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Desai PM, Bhugra C, Chowdhury A, Melkeri Y, Patel H, Lam S, Hayden T. Implementation of mechanistic modeling and global sensitivity analysis (GSA) for design, optimization, and scale-up of a roller compaction process. Int J Pharm 2024; 658:124201. [PMID: 38705250 DOI: 10.1016/j.ijpharm.2024.124201] [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: 04/29/2024] [Accepted: 05/02/2024] [Indexed: 05/07/2024]
Abstract
The pharmaceutical industry has been shifting towards the application of mechanistic modeling to improve process robustness, enable scale-up, and reduce time to market. Modeling approaches have been well-developed for processes such as roller compaction, a continuous dry granulation process. Several mechanistic models/approaches have been documented with limited application to high drug-loaded formulations. In this study, the Johanson model was employed to optimize roller compaction processing and guide its scale-up for a high drug loaded formulation. The model was calibrated using a pilot-scale Minipactor and was validated for a commercial-scale Macropactor. Global sensitivity analysis (GSA) was implemented to determine the impact of process parameter variations (roll force, gap, speed) on a quality attribute [solid fraction (SF)]. The throughput method, which estimates SF values of ribbons using granule production rate, was also studied. The model predicted SF values for all 14 Macropactor batches within ± 0.04 SF. The throughput method estimated SF with ± 0.06 SF for 7 out of 11 batches. GSA confirmed that roll force had the largest impact on SF. This case study represents a process modeling approach to build quality into the products/processes and expands the use of mechanistic modeling during drug product development.
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Affiliation(s)
- Parind M Desai
- Drug Product Development, GSK R&D, Collegeville, PA, United States.
| | - Chandan Bhugra
- Drug Product Development, GSK R&D, Collegeville, PA, United States
| | - Ananya Chowdhury
- Process Automation, Siemens Digital Industries Inc., Parsippany, NJ, United States
| | - Yash Melkeri
- Drug Product Development, GSK R&D, Collegeville, PA, United States
| | - Hridayi Patel
- Drug Product Development, GSK R&D, Collegeville, PA, United States
| | - Stephanie Lam
- Drug Substance Development, GSK R&D, Collegeville, PA, United States
| | - Tamika Hayden
- Biologics & Device Manufacturing, GSK Global Supply Chain, Zebulon, NC, United States
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Destro F, Barolo M. A review on the modernization of pharmaceutical development and manufacturing - Trends, perspectives, and the role of mathematical modeling. Int J Pharm 2022; 620:121715. [PMID: 35367580 DOI: 10.1016/j.ijpharm.2022.121715] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2022] [Revised: 03/23/2022] [Accepted: 03/29/2022] [Indexed: 01/20/2023]
Abstract
Recently, the pharmaceutical industry has been facing several challenges associated to the use of outdated development and manufacturing technologies. The return on investment on research and development has been shrinking, and, at the same time, an alarming number of shortages and recalls for quality concerns has been registered. The pharmaceutical industry has been responding to these issues through a technological modernization of development and manufacturing, under the support of initiatives and activities such as quality-by-design (QbD), process analytical technology, and pharmaceutical emerging technology. In this review, we analyze this modernization trend, with emphasis on the role that mathematical modeling plays within it. We begin by outlining the main socio-economic trends of the pharmaceutical industry, and by highlighting the life-cycle stages of a pharmaceutical product in which technological modernization can help both achieve consistently high product quality and increase return on investment. Then, we review the historical evolution of the pharmaceutical regulatory framework, and we discuss the current state of implementation and future trends of QbD. The pharmaceutical emerging technology is reviewed afterwards, and a discussion on the evolution of QbD into the more effective quality-by-control (QbC) paradigm is presented. Further, we illustrate how mathematical modeling can support the implementation of QbD and QbC across all stages of the pharmaceutical life-cycle. In this respect, we review academic and industrial applications demonstrating the impact of mathematical modeling on three key activities within pharmaceutical development and manufacturing, namely design space description, process monitoring, and active process control. Finally, we discuss some future research opportunities on the use of mathematical modeling in industrial pharmaceutical environments.
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Affiliation(s)
- Francesco Destro
- CAPE-Lab - Computer-Aided Process Engineering Laboratory, Department of Industrial Engineering, University of Padova, via Marzolo 9, 35131 Padova PD, Italy
| | - Massimiliano Barolo
- CAPE-Lab - Computer-Aided Process Engineering Laboratory, Department of Industrial Engineering, University of Padova, via Marzolo 9, 35131 Padova PD, Italy.
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Vasudevan KV, Pu YE, Amini H, Guarino C, Agrawal A, Akseli I. Using a Model-based Material Sparing Approach for Formulation and Process Development of a Roller Compacted Drug Product. Pharm Res 2022; 39:2083-2093. [PMID: 35218443 DOI: 10.1007/s11095-022-03192-3] [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: 09/21/2021] [Accepted: 02/07/2022] [Indexed: 11/28/2022]
Abstract
The present work details a material sparing approach that combines material profiling with Instron uniaxial die-punch tester and use of a roller compaction mathematical model to guide both formulation and process development of a roller-compacted drug product. True density, compression profiling, and frictional properties of the pre-blend powders are used as inputs for the predictive roller compaction model, while flow properties, particle size distribution, and assay uniformity of roller compaction granules are used to select formulation composition and ribbon solid fraction. Using less than 10 g of a model drug compound for material profiling, roller compacted blend in capsule formulations with appropriate excipient ratios were developed at both 1.4% and 14.4% drug loadings. Subsequently, scale-up batches were successfully manufactured based on the roller compaction process parameters obtained from predictive modeling. The measured solid fractions of roller compaction ribbon samples from the scale-up batches were in good agreement with the target solid fraction of the modeling. This approach demonstrated considerable advantages through savings in both materials and number of batches in the development of a roller-compacted drug product, which is of particular value at early development stages when drug substance is often limited and timelines are aggressive.
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Affiliation(s)
- Kalyan V Vasudevan
- Drug Product Development, Pharmaceutical Science & Technology, Bristol Myers Squibb, Summit, NJ, USA.
| | - Yu Elaine Pu
- Drug Product Development, Pharmaceutical Science & Technology, Bristol Myers Squibb, Summit, NJ, USA
| | - Hossein Amini
- Engineering Technology, Bristol Myers Squibb, Summit, NJ, USA
| | | | - Anjali Agrawal
- Drug Product Development, Pharmaceutical Science & Technology, Bristol Myers Squibb, Summit, NJ, USA
| | - Ilgaz Akseli
- Engineering Technology, Bristol Myers Squibb, Summit, NJ, USA
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Kleinebudde P. Improving Process Understanding in Roll Compaction. J Pharm Sci 2021; 111:552-558. [PMID: 34562447 DOI: 10.1016/j.xphs.2021.09.024] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Revised: 09/17/2021] [Accepted: 09/17/2021] [Indexed: 11/26/2022]
Abstract
Roll compaction/ dry granulation is gaining importance. Numerous papers have been published and many attempts to model the process are available in the meantime. Johanson published a model in 1965, which is the basis for many further modifications until today. The aim of the paper is to improve process understanding in roll compaction, which can be used to setup a roll compaction process, to design a scale-up strategy or to help in process transfer between different types of roll compactors. Based on some assumptions, simple considerations help to estimate a required densification factor and to visualize the relations between roll diameter, gap width and nip angle. Two recently published papers based on simplified Johansen models are used to visualize the relations between specific compaction force and the maximal pressure experienced by the material. The influence of roll diameter, gap width and compressibility constant are discussed. This helps to estimate, if a scale-up or process transfer is reasonable. The recently introduced dimensionless Midoux-number can also be used to design scale-up or process transfer of roll compaction without knowledge about the maximal pressure. Exploring the simple concepts can help to improve process understanding even without a background in engineering.
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Affiliation(s)
- Peter Kleinebudde
- Institute of Pharmaceutics and Biopharmaceutics, Heinrich Heine University Duesseldorf, Universitaetsstrasse 1, 40225 Duesseldorf, Germany.
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Shi G, Lin L, Liu Y, Chen G, Luo Y, Wu Y, Li H. Pharmaceutical application of multivariate modelling techniques: a review on the manufacturing of tablets. RSC Adv 2021; 11:8323-8345. [PMID: 35423324 PMCID: PMC8695199 DOI: 10.1039/d0ra08030f] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2020] [Accepted: 01/26/2021] [Indexed: 11/21/2022] Open
Abstract
The tablet manufacturing process is a complex system, especially in continuous manufacturing (CM). It includes multiple unit operations, such as mixing, granulation, and tableting. In tablet manufacturing, critical quality attributes are influenced by multiple factorial relationships between material properties, process variables, and interactions. Moreover, the variation in raw material attributes and manufacturing processes is an inherent characteristic and seriously affects the quality of pharmaceutical products. To deepen our understanding of the tablet manufacturing process, multivariable modeling techniques can replace univariate analysis to investigate tablet manufacturing. In this review, the roles of the most prominent multivariate modeling techniques in the tablet manufacturing process are discussed. The review mainly focuses on applying multivariate modeling techniques to process understanding, optimization, process monitoring, and process control within multiple unit operations. To minimize the errors in the process of modeling, good modeling practice (GMoP) was introduced into the pharmaceutical process. Furthermore, current progress in the continuous manufacturing of tablets and the role of multivariate modeling techniques in continuous manufacturing are introduced. In this review, information is provided to both researchers and manufacturers to improve tablet quality.
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Affiliation(s)
- Guolin Shi
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences Beijing 100700 China
| | - Longfei Lin
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences Beijing 100700 China
| | - Yuling Liu
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences Beijing 100700 China
| | - Gongsen Chen
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences Beijing 100700 China
| | - Yuting Luo
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences Beijing 100700 China
| | - Yanqiu Wu
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences Beijing 100700 China
| | - Hui Li
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences Beijing 100700 China
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Model-Based Scale-Up Methodologies for Pharmaceutical Granulation. Pharmaceutics 2020; 12:pharmaceutics12050453. [PMID: 32423051 PMCID: PMC7284585 DOI: 10.3390/pharmaceutics12050453] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2020] [Revised: 05/09/2020] [Accepted: 05/11/2020] [Indexed: 12/13/2022] Open
Abstract
In the pharmaceutical industry, it is a major challenge to maintain consistent quality of drug products when the batch scale of a process is changed from a laboratory scale to a pilot or commercial scale. Generally, a pharmaceutical manufacturing process involves various unit operations, such as blending, granulation, milling, tableting and coating and the process parameters of a unit operation have significant effects on the quality of the drug product. Depending on the change in batch scale, various process parameters should be strategically controlled to ensure consistent quality attributes of a drug product. In particular, the granulation may be significantly influenced by scale variation as a result of changes in various process parameters and equipment geometry. In this study, model-based scale-up methodologies for pharmaceutical granulation are presented, along with data from various related reports. The first is an engineering-based modeling method that uses dimensionless numbers based on process similarity. The second is a process analytical technology-based modeling method that maintains the desired quality attributes through flexible adjustment of process parameters by monitoring the quality attributes of process products in real time. The third is a physics-based modeling method that involves a process simulation that understands and predicts drug quality through calculation of the behavior of the process using physics related to the process. The applications of these three scale-up methods are summarized according to granulation mechanisms, such as wet granulation and dry granulation. This review shows that these model-based scale-up methodologies provide a systematic process strategy that can ensure the quality of drug products in the pharmaceutical industry.
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Yu M, Weidemann M, Omar CS, Schmidt A, Litster JD, Salman AD. Application of feeding guiders to improve the powder distribution in the two scales of roller compactors. Int J Pharm 2020; 573:118815. [PMID: 31751637 DOI: 10.1016/j.ijpharm.2019.118815] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2019] [Revised: 10/16/2019] [Accepted: 10/18/2019] [Indexed: 11/19/2022]
Abstract
Roller compaction is a continuous dry granulation process, where the powder is compressed between two counter-rotating rollers and compacted into ribbons. The quality and homogeneity of the granulate is determined by the uniformity and porosity of the ribbon, which depends on the feeding process of the primary powder to the rollers, the flow properties of the primary powder and process parameters such as roller forces. Previous work was conducted to improve the powder flow and distribution in the feeding zone by developing new feeding guiders, which are located in the feeding zone close to the rollers on the lab-scale roller compactor Alexanderwerk WP120 Pharma (Yu et al., 2018). These new feeding guiders were used to reduce the amount of powder that is delivered to the centre of the rollers and increase the amount of powder that is delivered to the sides of the rollers, in comparison to the original feeding guiders. This modified concept using new feeding guiders has been applied to the large-scale roller compactor Alexanderwerk WP200 Pharma in the present work. In order to evaluate the homogeneity of the ribbon properties across the ribbon width, the temperature profile and porosity distribution across the ribbon width were measured. The new feeding guiders resulted in ribbons being produced with a more uniform temperature profile and porosity distribution across the ribbon width when using the small and large scale roller compactors at different process parameters.
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Affiliation(s)
- Mingzhe Yu
- Department of Chemical and Biological Engineering, University of Sheffield, Mappin Street, Sheffield S1 3JD, United Kingdom
| | - Marcus Weidemann
- Alexanderwerk AG, Remscheid, North Rhine-Westphalia, 42857, Germany
| | - Chalak S Omar
- Department of Chemical and Biological Engineering, University of Sheffield, Mappin Street, Sheffield S1 3JD, United Kingdom
| | | | - James D Litster
- Department of Chemical and Biological Engineering, University of Sheffield, Mappin Street, Sheffield S1 3JD, United Kingdom
| | - Agba D Salman
- Department of Chemical and Biological Engineering, University of Sheffield, Mappin Street, Sheffield S1 3JD, United Kingdom.
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Muliadi AR, Banda A, Mao C. Recent Progress in Roll Compaction Process Development for Pharmaceutical Solid Dosage Form Manufacture. CONTINUOUS PHARMACEUTICAL PROCESSING 2020. [DOI: 10.1007/978-3-030-41524-2_7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/13/2023]
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9
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Pishnamazi M, Casilagan S, Clancy C, Shirazian S, Iqbal J, Egan D, Edlin C, Croker DM, Walker GM, Collins MN. Microcrystalline cellulose, lactose and lignin blends: Process mapping of dry granulation via roll compaction. POWDER TECHNOL 2019. [DOI: 10.1016/j.powtec.2018.07.003] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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11
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Dal-Pastro F, Facco P, Zamprogna E, Bezzo F, Barolo M. Model-based approach to the design and scale-up of wheat milling operations — Proof of concept. FOOD AND BIOPRODUCTS PROCESSING 2017. [DOI: 10.1016/j.fbp.2017.09.005] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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12
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Roller compaction scale-up using roll width as scale factor and laser-based determined ribbon porosity as critical material attribute. Eur J Pharm Sci 2016; 87:69-78. [DOI: 10.1016/j.ejps.2015.11.001] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2015] [Accepted: 11/01/2015] [Indexed: 11/18/2022]
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13
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Boersen N, Belair D, Peck GE, Pinal R. A dimensionless variable for the scale up and transfer of a roller compaction formulation. Drug Dev Ind Pharm 2015; 42:60-69. [PMID: 25853293 DOI: 10.3109/03639045.2015.1029937] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Affiliation(s)
- Nathan Boersen
- Department of Industrial and Physical Pharmacy, Purdue University, West Lafayette, INUSA
| | - David Belair
- Department of Industrial and Physical Pharmacy, Purdue University, West Lafayette, INUSA
| | - Garnet E. Peck
- Department of Industrial and Physical Pharmacy, Purdue University, West Lafayette, INUSA
| | - Rodolfo Pinal
- Department of Industrial and Physical Pharmacy, Purdue University, West Lafayette, INUSA
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14
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Souihi N, Reynolds G, Tajarobi P, Wikström H, Haeffler G, Josefson M, Trygg J. Roll compaction process modeling: Transfer between equipment and impact of process parameters. Int J Pharm 2015; 484:192-206. [DOI: 10.1016/j.ijpharm.2015.02.042] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2014] [Revised: 02/13/2015] [Accepted: 02/16/2015] [Indexed: 11/17/2022]
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15
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Facco P, Largoni M, Tomba E, Bezzo F, Barolo M. Transfer of process monitoring models between plants: Batch systems. Chem Eng Res Des 2014. [DOI: 10.1016/j.cherd.2013.07.010] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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16
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Latent variable modeling to assist the implementation of Quality-by-Design paradigms in pharmaceutical development and manufacturing: A review. Int J Pharm 2013; 457:283-97. [DOI: 10.1016/j.ijpharm.2013.08.074] [Citation(s) in RCA: 70] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2013] [Revised: 08/27/2013] [Accepted: 08/28/2013] [Indexed: 11/19/2022]
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17
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Transfer of a nanoparticle product between different mixers using latent variable model inversion. AIChE J 2013. [DOI: 10.1002/aic.14244] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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19
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MacGregor J, Cinar A. Monitoring, fault diagnosis, fault-tolerant control and optimization: Data driven methods. Comput Chem Eng 2012. [DOI: 10.1016/j.compchemeng.2012.06.017] [Citation(s) in RCA: 205] [Impact Index Per Article: 17.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Tomba E, Barolo M, García-Muñoz S. General Framework for Latent Variable Model Inversion for the Design and Manufacturing of New Products. Ind Eng Chem Res 2012. [DOI: 10.1021/ie301214c] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Emanuele Tomba
- Computer-Aided Process Engineering
Laboratory (CAPE-Lab), Dipartimento di Ingegneria Industriale, Università di Padova, via Marzolo 9, 35131 Padova
PD, Italy
| | - Massimiliano Barolo
- Computer-Aided Process Engineering
Laboratory (CAPE-Lab), Dipartimento di Ingegneria Industriale, Università di Padova, via Marzolo 9, 35131 Padova
PD, Italy
| | - Salvador García-Muñoz
- Pfizer Worldwide R&D, 445 Eastern Point Road, Groton, Connecticut 06340, United States
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