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Rajput A, Pillai M, Ajabiya J, Sengupta P. Integrating Quantitative Methods & Modeling and Analytical Techniques in Reverse Engineering; A Cutting-Edge Strategy in Complex Generic Development. AAPS PharmSciTech 2025; 26:92. [PMID: 40140161 DOI: 10.1208/s12249-025-03067-x] [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: 10/16/2024] [Accepted: 02/07/2025] [Indexed: 03/28/2025] Open
Abstract
Generic drugs are crucial for healthcare, offering affordable alternatives to brand-name drugs. Complex generics, with intricate ingredients, are gaining increasing importance in managing chronic conditions. However, prior to the regulatory market approval, they must demonstrate similarity in active ingredients, formulations, strength, and administration routes to ensure bioequivalence. The primary constraint lies in demonstrating bioequivalence with the innovator drug using traditional methods includes a lack of advanced technologies, and standardized protocols for analysing complex products. Given the multifaceted nature of these products, a single methodology may not suffice to establish in vitro/in vivo bioequivalence. Recognizing this, the USFDA conducts several workshops aiming advancement of complex generic drug product development. Notably, these efforts highlight the need to use Quantitative Methods and Modeling (QMM) approaches to support generic product development. QMM is a scientific approach used to analyze data and simulate drug development processes, ensuring safe, effective, and similar formulations of generic drugs using mathematical, statistical, and computational tools. QMM facilitates the design of formulations and processes, establishes a framework for in vivo BE studies, and suggests alternative ways to demonstrate BE. Appropriate utilization of the QMM approach can reduce the need for unwanted in vivo studies and bolster in vitro approaches for generic product development. Furthermore, use of orthogonal analytical techniques to characterize and decode innovator drugs can provide valuable insights into product attributes. Integrating this data into QMM enables the assessment of critical material attributes, or critical process parameters, thus demonstrating sameness. The combined application of QMM and analytical techniques not only supports regulatory decisions but also enhances the success rate of complex generic drug products.
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Affiliation(s)
- Akash Rajput
- Department of Pharmaceutical Analysis, National Institute of Pharmaceutical Education and Research-Ahmedabad (NIPER-A), An Institute of National Importance, Government of India, Opp. Airforce Station, Palaj, Gandhinagar, 382355, Gujarat, India
| | - Megha Pillai
- Department of Pharmaceutical Analysis, National Institute of Pharmaceutical Education and Research-Ahmedabad (NIPER-A), An Institute of National Importance, Government of India, Opp. Airforce Station, Palaj, Gandhinagar, 382355, Gujarat, India
| | - Jinal Ajabiya
- Department of Pharmaceutical Analysis, National Institute of Pharmaceutical Education and Research-Ahmedabad (NIPER-A), An Institute of National Importance, Government of India, Opp. Airforce Station, Palaj, Gandhinagar, 382355, Gujarat, India
| | - Pinaki Sengupta
- Department of Pharmaceutical Analysis, National Institute of Pharmaceutical Education and Research-Ahmedabad (NIPER-A), An Institute of National Importance, Government of India, Opp. Airforce Station, Palaj, Gandhinagar, 382355, Gujarat, India.
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Wang Y, Otte A, Park H, Park K. In vitro-in vivo correlation (IVIVC) development for long-acting injectable drug products based on poly(lactide-co-glycolide). J Control Release 2025; 377:186-196. [PMID: 39542257 DOI: 10.1016/j.jconrel.2024.11.021] [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: 07/17/2024] [Revised: 10/17/2024] [Accepted: 11/09/2024] [Indexed: 11/17/2024]
Abstract
In vitro-in vivo correlation (IVIVC), linking in vitro drug release to in vivo drug release or in vivo drug absorption, has been explored chiefly for oral extended-release dosage forms. Currently, there are no official guidelines on IVIVC development for non-oral drug delivery systems. Recently, many long-acting injectable (LAI) formulations based on poly(lactide-co-glycolide) (PLGA) have been developed to deliver various drugs, ranging from small molecules to peptides and proteins, for up to 6 months. The circumstances involved in the LAI formulations are drastically different from those in oral formulations, which generally deliver drugs for a maximum of 24 h. This article examines 37 IVIVC studies of PLGA microparticle formulations available in the literature. Understanding and establishing an IVIVC of LAI formulations requires more than merely plotting the percentage in vitro drug release against the percentage in vivo absorption. In vivo drug absorption (or release) should be measured to provide a complete pharmacokinetic profile when feasible. Accelerated in vitro release methods need to be respective of the real-time measurements by sharing the same release mechanism. Obtaining meaningful IVIVCs with predictive capability will be highly useful for future regulatory actions and for developing generic and new formulations.
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Affiliation(s)
- Yan Wang
- Food and Drug Administration, Center for Drug Evaluation and Research, Office of Generic Drugs, Office of Research and Standards, Silver Spring, MD 20993, USA
| | - Andrew Otte
- Purdue University, Weldon School of Biomedical Engineering, West Lafayette, IN 47907, USA
| | | | - Kinam Park
- Purdue University, Weldon School of Biomedical Engineering, West Lafayette, IN 47907, USA; Purdue University, Department of Industrial and Molecular Pharmaceutics, West Lafayette, IN 47907, USA.
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Nagpal S, Png J, Kahouadji L, Wacker MG. A bio-predictive release assay for liposomal prednisolone phosphate. J Control Release 2024; 374:61-75. [PMID: 39089507 DOI: 10.1016/j.jconrel.2024.07.069] [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: 02/14/2024] [Revised: 07/25/2024] [Accepted: 07/29/2024] [Indexed: 08/04/2024]
Abstract
Predictive performance assays are crucial for the development and approval of nanomedicines and their bioequivalent successors. At present, there are no established compendial methods that provide a reliable standard for comparing and selecting these formulation prototypes, and our understanding of the in vivo release remains still incomplete. Consequently, extensive animal studies, with enhanced analytical resolution for both, released and encapsulated drug, are necessary to assess bioequivalence. This significantly raises the cost and duration of nanomedicine development. This work presents the development of a discriminatory and biopredictive release test method for liposomal prednisolone phosphate. Using model-informed deconvolution, we identified an in vivo target release. The experimental design employed a discrete L-optimal configuration to refine the analytical method and determine the impact of in vitro parameters on the dosage form. A three-point specification evaluated the key phases of in vivo release: early (T-5%), intermediate (T-20%), and late release behavior (T-40%), compared to the in vivo release profile of the reference product, NanoCort®. Various levels of shear responses and the influence of clinically relevant release media compositions were tested. This enabled an assessment of the effect of shear on the release, an essential aspect of their in vivo deformation and release behavior. The type and concentration of proteins in the medium influence liposome release. Fetal bovine serum strongly impacted the discriminatory performance at intermediate shear conditions. The method provided deep insights into the release response of liposomes and offers an interesting workflow for in vitro bioequivalence evaluation.
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Affiliation(s)
- Shakti Nagpal
- National University of Singapore, Faculty of Science, Department of Pharmacy and Pharmaceutical Sciences, Singapore
| | - Jordan Png
- National University of Singapore, Faculty of Science, Department of Pharmacy and Pharmaceutical Sciences, Singapore
| | - Lyes Kahouadji
- Department of Chemical Engineering, Imperial College London, South Kensington Campus, SW7 2AZ London, United Kingdom
| | - Matthias G Wacker
- National University of Singapore, Faculty of Science, Department of Pharmacy and Pharmaceutical Sciences, Singapore.
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Gan K, Li Z, Darli PM, Wong T, Modh H, Gottier P, Halbherr S, Wacker MG. Understanding the In Vitro-In Vivo Nexus: Advanced correlation models predict clinical performance of liposomal doxorubicin. Int J Pharm 2024; 654:123942. [PMID: 38403086 DOI: 10.1016/j.ijpharm.2024.123942] [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: 09/10/2023] [Revised: 02/04/2024] [Accepted: 02/22/2024] [Indexed: 02/27/2024]
Abstract
In the century of precision medicine and predictive modeling, addressing quality-related issues in the medical supply chain is critical, with 62 % of the disruptions being attributable to quality challenges. This study centers on the development and safety of liposomal doxorubicin, where animal studies alone often do not adequately explain the complex interplay between critical quality attributes and in vivo performances. Anchored in our aim to elucidate this in vitro-in vivo nexus, we compared TLD-1, a novel liposomal doxorubicin delivery system, against the established formulations Doxil® and Lipodox®. Robust in vitro-in vivo correlations (IVIVCs) with excellent coefficients of determination (R2 > 0.98) were obtained in the presence of serum under dynamic high-shear conditions. They provided the foundation for an advanced characterization and benchmarking strategy. Despite the smaller vesicle size and reduced core crystallinity of TLD-1, its release behavior closely resembled that of Doxil®. Nevertheless, subtle differences between the dosage forms observed in the in vitro setting were reflected in the bioavailabilities observed in vivo. Data from a Phase-I clinical trial facilitated the development of patient-specific IVIVCs using the physiologically-based nanocarrier biopharmaceutics model, enabling a more accurate estimation of doxorubicin exposure. This advancement could impact clinical practice by allowing for more precise dose estimation and aiding in the assessment of the interchangeability of generic liposomal doxorubicin.
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Affiliation(s)
- Kennard Gan
- Department of Pharmacy and Pharmaceutical Sciences, Faculty of Science, National University of Singapore, Singapore, Singapore
| | - Zhuoxuan Li
- Department of Pharmacy and Pharmaceutical Sciences, Faculty of Science, National University of Singapore, Singapore, Singapore
| | - Phyo Maw Darli
- Department of Pharmacy and Pharmaceutical Sciences, Faculty of Science, National University of Singapore, Singapore, Singapore
| | - Teresa Wong
- Department of Pharmacy and Pharmaceutical Sciences, Faculty of Science, National University of Singapore, Singapore, Singapore
| | - Harshvardhan Modh
- Department of Pharmacy and Pharmaceutical Sciences, Faculty of Science, National University of Singapore, Singapore, Singapore
| | | | | | - Matthias G Wacker
- Department of Pharmacy and Pharmaceutical Sciences, Faculty of Science, National University of Singapore, Singapore, Singapore.
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Siemons M, Schroyen B, Darville N, Goyal N. Role of Modeling and Simulation in Preclinical and Clinical Long-Acting Injectable Drug Development. AAPS J 2023; 25:99. [PMID: 37848754 DOI: 10.1208/s12248-023-00864-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Accepted: 09/28/2023] [Indexed: 10/19/2023] Open
Abstract
Innovations in the field of long-acting injectable drug development are increasingly being reported. More advanced in vitro and in vivo characterization can improve our understanding of the injection space and aid in describing the long-acting injectable (LAI) drug's behavior at the injection site more mechanistically. These innovations may enable unlocking the potential of employing a model-based framework in the LAI preclinical and clinical space. This review provides a brief overview of the LAI development process before delving deeper into the current status of modeling and simulation approaches in characterizing the preclinical and clinical LAI pharmacokinetics, focused on aqueous crystalline suspensions. A closer look is provided on in vitro release methods, available biopharmaceutical models and reported in vitro/in vivo correlations (IVIVCs) that may advance LAI drug development. The overview allows identifying the opportunities for use of model-informed drug development approaches and potential gaps where further research may be most warranted. Continued investment in improving our understanding of LAI PK across species through translational approaches may facilitate the future development of LAI drug products.
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Affiliation(s)
- Maxime Siemons
- Janssen R&D, Johnson & Johnson, Turnhoutseweg 30, Beerse, Belgium.
| | - Bram Schroyen
- Janssen R&D, Johnson & Johnson, Turnhoutseweg 30, Beerse, Belgium
| | - Nicolas Darville
- Janssen R&D, Johnson & Johnson, Turnhoutseweg 30, Beerse, Belgium
| | - Navin Goyal
- Janssen R&D, Johnson & Johnson, Turnhoutseweg 30, Beerse, Belgium
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Dabke A, Ghosh S, Dabke P, Sawant K, Khopade A. Revisiting the in-vitro and in-vivo considerations for in-silico modelling of complex injectable drug products. J Control Release 2023; 360:185-211. [PMID: 37353161 DOI: 10.1016/j.jconrel.2023.06.029] [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: 01/28/2023] [Revised: 05/24/2023] [Accepted: 06/19/2023] [Indexed: 06/25/2023]
Abstract
Complex injectable drug products (CIDPs) have often been developed to modulate the pharmacokinetics along with efficacy for therapeutic agents used for remediation of chronic disorders. The effective development of CIDPs has exhibited complex kinetics associated with multiphasic drug release from the prepared formulations. Consequently, predictability of pharmacokinetic modelling for such CIDPs has been difficult and there is need for advanced complex computational models for the establishment of accurate prediction models for in-vitro-in-vivo correlation (IVIVC). The computational modelling aims at supplementing the existing knowledge with mathematical equations to develop formulation strategies for generation of predictable and discriminatory IVIVC. Such an approach would help in reduction of the burden of effect of hidden factors on preclinical to clinical translations. Computational tools like physiologically based pharmacokinetics (PBPK) modelling have combined physicochemical and physiological properties along with IVIVC characteristics of clinically used formulations. Such techniques have helped in prediction and understanding of variability in pharmacodynamic parameters of potential generic products to clinically used formulations like Doxil®, Ambisome®, Abraxane® in healthy and diseased population using mathematical equations. The current review highlights the important formulation characteristics, in-vitro, preclinical in-vivo aspects which need to be considered while developing a stimulatory predictive PBPK model in establishment of an IVIVC and in-vitro-in-vivo relationship (IVIVR).
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Affiliation(s)
- Amit Dabke
- Faculty of Pharmacy, Kalabhavan Campus, The Maharaja Sayajirao University of Baroda, Vadodara, Gujarat 390001, India; Formulation Research & Development- Biopharmaceutics, Sun Pharmaceutical Industries Ltd, Vadodara, Gujarat 390012, India
| | - Saikat Ghosh
- Faculty of Pharmacy, Kalabhavan Campus, The Maharaja Sayajirao University of Baroda, Vadodara, Gujarat 390001, India
| | - Pallavi Dabke
- Faculty of Pharmacy, Kalabhavan Campus, The Maharaja Sayajirao University of Baroda, Vadodara, Gujarat 390001, India
| | - Krutika Sawant
- Faculty of Pharmacy, Kalabhavan Campus, The Maharaja Sayajirao University of Baroda, Vadodara, Gujarat 390001, India.
| | - Ajay Khopade
- Faculty of Pharmacy, Kalabhavan Campus, The Maharaja Sayajirao University of Baroda, Vadodara, Gujarat 390001, India; Formulation Research & Development- Novel Drug Delivery Systems, Sun Pharmaceutical Industries Ltd, Vadodara, Gujarat 390012, India.
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