1
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Destro F, Wu W, Srinivasan P, Joseph J, Bal V, Neufeld C, Wolfrum JM, Manalis SR, Sinskey AJ, Springs SL, Barone PW, Braatz RD. The state of technological advancement to address challenges in the manufacture of rAAV gene therapies. Biotechnol Adv 2024; 76:108433. [PMID: 39168354 DOI: 10.1016/j.biotechadv.2024.108433] [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] [Received: 03/13/2024] [Revised: 07/04/2024] [Accepted: 08/17/2024] [Indexed: 08/23/2024]
Abstract
Current processes for the production of recombinant adeno-associated virus (rAAV) are inadequate to meet the surging demand for rAAV-based gene therapies. This article reviews recent advances that hold the potential to address current limitations in rAAV manufacturing. A multidisciplinary perspective on technological progress in rAAV production is presented, underscoring the necessity to move beyond incremental refinements and adopt a holistic strategy to address existing challenges. Since several recent reviews have thoroughly covered advancements in upstream technology, this article provides only a concise overview of these developments before moving to pivotal areas of rAAV manufacturing not well covered in other reviews, including analytical technologies for rapid and high-throughput measurement of rAAV quality attributes, mathematical modeling for platform and process optimization, and downstream approaches to maximize efficiency and rAAV yield. Novel technologies that have the potential to address the current gaps in rAAV manufacturing are highlighted. Implementation challenges and future research directions are critically discussed.
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Affiliation(s)
- Francesco Destro
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Weida Wu
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Prasanna Srinivasan
- Center for Biomedical Innovation, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - John Joseph
- Center for Biomedical Innovation, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Vivekananda Bal
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Caleb Neufeld
- Center for Biomedical Innovation, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jacqueline M Wolfrum
- Center for Biomedical Innovation, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Scott R Manalis
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Anthony J Sinskey
- Center for Biomedical Innovation, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Stacy L Springs
- Center for Biomedical Innovation, Massachusetts Institute of Technology, Cambridge, MA, USA.
| | - Paul W Barone
- Center for Biomedical Innovation, Massachusetts Institute of Technology, Cambridge, MA, USA.
| | - Richard D Braatz
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA; Center for Biomedical Innovation, Massachusetts Institute of Technology, Cambridge, MA, USA.
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2
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Tanabe S, Muraki T, Yaginuma K, Kim S, Kano M. Greedy design space construction based on regression and latent space extraction for pharmaceutical development. Int J Pharm 2023; 642:123178. [PMID: 37364782 DOI: 10.1016/j.ijpharm.2023.123178] [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] [Received: 01/15/2023] [Revised: 05/23/2023] [Accepted: 06/22/2023] [Indexed: 06/28/2023]
Abstract
Implementation of the design space (DS) is a scientific concept for ensuring quality to be submitted as a part of the regulatory filing of a drug product for approval to market. An empirical approach is constructing the DS based on the regression model whose inputs are process parameters and material attributes over the different unit operations, i.e., a high-dimensional statistical model. While the high-dimensional model assures quality and process flexibility through a comprehensive process understanding, it has difficulty visualizing the feasible range of input parameters, i.e., DS. Therefore, this study proposes a greedy approach to constructing the extensive and flexible low-dimensional DS based on the high-dimensional statistical model and the observed internal representations that satisfies both comprehensive process understanding and the DS visualization capability. Introducing the observed correlation structure enabled the dimensionality reduction of the DS. The non-critical controllable parameters were fixed to the target values in visualizing the low-dimensional DS as a function of critical parameters. The expected variation of non-critical non-controllable parameters was considered the source of variation in prediction. The case study demonstrated the proposed approach's usefulness for developing the pharmaceutical manufacturing process.
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Affiliation(s)
- Shuichi Tanabe
- Formulation Technology Research Laboratories, Daiichi Sankyo Co., Ltd., 1-12-1 Shinomiya, 2540014 Hiratsuka, Japan.
| | - Tatsuya Muraki
- Department of Systems Science, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 6068501, Japan
| | - Keita Yaginuma
- Formulation Technology Research Laboratories, Daiichi Sankyo Co., Ltd., 1-12-1 Shinomiya, 2540014 Hiratsuka, Japan
| | - Sanghong Kim
- Department of Applied Physics and Chemical Engineering, Tokyo University of Agriculture and Technology, 2-24-16 Naka-cho, Koganei 1840012, Japan
| | - Manabu Kano
- Department of Systems Science, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 6068501, Japan
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3
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Casas-Orozco D, Laky D, Mackey J, Reklaitis G, Nagy Z. Reaction kinetics determination and uncertainty analysis for the synthesis of the cancer drug lomustine. Chem Eng Sci 2023; 275:118591. [PMID: 38179266 PMCID: PMC10765472 DOI: 10.1016/j.ces.2023.118591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/29/2023]
Abstract
Fast and reliable model development frameworks are required to support current trends in modernization of pharmaceutical processing, promoting the use of digital platforms to assist process design and operation. In this work, we use a parameter estimation framework built into the PharmaPy library to determine rate parameters and uncertainty regions of different mechanistic and semi-empirical kinetic expressions for the synthesis of the drug lomustine. The parameter estimation procedure was complemented by identifiability analysis, resulting in simplified reaction mechanisms. Comparison of parameters and their uncertainty in process design was demonstrated through design space analysis, showing important differences in model prediction and the extent of their corresponding design spaces. The results of this work can serve to analyze lomustine manufacturing processes that include separation and isolation steps, where parametric sensitivity is expected to propagate along the manufacturing line and impact process feasible operation, and attainment of critical quality attributes of the product.
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4
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The Role of Process Systems Engineering in Applying Quality by Design (QbD) in Mesenchymal Stem Cell Production. Comput Chem Eng 2023. [DOI: 10.1016/j.compchemeng.2023.108144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
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5
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Kaiya Y, Tamura R, Tsuda K. Understanding Chemical Processes with Entropic Sampling. Org Process Res Dev 2022. [DOI: 10.1021/acs.oprd.2c00254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/05/2022]
Affiliation(s)
- Yuji Kaiya
- Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Chiba277-8561, Japan
| | - Ryo Tamura
- Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Chiba277-8561, Japan
- Research and Services Division of Materials Data and Integrated System, National Institute for Materials Science, Tsukuba, Ibaraki305-0044, Japan
- International Center for Materials Nanoarchitectonics (WPI-MANA), National Institute for Materials Science, Tsukuba, Ibaraki305-0044, Japan
- RIKEN Center for Advanced Intelligence Project, Tokyo103-0027, Japan
| | - Koji Tsuda
- Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Chiba277-8561, Japan
- Research and Services Division of Materials Data and Integrated System, National Institute for Materials Science, Tsukuba, Ibaraki305-0044, Japan
- RIKEN Center for Advanced Intelligence Project, Tokyo103-0027, Japan
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6
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Zhao F, Paz Ochoa M, Grossmann IE, García-Muñoz S, Stamatis SD. Novel formulations of flexibility index and design centering for design space definition. Comput Chem Eng 2022. [DOI: 10.1016/j.compchemeng.2022.107969] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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7
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Hirono K, A. Udugama I, Hayashi Y, Kino-oka M, Sugiyama H. A Dynamic and Probabilistic Design Space Determination Method for Mesenchymal Stem Cell Cultivation Processes. Ind Eng Chem Res 2022. [DOI: 10.1021/acs.iecr.2c00374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Keita Hirono
- Department of Chemical System Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan
| | - Isuru A. Udugama
- Department of Chemical System Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan
| | - Yusuke Hayashi
- Department of Chemical System Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan
| | - Masahiro Kino-oka
- Department of Biotechnology, Osaka University, 2-1 Yamadaoka, Suita, Osaka 565-0871, Japan
| | - Hirokazu Sugiyama
- Department of Chemical System Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan
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8
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Destro F, Barolo M. A review on the modernization of pharmaceutical development and manufacturing - Trends, perspectives, and the role of mathematical modeling. Int J Pharm 2022; 620:121715. [PMID: 35367580 DOI: 10.1016/j.ijpharm.2022.121715] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2022] [Revised: 03/23/2022] [Accepted: 03/29/2022] [Indexed: 01/20/2023]
Abstract
Recently, the pharmaceutical industry has been facing several challenges associated to the use of outdated development and manufacturing technologies. The return on investment on research and development has been shrinking, and, at the same time, an alarming number of shortages and recalls for quality concerns has been registered. The pharmaceutical industry has been responding to these issues through a technological modernization of development and manufacturing, under the support of initiatives and activities such as quality-by-design (QbD), process analytical technology, and pharmaceutical emerging technology. In this review, we analyze this modernization trend, with emphasis on the role that mathematical modeling plays within it. We begin by outlining the main socio-economic trends of the pharmaceutical industry, and by highlighting the life-cycle stages of a pharmaceutical product in which technological modernization can help both achieve consistently high product quality and increase return on investment. Then, we review the historical evolution of the pharmaceutical regulatory framework, and we discuss the current state of implementation and future trends of QbD. The pharmaceutical emerging technology is reviewed afterwards, and a discussion on the evolution of QbD into the more effective quality-by-control (QbC) paradigm is presented. Further, we illustrate how mathematical modeling can support the implementation of QbD and QbC across all stages of the pharmaceutical life-cycle. In this respect, we review academic and industrial applications demonstrating the impact of mathematical modeling on three key activities within pharmaceutical development and manufacturing, namely design space description, process monitoring, and active process control. Finally, we discuss some future research opportunities on the use of mathematical modeling in industrial pharmaceutical environments.
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Affiliation(s)
- Francesco Destro
- CAPE-Lab - Computer-Aided Process Engineering Laboratory, Department of Industrial Engineering, University of Padova, via Marzolo 9, 35131 Padova PD, Italy
| | - Massimiliano Barolo
- CAPE-Lab - Computer-Aided Process Engineering Laboratory, Department of Industrial Engineering, University of Padova, via Marzolo 9, 35131 Padova PD, Italy.
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9
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Investigating the Trade-Off between Design and Operational Flexibility in Continuous Manufacturing of Pharmaceutical Tablets: A Case Study of the Fluid Bed Dryer. Processes (Basel) 2022. [DOI: 10.3390/pr10030454] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Market globalisation, shortened patent lifetimes and the ongoing shift towards personalised medicines exert unprecedented pressure on the pharmaceutical industry. In the push for continuous pharmaceutical manufacturing, processes need to be shown to be agile and robust enough to handle variations with respect to product demands and operating conditions. In this paper we examine the use of operational envelopes to study the trade-off between the design and operational flexibility of the fluid bed dryer at the heart of a tablet manufacturing process. The operating flexibility of this unit is key to the flexibility of the full process and its supply chain. The methodology shows that for the fluid bed dryer case study there is significant effect on flexibility of the process at different drying times with the optimal obtained at 700s. The flexibility is not affected by the change in volumetric flowrate, but only by the change in temperature. Here the method used a black box model to show how it could be done without access to the full model equation set, as this often needs to be the case in commercial settings.
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10
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Zhao F, Grossmann IE, García‐Muñoz S, Stamatis SD. Design Space Description through Adaptive Sampling and Symbolic Computation. AIChE J 2022. [DOI: 10.1002/aic.17604] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Affiliation(s)
- Fei Zhao
- Center for Advanced Process Decision‐Making, Department of Chemical Engineering Carnegie Mellon University Pittsburgh Pennsylvania USA
| | - Ignacio E. Grossmann
- Center for Advanced Process Decision‐Making, Department of Chemical Engineering Carnegie Mellon University Pittsburgh Pennsylvania USA
| | - Salvador García‐Muñoz
- Synthetic Molecule Design and Development Lilly Research Laboratories Indianapolis Indiana USA
| | - Stephen D. Stamatis
- Synthetic Molecule Design and Development Lilly Research Laboratories Indianapolis Indiana USA
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11
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Zalai D, Kopp J, Kozma B, Küchler M, Herwig C, Kager J. Microbial technologies for biotherapeutics production: Key tools for advanced biopharmaceutical process development and control. DRUG DISCOVERY TODAY. TECHNOLOGIES 2021; 38:9-24. [PMID: 34895644 DOI: 10.1016/j.ddtec.2021.04.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Revised: 03/14/2021] [Accepted: 04/06/2021] [Indexed: 12/26/2022]
Abstract
Current trends in the biopharmaceutical market such as the diversification of therapies as well as the increasing time-to-market pressure will trigger the rethinking of bioprocess development and production approaches. Thereby, the importance of development time and manufacturing costs will increase, especially for microbial production. In the present review, we investigate three technological approaches which, to our opinion, will play a key role in the future of biopharmaceutical production. The first cornerstone of process development is the generation and effective utilization of platform knowledge. Building processes on well understood microbial and technological platforms allows to accelerate early-stage bioprocess development and to better condense this knowledge into multi-purpose technologies and applicable mathematical models. Second, the application of verified scale down systems and in silico models for process design and characterization will reduce the required number of large scale batches before dossier submission. Third, the broader availability of mathematical process models and the improvement of process analytical technologies will increase the applicability and acceptance of advanced control and process automation in the manufacturing scale. This will reduce process failure rates and subsequently cost of goods. Along these three aspects we give an overview of recently developed key tools and their potential integration into bioprocess development strategies.
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Affiliation(s)
- Denes Zalai
- Richter-Helm BioLogics GmbH & Co. KG, Suhrenkamp 59, 22335 Hamburg, Germany.
| | - Julian Kopp
- Research Division Biochemical Engineering, Institute of Chemical Environmental and Bioscience Engineering, Vienna University of Technology, Vienna, Austria
| | - Bence Kozma
- Research Division Biochemical Engineering, Institute of Chemical Environmental and Bioscience Engineering, Vienna University of Technology, Vienna, Austria
| | - Michael Küchler
- Richter-Helm BioLogics GmbH & Co. KG, Suhrenkamp 59, 22335 Hamburg, Germany
| | - Christoph Herwig
- Research Division Biochemical Engineering, Institute of Chemical Environmental and Bioscience Engineering, Vienna University of Technology, Vienna, Austria; Competence Center CHASE GmbH, Altenbergerstraße 69, 4040 Linz, Austria
| | - Julian Kager
- Research Division Biochemical Engineering, Institute of Chemical Environmental and Bioscience Engineering, Vienna University of Technology, Vienna, Austria
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12
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Zhu Q, Zhao Z, Liu F. Developing new products with kernel partial least squares model inversion. Comput Chem Eng 2021. [DOI: 10.1016/j.compchemeng.2021.107537] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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13
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Destro F, Hur I, Wang V, Abdi M, Feng X, Wood E, Coleman S, Firth P, Barton A, Barolo M, Nagy ZK. Mathematical modeling and digital design of an intensified filtration-washing-drying unit for pharmaceutical continuous manufacturing. Chem Eng Sci 2021; 244:116803. [PMID: 38229929 PMCID: PMC10790184 DOI: 10.1016/j.ces.2021.116803] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
This paper introduces a comprehensive mathematical model of a novel integrated filter-dryer carousel system, designed for continuously filtering, washing and drying a slurry stream into a crystals cake. The digital twin includes models for dead-end filtration, cake washing and convective cake drying, based on dynamic multi-component mass, energy and momentum balances. For set of feed conditions and control inputs, the model allows tracking the solvents and impurities content in the cake (critical quality attributes, CQAs) throughout the whole process. The model parameters were identified for the isolation of paracetamol from a multi-component slurry, containing a non-volatile impurity. The calibrated model was used for identifying the probabilistic design space and maximum throughput for the process, expressing the combinations of the carousel feed conditions and control inputs for which the probability of meeting the target CQAs is acceptable.
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Affiliation(s)
- Francesco Destro
- CAPE-Lab – Computer-Aided Process Engineering Laboratory, Department of Industrial Engineering, University of Padova, 35131 Padova PD, Italy
| | - Inyoung Hur
- Davidson School of Chemical Engineering, Purdue University, West Lafayette, IN 47906, USA
| | - Vivian Wang
- Office of Pharmaceutical Quality, Center for Drug Evaluation and Research, Food & Drug Administration, Silver Spring, MD, USA
| | - Mesfin Abdi
- Office of Pharmaceutical Quality, Center for Drug Evaluation and Research, Food & Drug Administration, Silver Spring, MD, USA
| | - Xin Feng
- Office of Pharmaceutical Quality, Center for Drug Evaluation and Research, Food & Drug Administration, Silver Spring, MD, USA
| | - Erin Wood
- Office of Pharmaceutical Quality, Center for Drug Evaluation and Research, Food & Drug Administration, Silver Spring, MD, USA
| | | | - Paul Firth
- Alconbury Weston Ltd, Stoke-on-Trent, UK
| | | | - Massimiliano Barolo
- CAPE-Lab – Computer-Aided Process Engineering Laboratory, Department of Industrial Engineering, University of Padova, 35131 Padova PD, Italy
| | - Zoltan K. Nagy
- Davidson School of Chemical Engineering, Purdue University, West Lafayette, IN 47906, USA
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14
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Gargalo CL, de Las Heras SC, Jones MN, Udugama I, Mansouri SS, Krühne U, Gernaey KV. Towards the Development of Digital Twins for the Bio-manufacturing Industry. ADVANCES IN BIOCHEMICAL ENGINEERING/BIOTECHNOLOGY 2020; 176:1-34. [PMID: 33349908 DOI: 10.1007/10_2020_142] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
The bio-manufacturing industry, along with other process industries, now has the opportunity to be engaged in the latest industrial revolution, also known as Industry 4.0. To successfully accomplish this, a physical-to-digital-to-physical information loop should be carefully developed. One way to achieve this is, for example, through the implementation of digital twins (DTs), which are virtual copies of the processes. Therefore, in this paper, the focus is on understanding the needs and challenges faced by the bio-manufacturing industry when dealing with this digitalized paradigm. To do so, two major building blocks of a DT, data and models, are highlighted and discussed. Hence, firstly, data and their characteristics and collection strategies are examined as well as new methods and tools for data processing. Secondly, modelling approaches and their potential of being used in DTs are reviewed. Finally, we share our vision with regard to the use of DTs in the bio-manufacturing industry aiming at bringing the DT a step closer to its full potential and realization.
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Affiliation(s)
- Carina L Gargalo
- Department of Chemical and Biochemical Engineering, Technical University of Denmark, Lyngby, Denmark
| | | | - Mark Nicholas Jones
- Department of Chemical and Biochemical Engineering, Technical University of Denmark, Lyngby, Denmark.,Molecular Quantum Solutions ApS, Copenhagen, Denmark
| | - Isuru Udugama
- Department of Chemical and Biochemical Engineering, Technical University of Denmark, Lyngby, Denmark
| | - Seyed Soheil Mansouri
- Department of Chemical and Biochemical Engineering, Technical University of Denmark, Lyngby, Denmark
| | - Ulrich Krühne
- Department of Chemical and Biochemical Engineering, Technical University of Denmark, Lyngby, Denmark
| | - Krist V Gernaey
- Department of Chemical and Biochemical Engineering, Technical University of Denmark, Lyngby, Denmark.
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15
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Usage of Digital Twins Along a Typical Process Development Cycle. ADVANCES IN BIOCHEMICAL ENGINEERING/BIOTECHNOLOGY 2020. [PMID: 33346864 DOI: 10.1007/10_2020_149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register]
Abstract
Digital methods for process design, monitoring, and control can convert classical trial-and-error bioprocess development to a quantitative engineering approach. By interconnecting hardware, software, data, and humans currently untapped process optimization potential can be accessed. The key component within such a framework is a digital twin interacting with its physical process counterpart. In this chapter, we show how digital twin guided process development can be applied on an exemplary microbial cultivation process. The usage of digital twins is described along a typical process development cycle, ranging from early strain characterization to real-time control applications. Along an illustrative case study on microbial upstream bioprocessing, we emphasize that digital twins can integrate entire process development cycles if the digital twin itself and the underlying models are continuously adapted to newly available data. Therefore, the digital twin can be regarded as a powerful knowledge management tool and a decision support system for efficient process development. Its full potential can be deployed in a real-time environment where targeted control actions can further improve process performance.
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16
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NMPC-Based Workflow for Simultaneous Process and Model Development Applied to a Fed-Batch Process for Recombinant C. glutamicum. Processes (Basel) 2020. [DOI: 10.3390/pr8101313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
For the fast and improved development of bioprocesses, new strategies are required where both strain and process development are performed in parallel. Here, a workflow based on a Nonlinear Model Predictive Control (NMPC) algorithm is described for the model-assisted development of biotechnological processes. By using the NMPC algorithm, the process is designed with respect to a target function (product yield, biomass concentration) with a drastically decreased number of experiments. A workflow for the usage of the NMPC algorithm as a process development tool is outlined. The NMPC algorithm is capable of improving various process states, such as product yield and biomass concentration. It uses on-line and at-line data and controls and optimizes the process by model-based process extrapolation. In this study, the algorithm is applied to a Corynebacterium glutamicum process. In conclusion, the potency of the NMPC algorithm as a powerful tool for process development is demonstrated. In particular, the benefits of the system regarding the characterization and optimization of a fed-batch process are outlined. With the NMPC algorithm, process development can be run simultaneously to strain development, resulting in a shortened time to market for novel products.
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von Stosch M, Schenkendorf R, Geldhof G, Varsakelis C, Mariti M, Dessoy S, Vandercammen A, Pysik A, Sanders M. Working within the Design Space: Do Our Static Process Characterization Methods Suffice? Pharmaceutics 2020; 12:E562. [PMID: 32560435 PMCID: PMC7356980 DOI: 10.3390/pharmaceutics12060562] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Revised: 06/10/2020] [Accepted: 06/11/2020] [Indexed: 11/29/2022] Open
Abstract
The Process Analytical Technology initiative and Quality by Design paradigm have led to changes in the guidelines and views of how to develop drug manufacturing processes. On this occasion the concept of the design space, which describes the impact of process parameters and material attributes on the attributes of the product, was introduced in the ICH Q8 guideline. The way the design space is defined and can be presented for regulatory approval seems to be left to the applicants, among who at least a consensus on how to characterize the design space seems to have evolved. The large majority of design spaces described in publications seem to follow a "static" statistical experimentation and modeling approach. Given that temporal deviations in the process parameters (i.e., moving within the design space) are of a dynamic nature, static approaches might not suffice for the consideration of the implications of variations in the values of the process parameters. In this paper, different forms of design space representations are discussed and the current consensus is challenged, which in turn, establishes the need for a dynamic representation and characterization of the design space. Subsequently, selected approaches for a dynamic representation, characterization and validation which are proposed in the literature are discussed, also showcasing the opportunity to integrate the activities of process characterization, process monitoring and process control strategy development.
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Affiliation(s)
- Moritz von Stosch
- GSK, B-1330 Rixensart, Belgium; (M.v.S.); (G.G.); (C.V.); (M.M.); (S.D.); (A.V.); (A.P.); (M.S.)
| | - René Schenkendorf
- Institute of Energy and Process Systems Engineering, TU Braunschweig, 38106 Braunschweig, Germany
- Center of Pharmaceutical Engineering, TU Braunschweig, 38106 Braunschweig, Germany
| | - Geoffroy Geldhof
- GSK, B-1330 Rixensart, Belgium; (M.v.S.); (G.G.); (C.V.); (M.M.); (S.D.); (A.V.); (A.P.); (M.S.)
| | - Christos Varsakelis
- GSK, B-1330 Rixensart, Belgium; (M.v.S.); (G.G.); (C.V.); (M.M.); (S.D.); (A.V.); (A.P.); (M.S.)
| | - Marco Mariti
- GSK, B-1330 Rixensart, Belgium; (M.v.S.); (G.G.); (C.V.); (M.M.); (S.D.); (A.V.); (A.P.); (M.S.)
| | - Sandrine Dessoy
- GSK, B-1330 Rixensart, Belgium; (M.v.S.); (G.G.); (C.V.); (M.M.); (S.D.); (A.V.); (A.P.); (M.S.)
| | - Annick Vandercammen
- GSK, B-1330 Rixensart, Belgium; (M.v.S.); (G.G.); (C.V.); (M.M.); (S.D.); (A.V.); (A.P.); (M.S.)
| | - Alexander Pysik
- GSK, B-1330 Rixensart, Belgium; (M.v.S.); (G.G.); (C.V.); (M.M.); (S.D.); (A.V.); (A.P.); (M.S.)
| | - Matthew Sanders
- GSK, B-1330 Rixensart, Belgium; (M.v.S.); (G.G.); (C.V.); (M.M.); (S.D.); (A.V.); (A.P.); (M.S.)
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18
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Kucherenko S, Giamalakis D, Shah N, García-Muñoz S. Computationally efficient identification of probabilistic design spaces through application of metamodeling and adaptive sampling. Comput Chem Eng 2020. [DOI: 10.1016/j.compchemeng.2019.106608] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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19
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Kusumo KP, Gomoescu L, Paulen R, García Muñoz S, Pantelides CC, Shah N, Chachuat B. Bayesian Approach to Probabilistic Design Space Characterization: A Nested Sampling Strategy. Ind Eng Chem Res 2019. [DOI: 10.1021/acs.iecr.9b05006] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Kennedy P. Kusumo
- Centre for Process Systems Engineering, Department of Chemical Engineering, Imperial College London, London SW7 2AZ, U.K
| | - Lucian Gomoescu
- Centre for Process Systems Engineering, Department of Chemical Engineering, Imperial College London, London SW7 2AZ, U.K
- Process Systems Enterprise, Ltd., London W6 7HA, U.K
| | - Radoslav Paulen
- Faculty of Chemical and Food Technology, Slovak University of Technology in Bratislava, 812 43 Bratislava, Slovakia
| | - Salvador García Muñoz
- Small Molecule Design and Development, Lilly Research Laboratories, Eli Lilly & Company, Indianapolis, Indiana 46285, United States
| | - Constantinos C. Pantelides
- Centre for Process Systems Engineering, Department of Chemical Engineering, Imperial College London, London SW7 2AZ, U.K
- Process Systems Enterprise, Ltd., London W6 7HA, U.K
| | - Nilay Shah
- Centre for Process Systems Engineering, Department of Chemical Engineering, Imperial College London, London SW7 2AZ, U.K
| | - Benoît Chachuat
- Centre for Process Systems Engineering, Department of Chemical Engineering, Imperial College London, London SW7 2AZ, U.K
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20
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Show Me the Money! Process Modeling in Pharma from the Investor’s Point of View. Processes (Basel) 2019. [DOI: 10.3390/pr7090596] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Process modeling in pharma is gradually gaining momentum in process development but budget restrictions are growing. We first examine whether and how current practices rationalize within a decision process framework with a fictitious investor facing a decision problem subject to incomplete information. We then develop an algorithmic procedure for investment evaluation on both monetary and diffusion-of-innovation fronts. Our methodology builds upon discounted cash flow analysis and Bayesian inference and utilizes the Rogers diffusion of innovation paradigm for computing lower expected returns. We also introduce a set of intangible metrics for quantifying the level of diffusion of process modeling within an organization.
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21
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Tabora JE, Lora Gonzalez F, Tom JW. Bayesian probabilistic modeling in pharmaceutical process development. AIChE J 2019. [DOI: 10.1002/aic.16744] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Affiliation(s)
- Jose E. Tabora
- Chemical & Synthetic Development, Product Development Bristol‐Myers Squibb Company New Brunswick NJ USA
| | - Federico Lora Gonzalez
- Chemical & Synthetic Development, Product Development Bristol‐Myers Squibb Company New Brunswick NJ USA
| | - Jean W. Tom
- Chemical & Synthetic Development, Product Development Bristol‐Myers Squibb Company New Brunswick NJ USA
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22
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Caspi DD, Diwan M, Califano JCC, Mack DJ, Shekhar S. Development of an Operational Space Using Mechanistic Models for a Pd-Catalyzed Amidation Reaction Used in the Synthesis of ABT-530. Org Process Res Dev 2019. [DOI: 10.1021/acs.oprd.9b00170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Daniel D. Caspi
- Process Research and Development, AbbVie Inc., 1 North Waukegan Road, North Chicago, Illinois 60064, United States
| | - Moiz Diwan
- Process Research and Development, AbbVie Inc., 1 North Waukegan Road, North Chicago, Illinois 60064, United States
| | - Jean-Christophe C. Califano
- Process Research and Development, AbbVie Inc., 1 North Waukegan Road, North Chicago, Illinois 60064, United States
| | - Daniel J. Mack
- Process Research and Development, AbbVie Inc., 1 North Waukegan Road, North Chicago, Illinois 60064, United States
| | - Shashank Shekhar
- Process Research and Development, AbbVie Inc., 1 North Waukegan Road, North Chicago, Illinois 60064, United States
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23
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Bano G, Facco P, Ierapetritou M, Bezzo F, Barolo M. Design space maintenance by online model adaptation in pharmaceutical manufacturing. Comput Chem Eng 2019. [DOI: 10.1016/j.compchemeng.2019.05.019] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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24
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Kotidis P, Demis P, Goey CH, Correa E, McIntosh C, Trepekli S, Shah N, Klymenko OV, Kontoravdi C. Constrained global sensitivity analysis for bioprocess design space identification. Comput Chem Eng 2019. [DOI: 10.1016/j.compchemeng.2019.01.022] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
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25
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O'Brien AG, Liu YC, Hughes MJ, Lim JJ, Hodnett NS, Falco N. Investigation of a Weak Temperature-Rate Relationship in the Carbamoylation of a Barbituric Acid Pharmaceutical Intermediate. J Org Chem 2019; 84:4948-4952. [PMID: 30840462 DOI: 10.1021/acs.joc.9b00411] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
The rate of reaction between N, N'-dicyclohexylbarbituric acid 1 and ethyl 2-isocyanatoacetate 2 is invariant with temperature. Positive orders in each reactant and dissociation of triethylammonium salts of 1 and product 3 at elevated temperature indicate that reaction occurs via a catalytic mechanism where changes to the positions of equilibria negate changes in the rate of the turnover-limiting step. A model for the consumption of 1 in a flow reactor accurately predicted the outcome of a laboratory-scale multivariate study.
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Affiliation(s)
- Alexander G O'Brien
- GlaxoSmithKline , 1250 South Collegeville Road , Collegeville , Pennsylvania 19426 , United States
| | - Yangmu Chloe Liu
- GlaxoSmithKline , 1250 South Collegeville Road , Collegeville , Pennsylvania 19426 , United States
| | - Mark J Hughes
- GlaxoSmithKline , Medicines Research Centre , Gunnels Wood Road , Stevenage , Hertfordshire SG1 2NY , United Kingdom
| | - John Jin Lim
- GlaxoSmithKline , 1250 South Collegeville Road , Collegeville , Pennsylvania 19426 , United States
| | - Neil S Hodnett
- GlaxoSmithKline , Medicines Research Centre , Gunnels Wood Road , Stevenage , Hertfordshire SG1 2NY , United Kingdom
| | - Nicholas Falco
- GlaxoSmithKline , 1250 South Collegeville Road , Collegeville , Pennsylvania 19426 , United States
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26
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Gonzalez FL, Tabora JE, Huang EC, Wisniewski SR, Carrasquillo-Flores R, Razler T, Mack B. Development and Implementation of a Quality Control Strategy for an Atropisomer Impurity Grounded in a Risk-Based Probabilistic Design Space. Org Process Res Dev 2019. [DOI: 10.1021/acs.oprd.8b00293] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Federico Lora Gonzalez
- Chemical and Synthetic Development, Bristol-Myers Squibb Company, One Squibb Drive, New Brunswick, New Jersey 08903, United States
| | - Jose E. Tabora
- Chemical and Synthetic Development, Bristol-Myers Squibb Company, One Squibb Drive, New Brunswick, New Jersey 08903, United States
| | - Eric C. Huang
- Chemical and Synthetic Development, Bristol-Myers Squibb Company, One Squibb Drive, New Brunswick, New Jersey 08903, United States
| | - Steven R. Wisniewski
- Chemical and Synthetic Development, Bristol-Myers Squibb Company, One Squibb Drive, New Brunswick, New Jersey 08903, United States
| | - Ronald Carrasquillo-Flores
- Chemical and Synthetic Development, Bristol-Myers Squibb Company, One Squibb Drive, New Brunswick, New Jersey 08903, United States
| | - Thomas Razler
- Chemical and Synthetic Development, Bristol-Myers Squibb Company, One Squibb Drive, New Brunswick, New Jersey 08903, United States
| | - Brendan Mack
- Chemical and Synthetic Development, Bristol-Myers Squibb Company, One Squibb Drive, New Brunswick, New Jersey 08903, United States
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27
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An Optimization-Based Framework to Define the Probabilistic Design Space of Pharmaceutical Processes with Model Uncertainty. Processes (Basel) 2019. [DOI: 10.3390/pr7020096] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
To increase manufacturing flexibility and system understanding in pharmaceutical development, the FDA launched the quality by design (QbD) initiative. Within QbD, the design space is the multidimensional region (of the input variables and process parameters) where product quality is assured. Given the high cost of extensive experimentation, there is a need for computational methods to estimate the probabilistic design space that considers interactions between critical process parameters and critical quality attributes, as well as model uncertainty. In this paper we propose two algorithms that extend the flexibility test and flexibility index formulations to replace simulation-based analysis and identify the probabilistic design space more efficiently. The effectiveness and computational efficiency of these approaches is shown on a small example and an industrial case study.
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28
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The Unreasonable Effectiveness of Equations: Advanced Modeling For Biopharmaceutical Process Development. COMPUTER AIDED CHEMICAL ENGINEERING 2019. [DOI: 10.1016/b978-0-12-818597-1.50023-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
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29
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Popkin ME, Omer BA, Seibert KD, Luciani CV, Srivastava S, Hobson L, Lepore JV. Part 3: Enhanced Approaches to the Development of the Control Strategy and its Implementation in the Manufacturing Process Description. J Pharm Innov 2018. [DOI: 10.1007/s12247-018-9340-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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30
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Cole KP, Johnson MD. Continuous flow technology vs. the batch-by-batch approach to produce pharmaceutical compounds. Expert Rev Clin Pharmacol 2017; 11:5-13. [DOI: 10.1080/17512433.2018.1413936] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
- Kevin P. Cole
- Small Molecule Design and Development, Eli Lilly and Company, Indianapolis, IN, USA
| | - Martin D. Johnson
- Small Molecule Design and Development, Eli Lilly and Company, Indianapolis, IN, USA
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31
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Tabora JE, Domagalski N. Multivariate Analysis and Statistics in Pharmaceutical Process Research and Development. Annu Rev Chem Biomol Eng 2017; 8:403-426. [DOI: 10.1146/annurev-chembioeng-060816-101418] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The application of statistics in pharmaceutical process research and development has evolved significantly over the past decades, motivated in part by the introduction of the Quality by Design paradigm, a landmark change in regulatory expectations for the level of scientific understanding associated with the manufacturing process. Today, statistical methods are increasingly applied to accelerate the characterization and optimization of new drugs created via numerous unit operations well known to the chemical engineering discipline. We offer here a review of the maturity in the implementation of design of experiment techniques, the increased incorporation of latent variable methods in process and material characterization, and the adoption of Bayesian methodology for process risk assessment.
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Affiliation(s)
- José E. Tabora
- Chemical & Synthetics Development, Pharmaceutical Development, Bristol-Myers Squibb Company, New Brunswick, New Jersey 08901;,
| | - Nathan Domagalski
- Chemical & Synthetics Development, Pharmaceutical Development, Bristol-Myers Squibb Company, New Brunswick, New Jersey 08901;,
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32
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Changi SM, Yokozawa T, Yamamoto T, Nakajima H, Embry MC, Vaid R, Luciani CV, Wong SW, Johnson M, Moher ED. Mechanistic investigation of a Ru-catalyzed direct asymmetric reductive amination reaction for a batch or continuous process scale-up: an industrial perspective. REACT CHEM ENG 2017. [DOI: 10.1039/c7re00055c] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Scale-up of a pharmaceutical process step via an experimental and model driven approach.
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Affiliation(s)
| | - Tohru Yokozawa
- Takasago International Corporation
- Corporate Research & Development Division
- Hiratsuka City
- Japan
| | - Tetsuya Yamamoto
- Takasago International Corporation
- Corporate Research & Development Division
- Hiratsuka City
- Japan
| | - Hikaru Nakajima
- Takasago International Corporation
- Corporate Research & Development Division
- Hiratsuka City
- Japan
| | - Matthew C. Embry
- Small Molecule Design & Development
- Eli Lilly and Company
- Indianapolis
- USA
| | - Radhe Vaid
- Small Molecule Design & Development
- Eli Lilly and Company
- Indianapolis
- USA
| | - Carla V. Luciani
- Small Molecule Design & Development
- Eli Lilly and Company
- Indianapolis
- USA
| | - Sze-Wing Wong
- Small Molecule Design & Development
- Eli Lilly and Company
- Indianapolis
- USA
| | - Martin Johnson
- Small Molecule Design & Development
- Eli Lilly and Company
- Indianapolis
- USA
| | - Eric D. Moher
- Small Molecule Design & Development
- Eli Lilly and Company
- Indianapolis
- USA
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33
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Cole KP, Campbell BM, Forst MB, McClary Groh J, Hess M, Johnson MD, Miller RD, Mitchell D, Polster CS, Reizman BJ, Rosemeyer M. An Automated Intermittent Flow Approach to Continuous Suzuki Coupling. Org Process Res Dev 2016. [DOI: 10.1021/acs.oprd.6b00030] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Affiliation(s)
- Kevin P. Cole
- Eli Lilly and Company, Indianapolis, Indiana 46285, United States
| | | | - Mindy B. Forst
- Eli Lilly and Company, Indianapolis, Indiana 46285, United States
| | | | - Molly Hess
- Eli Lilly and Company, Indianapolis, Indiana 46285, United States
| | | | | | - David Mitchell
- Eli Lilly and Company, Indianapolis, Indiana 46285, United States
| | | | | | - Morgan Rosemeyer
- D&M Continuous Solutions, LLC, Greenwood, Indiana 46143, United States
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34
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Seidl TL, Sundalam SK, McCullough B, Stuart DR. Unsymmetrical Aryl(2,4,6-trimethoxyphenyl)iodonium Salts: One-Pot Synthesis, Scope, Stability, and Synthetic Studies. J Org Chem 2016; 81:1998-2009. [PMID: 26828570 DOI: 10.1021/acs.joc.5b02833] [Citation(s) in RCA: 74] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Diaryliodonium salts have recently attracted significant attention as metal-free-arylation reagents in organic synthesis, and efficient access to these salts is critical for advancement of their use in reaction discovery and development. The trimethoxybenzene-derived auxiliary is a promising component of unsymmetrical variants, yet access remains limited. Here, a one-pot synthesis of aryl(2,4,6-trimethoxyphenyl)iodonium salts from aryl iodides, m-CPBA, p-toluenesulfonic acid, and trimethoxybenzene is described. Optimization of the reaction conditions for this one-pot synthesis was enabled by the method of multivariate analysis. The reaction is fast (<1 h), provides a high yield of product (>85% average), and has broad substrate scope (>25 examples) including elaborate aryl iodides. The utility of these reagents is demonstrated in moderate to high yielding arylation reactions with C-, N-, O-, and S-nucleophiles including the synthesis of a liquid crystal molecule.
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Affiliation(s)
- Thomas L Seidl
- Department of Chemistry, Portland State University , Portland, Oregon 97201, United States
| | - Sunil K Sundalam
- Department of Chemistry, Portland State University , Portland, Oregon 97201, United States
| | - Brennen McCullough
- Department of Chemistry, Portland State University , Portland, Oregon 97201, United States
| | - David R Stuart
- Department of Chemistry, Portland State University , Portland, Oregon 97201, United States
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35
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Merritt JM, Andiappan M, Pietz MA, Richey RN, Sullivan KA, Kjell DP. Mitigating the Risk of Coprecipitation of Pinacol during Isolation from Telescoped Miyaura Borylation and Suzuki Couplings Utilizing Boron Pinacol Esters: Use of Modeling for Process Design. Org Process Res Dev 2016. [DOI: 10.1021/acs.oprd.5b00324] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Jeremy M. Merritt
- Small Molecule Design and
Development, Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, Indiana 46221, United States
| | - Marimuthu Andiappan
- Small Molecule Design and
Development, Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, Indiana 46221, United States
| | - Mark A. Pietz
- Small Molecule Design and
Development, Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, Indiana 46221, United States
| | - Rachel N. Richey
- Small Molecule Design and
Development, Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, Indiana 46221, United States
| | - Kevin A. Sullivan
- Small Molecule Design and
Development, Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, Indiana 46221, United States
| | - Douglas P. Kjell
- Small Molecule Design and
Development, Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, Indiana 46221, United States
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