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Bhalode P, Tian H, Gupta S, Razavi SM, Roman-Ospino A, Talebian S, Singh R, Scicolone JV, Muzzio FJ, Ierapetritou M. Using residence time distribution in pharmaceutical solid dose manufacturing - A critical review. Int J Pharm 2021; 610:121248. [PMID: 34748808 DOI: 10.1016/j.ijpharm.2021.121248] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 10/04/2021] [Accepted: 10/27/2021] [Indexed: 11/18/2022]
Abstract
While continuous manufacturing (CM) of pharmaceutical solid-based drug products has been shown to be advantageous for improving the product quality and process efficiency in alignment with FDA's support of the quality-by-design paradigm (Lee, 2015; Ierapetritou et al., 2016; Plumb, 2005; Schaber, 2011), it is critical to enable full utilization of CM technology for robust production and commercialization (Schaber, 2011; Byrn, 2015). To do so, an important prerequisite is to obtain a detailed understanding of overall process characteristics to develop cost-effective and accurate predictive models for unit operations and process flowsheets. These models are utilized to predict product quality and maintain desired manufacturing efficiency (Ierapetritou et al., 2016). Residence time distribution (RTD) has been a widely used tool to characterize the extent of mixing in pharmaceutical unit operations (Vanhoorne, 2020; Rogers and Ierapetritou, 2015; Teżyk et al., 2015) and manufacturing lines and develop computationally cheap predictive models. These models developed using RTD have been demonstrated to be crucial for various flowsheet applications (Kruisz, 2017; Martinetz, 2018; Tian, 2021). Though extensively used in the literature (Gao et al., 2012), the implementation, execution, evaluation, and assessment of RTD studies has not been standardized by regulatory agencies and can thus lead to ambiguity regarding their accurate implementation. To address this issue and subsequently prevent unforeseen errors in RTD implementation, the presented article aims to aid in developing standardized guidelines through a detailed review and critical discussion of RTD studies in the pharmaceutical manufacturing literature. The review article is divided into two main sections - 1) determination of RTD including different steps for RTD evaluation including experimental approach, data acquisition and pre-treatment, RTD modeling, and RTD metrics and, 2) applications of RTD for solid dose manufacturing. Critical considerations, pertaining to the limitations of RTDs for solid dose manufacturing, are also examined along with a perspective discussion of future avenues of improvement.
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Affiliation(s)
- Pooja Bhalode
- Department of Chemical and Biochemical Engineering, Rutgers - The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Huayu Tian
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, DE 19716, USA
| | - Shashwat Gupta
- Department of Chemical and Biochemical Engineering, Rutgers - The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Sonia M Razavi
- Department of Chemical and Biochemical Engineering, Rutgers - The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Andres Roman-Ospino
- Department of Chemical and Biochemical Engineering, Rutgers - The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Shahrzad Talebian
- Department of Chemical and Biochemical Engineering, Rutgers - The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Ravendra Singh
- Department of Chemical and Biochemical Engineering, Rutgers - The State University of New Jersey, Piscataway, NJ 08854, USA
| | - James V Scicolone
- Department of Chemical and Biochemical Engineering, Rutgers - The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Fernando J Muzzio
- Department of Chemical and Biochemical Engineering, Rutgers - The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Marianthi Ierapetritou
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, DE 19716, USA.
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