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Sacher S, Kottlan A, Diop JB, Heimsten R. Prediction of in-vitro dissolution and tablet hardness from optical porosity measurements. Int J Pharm 2024; 660:124336. [PMID: 38871136 DOI: 10.1016/j.ijpharm.2024.124336] [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: 05/08/2024] [Revised: 06/10/2024] [Accepted: 06/11/2024] [Indexed: 06/15/2024]
Abstract
Advanced manufacturing technologies such as continuous processing require fast information on the quality of intermediates and products. Process analytical technologies (PAT) to monitor many critical quality attributes (CQAs) have been developed and successfully implemented in pharmaceutical industry. However, there are some CQAs, which still have to be measured off-line with significant effort due to the lack of suitable PAT sensors. Two prominent examples are the in-vitro dissolution and the tablet hardness. Both are obtained via destructive measurement, and the dissolution is tedious and time-consuming to determine. In this study, these two CQAs were predicted via correlation with the optical porosity of tablets. The optical porosity was measured via a novel combination of gas in scattering media absorption spectroscopy (GASMAS) and photon time of flight spectroscopy (pTOFS) with a SpectraPore instrument. The approach was tested in a continuous tableting line and showed promising results in predicting the amount of drug released after specific dissolution times as well as the tablet hardness. This indicates that the measurement of optical porosity can support control strategies within the real-time release testing (RTRT) concept.
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Affiliation(s)
- Stephan Sacher
- Research Center Pharmaceutical Engineering GmbH, Inffeldgasse 13/2 8010, Graz, Austria.
| | - Andreas Kottlan
- Research Center Pharmaceutical Engineering GmbH, Inffeldgasse 13/2 8010, Graz, Austria
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2
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Kakhi M, Li J, Dorantes A. Regulatory Experience with Continuous Manufacturing and Real Time Release Testing for Dissolution in New Drug Applications. J Pharm Sci 2023; 112:2604-2614. [PMID: 37572781 DOI: 10.1016/j.xphs.2023.08.004] [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: 06/06/2023] [Revised: 08/07/2023] [Accepted: 08/07/2023] [Indexed: 08/14/2023]
Abstract
Regulatory submissions involving the use of continuous manufacturing (CM)1 and/or real-time release testing for dissolution (RTRT-D) to the United States Food and Drug Administration (FDA) were identified spanning several years. The submissions were for orally administered IR tablets and they were examined from a biopharmaceutics perspective to highlight commonly occurring issues which the FDA's assessment teams identified with the proposed use of CM and/or RTRT-D. The objective of this study is to provide recommendations for best practices that will help advance the field by (i) generating greater opportunities for (drug) Applicants2 to benefit from the implementation of advanced manufacturing approaches, (ii) improving high quality regulatory submissions involving CM and RTRT-D, and thus (iii) lessening the regulatory review burden. This paper has identified several common deficiencies, such as inadequate strategies for stratified sampling of drug product (DP) units, inappropriate design of experiments (DoE), inability of the proposed RTRT-D model to account for dissolution variability and to predict the entire time course of dissolution, insufficient documentation, and unsuitable in vitro dissolution methods.
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Affiliation(s)
- Maziar Kakhi
- Division of Product Quality Research, Office of Testing and Research, Office of Pharmaceutical Quality, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, USA.
| | - Jing Li
- Division of Biopharmaceutics, Office of New Drug Products, Office of Pharmaceutical Quality, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, USA
| | - Angelica Dorantes
- Division of Biopharmaceutics, Office of New Drug Products, Office of Pharmaceutical Quality, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, USA
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3
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Ferdoush S, Gonzalez M. Semi-mechanistic reduced order model of pharmaceutical tablet dissolution for enabling Industry 4.0 manufacturing systems. Int J Pharm 2023; 631:122502. [PMID: 36529354 PMCID: PMC10759183 DOI: 10.1016/j.ijpharm.2022.122502] [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: 08/23/2022] [Revised: 12/10/2022] [Accepted: 12/12/2022] [Indexed: 12/23/2022]
Abstract
We propose a generalization of the Weibull dissolution model, referred to as generalized Weibull dissolution model, that seamlessly captures all three fractional dissolution rates experimentally observed in pharmaceutical solid tablets, namely decreasing, increasing, and non-monotonic rates. This is in contrast to traditional reduced order models, which capture at most two fractional dissolution rates and, thus, are not suitable for a wide range of product formulations hindering, for example, the adoption of knowledge management in the context of Industry 4.0. We extend the generalized Weibull dissolution model further to capture the relationship between critical process parameters (CPPs), critical materials attributes (CMAs), and dissolution profile to, in turn, facilitate real-time release testing (RTRT) and quality-by-control (QbC) strategies. Specifically, we endow the model with multivariate rational polynomials that interpolate the mechanistic limiting behavior of tablet dissolution as CPPs and CMAs approach certain values of physical significance (such as the upper and lower bounds of tablet porosity or lubrication conditions), thus the semi-mechanistic nature of the reduced order model. Restricting attention to direct compaction and using various case studies from the literature, we demonstrate the versatility and the capability of the semi-mechanistic ROM to estimate changes in dissolution due to process disturbances in tablet weight, porosity, lubrication conditions (i.e., the total amount of shear strain imparted during blending), and moisture content in the powder blend. In all of the cases considered in this work, the estimations of the model are in remarkable agreement with experimental data.
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Affiliation(s)
- Shumaiya Ferdoush
- School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907, USA
| | - Marcial Gonzalez
- School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907, USA; Ray W. Herrick Laboratories, Purdue University, West Lafayette, IN 47907, USA.
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Sousa AS, Serra J, Estevens C, Costa R, Ribeiro AJ. A quality by design approach in oral extended release drug delivery systems: where we are and where we are going? JOURNAL OF PHARMACEUTICAL INVESTIGATION 2022. [DOI: 10.1007/s40005-022-00603-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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5
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Real-time release testing of dissolution based on surrogate models developed by machine learning algorithms using NIR spectra, compression force and particle size distribution as input data. Int J Pharm 2021; 597:120338. [DOI: 10.1016/j.ijpharm.2021.120338] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Revised: 01/26/2021] [Accepted: 01/30/2021] [Indexed: 12/28/2022]
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6
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Razuc M, Grafia A, Gallo L, Ramírez-Rigo MV, Romañach RJ. Near-infrared spectroscopic applications in pharmaceutical particle technology. Drug Dev Ind Pharm 2019; 45:1565-1589. [DOI: 10.1080/03639045.2019.1641510] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Affiliation(s)
- M. Razuc
- Instituto de Química del Sur (INQUISUR), Universidad Nacional del Sur (UNS)-CONICET, Bahía Blanca, Argentina
- Departamento de Biología, Bioquímica y Farmacia, Universidad Nacional del Sur (UNS), Bahía Blanca, Argentina
| | - A. Grafia
- Planta Piloto de Ingeniería Química (PLAPIQUI), Universidad Nacional del Sur (UNS)- CONICET, Bahía Blanca, Argentina
| | - L. Gallo
- Departamento de Biología, Bioquímica y Farmacia, Universidad Nacional del Sur (UNS), Bahía Blanca, Argentina
- Planta Piloto de Ingeniería Química (PLAPIQUI), Universidad Nacional del Sur (UNS)- CONICET, Bahía Blanca, Argentina
| | - M. V. Ramírez-Rigo
- Departamento de Biología, Bioquímica y Farmacia, Universidad Nacional del Sur (UNS), Bahía Blanca, Argentina
- Planta Piloto de Ingeniería Química (PLAPIQUI), Universidad Nacional del Sur (UNS)- CONICET, Bahía Blanca, Argentina
| | - R. J. Romañach
- Department of Chemistry, Center for Structured Organic Particulate Systems, University of Puerto Rico – Mayagüez, Mayagüez, Puerto Rico
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7
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Zaborenko N, Shi Z, Corredor CC, Smith-Goettler BM, Zhang L, Hermans A, Neu CM, Alam MA, Cohen MJ, Lu X, Xiong L, Zacour BM. First-Principles and Empirical Approaches to Predicting In Vitro Dissolution for Pharmaceutical Formulation and Process Development and for Product Release Testing. AAPS J 2019; 21:32. [PMID: 30790200 PMCID: PMC6394641 DOI: 10.1208/s12248-019-0297-y] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2018] [Accepted: 11/02/2018] [Indexed: 11/30/2022] Open
Abstract
This manuscript represents the perspective of the Dissolution Working Group of the International Consortium for Innovation and Quality in Pharmaceutical Development (IQ) and of two focus groups of the American Association of Pharmaceutical Scientists (AAPS): Process Analytical Technology (PAT) and In Vitro Release and Dissolution Testing (IVRDT). The intent of this manuscript is to show recent progress in the field of in vitro predictive dissolution modeling and to provide recommended general approaches to developing in vitro predictive dissolution models for both early- and late-stage formulation/process development and batch release. Different modeling approaches should be used at different stages of drug development based on product and process understanding available at those stages. Two industry case studies of current approaches used for modeling tablet dissolution are presented. These include examples of predictive model use for product development within the space explored during formulation and process optimization, as well as of dissolution models as surrogate tests in a regulatory filing. A review of an industry example of developing a dissolution model for real-time release testing (RTRt) and of academic case studies of enabling dissolution RTRt by near-infrared spectroscopy (NIRS) is also provided. These demonstrate multiple approaches for developing data-rich empirical models in the context of science- and risk-based process development to predict in vitro dissolution. Recommendations of modeling best practices are made, focused primarily on immediate-release (IR) oral delivery products for new drug applications. A general roadmap is presented for implementation of dissolution modeling for enhanced product understanding, robust control strategy, batch release testing, and flexibility toward post-approval changes.
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Affiliation(s)
- Nikolay Zaborenko
- Small Molecule Design and Development, Eli Lilly and Company, Lilly Technology Center North, B302, Drop 3210, Indianapolis, Indiana, 46285, USA
| | - Zhenqi Shi
- Small Molecule Design and Development, Eli Lilly and Company, Lilly Technology Center North, B302, Drop 3210, Indianapolis, Indiana, 46285, USA.
| | - Claudia C Corredor
- Drug Product Science and Technology, Bristol-Myers Squibb, New Brunswick, New Jersey, 08903, USA
| | | | - Limin Zhang
- Drug Product Science and Technology, Bristol-Myers Squibb, New Brunswick, New Jersey, 08903, USA
| | - Andre Hermans
- Merck & Co., Inc., Kenilworth, New Jersey, 07033, USA
| | - Colleen M Neu
- Merck & Co., Inc., Kenilworth, New Jersey, 07033, USA
| | - Md Anik Alam
- Analytical Research and Development, Pfizer Inc., Groton, Connecticut, 06340, USA
| | - Michael J Cohen
- Global Chemistry and Manufacturing Controls, Pfizer Inc., Groton, Connecticut, 06340, USA
| | - Xujin Lu
- Drug Product Science and Technology, Bristol-Myers Squibb, New Brunswick, New Jersey, 08903, USA
| | - Leah Xiong
- Merck & Co., Inc., Kenilworth, New Jersey, 07033, USA
| | - Brian M Zacour
- Drug Product Science and Technology, Bristol-Myers Squibb, New Brunswick, New Jersey, 08903, USA
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8
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Caccavo D. An overview on the mathematical modeling of hydrogels' behavior for drug delivery systems. Int J Pharm 2019; 560:175-190. [PMID: 30763681 DOI: 10.1016/j.ijpharm.2019.01.076] [Citation(s) in RCA: 60] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2018] [Revised: 01/28/2019] [Accepted: 01/31/2019] [Indexed: 02/07/2023]
Abstract
Hydrogels-based systems (HBSs) for drug delivery are nowadays extensively used and the interest in modeling their behavior is dramatically increasing. In this review a critical overview on the modeling approaches is given, quantitatively and qualitatively analyzing the publications on the subject, the trend of the publications per year and the type of modeling approaches. It was found that, despite the drug release fitting models (i.e. Higuchi's equation) are the most abundant, their use for HBSs is decreasing in the last years and luckily, considering the limiting assumption on which they were built, they will be confined to simple mathematical fitting equations. Within the mechanistic models the "multi-component" with the swelling approximation (mass transport only) and with the mechanics (fully coupled) are experiencing the highest growth rate, with much more interest toward the last one that, in the next years could be able to provide a first principles model. Statistical models, especially based on the response surface methodology, are rapidly spreading in the scientific community mainly thanks to their ability to be predictive, regardless of the phenomenology, in the analyzed design space with very low efforts. Neural Networks models for HBSs, in countertrend with their use in the pharmaceutical industry, have never take off preferring less data demanding statistical models.
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Affiliation(s)
- Diego Caccavo
- Department of Industrial Engineering, University of Salerno, 84084 Fisciano, SA, Italy.
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Hattori Y, Sugata M, Kamata H, Nagata M, Nagato T, Hasegawa K, Otsuka M. Real-time monitoring of the tablet-coating process by near-infrared spectroscopy - Effects of coating polymer concentrations on pharmaceutical properties of tablets. J Drug Deliv Sci Technol 2018. [DOI: 10.1016/j.jddst.2018.04.018] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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10
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Markl D, Zeitler JA. A Review of Disintegration Mechanisms and Measurement Techniques. Pharm Res 2017; 34:890-917. [PMID: 28251425 PMCID: PMC5382187 DOI: 10.1007/s11095-017-2129-z] [Citation(s) in RCA: 183] [Impact Index Per Article: 26.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2017] [Accepted: 02/16/2017] [Indexed: 11/23/2022]
Abstract
Pharmaceutical solid dosage forms (tablets or capsules) are the predominant form to administer active pharmaceutical ingredients (APIs) to the patient. Tablets are typically powder compacts consisting of several different excipients in addition to the API. Excipients are added to a formulation in order to achieve the desired fill weight of a dosage form, to improve the processability or to affect the drug release behaviour in the body. These complex porous systems undergo different mechanisms when they come in contact with physiological fluids. The performance of a drug is primarily influenced by the disintegration and dissolution behaviour of the powder compact. The disintegration process is specifically critical for immediate-release dosage forms. Its mechanisms and the factors impacting disintegration are discussed and methods used to study the disintegration in-situ are presented. This review further summarises mathematical models used to simulate disintegration phenomena and to predict drug release kinetics.
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Affiliation(s)
- Daniel Markl
- Department of Chemical Engineering and Biotechnology, University of Cambridge, Philippa Fawcett Drive, Cambridge, CB3 0AS, UK
| | - J Axel Zeitler
- Department of Chemical Engineering and Biotechnology, University of Cambridge, Philippa Fawcett Drive, Cambridge, CB3 0AS, UK.
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