In-Depth Analysis of Physiologically Based Pharmacokinetic (PBPK) Modeling Utilization in Different Application Fields Using Text Mining Tools
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In the past decade, only a small number of papers have elaborated on the application of physiologically based pharmacokinetic (PBPK) modeling across different areas. In this review, an in-depth analysis of the distribution of PBPK modeling in relation to its application in various research topics and model validation was conducted by text mining tools. Orange 3.32.0, an open-source data mining program was used for text mining. PubMed was used for data retrieval, and the collected articles were analyzed by several widgets. A total of 2699 articles related to PBPK modeling met the predefined criteria. The number of publications per year has been rising steadily. Regarding the application areas, the results revealed that 26% of the publications described the use of PBPK modeling in early drug development, risk assessment and toxicity assessment, followed by absorption/formulation modeling (25%), prediction of drug-disease interactions (20%), drug-drug interactions (DDIs) (17%) and pediatr...ic drug development (12%). Furthermore, the analysis showed that only 12% of the publications mentioned model validation, of which 51% referred to literature-based validation and 26% to experimentally validated models. The obtained results present a valuable review of the state-of-the-art regarding PBPK modeling applications in drug discovery and development and related fields.
Keywords:
modeling and simulations (M&S) / physiologically based biopharmaceutics modeling (PBBM) / physiologically based pharmacokinetic modeling (PBPK) / text mining / topic modelingSource:
Pharmaceutics, 2023, 15, 1Publisher:
- MDPI
Funding / projects:
DOI: 10.3390/pharmaceutics15010107
ISSN: 1999-4923
PubMed: 36678737
WoS: 000928378700001
Scopus: 2-s2.0-85146623715
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PharmacyTY - JOUR AU - Krstevska, Aleksandra AU - Đuriš, Jelena AU - Ibrić, Svetlana AU - Cvijić, Sandra PY - 2023 UR - https://farfar.pharmacy.bg.ac.rs/handle/123456789/4420 AB - In the past decade, only a small number of papers have elaborated on the application of physiologically based pharmacokinetic (PBPK) modeling across different areas. In this review, an in-depth analysis of the distribution of PBPK modeling in relation to its application in various research topics and model validation was conducted by text mining tools. Orange 3.32.0, an open-source data mining program was used for text mining. PubMed was used for data retrieval, and the collected articles were analyzed by several widgets. A total of 2699 articles related to PBPK modeling met the predefined criteria. The number of publications per year has been rising steadily. Regarding the application areas, the results revealed that 26% of the publications described the use of PBPK modeling in early drug development, risk assessment and toxicity assessment, followed by absorption/formulation modeling (25%), prediction of drug-disease interactions (20%), drug-drug interactions (DDIs) (17%) and pediatric drug development (12%). Furthermore, the analysis showed that only 12% of the publications mentioned model validation, of which 51% referred to literature-based validation and 26% to experimentally validated models. The obtained results present a valuable review of the state-of-the-art regarding PBPK modeling applications in drug discovery and development and related fields. PB - MDPI T2 - Pharmaceutics T1 - In-Depth Analysis of Physiologically Based Pharmacokinetic (PBPK) Modeling Utilization in Different Application Fields Using Text Mining Tools VL - 15 IS - 1 DO - 10.3390/pharmaceutics15010107 ER -
@article{ author = "Krstevska, Aleksandra and Đuriš, Jelena and Ibrić, Svetlana and Cvijić, Sandra", year = "2023", abstract = "In the past decade, only a small number of papers have elaborated on the application of physiologically based pharmacokinetic (PBPK) modeling across different areas. In this review, an in-depth analysis of the distribution of PBPK modeling in relation to its application in various research topics and model validation was conducted by text mining tools. Orange 3.32.0, an open-source data mining program was used for text mining. PubMed was used for data retrieval, and the collected articles were analyzed by several widgets. A total of 2699 articles related to PBPK modeling met the predefined criteria. The number of publications per year has been rising steadily. Regarding the application areas, the results revealed that 26% of the publications described the use of PBPK modeling in early drug development, risk assessment and toxicity assessment, followed by absorption/formulation modeling (25%), prediction of drug-disease interactions (20%), drug-drug interactions (DDIs) (17%) and pediatric drug development (12%). Furthermore, the analysis showed that only 12% of the publications mentioned model validation, of which 51% referred to literature-based validation and 26% to experimentally validated models. The obtained results present a valuable review of the state-of-the-art regarding PBPK modeling applications in drug discovery and development and related fields.", publisher = "MDPI", journal = "Pharmaceutics", title = "In-Depth Analysis of Physiologically Based Pharmacokinetic (PBPK) Modeling Utilization in Different Application Fields Using Text Mining Tools", volume = "15", number = "1", doi = "10.3390/pharmaceutics15010107" }
Krstevska, A., Đuriš, J., Ibrić, S.,& Cvijić, S.. (2023). In-Depth Analysis of Physiologically Based Pharmacokinetic (PBPK) Modeling Utilization in Different Application Fields Using Text Mining Tools. in Pharmaceutics MDPI., 15(1). https://doi.org/10.3390/pharmaceutics15010107
Krstevska A, Đuriš J, Ibrić S, Cvijić S. In-Depth Analysis of Physiologically Based Pharmacokinetic (PBPK) Modeling Utilization in Different Application Fields Using Text Mining Tools. in Pharmaceutics. 2023;15(1). doi:10.3390/pharmaceutics15010107 .
Krstevska, Aleksandra, Đuriš, Jelena, Ibrić, Svetlana, Cvijić, Sandra, "In-Depth Analysis of Physiologically Based Pharmacokinetic (PBPK) Modeling Utilization in Different Application Fields Using Text Mining Tools" in Pharmaceutics, 15, no. 1 (2023), https://doi.org/10.3390/pharmaceutics15010107 . .
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