This commentary provides an update on the status of physiologically based pharmacokinetic modeling and simulation at the U.S. Food and Drug Administration's Office of Clinical Pharmacology. Limitations and knowledge gaps in integration of physiologically based pharmacokinetic approach to inform regulatory decision making, as well as the importance of scientific engagement with drug developers who intend to use this approach, are highlighted.

Since 2016, results from physiologically based pharmacokinetic (PBPK) analyses have been routinely found in the clinical pharmacology section of regulatory applications submitted to the US Food and Drug Administration (FDA). In 2018, the Food and Drug Administration's Office of Clinical Pharmacology published a commentary summarizing the application of PBPK modeling in the submissions it received between 2008 and 2017 and its impact on prescribing information. In this commentary, we provide an update on the application of PBPK modeling in submissions received between 2018 and 2019 and highlight a few notable examples.

Using flow cytometric assay and monoclonal anti-dengue Ab, we observed that both anti-E and anti-prM Abs could enhance dengue virus infection in a concentration-dependent but serotype-independent manner. Increases were found in both the percentage of dengue-infected cells and the expression of dengue E and NS1 protein per cell. Dengue virion binding and infection were enhanced on FcR-bearing cells via the Fc-FcγRII pathway. Furthermore, anti-prM Ab also enhanced dengue virion binding and infection on cells lacking FcR, such as BHK-21 or A549 cells, by the mechanism of peptide (CPFLKQNEPEDIDCW)-specific binding. Anti-prM Ab cross-reacted with BHK-21 or A549 cells and recognized self-Ags such as heat shock protein 60. In summary, a novel mechanism of anti-prM Ab-mediated enhancement on dengue virus infection was found to be mediated by dual specific binding to dengue virion and to target cells, in addition to the traditional enhancement on FcR-bearing cells.

Translation of in vitro antiviral activity to the in vivo setting is crucial to identify potentially effective dosing regimens of hydroxychloroquine. In vitro EC50/EC90 values for hydroxychloroquine should be compared to the in vivo free extracellular tissue concentration, which is similar to the free plasma hydroxychloroquine concentration.

The use of computational models in drug development has grown during the past decade. These model‐informed drug development (MIDD) approaches can inform a variety of drug development and regulatory decisions. When used for regulatory decision making, it is important to establish that the model is credible for its intended use. Currently, there is no consensus on how to establish and assess model credibility, including the selection of appropriate verification and validation activities. In this article, we apply a risk‐informed credibility assessment framework to physiologically‐based pharmacokinetic modeling and simulation and hypothesize this evidentiary framework may also be useful for evaluating other MIDD approaches. We seek to stimulate a scientific discussion around this framework as a potential starting point for uniform assessment of model credibility across MIDD. Ultimately, an overarching framework may help to standardize regulatory evaluation across therapeutic products (i.e., drugs and medical devices).

Drug-induced liver injury (DILI) is not only a major concern for all patients requiring drug therapy, but also for the pharmaceutical industry. Many new in vitro assays and pre-clinical animal models are being developed to help screen compounds for the potential to cause DILI. This study demonstrates that mechanistic, mathematical modeling offers a method for interpreting and extrapolating results. The DILIsym™ model (version 1A), a mathematical representation of DILI, was combined with in vitro data for the model hepatotoxicant methapyrilene (MP) to carry out an in vitro to in vivo extrapolation. In addition, simulations comparing DILI responses across species illustrated how modeling can aid in selecting the most appropriate pre-clinical species for safety testing results relevant to humans. The parameter inputs used to predict DILI for MP were restricted to in vitro inputs solely related to ADME (absorption, distribution, metabolism, elimination) processes. MP toxicity was correctly predicted to occur in rats, but was not apparent in the simulations for humans and mice (consistent with literature). When the hepatotoxicity of MP and acetaminophen (APAP) was compared across rats, mice, and humans at an equivalent dose, the species most susceptible to APAP was not susceptible to MP, and vice versa. Furthermore, consideration of variability in simulated population samples (SimPops™) provided confidence in the predictions and allowed examination of the biological parameters most predictive of outcome. Differences in model sensitivity to the parameters were related to species differences, but the severity of DILI for each drug/species combination was also an important factor.

N-acetylcysteine (NAC) is the treatment of choice for acetaminophen poisoning; standard 72-h oral or 21-h intravenous protocols are most frequently used. There is controversy regarding which protocol is optimal and whether the full treatment course is always necessary. It would be challenging to address these questions in a clinical trial. We used DILIsym, a mechanistic simulation of drug-induced liver injury, to investigate optimal NAC treatment after a single acetaminophen overdose for an average patient and a sample population (n ϭ 957). For patients presenting within 24 h of ingestion, we found that the oral NAC protocol preserves more hepatocytes than the 21-h intravenous protocol. In various modeled scenarios, we found that the 21-h NAC infusion is often too short, whereas the full 72-h oral course is often unnecessary. We found that there is generally a good correlation between the time taken to reach peak serum alanine aminotransferase (ALT) and the time taken to clear N-acetyl-p-benzoquinone imine (NAPQI) from the liver. We also found that the most frequently used treatment nomograms underestimate the risk for patients presenting within 8 h of overdose ingestion. V max for acetaminophen bioactivation to NAPQI was the most important variable in the model in determining interpatient differences in susceptibility. In conclusion, DILIsym predicts that the oral NAC treatment protocol, or an intravenous protocol with identical dosing, is superior to the 21-h intravenous protocol and ALT is the optimal available biomarker for discontinuation of the therapy. The modeling also suggests that modification of the current treatment nomograms should be considered.

Tolcapone and entacapone are catechol‐O‐methyltransferase (COMT) inhibitors developed as adjunct therapies for treating Parkinson's disease. While both drugs have been shown to cause mitochondrial dysfunction and inhibition of the bile salt export protein (BSEP), liver injury has only been associated with the use of tolcapone. Here we used a multiscale, mechanistic model (DILIsym®) to simulate the response to tolcapone and entacapone. In a simulated population (SimPops™) receiving recommended doses of tolcapone (200 mg t.i.d.), increases in serum alanine transaminase (ALT) >3× the upper limit of normal (ULN) were observed in 2.2% of the population. In contrast, no simulated patients receiving recommended doses of entacapone (200 mg 8× day) experienced serum ALT >3× ULN. Further, DILIsym® analyses revealed patient‐specific risk factors that may contribute to tolcapone‐mediated hepatotoxicity. In summary, the simulations demonstrated that differences in mitochondrial uncoupling potency and hepatic exposure primarily account for the difference in hepatotoxic potential for tolcapone and entacapone.