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Kollipara S, Bhattiprolu AK, Boddu R, Ahmed T, Chachad S. Best Practices for Integration of Dissolution Data into Physiologically Based Biopharmaceutics Models (PBBM): A Biopharmaceutics Modeling Scientist Perspective. AAPS PharmSciTech 2023; 24:59. [PMID: 36759492 DOI: 10.1208/s12249-023-02521-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2022] [Accepted: 01/24/2023] [Indexed: 02/11/2023] Open
Abstract
Dissolution is considered as a critical input into physiologically based biopharmaceutics models (PBBM) as it governs in vivo exposure. Despite many workshops, initiatives by academia, industry, and regulatory, wider practices are followed for dissolution data input into PBBM models. Due to variety of options available for dissolution data input into PBBM models, it is important to understand pros, cons, and best practices while using specific dissolution model. This present article attempts to summarize current understanding of various dissolution models and data inputs in PBBM software's and aims to discuss practical challenges and ways to overcome such scenarios. Different approaches to incorporate dissolution data for immediate, modified, and delayed release formulations are discussed in detail. Common challenges faced during fitting of z-factor are discussed along with novel approach of dissolution data incorporation using P-PSD model. Ways to incorporate dissolution data for MR formulations using Weibull and IVIVR approaches were portrayed with examples. Strategies to incorporate dissolution data for DR formulations was depicted along with practical aspects. Approaches to generate virtual dissolution profiles, using Weibull function, DDDPlus, and time scaling for defining dissolution safe space, and strategies to generate virtual dissolution profiles for justifying single and multiple dissolution specifications were discussed. Finally, novel ways to integrate dissolution data for complex products such as liposomes, data from complex dissolution systems, importance of precipitation, and bio-predictive ability of QC media for evaluation of CBA's impact were discussed. Overall, this article aims to provide an easy guide for biopharmaceutics modeling scientist to integrate dissolution data effectively into PBBM models.
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Affiliation(s)
- Sivacharan Kollipara
- Biopharmaceutics Group, Global Clinical Management, Integrated Product Development Organization (IPDO), Dr. Reddy's Laboratories Ltd, Bachupally, Medchal Malkajgiri District, Hyderabad, 500 090, Telangana, India
| | - Adithya Karthik Bhattiprolu
- Biopharmaceutics Group, Global Clinical Management, Integrated Product Development Organization (IPDO), Dr. Reddy's Laboratories Ltd, Bachupally, Medchal Malkajgiri District, Hyderabad, 500 090, Telangana, India
| | - Rajkumar Boddu
- Biopharmaceutics Group, Global Clinical Management, Integrated Product Development Organization (IPDO), Dr. Reddy's Laboratories Ltd, Bachupally, Medchal Malkajgiri District, Hyderabad, 500 090, Telangana, India
| | - Tausif Ahmed
- Biopharmaceutics Group, Global Clinical Management, Integrated Product Development Organization (IPDO), Dr. Reddy's Laboratories Ltd, Bachupally, Medchal Malkajgiri District, Hyderabad, 500 090, Telangana, India.
| | - Siddharth Chachad
- Biopharmaceutics Group, Global Clinical Management, Integrated Product Development Organization (IPDO), Dr. Reddy's Laboratories Ltd, Bachupally, Medchal Malkajgiri District, Hyderabad, 500 090, Telangana, India
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