Applications of Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulation During Regulatory Review

Zhao, Ping; Zhang, L.; Grillo, Joseph A.; Liu, Q.; Bullock, Julie; Moon, Young Jin; Song, Pengfei; Brar, Satjit; Madabushi, Rajanikanth; Wu, Ta C.; Booth, Brian; Rahman, Nam Atiqur; Reynolds, Kellie S.; Berglund, Eva Gil; Lesko, L. J.; Huang, Shiew‐Mei

doi:10.1038/clpt.2010.298

Cited by 442 publications

(382 citation statements)

References 40 publications

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“…Physiologically based pharmacokinetic (PBPK) modeling and simulation have demonstrated its utility in drug product development1 and regulatory assessment 2, 3, 4, 5. PBPK absorption models mathematically and mechanistically connect the physicochemical properties of drug substances, in vitro performance of drug products, and in vivo performance 5.…”

Section: Study Highlightsmentioning

confidence: 99%

IntegratingIn Vitro, Modeling, andIn VivoApproaches to Investigate Warfarin Bioequivalence

Zhang

Wen

Fan

et al. 2017

CPT Pharmacometrics Syst. Pharmacol.

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We demonstrate the use of modeling and simulation to investigate bioequivalence (BE) concerns raised about generic warfarin products. To test the hypothesis that the loss of isopropyl alcohol and slow dissolution in acidic pH has significant impact on the pharmacokinetics of warfarin sodium tablets, we conducted physiologically based pharmacokinetic absorption modeling and simulation using formulation factors or in vitro dissolution profiles as input parameters. Sensitivity analyses indicated that warfarin pharmacokinetics was not sensitive to solubility, particle size, density, or dissolution rate in pH 4.5, but was affected by dissolution rate in pH 6.8 and potency. Virtual BE studies suggested that stressed warfarin sodium tablets with slow dissolution rate in pH 4.5 but having similar dissolution rate in pH 6.8 would be bioequivalent to the unstressed warfarin sodium tablets. A four‐way, crossover, single‐dose BE study in healthy subjects was conducted to test the same hypothesis and confirmed the simulation conclusion.

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Section: Study Highlightsmentioning

confidence: 99%

IntegratingIn Vitro, Modeling, andIn VivoApproaches to Investigate Warfarin Bioequivalence

Zhang

Wen

Fan

et al. 2017

CPT Pharmacometrics Syst. Pharmacol.

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“…[50] But predictions performed from PBPK models are more accurate than predictions performed from allometric scaling, [20,21,22] although this is still an extrapolation to children.…”

Section: Discussionmentioning

confidence: 99%

“…PBPK models, as implemented in the software SIMCYP ® [15,16,17,18,19,20] ( SIMCYP Limited, Sheffield, UK), allow the description of the pharmacokinetics of a substance based on a physiological reality. [21] PBPK models are multicompartment models where compartments correspond to predefined organs and tissues of the body for which the interconnections correspond to flows (such as blood).…”

Section: Introductionmentioning

confidence: 99%

Optimal Sampling Times for a Drug and its Metabolite using SIMCYP® Simulations as Prior Information

et al. 2012

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Background: Since 2007, it is mandatory for the pharmaceutical companies to submit a Paediatric Investigation Plan to the Paediatric Committee at the European Medicines Agency for any drug in development in adults, and it often leads to the need to conduct a pharmacokinetic study in children. Pharmacokinetic studies in children raise ethical and methodological issues. Because of limitation of sampling times, appropriate methods, such as the population approach, are necessary for analysis of the pharmacokinetic data. The choice of the pharmacokinetic sampling design has an important impact on the precision of population parameter estimates. Approaches for design evaluation and optimization based on the evaluation of the Fisher information matrix (M F ) have been proposed and are now implemented in several software packages, such as PFIM in R.Objectives: The objectives of this work were to (i) develop a joint population pharmacokinetic model to describe the pharmacokinetic characteristics of a drug S and its active metabolite in children after intravenous drug administration from simulated plasma concentration-time data produced using physiologically based pharmacokinetic (PBPK) predictions; (ii) optimize the pharmacokinetic sampling times for an upcoming clinical study using a multi-response design approach, considering clinical constraints; and iii) evaluate the resulting design taking data below the lower limit of quantification (BLQ) into account.Methods: Plasma concentration-time profiles were simulated in children using a PBPK model previously developed with the software SIMCYP ® for the parent drug and its active metabolite. Data were analysed using non-linear mixed-effect models with the software NONMEM ® , using a joint model for the parent drug and its metabolite. The population pharmacokinetic design, for the future study in 82 children from 2 to 18 years old, each receiving a single dose of the drug, was then optimized using PFIM, assuming identical times for parent and metabolite concentration measurements and considering clinical constraints. Design evaluation was based on the relative standard errors (RSEs) of the parameters of interest. In the final evaluation of the proposed design, an approach was used to assess the possible effect of BLQ concentrations on the design efficiency. This approach consists of rescaling the M F , using, at each sampling time, the probability of observing a concentration BLQ computed from Monte-Carlo simulations.Results: A joint pharmacokinetic model with three compartments for the parent drug and one for its active metabolite, with random effects on four parameters, was used to fit the simulated PBPK concentration-time data. A combined error model best described the residual variability. Parameters and dose were expressed per kilogram of bodyweight. Reaching a compromise between PFIM results and clinical constraints, the optimal design was composed of four samples at 0.1, 1.8, 5 and 10 h after drug injection. This design predicted RSE lower than 30 % for the fo...

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“…Within the last year, the EMA has published a draft guideline on the qualification and reporting of PBPK modeling and simulation for application in drug-drug interactions and pediatric drug development [23]. Similarly, reviews by Zhao et al [24], Wagner et al [25] and Jamei [26] illustrate the contribution of PBPK modeling and simulation in several FDA approvals for a variety of novel compounds. Although to date, no specific waiver of a dedicated renal impairment study based on a PBPK model has been reported, the following case is presented to illustrate the value of mechanistic modeling to inform clinical development in patients with comorbid renal impairment.…”

Section: Role Of Modeling In Lieu Of Renal Impairment Studiesmentioning

confidence: 99%

Update and trends on pharmacokinetic studies in patients with impaired renal function: practical insight into application of the FDA and EMA guidelines

Paglialunga

Offman

Ichhpurani

et al. 2017

Expert Review of Clinical Pharmacology

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Introduction: The incidence of kidney dysfunction increases with age and is highly prevalent among patients with hypertension. Since many therapeutic compounds are primarily eliminated through the kidneys, impaired renal function can have negative consequences on drug disposition, efficacy and safety. Therefore, regulatory agencies such as the Food and Drug Administration (FDA) and European Medicines Agency (EMA) have issued detailed guidelines for new drug applications to determine posology requirements for patients with renal impairment. Areas covered: The current review highlights and contrasts agency requirements for pharmacokinetic renal impairment clinical studies. While many of the guidelines are similar among the two agencies, glomerular filtration rate (GFR) determination and reporting differ. Design considerations for a reduced, full or dialysis renal impairment study, as well as modifications to the FDA's draft guidance are discussed. Furthermore, scenarios where pharmacokinetic modelling analysis can benefit a drug development program are also reviewed. Moreover, practical solutions for patient recruitment challenges are addressed. Expert commentary: We summarize how 'one size does not fit all' for GFR assessment, and recommend when to use certain modalities. Finally, we highlight the need for the pharmaceutical industry to engage therapeutic experts to assist in protocol development for renal impairment studies, as these experts understand the nuances of this special population and recommended guidelines. ARTICLE HISTORY

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Applications of Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulation During Regulatory Review

Cited by 442 publications

References 40 publications

IntegratingIn Vitro, Modeling, andIn VivoApproaches to Investigate Warfarin Bioequivalence

IntegratingIn Vitro, Modeling, andIn VivoApproaches to Investigate Warfarin Bioequivalence

Optimal Sampling Times for a Drug and its Metabolite using SIMCYP® Simulations as Prior Information

Update and trends on pharmacokinetic studies in patients with impaired renal function: practical insight into application of the FDA and EMA guidelines

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