i Virgili, Campus Sescelades, Avinguda Paisos Catalans 26, 43007, Tarragona, Spain
| | - Gonzalo Guillén-Gosálbez
- Departament d’Enginyeria Quimica, Escola Tecnica Superior d’Enginyeria Quimica, Universitat Rovira i Virgili, Campus Sescelades, Avinguda Paisos Catalans 26, 43007, Tarragona, Spain
| | - Laureano Jiménez
- Departament d’Enginyeria Quimica, Escola Tecnica Superior d’Enginyeria Quimica, Universitat Rovira i Virgili, Campus Sescelades, Avinguda Paisos Catalans 26, 43007, Tarragona, Spain
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