Dose Optimization Informed by PBPK Modeling: State-of-the Art and Future

Model-informed drug development (MIDD) is a powerful quantitative approach that plays an integral role in drug development and regulatory review. While applied throughout the life cycle of the development of new drugs, a key application of MIDD is to inform clinical trial design including dose selection and optimization. To date, physiologically-based pharmacokinetic (PBPK) modeling, an established component of the MIDD toolkit, has mainly been used for assessment of drug-drug interactions (DDIs) and consequential dose adjustments in regulatory submissions. As a result of recent scientific advances and growing confidence in the utility of the approach, PBPK models are being increasingly applied to provide dose recommendations for subjects with differing ages, genetics, and disease states. In this review, we present our perspective on the current landscape of regulatory acceptance of PBPK applications supported by relevant case studies. We also discuss the recent progress and future challenges associated with expanding the utility of PBPK models into emerging areas for regulatory decision making, especially dose optimization in highly vulnerable and understudied populations and facilitating diversity in clinical trials.

Physiologically Based Pharmacokinetic Modeling to Investigate the Disease-Drug-Drug Interactions between Voriconazole and Nirmatrelvir/Ritonavir in COVID-19 Patients with CYP2C19 Phenotypes

Coronavirus disease 2019 (COVID-19)-associated pulmonary aspergillosis superinfection with cytokine storm is associated with increased mortality. This study aimed to establish a physiologically-based pharmacokinetic (PK) model to investigate the disease-drug-drug interactions between voriconazole and nirmatrelvir/ritonavir in patients with COVID-19 with elevated interleukin-6 (IL-6) levels carrying various CYP2C19 phenotypes. The model was constructed and validated using PK data on voriconazole, ritonavir, and IL-6, and was subsequently verified against clinical data from 78 patients with COVID-19. As a result, the model predicted voriconazole, ritonavir, and IL-6 PK parameters and drug-drug interaction-related fold changes in healthy subjects and patients with COVID-19 with acceptable prediction error, demonstrating its predictive capability. Simulations indicated ritonavir could increase voriconazole exposure to CYP2C19 intermediate and poor metabolizers rather than decrease it, in contrast to what is indicated in the drug package insert. However, the predicted ritonavir exposures were comparable across subjects. In patients with COVID-19, both ritonavir and IL-6 increased voriconazole trough concentrations, which may lead to CYP2C19 phenotype-dependent overexposure. In conclusion, COVID-19-induced IL-6 elevation and ritonavir increased voriconazole exposure, and the magnitude of interactions was influenced by CYP2C19 phenotype. Thus, caution is warranted when prescribing voriconazole concomitantly with Paxlovid in patients with COVID-19.

Assessment of CYP3A-mediated drug interaction via cytokine (IL-6) elevation for mosunetuzumab using physiologically-based pharmacokinetic modeling

Mosunetuzumab is a CD3/CD20 bispecific antibody. As an on-target effect, transient elevation of interleukin-6 (IL-6) occurs in early treatment cycles. A physiologically-based pharmacokinetic (PBPK) model was developed to assess potential drug interaction caused by IL-6 enzyme suppression on cytochrome P450 3A (CYP3A) during mosunetuzumab treatment. The model's performance in predicting IL-6 CYP3A suppression and subsequent drug-drug interactions (DDIs) was verified using existing clinical data of DDIs caused by chronic and transient IL-6 elevation. Sensitivity analyses were performed for a complete DDI risk assessment. The IL-6 concentration- and time-dependent CYP3A suppression during mosunetuzumab treatment was simulated using PBPK model with incorporation of in vitro IL-6 inhibition data. At clinically approved doses/regimens, the DDI at maximum CYP3A suppression was predicted to be a midazolam maximum drug concentration in plasma (Cmax ) and area under the plasma drug concentration-time curve (AUC) ratio of 1.17 and 1.37, respectively. At the 95th percentile of IL-6 concentration level or when gut CYP3A suppression was considered, the predicted DDI risk for mosunetuzumab remained low (<2-fold). The PBPK-based DDI predictions informed the mosunetuzumab product label to monitor, in early cycles, the concentrations and toxicities for sensitive CYP3A substrates with narrow therapeutic windows.

Unraveling the Effects of Acute Inflammation on Pharmacokinetics: A Model-Based Analysis Focusing on Renal Glomerular Filtration Rate and Cytochrome P450 3A4-Mediated Metabolism

BACKGROUND AND OBJECTIVES: Acute inflammation caused by infections or sepsis can impact pharmacokinetics. We used a model-based analysis to evaluate the effect of acute inflammation as represented by interleukin-6 (IL-6) levels on drug clearance, focusing on renal glomerular filtration rate (GFR) and cytochrome P450 3A4 (CYP3A4)-mediated metabolism.

METHODS

A physiologically based model incorporating renal and hepatic drug clearance was implemented. Functions correlating IL-6 levels with GFR and in vitro CYP3A4 activity were derived and incorporated into the modeling framework. We then simulated treatment scenarios for hypothetical drugs by varying the IL-6 levels, the contribution of renal and hepatic drug clearance, and protein binding. The relative change in observed area under the concentration-time curve (AUC) was computed for these scenarios.

RESULTS

Inflammation showed opposite effects on drug exposure for drugs eliminated via the liver and kidney, with the effect of inflammation being inversely proportional to the extraction ratio (ER). For renally cleared drugs, the relative decrease in AUC was close to 30% during severe inflammation. For CYP3A4 substrates, the relative increase in AUC could exceed 50% for low-ER drugs. Finally, the impact of inflammation-induced changes in drug clearance is smaller for drugs with a larger unbound fraction.

CONCLUSION

This analysis demonstrates differences in the impact of inflammation on drug clearance for different drug types. The effects of inflammation status on pharmacokinetics may explain the inter-individual variability in pharmacokinetics in critically ill patients. The proposed model-based analysis may be used to further evaluate the effect of inflammation, i.e., by incorporating the effect of inflammation on other drug-metabolizing enzymes or physiological processes.

Role of Cytochrome P450 2C9 in COVID-19 Treatment: Current Status and Future Directions

The major human liver drug metabolising cytochrome P450 (CYP) enzymes are downregulated during inflammation and infectious disease state, especially during coronavirus disease 2019 (COVID-19) infection. The influx of proinflammatory cytokines, known as a 'cytokine storm', during severe COVID-19 leads to the downregulation of CYPs and triggers new cytokine release, which further dampens CYP expression. Impaired drug metabolism, along with the inevitable co-administration of drugs or 'combination therapy' in patients with COVID-19 with various comorbidities, could cause drug-drug interactions, thus worsening the disease condition. Genetic variability or polymorphism in CYP2C9 across different ethnicities could contribute to COVID-19 susceptibility. A number of drugs used in patients with COVID-19 are inducers or inhibitors of, or are metabolised by, CYP2C9, and co-administration might cause pharmacokinetic and pharmacodynamic interactions. It is also worth mentioning that some of the COVID-19 drug interactions are due to altered activity of other CYPs including CYP3A4. Isoniazid/rifampin for COVID-19 and tuberculosis co-infection; lopinavir/ritonavir and cobicistat/remdesivir combination therapy; or multi-drug therapy including ivermectin, azithromycin, montelukast and acetylsalicylic acid, known as TNR4 therapy, all improved recovery in patients with COVID-19. However, a combination of CYP2C9 inducers, inhibitors or both, and plausibly different CYP isoforms could lead to treatment failure, hepatotoxicity or serious side effects including thromboembolism or bleeding, as observed in the combined use of azithromycin/warfarin. Further, herbs that are CYP2C9 inducers and inhibitors, showed anti-COVID-19 properties, and in silico predictions postulated that phytochemical compounds could inhibit SARS-CoV-2 virus particles. COVID-19 vaccines elicit immune responses that activate cytokine release, which in turn suppresses CYP expression that could be the source of compromised CYP2C9 drug metabolism and the subsequent drug-drug interaction. Future studies are recommended to determine CYP regulation in COVID-19, while recognising the involvement of CYP2C9 and possibly utilising CYP2C9 as a target gene to tackle the ever-mutating SARS-CoV-2.