Application Simulation
Intended-use scenario-based applications:
DDI
Application Case Examples
Case-scenario of an industry-application PBPK bottom-up modeling approach used to evaluate the DDI potential of acalabrutinib and its active metabolite, with CYP3A inhibitors and inducers [149].
Model Template Development
Türk’s paper describes a comprehensive workflow of DDI module in PK-Sim and the Supplementary Materials to this manuscript were compiled as one comprehensive reference manual with transparent documentation of the model performance to support DDI investigations during drug development, labeling, and submission for regulatory approval of new drugs [145].
Special Populations / Organ Impairment
Pediatrics
Yun’s paper determined the appropriateness of the virtual individual creating algorithm in PK-Sim® in predicting PK parameters and their variability in children by comparing a model output, clearance, to observed data. Identified the critical system specific input parameters within a pediatric PBPK model structure for estimating exposure in children via a sensitivity analysis [147].
A brief overview of the development of pediatric physiologically based pharmacokinetic (PPBPK) models, the challenges of uncertain systems information, and finally performance verification considering recent regulatory guidance [138].
Pregnancy
These manuscripts provide overview of pregnancy model in PK-Sim and its major aspect of the model and physiology changes [132]
Organ Impairment
Reviews
PBPK predictions can help determine the need and timing of organ impairment study. It may be suitable for predicting the impact of RI on PK of drugs predominantly cleared by metabolism with varying contribution of renal clearance [136].
CKD
The renal diseases also affect drug metabolization by the liver. Tan et al. provides a comprehensive workflow used for investigation of pharmacokinetics on patients with CKD [144].
Liver
PBPK Modeling for prospective dose recommendations and efficacy/safety assessment in special populations (when consistent clinical data are lacking). Example for a PBPK model to predict the effect of moderate and severe hepatic impairment on the PK of alectinib to best inform clinical study design [141].
Regulatory Review
This report reviews the use of PBPK in decision-making during regulatory review. The report also discusses the challenges encountered when PBPK modeling and simulation were used in these cases and recommends approaches to facilitating full utilization of this tool.It also summarize general schemes of PBPK simulation and propose procedures to obtain necessary data to construct PBPK models. In order to fully utilize PBPK in drug development and regulatory review, it is critical to adequately define mechanisms of drug disposition and understand general physiological perturbations related to diseases,age, and organ dysfunction [148].
This white Paper summarises the FDA's view how a framework for evidential criteria for PBPK models can be established. With that the FDA reached out to the scientific community to stimulate a discussion about this topic [137].
Overview on use of PBPK for submissions to the FDA. Discusses limitations and knowledge gaps in integration of PBPK to inform regulatory decision making, as well as the importance of scientific engagement with drug developers who intend to use this approach [135].
Simulation (i.e. application) design / strategy considerations:
Population-level vs mean
This case study for Caffeine shows that individual pharmacokinetic profiles can be predicted more accurately by considering individual attributes and that personalized PBPK models could be a valuable tool for model informed precision dosing approaches in the future [134].
Workflow Review
This review of several case studies provides is for a better understanding of the absorption, distribution, metabolism and excretion (ADME) workflow of a drug candidate, and the applications to increase efficiency, reduce the need for animal studies, and perhaps to replace clinical trials. The regulatory acceptance and industrial practices around PBPK modeling and simulation is also discussed [150].
Hypothesis generation
The aim of this paper was to develop an analysis framework to investigate whether population modelling approach can be used to estimate PBPK model parameters from clinical PK data and establish the required criteria for such estimations [131].
Regulatory Confidence
It is a perspective case of workshop entitled “Application of Physiologically-based Pharmacokinetic (PBPK) Modeling to Support Dose Selection” was hosted on March 10, 2014 by the US Food and Drug Administration (FDA) at its White Oak Campus in Silver Spring, MD. The workshop endeavored to (i) assess the current state of knowledge in the application of PBPK in regulatory decision-making, and (ii) share and discuss best practices in the use of PBPK modeling to inform dose selection in specific patient populations [146]
This white Paper summarises the FDA's view how a framework for evidential criteria for PBPK models can be established. With that the FDA reached out to the scientific community to stimulate a discussion about this topic [137].
Case-based strategies for different application scenarios
This work presents a systematic assessment of the current challenges to establishing confidence in PBPK models with respect to parameter estimation and model verification in each of the three major areas of PBPK application absorption prediction, exposure prediction in a target population, and DDI risk assessment during drug development [142].
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