1
|
Winter M, Achleitner L, Satzer P. Soft sensor for viable cell counting by measuring dynamic oxygen uptake rate. N Biotechnol 2024; 83:16-25. [PMID: 38878999 DOI: 10.1016/j.nbt.2024.06.001] [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: 01/19/2024] [Revised: 05/27/2024] [Accepted: 06/08/2024] [Indexed: 06/20/2024]
Abstract
Regulatory authorities in biopharmaceutical industry emphasize process design by process understanding but applicable tools that are easy to implement are still missing. Soft sensors are a promising tool for the implementation of the Quality by Design (QbD) approach and Process Analytical Technology (PAT). In particular, the correlation between viable cell counting and oxygen consumption was investigated, but problems remained: Either the process had to be modified for excluding CO2 in pH control, or complex kLa models had to be set up for specific processes. In this work, a non-invasive soft sensor for simplified on-line cell counting based on dynamic oxygen uptake rate was developed with no need of special equipment. The dynamic oxygen uptake rates were determined by automated and periodic interruptions of gas supply in DASGIP® bioreactor systems, realized by a programmed Visual Basic script in the DASware® control software. With off-line cell counting, the two parameters were correlated based on linear regression and led to a robust model with a correlation coefficient of 0.92. Avoidance of oxygen starvation was achieved by gas flow reactivation at a certain minimum dissolved oxygen concentration. The soft sensor model was established in the exponential growth phase of a Chinese Hamster Ovary fed-batch process. Control studies showed no impact on cell growth by the discontinuous gas supply. This soft sensor is the first to be presented that does not require any specialized additional equipment as the methodology relies solely on the direct measurement of oxygen consumed by the cells in the bioreactor.
Collapse
Affiliation(s)
- M Winter
- Department of Biotechnology, University of Natural Resources and Life Sciences, Vienna, Austria
| | - L Achleitner
- Department of Biotechnology, University of Natural Resources and Life Sciences, Vienna, Austria; Austrian Centre of Industrial Biotechnology, Muthgasse 11, 1190 Wien, Austria
| | - P Satzer
- Department of Biotechnology, University of Natural Resources and Life Sciences, Vienna, Austria.
| |
Collapse
|
2
|
da Silva Cavalcante PE, Públio Rabello J, Leme J, Aragão Tejo Dias V, Correia Barrence FA, de Oliveira Guardalini LG, Consoni Bernardino T, Almeida S, Tonso A, Attie Calil Jorge S, Fernández Núñez EG. Raman laser intensity and sample clarification on biochemical monitoring over Zika-VLP upstream stages. Biochem Biophys Res Commun 2024; 733:150671. [PMID: 39298919 DOI: 10.1016/j.bbrc.2024.150671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2024] [Revised: 08/19/2024] [Accepted: 09/06/2024] [Indexed: 09/22/2024]
Abstract
In the current biopharmaceutical scenario, constant bioprocess monitoring is crucial for the quality and integrity of final products. Thus, process analytical techniques, such as those based on Raman spectroscopy, have been used as multiparameter tracking methods in pharma bioprocesses, which can be combined with chemometric tools, like Partial Least Squares (PLS) and Artificial Neural Networks (ANN). In some cases, applying spectra pre-processing techniques before modeling can improve the accuracy of chemometric model fittings to observed values. One of the biological applications of these techniques could have as a target the virus-like particles (VLP), a vaccine production platform for viral diseases. A disease that has drawn attention in recent years is Zika, with large-scale production sometimes challenging without an appropriate monitoring approach. This work aimed to define global models for Zika VLP upstream production monitoring with Raman considering different laser intensities (200 mW and 495 mW), sample clarification (with or without cells), spectra pre-processing approaches, and PLS and ANN modeling techniques. Six experiments were performed in a benchtop bioreactor to collect the Raman spectral and biochemical datasets for modeling calibration. The best models generated presented a mean absolute error and mean relative error respectively of 3.46 × 105 cell/mL and 35 % for viable cell density (Xv); 4.1 % and 5 % for cell viability (CV); 0.245 g/L and 3 % for glucose (Glc); 0.006 g/L and 18 % for lactate (Lac); 0.115 g/L and 26 % for glutamine (Gln); 0.132 g/L and 18 % for glutamate (Glu); 0.0029 g/L and 3 % for ammonium (NH4+); and 0.0103 g/L and 2 % for potassium (K+). Sample without conditioning (with cells) improved the models' adequacy, except for Glutamine. ANN better predicted CV, Gln, Glu, and K+, while Xv, Glc, Lac, and NH4+ presented no statistical difference between the chemometric tools. For most of the assessed experimental parameters, there was no statistical need for spectra pre-filtering, for which the models based on the raw spectra were selected as the best ones. Laser intensity impacts quality model predictions in some parameters, Xv, Gln, and K+ had a better performance with 200 mW of intensity (for PLS, ANN, and ANN, respectively), for CV the 495 mW laser intensity was better (for PLS), and for the other biochemical variables, the use of 200 or 495 mW did not impact model fitting adequacy.
Collapse
Affiliation(s)
| | - Júlia Públio Rabello
- Laboratório de Engenharia de Bioprocessos. Escola de Artes, Ciências e Humanidades (EACH), Universidade de São Paulo, Rua Arlindo Béttio, 1000, CEP 03828-000, São Paulo, SP, Brazil
| | - Jaci Leme
- Laboratório de Biotecnologia Viral, Instituto Butantan, Av Vital Brasil 1500, CEP 05503-900, São Paulo, SP, Brazil
| | - Vinícius Aragão Tejo Dias
- Laboratório de Engenharia de Bioprocessos. Escola de Artes, Ciências e Humanidades (EACH), Universidade de São Paulo, Rua Arlindo Béttio, 1000, CEP 03828-000, São Paulo, SP, Brazil
| | - Fernanda Angela Correia Barrence
- Laboratório de Engenharia de Bioprocessos. Escola de Artes, Ciências e Humanidades (EACH), Universidade de São Paulo, Rua Arlindo Béttio, 1000, CEP 03828-000, São Paulo, SP, Brazil
| | | | - Thaissa Consoni Bernardino
- Laboratório de Biotecnologia Viral, Instituto Butantan, Av Vital Brasil 1500, CEP 05503-900, São Paulo, SP, Brazil
| | - Sabrina Almeida
- Grupo de Espectroscopia. Astro34. Rua Belém, 106 - Jardim Vista Alegre, Embu das Artes - SP, CEP: 06807-340, São Paulo, SP-Brazil
| | - Aldo Tonso
- Laboratório de Células Animais, Departamento de Engenharia Química, Escola Politécnica, Universidade de São Paulo, Av. Prof. Luciano Gualberto, Travessa do Politécnico, 380, 05508-010, São Paulo, SP, Brazil
| | - Soraia Attie Calil Jorge
- Laboratório de Biotecnologia Viral, Instituto Butantan, Av Vital Brasil 1500, CEP 05503-900, São Paulo, SP, Brazil
| | - Eutimio Gustavo Fernández Núñez
- Laboratório de Engenharia de Bioprocessos. Escola de Artes, Ciências e Humanidades (EACH), Universidade de São Paulo, Rua Arlindo Béttio, 1000, CEP 03828-000, São Paulo, SP, Brazil.
| |
Collapse
|
3
|
Graf T, Naumann L, Bonnington L, Heckel J, Spensberger B, Klein S, Brey C, Nachtigall R, Mroz M, Hogg TV, McHardy C, Martinez A, Braaz R, Leiss M. Expediting online liquid chromatography for real-time monitoring of product attributes to advance process analytical technology in downstream processing of biopharmaceuticals. J Chromatogr A 2024; 1729:465013. [PMID: 38824753 DOI: 10.1016/j.chroma.2024.465013] [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: 03/18/2024] [Revised: 05/16/2024] [Accepted: 05/20/2024] [Indexed: 06/04/2024]
Abstract
The application of Process Analytical Technology (PAT) principles for manufacturing of biotherapeutics proffers the prospect of ensuring consistent product quality along with increased productivity as well as substantial cost and time savings. Although this paradigm shift from a traditional, rather rigid manufacturing model to a more scientific, risk-based approach has been advocated by health authorities for almost two decades, the practical implementation of PAT in the biopharmaceutical industry is still limited by the lack of fit-for-purpose analytical methods. In this regard, most of the proposed spectroscopic techniques are sufficiently fast but exhibit deficiencies in terms of selectivity and sensitivity, while well-established offline methods, such as (ultra-)high-performance liquid chromatography, are generally considered as too slow for this task. To address these reservations, we introduce here a novel online Liquid Chromatography (LC) setup that was specifically designed to enable real-time monitoring of critical product quality attributes during time-sensitive purification operations in downstream processing. Using this online LC solution in combination with fast, purpose-built analytical methods, sampling cycle times between 1.30 and 2.35 min were achieved, without compromising on the ability to resolve and quantify the product variants of interest. The capabilities of our approach are ultimately assessed in three case studies, involving various biotherapeutic modalities, downstream processes and analytical chromatographic separation modes. Altogether, our results highlight the expansive opportunities of online LC based applications to serve as a PAT tool for biopharmaceutical manufacturing.
Collapse
Affiliation(s)
- Tobias Graf
- Pharma Technical Development Analytics, Roche Diagnostics GmbH, 82377 Penzberg, Germany
| | - Lukas Naumann
- Pharma Technical Development Analytics, Roche Diagnostics GmbH, 82377 Penzberg, Germany
| | - Lea Bonnington
- Pharma Technical Development Analytics, Roche Diagnostics GmbH, 82377 Penzberg, Germany
| | - Jakob Heckel
- Pharma Technical Development Analytics, Roche Diagnostics GmbH, 82377 Penzberg, Germany
| | - Bernhard Spensberger
- Pharma Research and Early Development (pRED), Roche Innovation Center Munich, Roche Diagnostics GmbH, Nonnenwald 2, 82377 Penzberg, Germany
| | - Sascha Klein
- Pharma Technical Development Bioprocessing, Roche Diagnostics GmbH, 82377 Penzberg, Germany
| | - Christoph Brey
- Pharma Technical Development Bioprocessing, Roche Diagnostics GmbH, 82377 Penzberg, Germany
| | - Ronnie Nachtigall
- Pharma Technical Development Bioprocessing, Roche Diagnostics GmbH, 82377 Penzberg, Germany
| | - Maximilian Mroz
- Pharma Technical Development Bioprocessing, Roche Diagnostics GmbH, 82377 Penzberg, Germany
| | - Thomas Vagn Hogg
- Pharma Research and Early Development (pRED), Roche Innovation Center Munich, Roche Diagnostics GmbH, Nonnenwald 2, 82377 Penzberg, Germany
| | - Christopher McHardy
- Pharma Technical Development Bioprocessing, Roche Diagnostics GmbH, 82377 Penzberg, Germany
| | - Andrés Martinez
- Gene Therapy Technical Development, Roche Diagnostics GmbH, 82377 Penzberg, Germany
| | - Reinhard Braaz
- Pharma Technical Development Clinical Supply Center, Roche Diagnostics GmbH, 82377 Penzberg, Germany
| | - Michael Leiss
- Pharma Technical Development Analytics, Roche Diagnostics GmbH, 82377 Penzberg, Germany.
| |
Collapse
|
4
|
Neugebauer P, Zettl M, Moser D, Poms J, Kuchler L, Sacher S. Process analytical technology in Downstream-Processing of Drug Substances- A review. Int J Pharm 2024; 661:124412. [PMID: 38960339 DOI: 10.1016/j.ijpharm.2024.124412] [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: 04/30/2024] [Revised: 06/11/2024] [Accepted: 06/29/2024] [Indexed: 07/05/2024]
Abstract
Process Analytical Technology (PAT) has revolutionized pharmaceutical manufacturing by providing real-time monitoring and control capabilities throughout the production process. This review paper comprehensively examines the application of PAT methodologies specifically in the production of solid active pharmaceutical ingredients (APIs). Beginning with an overview of PAT principles and objectives, the paper explores the integration of advanced analytical techniques such as spectroscopy, imaging modalities and others into solid API substance production processes. Novel developments in in-line monitoring at academic level are also discussed. Emphasis is placed on the role of PAT in ensuring product quality, consistency, and compliance with regulatory requirements. Examples from existing literature illustrate the practical implementation of PAT in solid API substance production, including work-up, crystallization, filtration, and drying processes. The review addresses the quality and reliability of the measurement technologies, aspects of process implementation and handling, the integration of data treatment algorithms and current challenges. Overall, this review provides valuable insights into the transformative impact of PAT on enhancing pharmaceutical manufacturing processes for solid API substances.
Collapse
Affiliation(s)
- Peter Neugebauer
- Research Center Pharmaceutical Engineering GmbH, 8010 Graz, Austria; Institute of Process and Particle Engineering, Graz University of Technology, 8010 Graz, Austria
| | - Manuel Zettl
- Research Center Pharmaceutical Engineering GmbH, 8010 Graz, Austria
| | - Daniel Moser
- Research Center Pharmaceutical Engineering GmbH, 8010 Graz, Austria
| | - Johannes Poms
- Research Center Pharmaceutical Engineering GmbH, 8010 Graz, Austria
| | - Lisa Kuchler
- Research Center Pharmaceutical Engineering GmbH, 8010 Graz, Austria
| | - Stephan Sacher
- Research Center Pharmaceutical Engineering GmbH, 8010 Graz, Austria.
| |
Collapse
|
5
|
Dürauer A, Jungbauer A, Scharl T. Sensors and chemometrics in downstream processing. Biotechnol Bioeng 2024; 121:2347-2364. [PMID: 37470278 DOI: 10.1002/bit.28499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 06/14/2023] [Accepted: 07/07/2023] [Indexed: 07/21/2023]
Abstract
The biopharmaceutical industry is still running in batch mode, mostly because it is highly regulated. In the past, sensors were not readily available and in-process control was mainly executed offline. The most important product parameters are quantity, purity, and potency, in addition to adventitious agents and bioburden. New concepts using disposable single-use technologies and integrated bioprocessing for manufacturing will dominate the future of bioprocessing. To ensure the quality of pharmaceuticals, initiatives such as Process Analytical Technologies, Quality by Design, and Continuous Integrated Manufacturing have been established. The aim is that these initiatives, together with technology development, will pave the way for process automation and autonomous bioprocessing without any human intervention. Then, real-time release would be realized, leading to a highly predictive and robust biomanufacturing system. The steps toward such automated and autonomous bioprocessing are reviewed in the context of monitoring and control. It is possible to integrate real-time monitoring gradually, and it should be considered from a soft sensor perspective. This concept has already been successfully implemented in other industries and requires relatively simple model training and the use of established statistical tools, such as multivariate statistics or neural networks. This review describes a scenario for integrating soft sensors and predictive chemometrics into modern process control. This is exemplified by selective downstream processing steps, such as chromatography and membrane filtration, the most common unit operations for separation of biopharmaceuticals.
Collapse
Affiliation(s)
- Astrid Dürauer
- Institute of Bioprocessing Science and Engineering, University of Natural Resources and Life Sciences, Vienna, Austria
| | - Alois Jungbauer
- Institute of Bioprocessing Science and Engineering, University of Natural Resources and Life Sciences, Vienna, Austria
- Austrian Centre of Industrial Biotechnology, Vienna, Austria
| | - Theresa Scharl
- Institute of Statistics, University of Natural Resources and Life Sciences, Vienna, Austria
| |
Collapse
|
6
|
Zhong Y, Wen W, Fan X, Cheng N. An intelligent process analysis method for rapidly evaluating the quality of Chinese medicine with near-infrared non-contact hyperspectral imaging: A case study of Weifuchun concentrate. PHYTOCHEMICAL ANALYSIS : PCA 2024. [PMID: 38924197 DOI: 10.1002/pca.3408] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 06/04/2024] [Accepted: 06/08/2024] [Indexed: 06/28/2024]
Abstract
INTRODUCTION The quality of Chinese medicine preparations can be greatly influenced by the quality of the intermediates such as extracts or concentrates. However, it is highly challenging to evaluate the quality in a rapid and non-contact manner during manufacturing. Here, we introduce an intelligent hyperspectral analysis method integrating a self-built abnormal region removal algorithm with machine learning and demonstrate its utility using the concentrate of Weifuchun (WFC), a traditional Chinese medicine preparation made from Ginseng Radix et Rhizoma Rubra, Rabdosia Amethystoides, and Aurantii Fructus. OBJECTIVE To rapidly and non-destructively detect quality attributes of the intermediates in the manufacturing processes of Chinese medicine, an intelligent hyperspectral analysis method was developed for simultaneously quantifying the contents of naringin, neohesperidin, rosmarinic acid, and relative density of WFC concentrates. METHODOLOGY Samples were evenly spread on solid white flat bottom containers, which were batch placed on a horizontal sample stage. Subsequent to the acquisition of near-infrared (NIR) hyperspectral images, abnormal pixels such as large/small bubbles and fine solids were first removed according to the differential pixel values in the binary grayscale map and the Mahalanobis distance metric. Then, partial least squares (PLS) and support vector machine (SVM) algorithms were used to construct hyperspectral quantitative calibration models for quality attributes. The hyperspectral images were reconstructed based on these models to visually evaluate the quality of the concentrates during manufacturing. RESULTS As a case study, quality attributes of the WFC concentrates including contents of naringin, neohesperidin, rosmarinic acid, and relative density were determined simultaneously, and coefficients of determination of these quantitative correction models were 0.900, 0.891, 0.851, and 0.920, respectively. CONCLUSION The method proposed in this study favors real-time determination of multiple attributes in viscous samples with industrial application prospects.
Collapse
Affiliation(s)
- Yi Zhong
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
| | - Wu Wen
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
| | - Xiaohui Fan
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
| | - Ningtao Cheng
- School of Medicine, Zhejiang University, Hangzhou, China
| |
Collapse
|
7
|
Yuan W, Jiao K, Yuan H, Sun H, Lim EG, Mitrovic I, Duan S, Cong S, Yong R, Li F, Song P. Metal-Organic Frameworks/Heterojunction Structures for Surface-Enhanced Raman Scattering with Enhanced Sensitivity and Tailorability. ACS APPLIED MATERIALS & INTERFACES 2024; 16:26374-26385. [PMID: 38716706 PMCID: PMC11129117 DOI: 10.1021/acsami.4c01588] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/28/2024] [Revised: 04/04/2024] [Accepted: 04/08/2024] [Indexed: 05/24/2024]
Abstract
Metal-organic frameworks (MOFs), which are composed of crystalline microporous materials with metal ions, have gained considerable interest as promising substrate materials for surface-enhanced Raman scattering (SERS) detection via charge transfer. Research on MOF-based SERS substrates has advanced rapidly because of the MOFs' excellent structural tunability, functionalizable pore interiors, and ultrahigh surface-to-volume ratios. Compared with traditional noble metal SERS plasmons, MOFs exhibit better biocompatibility, ease of operation, and tailorability. However, MOFs cannot produce a sufficient limit of detection (LOD) for ultrasensitive detection, and therefore, developing an ultrasensitive MOF-based SERS substrate is imperative. To the best of our knowledge, this is the first study to develop an MOFs/heterojunction structure as an SERS enhancing material. We report an in situ ZIF-67/Co(OH)2 heterojunction-based nanocellulose paper (nanopaper) plate (in situ ZIF-67 nanoplate) as a device with an LOD of 0.98 nmol/L for Rhodamine 6G and a Raman enhancement of 1.43 × 107, which is 100 times better than that of the pure ZIF-67-based SERS substrate. Further, we extend this structure to other types of MOFs and develop an in situ HKUST-1 nanoplate (with HKUST-1/Cu(OH)2). In addition, we demonstrate that the formation of heterojunctions facilitates efficient photoinduced charge transfer for SERS detection by applying the Mx(OH)y-assisted (where M = Co, Cu, or other metals) MOFs/heterojunction structure. Finally, we successfully demonstrate the application of medicine screening on our nanoplates, specifically for omeprazole. The nanoplates we developed still maintain the tailorability of MOFs and perform high anti-interference ability. Our approach provides customizing options for MOF-based SERS detection, catering to diverse possibilities in future research and applications.
Collapse
Affiliation(s)
- Wenwen Yuan
- School
of Advanced Technology, Xi’an Jiaotong
- Liverpool University, Suzhou 215123, China
- Department
of Electrical Engineering and Electronics, University of Liverpool, Liverpool L69 7ZX, U.K.
- State
Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiaotong University, Xi’an 710049, China
| | - Keran Jiao
- School
of Advanced Technology, Xi’an Jiaotong
- Liverpool University, Suzhou 215123, China
- Department
of Electrical Engineering and Electronics, University of Liverpool, Liverpool L69 7ZX, U.K.
| | - Hang Yuan
- School
of Advanced Technology, Xi’an Jiaotong
- Liverpool University, Suzhou 215123, China
| | - Hongzhao Sun
- School
of Physical Science and Technology, Suzhou
University of Science and Technology, Suzhou 215009, China
| | - Eng Gee Lim
- School
of Advanced Technology, Xi’an Jiaotong
- Liverpool University, Suzhou 215123, China
- Department
of Electrical Engineering and Electronics, University of Liverpool, Liverpool L69 7ZX, U.K.
| | - Ivona Mitrovic
- Department
of Electrical Engineering and Electronics, University of Liverpool, Liverpool L69 7ZX, U.K.
| | - Sixuan Duan
- School
of Advanced Technology, Xi’an Jiaotong
- Liverpool University, Suzhou 215123, China
- Department
of Electrical Engineering and Electronics, University of Liverpool, Liverpool L69 7ZX, U.K.
- Key
Laboratory of Bionic Engineering, Jilin
University, Changchun 130022, China
| | - Shan Cong
- School of
Nano-Tech and Nano-Bionics, University of
Science and Technology of China, Suzhou 215123, China
| | - Ruiqi Yong
- School
of Advanced Technology, Xi’an Jiaotong
- Liverpool University, Suzhou 215123, China
| | - Feifan Li
- School of
Nano-Tech and Nano-Bionics, University of
Science and Technology of China, Suzhou 215123, China
| | - Pengfei Song
- School
of Advanced Technology, Xi’an Jiaotong
- Liverpool University, Suzhou 215123, China
- Department
of Electrical Engineering and Electronics, University of Liverpool, Liverpool L69 7ZX, U.K.
| |
Collapse
|
8
|
Spoor E, Oerke V, Rädle M, Repke JU. Raman Spectroscopy of Disperse Systems with Varying Particle Sizes and Correction of Signal Losses. SENSORS (BASEL, SWITZERLAND) 2024; 24:3132. [PMID: 38793986 PMCID: PMC11125269 DOI: 10.3390/s24103132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/11/2024] [Revised: 05/06/2024] [Accepted: 05/13/2024] [Indexed: 05/26/2024]
Abstract
In this paper, a dispersion of glass beads of different sizes in an ammonium nitrate solution is investigated with the aid of Raman spectroscopy. The signal losses caused by the dispersion are quantified by an additional scattered light measurement and used to correct the measured ammonium nitrate concentration. Each individual glass bead represents an interface at which the excitation laser is deflected from its direction causing distortion in the received Raman signal. It is shown that the scattering losses measured with the scattered light probe correlate with the loss of the Raman signal, which means that the data obtained can be used to correct the measured values. The resulting correction function considers different particle sizes in the range of 2-99 µm as well as ammonium nitrate concentrations of 0-20 wt% and delivers an RMSEP of 1.952 wt%. This correction provides easier process access to dispersions that were previously difficult or impossible to measure.
Collapse
Affiliation(s)
- Erik Spoor
- CeMOS Research and Transfer Center, Mannheim University of Applied Sciences, Paul-Wittsack-Str. 10, 68163 Mannheim, Germany (M.R.)
| | - Viktoria Oerke
- CeMOS Research and Transfer Center, Mannheim University of Applied Sciences, Paul-Wittsack-Str. 10, 68163 Mannheim, Germany (M.R.)
| | - Matthias Rädle
- CeMOS Research and Transfer Center, Mannheim University of Applied Sciences, Paul-Wittsack-Str. 10, 68163 Mannheim, Germany (M.R.)
| | - Jens-Uwe Repke
- Process Dynamics and Operations Group, Technische Universität Berlin, Straße des 17. Juni 135, 10623 Berlin, Germany;
| |
Collapse
|
9
|
Liu Q, Wu C, Liu H, Wang M, Zhao C, Zhang F. Real-Time Monitoring of Multistep Batch and Flow Synthesis Processes of a Key Intermediate of Lifitegrast by a Combined Spectrometer System with Both Near-Infrared and Raman Spectroscopies Coupled to Partial Least-Squares. ACS OMEGA 2024; 9:20214-20222. [PMID: 38737057 PMCID: PMC11079892 DOI: 10.1021/acsomega.4c00565] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 04/10/2024] [Accepted: 04/16/2024] [Indexed: 05/14/2024]
Abstract
Process analytical technology (PAT) has been successfully applied in numerous chemical synthesis cases and is an important tool in pharmaceutical process research and development. PAT brings new methods and opportunities for the real-time monitoring of chemical processes. In multistep synthesis, real-time monitoring of the complex reaction mixtures is a significant challenge but provides an opportunity to enhance reaction understanding and control. In this study, a combined multichannel spectrometer system with both near-infrared and Raman spectroscopy was built, and calibration models were developed to quantify the desired products, intermediates, and impurities in real-time at multiple points along the synthetic pathway. The capabilities of the system have been demonstrated by operating dynamic experiments in both batch and continuous-flow processes. It represents a significant step forward in data-driven, multistep pharmaceutical ingredient synthesis.
Collapse
Affiliation(s)
- Quan Liu
- School
of Pharmaceutical Science, Shanghai Jiao
Tong University, Minhang District, 200240 Shanghai, China
| | - Chuanjun Wu
- Shanghai
Institute of Pharmaceutical Industry, China
State Institute of Pharmaceutical Industry, Pudong District, 201203 Shanghai, China
| | - Huiting Liu
- Shanghai
PROXS Chemical Technology Co. Ltd., Pudong District, 201203 Shanghai, China
| | - Mengfei Wang
- Shanghai
Institute of Pharmaceutical Industry, China
State Institute of Pharmaceutical Industry, Pudong District, 201203 Shanghai, China
| | - Chuanmeng Zhao
- Shanghai
Institute of Pharmaceutical Industry, China
State Institute of Pharmaceutical Industry, Pudong District, 201203 Shanghai, China
| | - Fuli Zhang
- Shanghai
Institute of Pharmaceutical Industry, China
State Institute of Pharmaceutical Industry, Pudong District, 201203 Shanghai, China
| |
Collapse
|
10
|
Polak J, Huang Z, Sokolov M, von Stosch M, Butté A, Hodgman CE, Borys M, Khetan A. An innovative hybrid modeling approach for simultaneous prediction of cell culture process dynamics and product quality. Biotechnol J 2024; 19:e2300473. [PMID: 38528367 DOI: 10.1002/biot.202300473] [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: 09/12/2023] [Revised: 02/27/2024] [Accepted: 02/29/2024] [Indexed: 03/27/2024]
Abstract
The use of hybrid models is extensively described in the literature to predict the process evolution in cell cultures. These models combine mechanistic and machine learning methods, allowing the prediction of complex process behavior, in the presence of many process variables, without the need to collect a large amount of data. Hybrid models cannot be directly used to predict final product critical quality attributes, or CQAs, because they are usually measured only at the end of the process, and more mechanistic knowledge is needed for many classes of CQAs. The historical models can instead predict the CQAs better; however, they cannot directly relate manipulated process parameters to final CQAs, as they require knowledge of the process evolution. In this work, we propose an innovative modeling approach based on combining a hybrid propagation model with a historical data-driven model, that is, the combined hybrid model, for simultaneous prediction of full process dynamics and CQAs. The performance of the combined hybrid model was evaluated on an industrial dataset and compared to classical black-box models, which directly relate manipulated process parameters to CQAs. The proposed combined hybrid model outperforms the black-box model by 33% on average in predicting the CQAs while requiring only around half of the data for model training to match performance. Thus, in terms of model accuracy and experimental costs, the combined hybrid model in this study provides a promising platform for process optimization applications.
Collapse
Affiliation(s)
| | - Zhuangrong Huang
- Biologics Development, Global Product Development and Supply, Bristol Myers Squibb, Devens, Massachusetts, USA
| | | | | | | | - C Eric Hodgman
- Biologics Development, Global Product Development and Supply, Bristol Myers Squibb, Devens, Massachusetts, USA
| | - Michael Borys
- Biologics Development, Global Product Development and Supply, Bristol Myers Squibb, Devens, Massachusetts, USA
| | - Anurag Khetan
- Biologics Development, Global Product Development and Supply, Bristol Myers Squibb, Devens, Massachusetts, USA
| |
Collapse
|
11
|
Finnegan EW, Goulding DA, O'Callaghan TF, O'Mahony JA. From lab-based to in-line: Analytical tools for the characterization of whey protein denaturation and aggregation-A review. Compr Rev Food Sci Food Saf 2024; 23:e13289. [PMID: 38343297 DOI: 10.1111/1541-4337.13289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 10/14/2023] [Accepted: 12/11/2023] [Indexed: 02/15/2024]
Abstract
Whey protein denaturation and aggregation have long been areas of research interest to the dairy industry, having significant implications for process performance and final product functionality and quality. As such, a significant number of analytical techniques have been developed or adapted to assess and characterize levels of whey protein denaturation and aggregation, to either maximize processing efficiency or create products with enhanced functionality (both technological and biological). This review aims to collate and critique these approaches based on their analytical principles and outline their application for the assessment of denaturation and aggregation. This review also provides insights into recent developments in process analytical technologies relating to whey protein denaturation and aggregation, whereby some of the analytical methods have been adapted to enable measurements in-line. Developments in this area will enable more live, in-process data to be generated, which will subsequently allow more adaptive processing, enabling improved product quality and processing efficiency. Along with the applicability of these techniques for the assessment of whey protein denaturation and aggregation, limitations are also presented to help assess the suitability of each analytical technique for specific areas of interest.
Collapse
Affiliation(s)
- Eoin W Finnegan
- School of Food and Nutritional Sciences, University College Cork, Cork, Ireland
- Dairy Processing Technology Centre, University College Cork, Cork, Ireland
| | - David A Goulding
- School of Food and Nutritional Sciences, University College Cork, Cork, Ireland
| | - T F O'Callaghan
- School of Food and Nutritional Sciences, University College Cork, Cork, Ireland
- Dairy Processing Technology Centre, University College Cork, Cork, Ireland
| | - James A O'Mahony
- School of Food and Nutritional Sciences, University College Cork, Cork, Ireland
- Dairy Processing Technology Centre, University College Cork, Cork, Ireland
| |
Collapse
|
12
|
Leonov AI, Hammer AJS, Lach S, Mehr SHM, Caramelli D, Angelone D, Khan A, O'Sullivan S, Craven M, Wilbraham L, Cronin L. An integrated self-optimizing programmable chemical synthesis and reaction engine. Nat Commun 2024; 15:1240. [PMID: 38336880 PMCID: PMC10858227 DOI: 10.1038/s41467-024-45444-3] [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] [Received: 02/21/2023] [Accepted: 01/22/2024] [Indexed: 02/12/2024] Open
Abstract
Robotic platforms for chemistry are developing rapidly but most systems are not currently able to adapt to changing circumstances in real-time. We present a dynamically programmable system capable of making, optimizing, and discovering new molecules which utilizes seven sensors that continuously monitor the reaction. By developing a dynamic programming language, we demonstrate the 10-fold scale-up of a highly exothermic oxidation reaction, end point detection, as well as detecting critical hardware failures. We also show how the use of in-line spectroscopy such as HPLC, Raman, and NMR can be used for closed-loop optimization of reactions, exemplified using Van Leusen oxazole synthesis, a four-component Ugi condensation and manganese-catalysed epoxidation reactions, as well as two previously unreported reactions, discovered from a selected chemical space, providing up to 50% yield improvement over 25-50 iterations. Finally, we demonstrate an experimental pipeline to explore a trifluoromethylations reaction space, that discovers new molecules.
Collapse
Affiliation(s)
- Artem I Leonov
- School of Chemistry, The University of Glasgow, University Avenue, Glasgow, G12 8QQ, UK
| | - Alexander J S Hammer
- School of Chemistry, The University of Glasgow, University Avenue, Glasgow, G12 8QQ, UK
| | - Slawomir Lach
- School of Chemistry, The University of Glasgow, University Avenue, Glasgow, G12 8QQ, UK
| | - S Hessam M Mehr
- School of Chemistry, The University of Glasgow, University Avenue, Glasgow, G12 8QQ, UK
| | - Dario Caramelli
- School of Chemistry, The University of Glasgow, University Avenue, Glasgow, G12 8QQ, UK
| | - Davide Angelone
- School of Chemistry, The University of Glasgow, University Avenue, Glasgow, G12 8QQ, UK
| | - Aamir Khan
- School of Chemistry, The University of Glasgow, University Avenue, Glasgow, G12 8QQ, UK
| | - Steven O'Sullivan
- School of Chemistry, The University of Glasgow, University Avenue, Glasgow, G12 8QQ, UK
| | - Matthew Craven
- School of Chemistry, The University of Glasgow, University Avenue, Glasgow, G12 8QQ, UK
| | - Liam Wilbraham
- School of Chemistry, The University of Glasgow, University Avenue, Glasgow, G12 8QQ, UK
| | - Leroy Cronin
- School of Chemistry, The University of Glasgow, University Avenue, Glasgow, G12 8QQ, UK.
| |
Collapse
|
13
|
Spoor E, Rädle M, Repke JU. Raman Spectroscopy of Glass Beads in Ammonium Nitrate Solution and Compensation of Signal Losses. SENSORS (BASEL, SWITZERLAND) 2024; 24:314. [PMID: 38257407 PMCID: PMC10819147 DOI: 10.3390/s24020314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 12/28/2023] [Accepted: 01/04/2024] [Indexed: 01/24/2024]
Abstract
In the present study, the influence of disperse systems on Raman scattering was investigated. How an increasing particle concentration weakens the quantitative signal of the Raman spectrum is shown. Furthermore, the change in the position of the optimal measurement point in the fluid was considered in detail. Additional transmission measurements can be used to derive a simple and robust correction method that allows the actual concentration of the continuous phase to be determined with a standard deviation of 2.6%.
Collapse
Affiliation(s)
- Erik Spoor
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Paul-Wittsack-Str. 10, 68163 Mannheim, Germany;
| | - Matthias Rädle
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Paul-Wittsack-Str. 10, 68163 Mannheim, Germany;
| | - Jens-Uwe Repke
- Process Dynamics and Operations Group, Technische Universität Berlin, Straße des 17. Juni 135, 10623 Berlin, Germany;
| |
Collapse
|
14
|
Hara R, Kobayashi W, Yamanaka H, Murayama K, Shimoda S, Ozaki Y. Validation of the cell culture monitoring using a Raman spectroscopy calibration model developed with artificially mixed samples and investigation of model learning methods using initial batch data. Anal Bioanal Chem 2024; 416:569-581. [PMID: 38099966 DOI: 10.1007/s00216-023-05065-z] [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: 09/28/2023] [Revised: 11/20/2023] [Accepted: 11/21/2023] [Indexed: 01/04/2024]
Abstract
The development of calibration models using Raman spectra data has long been challenged owing to the substantial time and cost required for robust data acquisition. To reduce the number of experiments involving actual incubation, a calibration model development method was investigated by measuring artificially mixed samples. In this method, calibration datasets were prepared using spectra from artificially mixed samples with adjusted concentrations based on design of experiments. The precision of these calibration models was validated using the actual cell culture sample. The results showed that when the culture conditions were unchanged, the root mean square error of prediction (RMSEP) of glucose, lactate, and antibody concentrations was 0.34, 0.33, and 0.25 g/L, respectively. Even when variables such as cell line or culture media were changed, the RMSEPs of glucose, lactate, and antibody concentrations remained within acceptable limits, demonstrating the robustness of the calibration models with artificially mixed samples. To further improve accuracy, a model training method for small datasets was also investigated. The spectral pretreatment conditions were optimized using error heat maps based on the first batch of each cell culture condition and applied these settings to the second and third batches. The RMSEPs improved for glucose, lactate, and antibody concentration, with values of 0.44, 0.19, and 0.18 g/L under constant culture conditions, 0.37, 0.12, and 0.12 g/L for different cell lines, and 0.26, 0.40, and 0.12 g/L when the culture media was changed. These results indicated the efficacy of calibration modeling with artificially mixed samples for actual incubations under various conditions.
Collapse
Affiliation(s)
- Risa Hara
- Research and Development Department, Yokogawa Electric Corporation, Musashino, Tokyo, 180-8750, Japan.
| | - Wataru Kobayashi
- Life Business Department, Yokogawa Electric Corporation, Musashino, Tokyo, 180-8750, Japan
| | - Hiroaki Yamanaka
- Life Business Department, Yokogawa Electric Corporation, Musashino, Tokyo, 180-8750, Japan
| | - Kodai Murayama
- Research and Development Department, Yokogawa Electric Corporation, Musashino, Tokyo, 180-8750, Japan
- Research and Development Department, SYNCREST Inc., Fujisawa, Kanagawa, 251-8555, Japan
| | - Soichiro Shimoda
- Life Business Department, Yokogawa Electric Corporation, Musashino, Tokyo, 180-8750, Japan.
| | - Yukihiro Ozaki
- School of Biological and Environmental Sciences, Kwansei Gakuin University, Sanda, Hyogo, 669-1330, Japan
| |
Collapse
|
15
|
Dan A, Vaswani H, Šimonová A, Grząbka-Zasadzińska A, Li J, Sen K, Paul S, Tseng YC, Ramachandran R. End-point determination of heterogeneous formulations using inline torque measurements for a high-shear wet granulation process. Int J Pharm X 2023; 6:100188. [PMID: 37387778 PMCID: PMC10300204 DOI: 10.1016/j.ijpx.2023.100188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 06/06/2023] [Accepted: 06/07/2023] [Indexed: 07/01/2023] Open
Abstract
In this study, the torque profiles of heterogeneous granulation formulations with varying powder properties in terms of particle size, solubility, deformability, and wettability, were studied, and the feasibility of identifying the end-point of the granulation process for each formulation based on the torque profiles was evaluated. Dynamic median particle size (d50) and porosity were correlated to the torque measurements to understand the relationship between torque and granule properties, and to validate distinction between different granulation stages based on the torque profiles made in previous studies. Generally, the torque curves obtained from the different granulation runs in this experimental design could be categorized into two different types of torque profiles. The primary factor influencing the likelihood of producing each profile was the binder type used in the formulation. A lower viscosity, higher solubility binder resulted in a type 1 profile. Other contributing factors that affected the torque profiles include API type and impeller speed. Material properties such as the deformability and solubility of the blend formulation and the binder were identified as important factors affecting both granule growth and the type of torque profiles observed. By correlating dynamic granule properties with torque values, it was possible to determine the granulation end-point based on a pre-determined target median particle size (d50) range which corresponded to specific markers identified in the torque profiles. In type 1 torque profiles, the end-point markers corresponded to the plateau phase, whereas in type 2 torque profiles the markers were indicated by the inflection point where the slope gradient changes. Additionally, we proposed an alternative method of identification by using the first derivative of the torque values, which facilitates an easier identification of the system approaching the end-point. Overall, this study identified the effects of different variations in formulation parameters on torque profiles and granule properties and implemented an improved method of identification of granulation end-point that is not dependent on the different types of torque profiles observed.
Collapse
Affiliation(s)
- Ashley Dan
- Department of Chemical and Biochemical Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ, USA 08854
| | - Haresh Vaswani
- Department of Chemical and Biochemical Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ, USA 08854
| | - Alice Šimonová
- Department of Analytical Chemistry, Charles University, Hlavova 2030/8, 12843, Prague, Czech Republic
- Zentiva k. s., U Kabelovny 130, Prague, Czech Republic
| | - Aleksandra Grząbka-Zasadzińska
- Institute of Chemical Technology and Engineering, Poznan University of Technology, ul. Berdychowo 4, 60-965 Poznań, Poland
| | - Jingzhe Li
- Boehringer Ingelheim Pharmaceuticals Inc, 900 Ridgebury Rd, Ridgefield, CT 06877, United States of America
| | - Koyel Sen
- Boehringer Ingelheim Pharmaceuticals Inc, 900 Ridgebury Rd, Ridgefield, CT 06877, United States of America
| | - Shubhajit Paul
- Boehringer Ingelheim Pharmaceuticals Inc, 900 Ridgebury Rd, Ridgefield, CT 06877, United States of America
| | - Yin-Chao Tseng
- Boehringer Ingelheim Pharmaceuticals Inc, 900 Ridgebury Rd, Ridgefield, CT 06877, United States of America
| | - Rohit Ramachandran
- Department of Chemical and Biochemical Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ, USA 08854
| |
Collapse
|
16
|
Dunn ZD, Bohman P, Quinteros A, Sauerborn B, Milman F, Patel M, Kargupta R, Wu S, Hornshaw M, Barrientos R, Bones J, Tayi VS, Abaroa N, Patel B, Appiah-Amponsah E, Regalado EL. Automated Online-Sampling Multidimensional Liquid Chromatography with Feedback-Control Capability as a Framework for Real-Time Monitoring of mAb Critical Quality Attributes in Multiple Bioreactors. Anal Chem 2023; 95:18130-18138. [PMID: 38015205 DOI: 10.1021/acs.analchem.3c03528] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Real-time monitoring of biopharmaceutical reactors is becoming increasingly important as the processes become more complex. During the continuous manufacturing of monoclonal antibodies (mAbs), the desired mAb product is continually created and collected over a 30 day process, where there can be changes in quality over that time. Liquid chromatography (LC) is the workhorse instrumentation capable of measuring mAb concentration as well as quality attributes such as aggregation, charge variants, oxidation, etc. However, traditional offline sampling is too infrequent to fully characterize bioprocesses, and the typical time from sample generation to data analysis and reporting can take weeks. To circumvent these limitations, an automated online sampling multidimensional workflow was developed to enable streamlined measurements of mAb concentration, aggregation, and charge variants. This analytical framework also facilitates automated data export for real-time analysis of up to six bioreactors, including feedback-controlling capability using readily available LC technology. This workflow increases the data points per bioreactor, improving the understanding of each experiment while also reducing the data turnaround time from weeks to hours. Examples of effective real-time analyses of mAb critical quality attributes are illustrated, showing substantial throughput improvements and accurate results while minimizing labor and manual intervention.
Collapse
Affiliation(s)
- Zachary D Dunn
- Analytical Research and Development, MRL, Merck & Co., Inc., Rahway, New Jersey 07065, United States
| | - Patrick Bohman
- Thermo Fisher Scientific, 168 Third Avenue, Waltham, Massachusetts 02451, United States
| | - Alexis Quinteros
- Process Research and Development, MRL, Merck & Co., Inc., Rahway, New Jersey 07065, United States
| | - Brian Sauerborn
- Engineering, MRL, Merck & Co., Inc., Rahway, New Jersey 07065, United States
| | - Felix Milman
- Engineering, MRL, Merck & Co., Inc., Rahway, New Jersey 07065, United States
| | - Misaal Patel
- Process Research and Development, MRL, Merck & Co., Inc., Rahway, New Jersey 07065, United States
| | - Roli Kargupta
- Process Research and Development, MRL, Merck & Co., Inc., Rahway, New Jersey 07065, United States
| | - Suyang Wu
- Process Research and Development, MRL, Merck & Co., Inc., Rahway, New Jersey 07065, United States
| | - Martin Hornshaw
- Thermo Fisher Scientific, 168 Third Avenue, Waltham, Massachusetts 02451, United States
| | - Rodell Barrientos
- Analytical Research and Development, MRL, Merck & Co., Inc., Rahway, New Jersey 07065, United States
| | - Jonathan Bones
- The National Institute for Bioprocessing Research and Training, Foster Avenue, Mount Merrion, Blackrock, Co., Dublin A94 X099, Ireland
- School of Chemical and Bioprocess Engineering, University College Dublin, Belfield, Dublin 4 D04 V1W8, Ireland
| | - Venkata S Tayi
- Process Research and Development, MRL, Merck & Co., Inc., Rahway, New Jersey 07065, United States
| | - Nicholas Abaroa
- Engineering, MRL, Merck & Co., Inc., Rahway, New Jersey 07065, United States
| | - Bhumit Patel
- Analytical Research and Development, MRL, Merck & Co., Inc., Rahway, New Jersey 07065, United States
| | - Emmanuel Appiah-Amponsah
- Analytical Research and Development, MRL, Merck & Co., Inc., Rahway, New Jersey 07065, United States
| | - Erik L Regalado
- Analytical Research and Development, MRL, Merck & Co., Inc., Rahway, New Jersey 07065, United States
| |
Collapse
|
17
|
Prasad R, Crouse SH, Rousseau RW, Grover MA. Quantifying Dense Multicomponent Slurries with In-Line ATR-FTIR and Raman Spectroscopies: A Hanford Case Study. Ind Eng Chem Res 2023; 62:15962-15973. [PMID: 37810994 PMCID: PMC10557100 DOI: 10.1021/acs.iecr.3c01249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2023] [Revised: 07/29/2023] [Accepted: 09/08/2023] [Indexed: 10/10/2023]
Abstract
The multiphase nature of slurries can make them difficult to process and monitor in real time. For example, the nuclear waste slurries present at the Hanford site in Washington State are multicomponent, multiphase, and inhomogeneous. Current analytical techniques for analyzing radioactive waste at Hanford rely on laboratory results from an on-site analytical laboratory, which can delay processing speed and create exposure risks for workers. However, in-line probes can provide an alternative route to collect the necessary composition information. In the present work, Raman spectroscopy and attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy are tested on simulants of nuclear waste slurries containing up to 23.2 wt % solids. We observe ATR-FTIR spectroscopy to be effective in measuring the solution phase of the studied slurry systems (3.52% mean percent error), while Raman spectroscopy provides information about the suspended solids in the slurry system (18.21% mean percent error). In-line measurement of multicomponent solids typical of nuclear waste processing has been previously unreported. The composition of both the solution and solid phases is vital in ensuring stable glass formulation and effective disposal of nuclear waste at Hanford. Raman and ATR-FTIR spectroscopies can provide a safer and faster alternative for acquiring compositional information on nuclear waste slurries.
Collapse
Affiliation(s)
| | | | - Ronald W. Rousseau
- School of Chemical and Biomolecular
Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Martha A. Grover
- School of Chemical and Biomolecular
Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| |
Collapse
|
18
|
Feng Báez JP, George De la Rosa MV, Alvarado-Hernández BB, Romañach RJ, Stelzer T. Evaluation of a compact composite sensor array for concentration monitoring of solutions and suspensions via multivariate analysis. J Pharm Biomed Anal 2023; 233:115451. [PMID: 37182364 PMCID: PMC10330539 DOI: 10.1016/j.jpba.2023.115451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 04/24/2023] [Accepted: 05/07/2023] [Indexed: 05/16/2023]
Abstract
Compact composite probes were identified as a priority to alleviate space constraints in miniaturized unit operations and pharmaceutical manufacturing platforms. Therefore, in this proof of principle study, a compact composite sensor array (CCSA) combining ultraviolet and near infrared features at four different wavelengths (280, 340, 600, 860 nm) in a 380 × 30 mm housing (length x diameter, 7 mm diameter at the probe head), was evaluated for its capabilities to monitor in situ concentration of solutions and suspensions via multivariate analysis using partial least squares (PLS) regression models. Four model active pharmaceutical ingredients (APIs): warfarin sodium isopropanol solvate (WS), lidocaine hydrochloride monohydrate (LID), 6-mercaptopurine monohydrate (6-MP), and acetaminophen (ACM) in their aqueous solution and suspension formulation were used for the assessment. The results demonstrate that PLS models can be applied for the CCSA prototype to measure the API concentrations with similar accuracy (validation samples within the United States Pharmacopeia (USP) limits), compared to univariate CCSA models and multivariate models for an established Raman spectrometer. Specifically, the multivariate CCSA models applied to the suspensions of 6-MP and ACM demonstrate improved accuracy of 63% and 31%, respectively, compared to the univariate CCSA models [1]. On the other hand, the PLS models for the solutions WS and LID showed a reduced accuracy compared to the univariate models [1].
Collapse
Affiliation(s)
- Jean P Feng Báez
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Puerto Rico, Medical Sciences Campus, San Juan, PR 00936, USA; Crystallization Design Institute, Molecular Sciences Research Center, University of Puerto Rico, San Juan, PR 00926, USA
| | - Mery Vet George De la Rosa
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Puerto Rico, Medical Sciences Campus, San Juan, PR 00936, USA; Crystallization Design Institute, Molecular Sciences Research Center, University of Puerto Rico, San Juan, PR 00926, USA
| | | | - Rodolfo J Romañach
- Department of Chemistry, University of Puerto Rico, Mayagüez Campus, Mayagüez, PR 00681, USA
| | - Torsten Stelzer
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Puerto Rico, Medical Sciences Campus, San Juan, PR 00936, USA; Crystallization Design Institute, Molecular Sciences Research Center, University of Puerto Rico, San Juan, PR 00926, USA.
| |
Collapse
|
19
|
Tian W, Li W, Yang H. Protein Nucleation and Crystallization Process with Process Analytical Technologies in a Batch Crystallizer. CRYSTAL GROWTH & DESIGN 2023; 23:5181-5193. [PMID: 37426550 PMCID: PMC10326882 DOI: 10.1021/acs.cgd.3c00411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 06/01/2023] [Indexed: 07/11/2023]
Abstract
Protein crystallization has drawn great attention to replacing the traditional downstream processing for protein-based pharmaceuticals due to its advantages in stability, storage, and delivery. Limited understanding of the protein crystallization processes requires essential information based on real-time tracking during the crystallization process. A batch crystallizer of 100 mL fitted with a focused beam reflectance measurement (FBRM) probe and a thermocouple was designed for in situ monitoring of the protein crystallization process, with simutaneously record of off-line concentrations and crystal images. Three stages in the protein batch crystallization process were identified: long-period slow nucleation, rapid crystallization, and slow growth and breakage. The induction time was estimated by FBRM, i.e., increasing numbers of particles in the solution, which could be half of the time required for detecting the decrease of the concentration, by offline measurement. The induction time decreased with an increase in supersaturation within the same salt concentration. The interfacial energy for nucleation was analyzed based on each experimental group with equal salt concentration and different concentrations of lysozyme. The interfacial energy reduced with an increase in salt concentration in the solution. The yield of the experiments was significantly affected by the protein and salt concentrations and could achieve up to 99% yield with a 26.5 μm median crystal size upon stabilized concentration readings.
Collapse
|
20
|
Remoto PIJG, Bērziņš K, Fraser-Miller SJ, Korter TM, Rades T, Rantanen J, Gordon KC. Exploring the Solid-State Landscape of Carbamazepine during Dehydration: A Low Frequency Raman Spectroscopy Perspective. Pharmaceutics 2023; 15:pharmaceutics15051526. [PMID: 37242768 DOI: 10.3390/pharmaceutics15051526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 05/08/2023] [Accepted: 05/10/2023] [Indexed: 05/28/2023] Open
Abstract
The solid-state landscape of carbamazepine during its dehydration was explored using Raman spectroscopy in the low- (-300 to -15, 15 to 300) and mid- (300 to 1800 cm-1) frequency spectral regions. Carbamazepine dihydrate and forms I, III, and IV were also characterized using density functional theory with periodic boundary conditions and showed good agreement with experimental Raman spectra with mean average deviations less than 10 cm-1. The dehydration of carbamazepine dihydrate was examined under different temperatures (40, 45, 50, 55, and 60 °C). Principal component analysis and multivariate curve resolution were used to explore the transformation pathways of different solid-state forms during the dehydration of carbamazepine dihydrate. The low-frequency Raman domain was able to detect the rapid growth and subsequent decline of carbamazepine form IV, which was not as effectively observed by mid-frequency Raman spectroscopy. These results showcased the potential benefits of low-frequency Raman spectroscopy for pharmaceutical process monitoring and control.
Collapse
Affiliation(s)
- Peter Iii J G Remoto
- The Dodd-Walls Centre for Photonic and Quantum Technologies, Department of Chemistry, University of Otago, Dunedin 9016, New Zealand
| | - Kārlis Bērziņš
- The Dodd-Walls Centre for Photonic and Quantum Technologies, Department of Chemistry, University of Otago, Dunedin 9016, New Zealand
| | - Sara J Fraser-Miller
- The Dodd-Walls Centre for Photonic and Quantum Technologies, Department of Chemistry, University of Otago, Dunedin 9016, New Zealand
| | - Timothy M Korter
- Department of Chemistry, Center for Science and Technology, Syracuse University, Syracuse, NY 13244, USA
| | - Thomas Rades
- Department of Pharmacy, Faculty of Health and Medical Sciences, University of Copenhagen, 2100 Copenhagen, Denmark
| | - Jukka Rantanen
- Department of Pharmacy, Faculty of Health and Medical Sciences, University of Copenhagen, 2100 Copenhagen, Denmark
| | - Keith C Gordon
- The Dodd-Walls Centre for Photonic and Quantum Technologies, Department of Chemistry, University of Otago, Dunedin 9016, New Zealand
| |
Collapse
|
21
|
Hara R, Kobayashi W, Yamanaka H, Murayama K, Shimoda S, Ozaki Y. Development of Raman Calibration Model Without Culture Data for In-Line Analysis of Metabolites in Cell Culture Media. APPLIED SPECTROSCOPY 2023; 77:521-533. [PMID: 36765462 DOI: 10.1177/00037028231160197] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
In this study, we developed a method to build Raman calibration models without culture data for cell culture monitoring. First, Raman spectra were collected and then analyzed for the signals of all the mentioned analytes: glucose, lactate, glutamine, glutamate, ammonia, antibody, viable cells, media, and feed agent. Using these spectral data, the specific peak positions and intensities for each factor were detected. Next, according to the design of the experiment method, samples were prepared by mixing the above-mentioned factors. Raman spectra of these samples were collected and were used to build calibration models. Several combinations of spectral pretreatments and wavenumber regions were compared to optimize the calibration model for cell culture monitoring without culture data. The accuracy of the developed calibration model was evaluated by performing actual cell culture and fitting the in-line measured spectra to the developed calibration model. As a result, the calibration model achieved sufficiently good accuracy for the three components, glucose, lactate, and antibody (root mean square errors of prediction, or RMSEP = 0.23, 0.29, and 0.20 g/L, respectively). This study has presented innovative results in developing a culture monitoring method without using culture data, while using a basic conventional method of investigating the Raman spectra of each component in the culture media and then utilizing a design of experiment approach.
Collapse
Affiliation(s)
- Risa Hara
- Department of Research and Development, Yokogawa Electric Corporation, Musashino, Japan
| | - Wataru Kobayashi
- Department of Life Business, Yokogawa Electric Corporation, Musashino, Japan
| | - Hiroaki Yamanaka
- Department of Life Business, Yokogawa Electric Corporation, Musashino, Japan
| | - Kodai Murayama
- Department of Research and Development, Yokogawa Electric Corporation, Musashino, Japan
| | - Soichiro Shimoda
- Department of Life Business, Yokogawa Electric Corporation, Musashino, Japan
| | - Yukihiro Ozaki
- School of Biological and Environmental Sciences, Kwansei Gakuin University, Sanda, Japan
| |
Collapse
|
22
|
Compact capillary high performance liquid chromatography system for pharmaceutical on-line reaction monitoring. Anal Chim Acta 2023; 1247:340903. [PMID: 36781255 DOI: 10.1016/j.aca.2023.340903] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 01/26/2023] [Accepted: 01/27/2023] [Indexed: 01/30/2023]
Abstract
Due to their size, conventional high performance liquid chromatographs (HPLCs) are difficult to place close to a reaction vessel within a pharmaceutical manufacturing or development site. Typically, long transfer lines are required to move sample from the reactor to the HPLC for analysis and high solvent usage is required. However, herein a compact and modular separation system has been developed to enable co-location of an HPLC with a small-scale reactor for reaction monitoring in the synthesis of active pharmaceutical ingredients. Using a framework based on capillary HPLC, a compact gradient separation system with a fully modular architecture is described. A custom miniature diode-array detector with a linear dynamic range (up to 1500 mAU at 210 nm) was integrated and evaluated for on-line reaction monitoring. In evaluating system suitability, average peak area %RSD of <3%, and an average retention time %RSD of <0.7%, were achieved. To demonstrate practical utility, the compact system was coupled directly to an on-line lab-scale flow through reactor for continuous reaction monitoring in the laboratory fume hood, where a study of the 3rd Bourne reaction was used to compare the performance of the compact system with a commercially available process HPLC instrument (Waters PATROL UPLC). Further, 33 off-line samples from a continuous crystallization reactor were analysed and it was found that the developed compact HPLC system showed equivalent quantitative performance to an Agilent 1290 Infinity II HPLC system.
Collapse
|
23
|
UV/VIS-Spectroscopic Inline Measurement for the Detection of Fouling Processes during the Polymerization of N-Vinylpyrrolidone. REACTIONS 2023. [DOI: 10.3390/reactions4010011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/05/2023] Open
Abstract
With the goal to better process the monitoring of occurring fouling, a backscatter probe was developed to perform in-line measurements in a half-shell reactor during the reaction of N-vinylpyrrolidone (NVP) to polyvinylpyrrolidone (PVP). The measurement technique detects the changes of bands in the UV range, which allows a direct correlation with the concentration. Thus, the measured absorbance signal allows a conclusion on the accumulation of fouling in the reactor and on changes in the conversion at the measurement location.
Collapse
|
24
|
Interpretable artificial neural networks for retrospective QbD of pharmaceutical tablet manufacturing based on a pilot-scale developmental dataset. Int J Pharm 2023; 633:122620. [PMID: 36669581 DOI: 10.1016/j.ijpharm.2023.122620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 01/12/2023] [Accepted: 01/13/2023] [Indexed: 01/19/2023]
Abstract
As the pharmaceutical industry increasingly adopts the Pharma 4.0. concept, there is a growing need to effectively predict the product quality based on manufacturing or in-process data. Although artificial neural networks (ANNs) have emerged as powerful tools in data-rich environments, their implementation in pharmaceutical manufacturing is hindered by their black-box nature. In this work, ANNs were developed and interpreted to demonstrate their applicability to increase process understanding by retrospective analysis of developmental or manufacturing data. The in vitro dissolution and hardness of extended-release, directly compressed tablets were predicted from manufacturing and spectroscopic data of pilot-scale development. The ANNs using material attributes and operational parameters provided better results than using NIR or Raman spectra as predictors. ANNs were interpreted by sensitivity analysis, helping to identify the root cause of the batch-to-batch variability, e.g., the variability in particle size, grade, or substitution of the hydroxypropyl methylcellulose excipient. An ANN-based control strategy was also successfully utilized to mitigate the batch-to-batch variability by flexibly operating the tableting process. The presented methodology can be adapted to arbitrary data-rich manufacturing steps from active substance synthesis to formulation to predict the quality from manufacturing or development data and gain process understanding and consistent product quality.
Collapse
|
25
|
Machine learning and metabolic modelling assisted implementation of a novel process analytical technology in cell and gene therapy manufacturing. Sci Rep 2023; 13:834. [PMID: 36646795 PMCID: PMC9842697 DOI: 10.1038/s41598-023-27998-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Accepted: 01/11/2023] [Indexed: 01/18/2023] Open
Abstract
Process analytical technology (PAT) has demonstrated huge potential to enable the development of improved biopharmaceutical manufacturing processes by ensuring the reliable provision of quality products. However, the complexities associated with the manufacture of advanced therapy medicinal products have resulted in a slow adoption of PAT tools into industrial bioprocessing operations, particularly in the manufacture of cell and gene therapy products. Here we describe the applicability of a novel refractometry-based PAT system (Ranger system), which was used to monitor the metabolic activity of HEK293T cell cultures during lentiviral vector (LVV) production processes in real time. The PAT system was able to rapidly identify a relationship between bioreactor pH and culture metabolic activity and this was used to devise a pH operating strategy that resulted in a 1.8-fold increase in metabolic activity compared to an unoptimised bioprocess in a minimal number of bioreactor experiments; this was achieved using both pre-programmed and autonomous pH control strategies. The increased metabolic activity of the cultures, achieved via the implementation of the PAT technology, was not associated with increased LVV production. We employed a metabolic modelling strategy to elucidate the relationship between these bioprocess level events and HEK293T cell metabolism. The modelling showed that culturing of HEK293T cells in a low pH (pH 6.40) environment directly impacted the intracellular maintenance of pH and the intracellular availability of oxygen. We provide evidence that the elevated metabolic activity was a response to cope with the stress associated with low pH to maintain the favourable intracellular conditions, rather than being indicative of a superior active state of the HEK293T cell culture resulting in enhanced LVV production. Forecasting strategies were used to construct data models which identified that the novel PAT system not only had a direct relationship with process pH but also with oxygen availability; the interaction and interdependencies between these two parameters had a direct effect on the responses observed at the bioprocess level. We present data which indicate that process control and intervention using this novel refractometry-based PAT system has the potential to facilitate the fine tuning and rapid optimisation of the production environment and enable adaptive process control for enhanced process performance and robustness.
Collapse
|
26
|
Simone E, Beveridge G, Sillers P, Webb J, George N, Hone J. Analysis of the Dissolution and Crystallization of Partly Immiscible Ternary Mixtures Using a Composite Sensor Array of In Situ ATR-FTIR, Laser Backscattering, and Imaging. Ind Eng Chem Res 2022. [DOI: 10.1021/acs.iecr.2c03494] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- Elena Simone
- Department of Applied Science and Technology, Politecnico di Torino, Torino 10129, Italy
- Food Colloids and Bioprocessing Group, School of Food Science and Nutrition, University of Leeds, Leeds LS29JT, United Kingdom
| | - Gillian Beveridge
- Syngenta Grangemouth Manufacturing Centre, Grangemouth FK3 8XG, United Kingdom
| | - Pauline Sillers
- Syngenta Grangemouth Manufacturing Centre, Grangemouth FK3 8XG, United Kingdom
| | - Jennifer Webb
- Syngenta Jealott’s Hill International Research Centre, Warfield, Bracknell RG42 6EY, United Kingdom
| | - Neil George
- Syngenta Jealott’s Hill International Research Centre, Warfield, Bracknell RG42 6EY, United Kingdom
- School of Chemical and Process Engineering, University of Leeds, Leeds LS29JT, United Kingdom
| | - John Hone
- Syngenta Jealott’s Hill International Research Centre, Warfield, Bracknell RG42 6EY, United Kingdom
| |
Collapse
|
27
|
Duong-Trung N, Born S, Kim JW, Schermeyer MT, Paulick K, Borisyak M, Cruz-Bournazou MN, Werner T, Scholz R, Schmidt-Thieme L, Neubauer P, Martinez E. When Bioprocess Engineering Meets Machine Learning: A Survey from the Perspective of Automated Bioprocess Development. Biochem Eng J 2022. [DOI: 10.1016/j.bej.2022.108764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
|
28
|
Stubbs S, Yousaf S, Khan I. A review on the synthesis of bio-based surfactants using green chemistry principles. Daru 2022; 30:407-426. [PMID: 36190619 PMCID: PMC9715898 DOI: 10.1007/s40199-022-00450-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Accepted: 08/14/2022] [Indexed: 06/16/2023] Open
Abstract
OBJECTIVES With increasing awareness of the potential adverse impact of conventional surfactants on the environment and human health, there is mounting interest in the development of bio-based surfactants (which are deemed to be safer, more affordable, are in abundance, are biodegradable, biocompatible and possess scalability, mildness and performance in formulation) in personal care products. METHOD A comprehensive literature review around alkyl polyglucosides (APGs) and sucrose esters (SEs) as bio-based surfactants, through the lens of the 12 green chemistry principles was conducted. An overview of the use of bio-based surfactants in personal care products was also provided. RESULTS Bio-based surfactants are derived primarily from natural sources (i.e. both the head and tail molecular group). One of the more common types of bio-based surfactants are those with carbohydrate head groups, where alkyl polyglucosides (APGs) and sucrose esters (SEs) lead this sub-category. As global regulations and user mandate for sustainability and safety increase, evidence to further support these bio-based surfactants as alternatives to their petrochemical counterparts is advantageous. Use of the green chemistry framework is a suitable way to do this. While many of the discussed principles are enforced industrially, others have only yet been applied at a laboratory scale or are not apparent in literature. CONCLUSION Many of the principles of green chemistry are currently used in the synthesis of APGs and SEs. These and other bio-based surfactants should, therefore, be considered suitable and sustainable alternatives to conventional surfactants. To further encourage the use of these novel surfactants, industry must make an effort to implement and improve the use of the remaining principles at a commercial level.
Collapse
Affiliation(s)
- Shea Stubbs
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Liverpool, L3 3AF, UK
| | - Sakib Yousaf
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Liverpool, L3 3AF, UK
| | - Iftikhar Khan
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Liverpool, L3 3AF, UK.
| |
Collapse
|
29
|
Kaisin G, Bovy L, Joyard Y, Maindron N, Tadino V, Monbaliu JCM. A perspective on automated advanced continuous flow manufacturing units for the upgrading of biobased chemicals toward pharmaceuticals. J Flow Chem 2022; 13:1-15. [PMID: 36467977 PMCID: PMC9707424 DOI: 10.1007/s41981-022-00247-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Accepted: 11/04/2022] [Indexed: 11/30/2022]
Abstract
Biomass is a renewable, almost infinite reservoir of a large diversity of highly functionalized chemicals. The conversion of biomass toward biobased platform molecules through biorefineries generally still lacks economic viability. Profitability could be enhanced through the development of new market opportunities for these biobased platform chemicals. The fine chemical industry, and more specifically the manufacturing of pharmaceuticals is one of the sectors bearing significant potential for these biobased building blocks to rapidly emerge and make a difference. There are, however, still many challenges to be dealt with before this market can thrive. Continuous flow technology and its integration for the upgrading of biobased platform molecules for the manufacturing of pharmaceuticals is foreseen as a game-changer. This perspective reflects on the main challenges relative to chemical, process, regulatory and supply chain-related burdens still to be addressed. The implementation of integrated continuous flow processes and their automation into modular units will help for tackling with these challenges. Graphical abstract
Collapse
Affiliation(s)
- Geoffroy Kaisin
- SynLock SRL, Rue de la Vieille Sambre 153, B-5190 Jemeppe-sur-Sambre, Belgium
| | - Loïc Bovy
- Center for Integrated Technology and Organic Synthesis, Research Unit MolSys, University of Liège, B-4000 Liège, Sart Tilman, Belgium
| | - Yoann Joyard
- SynLock SRL, Rue de la Vieille Sambre 153, B-5190 Jemeppe-sur-Sambre, Belgium
| | - Nicolas Maindron
- SynLock SRL, Rue de la Vieille Sambre 153, B-5190 Jemeppe-sur-Sambre, Belgium
| | - Vincent Tadino
- SynLock SRL, Rue de la Vieille Sambre 153, B-5190 Jemeppe-sur-Sambre, Belgium
| | - Jean-Christophe M. Monbaliu
- Center for Integrated Technology and Organic Synthesis, Research Unit MolSys, University of Liège, B-4000 Liège, Sart Tilman, Belgium
| |
Collapse
|
30
|
Chong MWS, McGlone T, Chai CY, Briggs NEB, Brown CJ, Perciballi F, Dunn J, Parrott AJ, Dallin P, Andrews J, Nordon A, Florence AJ. Temperature Correction of Spectra to Improve Solute Concentration Monitoring by In Situ Ultraviolet and Mid-Infrared Spectrometries toward Isothermal Local Model Performance. Org Process Res Dev 2022; 26:3096-3105. [DOI: 10.1021/acs.oprd.2c00238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Indexed: 11/06/2022]
Affiliation(s)
- Magdalene W. S. Chong
- EPSRC Future Continuous Manufacturing and Advanced Crystallisation Research Hub, University of Strathclyde, 99 George Street, Glasgow G1 1RD, U.K
- WestCHEM, Department of Pure and Applied Chemistry, and Centre for Process Analytics and Control Technology (CPACT), University of Strathclyde, 295 Cathedral Street, Glasgow G1 1XL, U.K
| | - Thomas McGlone
- EPSRC Future Continuous Manufacturing and Advanced Crystallisation Research Hub, University of Strathclyde, 99 George Street, Glasgow G1 1RD, U.K
| | - Ching Yee Chai
- EPSRC Centre for Innovative Manufacturing in Continuous Manufacturing and Crystallisation, Strathclyde Institute of Pharmacy and Biomedical Sciences, Technology and Innovation Centre, University of Strathclyde, 99 George Street, Glasgow G1 1RD, U.K
| | - Naomi E. B. Briggs
- EPSRC Centre for Innovative Manufacturing in Continuous Manufacturing and Crystallisation, Strathclyde Institute of Pharmacy and Biomedical Sciences, Technology and Innovation Centre, University of Strathclyde, 99 George Street, Glasgow G1 1RD, U.K
| | - Cameron J. Brown
- EPSRC Future Continuous Manufacturing and Advanced Crystallisation Research Hub, University of Strathclyde, 99 George Street, Glasgow G1 1RD, U.K
| | - Francesca Perciballi
- EPSRC Centre for Innovative Manufacturing in Continuous Manufacturing and Crystallisation, Strathclyde Institute of Pharmacy and Biomedical Sciences, Technology and Innovation Centre, University of Strathclyde, 99 George Street, Glasgow G1 1RD, U.K
| | - Jaclyn Dunn
- WestCHEM, Department of Pure and Applied Chemistry, and Centre for Process Analytics and Control Technology (CPACT), University of Strathclyde, 295 Cathedral Street, Glasgow G1 1XL, U.K
- EPSRC Centre for Innovative Manufacturing in Continuous Manufacturing and Crystallisation, Strathclyde Institute of Pharmacy and Biomedical Sciences, Technology and Innovation Centre, University of Strathclyde, 99 George Street, Glasgow G1 1RD, U.K
| | - Andrew J. Parrott
- WestCHEM, Department of Pure and Applied Chemistry, and Centre for Process Analytics and Control Technology (CPACT), University of Strathclyde, 295 Cathedral Street, Glasgow G1 1XL, U.K
| | - Paul Dallin
- Clairet Scientific, 17/18 Scirocco Close, Moulton Park Industrial Estate, Northampton NN3 6AP, U.K
| | - John Andrews
- Clairet Scientific, 17/18 Scirocco Close, Moulton Park Industrial Estate, Northampton NN3 6AP, U.K
| | - Alison Nordon
- EPSRC Future Continuous Manufacturing and Advanced Crystallisation Research Hub, University of Strathclyde, 99 George Street, Glasgow G1 1RD, U.K
- WestCHEM, Department of Pure and Applied Chemistry, and Centre for Process Analytics and Control Technology (CPACT), University of Strathclyde, 295 Cathedral Street, Glasgow G1 1XL, U.K
| | - Alastair J. Florence
- EPSRC Future Continuous Manufacturing and Advanced Crystallisation Research Hub, University of Strathclyde, 99 George Street, Glasgow G1 1RD, U.K
| |
Collapse
|
31
|
Gyürkés M, Madarász L, Záhonyi P, Köte Á, Nagy B, Pataki H, Nagy ZK, Domokos A, Farkas A. Soft sensor for content prediction in an integrated continuous pharmaceutical formulation line based on the residence time distribution of unit operations. Int J Pharm 2022; 624:121950. [PMID: 35753540 DOI: 10.1016/j.ijpharm.2022.121950] [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: 03/31/2022] [Revised: 06/14/2022] [Accepted: 06/20/2022] [Indexed: 12/01/2022]
Abstract
In this study, a concentration predicting soft sensor was achieved based on the Residence Time Distribution (RTD) of an integrated, three-step pharmaceutical formulation line. The RTD was investigated with color-based tracer experiments using image analysis. Twin-screw wet granulation (TSWG) was directly coupled with a horizontal fluid bed dryer and an oscillating mill. Based on integrated measurement, we proved that it is also possible to couple the unit operations in silico. Three surrogate tracers were produced with a coloring agent to investigate the separated unit operations and the solid and liquid inputs of the TSWG. The soft sensor's prediction was compared to validating experiments of a 0.05 mg/g (15% of the nominal) concentration change with High-Performance Liquid Chromatography (HPLC) reference measurements of the active ingredient proving the adequacy of the soft sensor (RMSE < 4%).
Collapse
Affiliation(s)
- Martin Gyürkés
- Department of Organic Chemistry and Technology, Budapest University of Technology and Economics, Műegyetem rkp. 3., H-1111 Budapest, Hungary
| | - Lajos Madarász
- Department of Organic Chemistry and Technology, Budapest University of Technology and Economics, Műegyetem rkp. 3., H-1111 Budapest, Hungary
| | - Petra Záhonyi
- Department of Organic Chemistry and Technology, Budapest University of Technology and Economics, Műegyetem rkp. 3., H-1111 Budapest, Hungary
| | - Ákos Köte
- Department of Organic Chemistry and Technology, Budapest University of Technology and Economics, Műegyetem rkp. 3., H-1111 Budapest, Hungary
| | - Brigitta Nagy
- Department of Organic Chemistry and Technology, Budapest University of Technology and Economics, Műegyetem rkp. 3., H-1111 Budapest, Hungary
| | - Hajnalka Pataki
- Department of Organic Chemistry and Technology, Budapest University of Technology and Economics, Műegyetem rkp. 3., H-1111 Budapest, Hungary
| | - Zsombor Kristóf Nagy
- Department of Organic Chemistry and Technology, Budapest University of Technology and Economics, Műegyetem rkp. 3., H-1111 Budapest, Hungary
| | - András Domokos
- Department of Organic Chemistry and Technology, Budapest University of Technology and Economics, Műegyetem rkp. 3., H-1111 Budapest, Hungary
| | - Attila Farkas
- Department of Organic Chemistry and Technology, Budapest University of Technology and Economics, Műegyetem rkp. 3., H-1111 Budapest, Hungary
| |
Collapse
|
32
|
Gaudreault J, Durocher Y, Henry O, De Crescenzo G. Multi-temperature experiments to ease analysis of heterogeneous binder solutions by surface plasmon resonance biosensing. Sci Rep 2022; 12:14401. [PMID: 36002549 PMCID: PMC9402583 DOI: 10.1038/s41598-022-18450-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Accepted: 08/11/2022] [Indexed: 11/09/2022] Open
Abstract
Surface Plasmon Resonance (SPR) biosensing is a well-established tool for the investigation of binding kinetics between a soluble species and an immobilized (bio)molecule. While robust and accurate data analysis techniques are readily available for single species, methods to exploit data collected with a solution containing multiple interactants are scarce. In a previous study, our group proposed two data analysis algorithms for (1) the precise and reliable identification of the kinetic parameters of N interactants present at different ratios in N mixtures and (2) the estimation of the composition of a given mixture, assuming that the kinetic parameters and the total concentration of all interactants are known. Here, we extend the first algorithm by reducing the number of necessary mixtures. This is achieved by conducting experiments at different temperatures. Through the Van't Hoff and Eyring equations, identifying the kinetic and thermodynamic parameters of N binders becomes possible with M mixtures with M comprised between 2 and N and at least N/M temperatures. The second algorithm is improved by adding the total analyte concentration as a supplementary variable to be identified in an optimization routine. We validated our analysis framework experimentally with a system consisting of mixtures of low molecular weight drugs, each competing to bind to an immobilized protein. We believe that the analysis of mixtures and composition estimation could pave the way for SPR biosensing to become a bioprocess monitoring tool, on top of expanding its already substantial role in drug discovery and development.
Collapse
Affiliation(s)
- Jimmy Gaudreault
- Department of Chemical Engineering, Polytechnique Montréal, Centre-Ville Station, P.O. Box 6079, Montreal, QC, H3C 3A7, Canada
| | - Yves Durocher
- Life Sciences, NRC Human Health Therapeutics Portfolio, Building Montreal-Royalmount, National Research Council Canada, Montreal, QC, H4P 2R2, Canada
| | - Olivier Henry
- Department of Chemical Engineering, Polytechnique Montréal, Centre-Ville Station, P.O. Box 6079, Montreal, QC, H3C 3A7, Canada.
| | - Gregory De Crescenzo
- Department of Chemical Engineering, Polytechnique Montréal, Centre-Ville Station, P.O. Box 6079, Montreal, QC, H3C 3A7, Canada.
| |
Collapse
|
33
|
Mishra P, Xu J, Liland KH, Tran T. META-PLS modelling: An integrated approach to automatic model optimization for near-infrared spectra. Anal Chim Acta 2022; 1221:340142. [DOI: 10.1016/j.aca.2022.340142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Revised: 06/28/2022] [Accepted: 06/30/2022] [Indexed: 11/01/2022]
|
34
|
Ralbovsky NM, Smith JP. Process analytical technology and its recent applications for asymmetric synthesis. Talanta 2022; 252:123787. [DOI: 10.1016/j.talanta.2022.123787] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Accepted: 07/25/2022] [Indexed: 11/27/2022]
|
35
|
Bowler AL, Pound MP, Watson NJ. A review of ultrasonic sensing and machine learning methods to monitor industrial processes. ULTRASONICS 2022; 124:106776. [PMID: 35653984 DOI: 10.1016/j.ultras.2022.106776] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Revised: 04/29/2022] [Accepted: 05/26/2022] [Indexed: 06/15/2023]
Abstract
Supervised machine learning techniques are increasingly being combined with ultrasonic sensor measurements owing to their strong performance. These techniques also offer advantages over calibration procedures of more complex fitting, improved generalisation, reduced development time, ability for continuous retraining, and the correlation of sensor data to important process information. However, their implementation requires expertise to extract and select appropriate features from the sensor measurements as model inputs, select the type of machine learning algorithm to use, and find a suitable set of model hyperparameters. The aim of this article is to facilitate implementation of machine learning techniques in combination with ultrasonic measurements for in-line and on-line monitoring of industrial processes and other similar applications. The article first reviews the use of ultrasonic sensors for monitoring processes, before reviewing the combination of ultrasonic measurements and machine learning. We include literature from other sectors such as structural health monitoring. This review covers feature extraction, feature selection, algorithm choice, hyperparameter selection, data augmentation, domain adaptation, semi-supervised learning and machine learning interpretability. Finally, recommendations for applying machine learning to the reviewed processes are made.
Collapse
Affiliation(s)
- Alexander L Bowler
- Food, Water, Waste Research Group, Faculty of Engineering, University of Nottingham, University Park, Nottingham NG7 2RD, UK
| | - Michael P Pound
- School of Computer Science, Jubilee Campus, University of Nottingham, Nottingham NG8 1BB, UK
| | - Nicholas J Watson
- Food, Water, Waste Research Group, Faculty of Engineering, University of Nottingham, University Park, Nottingham NG7 2RD, UK.
| |
Collapse
|
36
|
Casian T, Nagy B, Kovács B, Galata DL, Hirsch E, Farkas A. Challenges and Opportunities of Implementing Data Fusion in Process Analytical Technology-A Review. Molecules 2022; 27:4846. [PMID: 35956791 PMCID: PMC9369811 DOI: 10.3390/molecules27154846] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 07/20/2022] [Accepted: 07/22/2022] [Indexed: 12/03/2022] Open
Abstract
The release of the FDA's guidance on Process Analytical Technology has motivated and supported the pharmaceutical industry to deliver consistent quality medicine by acquiring a deeper understanding of the product performance and process interplay. The technical opportunities to reach this high-level control have considerably evolved since 2004 due to the development of advanced analytical sensors and chemometric tools. However, their transfer to the highly regulated pharmaceutical sector has been limited. To this respect, data fusion strategies have been extensively applied in different sectors, such as food or chemical, to provide a more robust performance of the analytical platforms. This survey evaluates the challenges and opportunities of implementing data fusion within the PAT concept by identifying transfer opportunities from other sectors. Special attention is given to the data types available from pharmaceutical manufacturing and their compatibility with data fusion strategies. Furthermore, the integration into Pharma 4.0 is discussed.
Collapse
Affiliation(s)
- Tibor Casian
- Department of Pharmaceutical Technology and Biopharmacy, “Iuliu Hatieganu” University of Medicine and Pharmacy, 400012 Cluj-Napoca, Romania;
| | - Brigitta Nagy
- Department of Organic Chemistry and Technology, Budapest University of Technology and Economics, H-1111 Budapest, Hungary; (D.L.G.); (E.H.); (A.F.)
| | - Béla Kovács
- Department of Biochemistry and Environmental Chemistry, George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Târgu Mureș, 540139 Târgu Mureș, Romania;
| | - Dorián László Galata
- Department of Organic Chemistry and Technology, Budapest University of Technology and Economics, H-1111 Budapest, Hungary; (D.L.G.); (E.H.); (A.F.)
| | - Edit Hirsch
- Department of Organic Chemistry and Technology, Budapest University of Technology and Economics, H-1111 Budapest, Hungary; (D.L.G.); (E.H.); (A.F.)
| | - Attila Farkas
- Department of Organic Chemistry and Technology, Budapest University of Technology and Economics, H-1111 Budapest, Hungary; (D.L.G.); (E.H.); (A.F.)
| |
Collapse
|
37
|
Xiouras C, Cameli F, Quilló GL, Kavousanakis ME, Vlachos DG, Stefanidis GD. Applications of Artificial Intelligence and Machine Learning Algorithms to Crystallization. Chem Rev 2022; 122:13006-13042. [PMID: 35759465 DOI: 10.1021/acs.chemrev.2c00141] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Artificial intelligence and specifically machine learning applications are nowadays used in a variety of scientific applications and cutting-edge technologies, where they have a transformative impact. Such an assembly of statistical and linear algebra methods making use of large data sets is becoming more and more integrated into chemistry and crystallization research workflows. This review aims to present, for the first time, a holistic overview of machine learning and cheminformatics applications as a novel, powerful means to accelerate the discovery of new crystal structures, predict key properties of organic crystalline materials, simulate, understand, and control the dynamics of complex crystallization process systems, as well as contribute to high throughput automation of chemical process development involving crystalline materials. We critically review the advances in these new, rapidly emerging research areas, raising awareness in issues such as the bridging of machine learning models with first-principles mechanistic models, data set size, structure, and quality, as well as the selection of appropriate descriptors. At the same time, we propose future research at the interface of applied mathematics, chemistry, and crystallography. Overall, this review aims to increase the adoption of such methods and tools by chemists and scientists across industry and academia.
Collapse
Affiliation(s)
- Christos Xiouras
- Chemical Process R&D, Crystallization Technology Unit, Janssen R&D, Turnhoutseweg 30, 2340 Beerse, Belgium
| | - Fabio Cameli
- Department of Chemical and Biomolecular Engineering, University of Delaware, 150 Academy Street, Newark, Delaware 19716, United States
| | - Gustavo Lunardon Quilló
- Chemical Process R&D, Crystallization Technology Unit, Janssen R&D, Turnhoutseweg 30, 2340 Beerse, Belgium.,Chemical and BioProcess Technology and Control, Department of Chemical Engineering, Faculty of Engineering Technology, KU Leuven, Gebroeders de Smetstraat 1, 9000 Ghent, Belgium
| | - Mihail E Kavousanakis
- School of Chemical Engineering, National Technical University of Athens, Heroon Polytechniou 9, 15780 Zografou, Greece
| | - Dionisios G Vlachos
- Department of Chemical and Biomolecular Engineering, University of Delaware, 150 Academy Street, Newark, Delaware 19716, United States
| | - Georgios D Stefanidis
- School of Chemical Engineering, National Technical University of Athens, Heroon Polytechniou 9, 15780 Zografou, Greece.,Laboratory for Chemical Technology, Ghent University; Tech Lane Ghent Science Park 125, B-9052 Ghent, Belgium
| |
Collapse
|
38
|
Real-time coating thickness measurement and defect recognition of film coated tablets with machine vision and deep learning. Int J Pharm 2022; 623:121957. [PMID: 35760260 DOI: 10.1016/j.ijpharm.2022.121957] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Revised: 06/20/2022] [Accepted: 06/21/2022] [Indexed: 11/22/2022]
Abstract
This paper presents a system, where images acquired with a digital camera are coupled with image analysis and deep learning to identify and categorize film coating defects and to measure the film coating thickness of tablets. There were 5 different classes of defective tablets, and the YOLOv5 algorithm was utilized to recognize defects, the accuracy of the classification was 98.2%. In order to characterize coating thickness, the diameter of the tablets in pixels was measured, which was used to measure the coating thickness of the tablets. The proposed system can be easily scaled up to match the production capability of continuous film coaters. With the developed technique, the complete screening of the produced tablets can be achieved in real-time resulting in the improvement of quality control.
Collapse
|
39
|
Sørensen DH, Christensen NPA, Skibsted E, Rantanen J, Rinnan Å. In-line fluorescence spectroscopy for quantification of low amount of active pharmaceutical ingredient. J Pharm Sci 2022; 111:2406-2410. [PMID: 35724737 DOI: 10.1016/j.xphs.2022.06.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 05/25/2022] [Accepted: 06/08/2022] [Indexed: 11/25/2022]
Abstract
The pharmaceutical industry is currently implementing new manufacturing principles and modernizing the related processing solutions. A key element in this development is implementation of process analytical technologies (PAT) for measuring product quality in a real-time mode, ideally for a continuously operating processing line. Near-infrared (NIR) spectroscopy is widely used for this purpose, but has limited use for low concentration formulations, due to its inherent detection limit. Light-induced fluorescence (LIF) spectroscopy is a PAT tool that can be used to quantify low concentrations of active pharmaceutical ingredient, and recent development of instrumentation has made it available for in-line applications. In this study, the content of tryptophan in a dynamic powder flow could be measured as low as 0.10 w/w % with LIF spectroscopy with good accuracy of RMSEP = 0.008 w/w %. Both partial least squares regression and support vector machines (SVM) were investigated, but we found SVM to be the better option due to non-linearities between the calibration test and the in-line measurements. With the use of SVM, LIF spectroscopy is a promising candidate for low concentration applications where NIR is not suitable.
Collapse
Affiliation(s)
| | | | - Erik Skibsted
- Novo Nordisk A/S, Department Oral Protein Formulation, 2760 Måløv, Denmark
| | - Jukka Rantanen
- Department of Pharmacy, Faculty of Health and Medical Sciences, University of Copenhagen, 2100 Copenhagen, Denmark
| | - Åsmund Rinnan
- Department of Food Science, Faculty of Science, University of Copenhagen, 1958 Frederiksberg C, Denmark.
| |
Collapse
|
40
|
Coliaie P, Prajapati A, Ali R, Boukerche M, Korde A, Kelkar MS, Nere NK, Singh MR. In-line measurement of liquid-liquid phase separation boundaries using a turbidity-sensor-integrated continuous-flow microfluidic device. LAB ON A CHIP 2022; 22:2299-2306. [PMID: 35451445 DOI: 10.1039/d1lc01112j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Liquid-liquid phase separation (LLPS), also known as oiling-out, is the appearance of the second liquid phase preceding the crystallization. LLPS is an undesirable phenomenon that can occur during the crystallization of active pharmaceutical ingredients (APIs), proteins, and polymers. It is typically avoided during crystallization due to its detrimental impacts on crystalline products due to lowered crystallization rate, the inclusion of impurities, and alteration in particle morphology and size distribution. In situ monitoring of phase separation enables investigating LLPS and identifying the phase separation boundaries. Various process analytical technologies (PATs) have been implemented to determine the LLPS boundaries prior to crystallization to prevent oiling out of compounds. The LLPS measurements using PATs can be time-consuming, expensive, and challenging. Here, we have implemented a fully integrated continuous-flow microfluidic device with a turbidity sensor to quickly and accurately evaluate the LLPS boundaries for a β-alanine, water, and IPA mixture. The turbidity-sensor-integrated continuous-flow microfluidic device is also placed under an optical microscope to visually track and record the appearance and disappearance of oil droplets. Streams of an aqueous solution of β-alanine, pure solvent (water), and pure antisolvent (IPA or ethanol) are pumped into the continuous-flow microfluidic device at various flow rates to obtain the compositions at which the solution becomes turbid. The onset of turbidity is measured using a custom-designed, in-line turbidity sensor. The LLPS boundaries can be estimated using the turbidity-sensor-integrated microfluidic device in less than 30 min, which will significantly improve and enhance the workflow of the pharmaceutical drug (or crystalline material) development process.
Collapse
Affiliation(s)
- Paria Coliaie
- Department of Chemical Engineering, University of Illinois Chicago, 929 W. Taylor St., Chicago, IL 60607, USA.
| | - Aditya Prajapati
- Department of Chemical Engineering, University of Illinois Chicago, 929 W. Taylor St., Chicago, IL 60607, USA.
| | - Rabia Ali
- Department of Chemical Engineering, University of Illinois Chicago, 929 W. Taylor St., Chicago, IL 60607, USA.
| | - Moussa Boukerche
- Center of Excellence for Isolation & Separation Technologies (CoExIST), Process R&D, AbbVie Inc., North Chicago, IL 60064, USA
| | - Akshay Korde
- Center of Excellence for Isolation & Separation Technologies (CoExIST), Process R&D, AbbVie Inc., North Chicago, IL 60064, USA
| | - Manish S Kelkar
- Center of Excellence for Isolation & Separation Technologies (CoExIST), Process R&D, AbbVie Inc., North Chicago, IL 60064, USA
| | - Nandkishor K Nere
- Department of Chemical Engineering, University of Illinois Chicago, 929 W. Taylor St., Chicago, IL 60607, USA.
- Center of Excellence for Isolation & Separation Technologies (CoExIST), Process R&D, AbbVie Inc., North Chicago, IL 60064, USA
| | - Meenesh R Singh
- Department of Chemical Engineering, University of Illinois Chicago, 929 W. Taylor St., Chicago, IL 60607, USA.
| |
Collapse
|
41
|
NIR spectroscopy for reaction monitoring and reaction mixture identification of cycloaliphatic epoxides. JOURNAL OF POLYMER RESEARCH 2022. [DOI: 10.1007/s10965-022-03038-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
AbstractThe industrially relevant cycloaliphatic epoxides do not have a directly distinguishable band in the NIR spectrum and their polymerisation conversion has so far typically been estimated via the simultaneous polymerisation of vinyl ethers. Here, an analytical procedure is presented for the quantitative inline analysis of 4-epoxycyclohexyl methyl-3,4-epoxycyclohexane carboxylate without the need to mix cycloaliphatic epoxides with vinyl ethers. By employing multivariate data analysis on the reaction spectra, the conversion could be analysed spectroscopically. This resulted in a mean uncertainty of 3.38% conversion in the range between 0 and 40% conversion. In addition, a deviation from the initial monomer concentration of 5 w% over a temperature range of 100 °C can be detected and identified via principal component analysis.
Collapse
|
42
|
Mishra P, Liland KH. Swiss knife partial least squares (SKPLS): One tool for modelling single block, multiblock, multiway, multiway multiblock including multi-responses and meta information under the ROSA framework. Anal Chim Acta 2022; 1206:339786. [DOI: 10.1016/j.aca.2022.339786] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2022] [Revised: 03/25/2022] [Accepted: 03/28/2022] [Indexed: 11/01/2022]
|
43
|
Aničić N, Smrdel P, Kitak D, Morožin T, Jaklič M, Usenik P, Vidovič S. Applicability of Image Analysis to Support QbD driven Development of Pellets. Drug Dev Ind Pharm 2022; 47:1794-1808. [PMID: 35389314 DOI: 10.1080/03639045.2022.2063880] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Objective The stages of preparing high drug loaded pellets were investigated using static and dynamic imaging techniques to provide a greater understanding and ease the scale up process. Significance: An example of a real case laboratory and production scale Quality by design (QbD) based development of pellets is demonstrated. Potential Process analytical technology (PAT) approaches by dynamic image analysis (DIA) are presented in various process phases. Methods: Pellets were prepared at laboratory and production scale (high shear granulation, extrusion/spheronization, drying, coating). The influence of process parameters on pellet properties (aspect ratio, yield, pellet size, and their distribution) was investigated using static and dynamic image analysis. During coating, we focused on the coating thickness and identification of potential agglomeration. Results and conclusions: The effects of kneading time, amount of water, extrusion screen plate (ESP) opening diameter and thickness on pellet properties were confirmed in accordance with literature. In terms of screw speed, spheronization speed and time, no considerable influence on pellet properties was observed in the range of studied process parameters, thereby confirming the design space. . In addition to the ESP thickness and opening diameter, quality of the ESP impacts the pellet properties. Lastly, coating thickness measurements with dynamic and static image analysis were comparable and an exemplary case of in-line agglomeration detection was presented. Real time evaluation with PATVIS APA is an effective PAT tool for the evaluation of spheronization (pellet size distribution, aspect ratio, yield) and coating (coating thickness, agglomeration detection).
Collapse
Affiliation(s)
- Nemanja Aničić
- Lek Pharmaceuticals d.d., Verovškova 57, Ljubljana, Slovenia
| | - Polona Smrdel
- Lek Pharmaceuticals d.d., Verovškova 57, Ljubljana, Slovenia
| | - Domen Kitak
- Sensum, Computer Vision Systems d.o.o., Tehnološki park 21, Ljubljana, Slovenia
| | - Teo Morožin
- Lek Pharmaceuticals d.d., Verovškova 57, Ljubljana, Slovenia
| | - Miha Jaklič
- Lek Pharmaceuticals d.d., Verovškova 57, Ljubljana, Slovenia
| | - Peter Usenik
- Sensum, Computer Vision Systems d.o.o., Tehnološki park 21, Ljubljana, Slovenia
| | - Sara Vidovič
- Lek Pharmaceuticals d.d., Verovškova 57, Ljubljana, Slovenia.,Faculty of Pharmacy, University of Ljubljana, Aškerčeva 7, Ljubljana, Slovenia
| |
Collapse
|
44
|
Ihling N, Munkler LP, Paul R, Berg C, Reichenbächer B, Kadisch M, Lang D, Büchs J. Non-invasive and time-resolved measurement of the respiration activity of Chinese hamster ovary cells enables prediction of key culture parameters in shake flasks. Biotechnol J 2022; 17:e2100677. [PMID: 35377965 DOI: 10.1002/biot.202100677] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 03/27/2022] [Accepted: 04/01/2022] [Indexed: 11/09/2022]
Abstract
BACKGROUND Shake flasks are frequently used for mammalian cell suspension cultures. For process development and routine culture monitoring, information on culture behaviour is needed early on. MAIN METHODS AND MAJOR RESULTS Here, cell-specific oxygen uptake rates (qO2 ) of two CHO cell lines were determined from shake flask experiments by simultaneous measurement of oxygen transfer rates (OTR) and viable cell concentrations (VCC). For cell line one, qO2 decreased from 2.38∙10-10 mmol cell-1 h-1 to 1.02∙10-10 mmol cell-1 h-1 during batch growth. For cell line two, qO2 was constant (1.90∙10-10 mmol h-1 ). Determined qO2 values were used to calculate the VCC from OTR data. Cumulated oxygen consumption and glucose consumption were correlated for both cell lines and enabled calculation of glucose concentrations from OTR data. IgG producing cell line one had an oxygen demand of ∼15 mmoloxygen gglucose -1 , cell line two consumed ∼5 mmoloxygen gglucose -1 . The established correlations for determination of VCC and glucose were successfully transferred to subsequent cultivations for both cell lines. Combined measurement of the OTR and the carbon dioxide transfer rate enabled quantitative determination of the lactate concentration (production and consumption) without sampling. CONCLUSIONS AND IMPLICATIONS Taken together, non-invasive measurement of the respiration activity enabled time-resolved determination of key culture parameters for increased process understanding in shake flasks. This article is protected by copyright. All rights reserved.
Collapse
Affiliation(s)
- Nina Ihling
- AVT - Biochemical Engineering, RWTH Aachen University, Forckenbeckstr. 51, Aachen, D-52074, Germany
| | - Lara Pauline Munkler
- AVT - Biochemical Engineering, RWTH Aachen University, Forckenbeckstr. 51, Aachen, D-52074, Germany
| | - Richard Paul
- AVT - Biochemical Engineering, RWTH Aachen University, Forckenbeckstr. 51, Aachen, D-52074, Germany
| | - Christoph Berg
- AVT - Biochemical Engineering, RWTH Aachen University, Forckenbeckstr. 51, Aachen, D-52074, Germany
| | | | - Marvin Kadisch
- Rentschler Biopharma SE, Erwin-Rentschler-Str. 21, Laupheim, 88471, Germany
| | - Dietmar Lang
- Rentschler Biopharma SE, Erwin-Rentschler-Str. 21, Laupheim, 88471, Germany
| | - Jochen Büchs
- AVT - Biochemical Engineering, RWTH Aachen University, Forckenbeckstr. 51, Aachen, D-52074, Germany
| |
Collapse
|
45
|
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.
Collapse
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.
| |
Collapse
|
46
|
Zlota AA. Recommendations for Effective and Defendable Implementation of Quality by Design. Org Process Res Dev 2022. [DOI: 10.1021/acs.oprd.1c00265] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Andrei A. Zlota
- The Zlota Company, LLC, 97 Brooksmont Drive, Holliston, Massachusetts 01746-1770, United States
| |
Collapse
|
47
|
Prediction of Solid-State Form of SLS 3D Printed Medicines Using NIR and Raman Spectroscopy. Pharmaceutics 2022; 14:pharmaceutics14030589. [PMID: 35335965 PMCID: PMC8949593 DOI: 10.3390/pharmaceutics14030589] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 03/03/2022] [Accepted: 03/06/2022] [Indexed: 01/25/2023] Open
Abstract
Selective laser sintering (SLS) 3D printing is capable of revolutionising pharmaceutical manufacturing, by producing amorphous solid dispersions in a one-step manufacturing process. Here, 3D-printed formulations loaded with a model BCS class II drug (20% w/w itraconazole) and three grades of hydroxypropyl cellulose (HPC) polymer (-SSL, -SL and -L) were produced using SLS 3D printing. Interestingly, the polymers with higher molecular weights (HPC-L and -SL) were found to undergo a uniform sintering process, attributed to the better powder flow characteristics, compared with the lower molecular weight grade (HPC-SSL). XRPD analyses found that the SLS 3D printing process resulted in amorphous conversion of itraconazole for all three polymers, with HPC-SSL retaining a small amount of crystallinity on the drug product surface. The use of process analytical technologies (PAT), including near infrared (NIR) and Raman spectroscopy, was evaluated, to predict the amorphous content, qualitatively and quantitatively, within itraconazole-loaded formulations. Calibration models were developed using partial least squares (PLS) regression, which successfully predicted amorphous content across the range of 0–20% w/w. The models demonstrated excellent linearity (R2 = 0.998 and 0.998) and accuracy (RMSEP = 1.04% and 0.63%) for NIR and Raman spectroscopy models, respectively. Overall, this article demonstrates the feasibility of SLS 3D printing to produce solid dispersions containing a BCS II drug, and the potential for NIR and Raman spectroscopy to quantify amorphous content as a non-destructive quality control measure at the point-of-care.
Collapse
|
48
|
Sá M, Ferrer-Ledo N, Gao F, Bertinetto CG, Jansen J, Crespo JG, Wijffels RH, Barbosa M, Galinha CF. Perspectives of fluorescence spectroscopy for online monitoring in microalgae industry. Microb Biotechnol 2022; 15:1824-1838. [PMID: 35175653 PMCID: PMC9151345 DOI: 10.1111/1751-7915.14013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 01/25/2022] [Accepted: 01/27/2022] [Indexed: 11/27/2022] Open
Abstract
Microalgae industrial production is viewed as a solution for alternative production of nutraceuticals, cosmetics, biofertilizers, and biopolymers. Throughout the years, several technological advances have been implemented, increasing the competitiveness of microalgae industry. However, online monitoring and real-time process control of a microalgae production factory still require further development. In this mini-review, non-destructive tools for online monitoring of cellular agriculture applications are described. Still, the focus is on the use of fluorescence spectroscopy to monitor several parameters (cell concentration, pigments, and lipids) in the microalgae industry. The development presented makes it the most promising solution for monitoring up-and downstream processes, different biological parameters simultaneously, and different microalgae species. The improvements needed for industrial application of this technology are also discussed.
Collapse
Affiliation(s)
- Marta Sá
- Bioprocess Engineering, Wageningen University and Research, Wageningen, 6708PB, The Netherlands.,Stichting imec Nederland - OnePlanet Research Center, Wageningen, 6708WH, The Netherlands
| | - Narcis Ferrer-Ledo
- Bioprocess Engineering, Wageningen University and Research, Wageningen, 6708PB, The Netherlands
| | - Fengzheng Gao
- Bioprocess Engineering, Wageningen University and Research, Wageningen, 6708PB, The Netherlands
| | - Carlo G Bertinetto
- Institute for Molecules and Materials (Analytical Chemistry), Radboud University, Nijmegen, The Netherlands
| | - Jeroen Jansen
- Institute for Molecules and Materials (Analytical Chemistry), Radboud University, Nijmegen, The Netherlands
| | - João G Crespo
- LAQV-REQUIMTE, Department of Chemistry, NOVA School of Science and Technology, FCT NOVA, Caparica, 2829-516, Portugal
| | - Rene H Wijffels
- Bioprocess Engineering, Wageningen University and Research, Wageningen, 6708PB, The Netherlands.,Faculty of Biosciences and Aquaculture, Nord University, Bodø, N-8049, Norway
| | - Maria Barbosa
- Bioprocess Engineering, Wageningen University and Research, Wageningen, 6708PB, The Netherlands
| | - Claudia F Galinha
- LAQV-REQUIMTE, Department of Chemistry, NOVA School of Science and Technology, FCT NOVA, Caparica, 2829-516, Portugal
| |
Collapse
|
49
|
|
50
|
Gerzon G, Sheng Y, Kirkitadze M. Process Analytical Technologies - Advances in bioprocess integration and future perspectives. J Pharm Biomed Anal 2022; 207:114379. [PMID: 34607168 DOI: 10.1016/j.jpba.2021.114379] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 09/12/2021] [Accepted: 09/15/2021] [Indexed: 12/22/2022]
Abstract
Process Analytical Technology (PAT) instruments include analyzers capable of measuring physical and chemical process parameters and key attributes with the goal of optimizing process controls. PAT in the form of a probe or sensor is designed to integrate within the pharmaceutical manufacturing line and is coupled with computing equipment to perform chemometric modeling for result interpretation and multilayer statistical control of processes. PAT solutions are intended for understanding bioprocesses with a goal to control quality at all stages of product manufacturing and achieve quality by design (QbD). The goal of PAT implementation is to promote real-time release of products to decrease the cycle time and cost of production. This review focuses on the applications of PAT solutions at different stages of the manufacturing process for vaccine production, the advantages, challenges at present state, and the vision of the future development of biopharmaceutical industries.
Collapse
Affiliation(s)
- Gabriella Gerzon
- Department of Biology, Faculty of Science, York University, Toronto, Canada; Analytical Sciences, Sanofi Pasteur, Toronto, Canada
| | - Yi Sheng
- Department of Biology, Faculty of Science, York University, Toronto, Canada
| | | |
Collapse
|