The DOI matches its Crossref record; 41 of the 41 references it cites were found in a registry or an index.
Recent Advances in Development and Application of Physiologically-Based Pharmacokinetic (PBPK) Models: a Transition from Academic Curiosity to Regulatory Acceptance
Open accessAbstract
There is a renewed surge of interest in applications of physiologically-based pharmacokinetic (PBPK) models by the pharmaceutical industry and regulatory agencies. Developing PBPK models within a systems pharmacology context allows separation of the parameters pertaining to the animal or human body (the system) from that of the drug and the study design which is essential to develop generic drug-independent models used to extrapolate PK/PD properties in various healthy and patient populations. This has expanded the classical paradigm to a 'predict-learn-confirm-apply' concept. Recently, a number of drug labels are informed by simulation results generated using PBPK models. These cases show that either the simulations are used in lieu of conducting clinical studies or have informed the drug label that otherwise would have been silent in some specific situations. It will not be surprising to see applications of these models in implementing precision dosing at the point of care in the near future.
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![Fig. 2 The distribution of area of applications of 136 regulatory submissions to FDA (until Oct 2014) where PBPK modelling has been applied, updated by Grillo [10] after [14]](/paper-figures/d1046e2f4094474aa604ab0684e7ec80/recent-advances-in-development-and-application-of-physiologically-based-figure-2.jpg)
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Rodgers, T., & Rowland, M. (2006) · Journal of Pharmaceutical Sciences · doi:10.1002/jps.20502 · Cited by 949
Physiologically-Based Pharmacokinetics in Drug Development and Regulatory Science
Rowland, M., Peck, C., & Tucker, G. (2011) · Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev-pharmtox-010510-100540 · Cited by 662
Sager, J. E., Yu, J., Ragueneau, I., & Isoherranen, N. (2015) · Drug Metabolism and Disposition · doi:10.1124/dmd.115.065920 · Cited by 541
Simulation and prediction of in vivo drug metabolism in human populations from in vitro data
Rostami‐Hodjegan, A., & Tucker, G. T. (2007) · Nature Reviews Drug Discovery · doi:10.1038/nrd2173 · Cited by 533
Zhao, P., Zhang, L., Grillo, J. A., Liu, Q., Bullock, J. M., Moon, Y. J., Song, P., Brar, S. S., Madabushi, R., Wu, T. C., et al. (2010) · Clinical Pharmacology & Therapeutics · doi:10.1038/clpt.2010.298 · Cited by 524
Jones, H., Chen, Y., Gibson, C., Heimbach, T., Parrott, N., Peters, S., Snoeys, J., Upreti, V., Zheng, M., & Hall, S. (2015) · Clinical Pharmacology & Therapeutics · doi:10.1002/cpt.37 · Cited by 488
Jamei, M., Dickinson, G. L., & Rostami‐Hodjegan, A. (2009) · Drug Metabolism and Pharmacokinetics · doi:10.2133/dmpk.24.53 · Cited by 377
Self-citationRostami-Hodjegan, A. (2012) · Clinical Pharmacology & Therapeutics · doi:10.1038/clpt.2012.65 · Cited by 331
Poulin, P., & Theil, F. (2002) · Journal of Pharmaceutical Sciences · doi:10.1002/jps.10128 · Cited by 303
Wagner, C., Zhao, P., Pan, Y., Hsu, V, Grillo, J., Huang, S., & Sinha, V (2015) · CPT: Pharmacometrics & Systems Pharmacology · doi:10.1002/psp4.33 · Cited by 276
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Muratov, E. N., Bajorath, J., Sheridan, R. P., Tetko, I. V., Filimonov, D., Poroikov, V., Oprea, T. I., Baskin, I. I., Varnek, A., Roitberg, A., et al. (2020) · Chemical Society Reviews · doi:10.1039/d0cs00098a · Cited by 913
Darwich, A. S., Ogungbenro, K., Vinks, A. A. T. M. M., Powell, J. R., Reny, J., Marsousi, N., Daali, Y., Fairman, D., Cook, J., Lesko, L. J., et al. (2017) · Clinical Pharmacology & Therapeutics · doi:10.1002/cpt.659 · Cited by 287
Cardiovascular disease models: A game changing paradigm in drug discovery and screening
Savoji, H., Mohammadi, M. H., Rafatian, N., Toroghi, M. K., Wang, E. Y., Zhao, Y., Korolj, A., Ahadian, S., & Radisic, M. (2019) · Biomaterials · doi:10.1016/j.biomaterials.2018.09.036 · Cited by 223
Physiologically-based pharmacokinetic models for children: Starting to reach maturation?
Verscheijden, L. F. M., Koenderink, J. B., Johnson, T. N., de Wildt, S. N., & Rüssel, F. G. M. (2020) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2020.107541 · Cited by 153
An in vitro toolbox to accelerate anti-malarial drug discovery and development
Charman, S. A., Andreu, A., Barker, H., Blundell, S. A., Campbell, A., Campbell, M., Chen, G., Chiu, F. C. K., Crighton, E., Katneni, K., et al. (2020) · Malaria Journal · doi:10.1186/s12936-019-3075-5 · Cited by 154
Metadata
- Authors
- Jamei, M.
- Affiliations
- Simcyp (United Kingdom) (GB)
- Corresponding author
- Jamei, Masoud
- ORCID
- Jamei, Masoud
- Venue
- Current Pharmacology Reports
- Published
- 2016-04-14
- Volume
- 2
- Issue
- 3
- Pages
- 161-169
- ISSN
- 2198-641X (ISSN-L)
- PMC
- PMC4856711
- OpenAlex
- W2341647963
- Cited by
- 244
- References
- 41
- Citations by year
- 2026: 10 · 2025: 21 · 2024: 17 · 2023: 29 · 2022: 20 · 2021: 25 · 2020: 31 · 2019: 24 · 2018: 24 · 2017: 37 · 2016: 6
- FWCI
- 4.70
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Current Pharmacology Reports (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- Simcyp Limited (A Certara Company)
- Topics
- Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Pharmaceutical studies and practices
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmacology › Pharmacogenetics and Drug Metabolism
- Keywords
- physiologically based pharmacokinetic modeling, regulatory acceptance, systems pharmacology, precision dosing
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