Prediction of oral clearance fromin vitrometabolic data using recombinant CYPs: Comparison among well-stirred, parallel-tube, distributed and dispersion models

A Physiologically-Based Pharmacokinetic Model for Cannabidiol in Healthy Adults, Hepatically-Impaired Adults, and Children

Cannabidiol (CBD) is available as a prescription oral drug that is indicated for the treatment of some types of epilepsy in children and adults. CBD is also available over-the-counter and is used to self-treat a variety of other ailments, including pain, anxiety, and insomnia. Accordingly, CBD may be consumed with other medications, resulting in possible CBD-drug interactions. Such interactions can be predicted in healthy and hepatically-impaired (HI) adults and in children through physiologically based pharmacokinetic (PBPK) modeling and simulation. These PBPK models must be populated with CBD-specific parameters, including the enzymes that metabolize CBD in adults. In vitro reaction phenotyping experiments showed that UDP-glucuronosyltransferases (UGTs, 80%), particularly UGT2B7 (64%), were the major contributors to CBD metabolism in adult human liver microsomes. Among the cytochrome P450s (CYPs) tested, CYP2C19 (5.7%) and CYP3A (6.5%) were the major CYPs responsible for CBD metabolism. Using these and other physicochemical parameters, a CBD PBPK model was developed and validated for healthy adults. This model was then extended to predict CBD systemic exposure in HI adults and children. Our PBPK model successfully predicted CBD systemic exposure in both populations within 0.5- to 2-fold of the observed values. In conclusion, we developed and validated a PBPK model to predict CBD systemic exposure in healthy and HI adults and children. This model can be used to predict CBD-drug or CBD-drug-disease interactions in these populations. SIGNIFICANCE STATEMENT: Our PBPK model successfully predicted CBD systemic exposure in healthy and hepatically-impaired adults, as well as children with epilepsy. This model could be used in the future to predict CBD-drug or CBD-drug-disease interactions in these special populations.

In Vitro Hepatic Models to Assess Herb-Drug Interactions: Approaches and Challenges

A newfound appreciation for the benefits of herbal treatments has emerged in recent decades. However, herbal medication production still needs to establish standardized protocols that adhere to strict guidelines for quality assurance and risk minimization. Although the therapeutic effects of herbal medicines are extensive, the risk of herb-drug interactions remains a serious concern, limiting their use. Therefore, a robust, well-established liver model that can fully represent the liver tissue is required to study potential herb-drug interactions to ensure herbal medicines' safe and effective use. In light of this, this mini review investigates the existing in vitro liver models applicable to detecting herbal medicines' toxicity and other pharmacological targets. This article analyzes the benefits and drawbacks of existing in vitro liver cell models. To maintain relevance and effectively express the offered research, a systematic strategy was employed to search for and include all discussed studies. In brief, from 1985 to December 2022, the phrases "liver models", "herb-drug interaction", "herbal medicine", "cytochrome P450", "drug transporters pharmacokinetics", and "pharmacodynamics" were combined to search the electronic databases PubMed, ScienceDirect, and the Cochrane Library.

Prediction of Drug Clearance from Enzyme and Transporter Kinetics

Accurate estimation of in vivo clearance in human is pivotal to determine the dose and dosing regimen for drug development. In vitro-in vivo extrapolation (IVIVE) has been performed to predict drug clearance using empirical and physiological scalars. Multiple in vitro systems and mathematical modeling techniques have been employed to estimate in vivo clearance. The models for predicting clearance have significantly improved and have evolved to become more complex by integrating multiple processes such as drug metabolism and transport as well as passive diffusion. This chapter covers the use of conventional as well as recently developed methods to predict metabolic and transporter-mediated clearance along with the advantages and disadvantages of using these methods and the associated experimental considerations. The general approaches to improve IVIVE by use of appropriate scalars, incorporation of extrahepatic metabolism and transport and application of physiologically based pharmacokinetic (PBPK) models with proteomics data are also discussed. The chapter also provides an overview of the advantages of using such dynamic mechanistic models over static models for clearance predictions to improve IVIVE.

Human hepatocyte assessment of imatinib drug-drug interactions - complexities in clinical translation

AIM

Inducers and inhibitors of CYP3A, such as ritonavir and efavirenz, may be used as part of the highly active antiretroviral therapy (HAART) to treat HIV patients. HIV patients with chronic myeloid leukemia or gastrointestinal stromal tumour may need imatinib, a CYP3A4 substrate with known exposure response-relationships. Administration of imatinib to patients on ritonavir or efavirenz may result in altered imatinib exposure leading to increased toxicity or failure of therapy, respectively. We used primary human hepatocyte cultures to evaluate the magnitude of interaction between imatinib and ritonavir/efavirenz.

METHODS

Hepatocytes were pre-treated with vehicle, ritonavir, ketoconazole, efavirenz or rifampicin, and the metabolism of imatinib was characterized over time. Concentrations of imatinib and metabolite were quantitated in combined lysate and medium, using LC-MS.

RESULTS

The predicted changes in imatinib CLoral (95% CI) with ketoconazole, ritonavir, rifampicin and efavirenz were 4.0-fold (0, 9.2) lower, 2.8-fold (0.04, 5.5) lower, 2.9-fold (2.2, 3.5) higher and 2.0-fold (0.42, 3.5) higher, respectively. These predictions were in good agreement with clinical single dose drug-drug interaction studies, but not with reports of imatinib interactions at steady-state. Alterations in metabolism were similar after acute or chronic imatinib exposure.

CONCLUSIONS

In vitro human hepatocytes predicted increased clearance of imatinib with inducers and decreased clearance with inhibitors of CYP enzymes. The impact of HAART on imatinib may depend on whether it is being initiated or has already been dosed chronically in patients. Therapeutic drug monitoring may have a role in optimizing imatinib therapy in this patient population.

Potential interactions between HIV drugs, ritonavir and efavirenz and anticancer drug, nilotinib--a study in primary cultures of human hepatocytes that is applicable to HIV patients with cancer

Nilotinib is used to treat chronic myeloid leukemia (CML), and is metabolized by CYP3A. With a black-box warning for QT prolongation, which is exposure dependent, controlling for drug interactions is clinically relevant. Treatments of HIV patients with CML are with HAART drugs, ritonavir and efavirenz, may cause complex drug interactions through CYP3A inhibition or induction. We evaluated the interactions of ritonavir or efavirenz on nilotinib using human hepatocytes and compared these interactions with those of ketoconazole or rifampin, classical CYP3A inhibitor and inducer, respectively. Hepatocytes were treated with vehicle, ritonavir (10 μM), ketoconazole (10 μM), efavirenz (10 μM), or rifampin (10 μM) for 5 days. On day 5, nilotinib (3 μM) was coincubated for an additional 24-48 hours. The concentrations of nilotinib were quantitated in collected samples (combined lysate and medium) by LC-MS. Apparent intrinsic clearance (CL(int,app)) of nilotinib was lowered 5.8- and 3.1-fold, respectively, by ritonavir and ketoconazole. Efavirenz and rifampin increased the CL(int,app) of nilotinib by 2.1- and 4.1-fold, respectively. The clinically recommended dose (300 mg twice daily) of nilotinib may have to be reduced substantially (150 mg once daily) or increased (400 mg thrice daily), respectively, to achieve desired drug exposure, when ritonavir or efavirenz is co-administered.

Ritonavir and efavirenz significantly alter the metabolism of erlotinib--an observation in primary cultures of human hepatocytes that is relevant to HIV patients with cancer

Erlotinib is approved for the treatment of non-small cell lung and pancreatic cancers, and is metabolized by CYP3A4. Inducers and inhibitors of CYP3A enzymes such as ritonavir and efavirenz, respectively, may be used as part of the highly active antiretroviral therapy drugs to treat patients with human immunodeficiency virus (HIV). When HIV patients with a malignancy need treatment with erlotinib, there is a potential of as-yet-undefined drug-drug interaction. We evaluated these interactions using human hepatocytes benchmarked against the interaction of erlotinib with ketoconazole and rifampin, the archetype cytochrome P450 inhibitor and inducer, respectively. Hepatocytes were treated with vehicle [0.1% dimethylsulfoxide, ritonavir (10 μM)], ketoconazole (10 μM), efavirenz (10 μM), or rifampin (10 μM) for 4 days. On day 5, erlotinib (5 μM) was incubated with the above agents for another 24-48 hours. Concentrations of erlotinib and O-desmethyl erlotinib were quantitated in collected samples (combined lysate and medium) using liquid chromatography and tandem mass spectrometry. The half-life (t(½)) of erlotinib increased from 10.6 ± 2.6 to 153 ± 80 and 23.9 ± 4.8 hours, respectively, upon treatment with ritonavir and ketoconazole. The apparent intrinsic clearance (C(Lint, app)) of erlotinib was lowered 16-fold by ritonavir and 1.9-fold by ketoconazole. Efavirenz and rifampin decreased t1/2 of erlotinib from 10.3 ± 1.1 to 5.0 ± 1.5 and 3.4 ± 0.2 hours, respectively. Efavirenz and rifampin increased the C(Lint, app) of erlotinib by 2.2- and 2-fold, respectively. Our results suggest that to achieve desired drug exposure, the clinically used dose (150 mg daily) of erlotinib may have to be significantly reduced (25 mg every other day) or increased (300 mg daily), respectively, when ritonavir or efavirenz is coadministered.

Prediction of hepatic clearance in human from in vitro data for successful drug development

The in vivo metabolic clearance in human has been successfully predicted by using in vitro data of metabolic stability in cryopreserved preparations of human hepatocytes. In the predictions by human hepatocytes, the systematic underpredictions of in vivo clearance have been commonly observed among different datasets. The regression-based scaling factor for the in vitro-to-in vivo extrapolation has mitigated discrepancy between in vitro prediction and in vivo observation. In addition to the elimination by metabolic degradation, the important roles of transporter-mediated hepatic uptake and canalicular excretion have been increasingly recognized as a rate-determining step in the hepatic clearance. It has been, therefore, proposed that the in vitro assessment should allow the evaluation of clearances for both transporter(s)-mediated uptake/excretion and metabolic degradation. This review first outlines the limited ability of subcellular fractions such as liver microsomes to predict hepatic clearance in vivo. It highlights the advantages of cryopreserved human hepatocytes as one of the versatile in vitro systems for the prediction of in vivo metabolic clearance in human at the early development stage. The following section discusses the mechanisms underlying the systematic underprediction of in vivo intrinsic clearance by hepatocytes. It leads to the proposal for the assessment of hepatic uptake clearance as one of the kinetically important determinants for accurate predictions of hepatic clearance in human. The judicious combination of advanced technologies and understandings for the drug disposition allows us to rationally optimize new chemical entities to the drug candidate with higher probability of success during the clinical development.

Prediction of drug distribution within blood

Drug distribution in blood, defined as drug blood-to-plasma concentration ratio (R(b)), is a fundamental pharmacokinetic parameter. It relates the plasma clearance to the blood clearance, enabling the physiological interpretation of this parameter. Although easily experimentally determined, R(b) values are lacking for the vast majority of drugs. We present a systematic approach using mechanistic, partial least squares (PLS) regression and artificial neural network (ANN) models to relate various in vitro and in silico molecular descriptors to a dataset of 93 drug R(b) values collected in the literature. The ANN model resulted in the best overall approach, with r(2)=0.927 and r(2)=0.871 for the train and the test sets, respectively. PLS regression presented r(2)=0.557 for the train and r(2)=0.656 for the test set. The mechanistic model provided the worst results, with r(2)=0.342 and, additionally, is limited to drugs with a basic ionised group with pKa<7. The ANN model for drug distribution in blood can be a valuable tool in clinical pharmacokinetics as well as in new drug design, providing predictions of R(b) with a percentage of correct values within a 1.25-fold error of 86%, 84% and 87% in the train, test and validation set of data.

Hepatocytes—the choice to investigate drug metabolism and toxicity in man: In vitro variability as a reflection of in vivo

The pharmaceutical industry is committed to marketing safer drugs with fewer side effects, predictable pharmacokinetic properties and quantifiable drug-drug interactions. Drug metabolism is a major determinant of drug clearance and interindividual pharmacokinetic differences, and an indirect determinant of the clinical efficacy and toxicity of drugs. Progressive advances in the knowledge of metabolic routes and enzymes responsible for drug biotransformation have contributed to understanding the great metabolic variations existing in human beings. Phenotypic as well genotypic differences in the expression of the enzymes involved in drug metabolism are the main causes of this variability. However, only a minor part of phenotypic variability in man is attributable to gene polymorphisms, thus making the definition of a normal liver complex. At present, the use of human in vitro hepatic models at early preclinical stages means that the process of selecting drug candidates is becoming much more rational. Cultured human hepatocytes are considered to be the closest model to human liver. However, the fact that hepatocytes are located in a microenvironment that differs from that of the cell in the liver raises the question: to what extent does drug metabolism variability observed in vitro actually reflect that of the liver in vivo? By comparing the metabolism of a model compound both in vitro and in vivo in the same individual, a good correlation between the in vitro and in vivo relative abundance of oxidized metabolites and the hydrolysis of the compound was observed. Thus, it is reasonable to consider that the variability observed in human hepatocytes reflects the existing phenotypic heterogeneity of the P450 expression in human liver.

Drug disposition of chiral and achiral drug substrates metabolized by cytochrome P450 2D6 isozyme: case studies, analytical perspectives and developmental implications

The concepts of drug development have evolved over the last few decades. Although number of novel chemical entitities belonging to varied classes have made it to the market, the process of drug development is challenging, intertwined as it is with complexities and uncertainities. The intention of this article is to provide a comprehensive review of novel chemical entities (NCEs) that are substrates to cytochrome P450 (CYP) 2D6 isozyme. Topics covered in this review aim: (1) to provide a framework of the importance of CYP2D6 isozyme in the biotransformation of NCEs as stand-alones and/or in conjunction with other CYP isozymes; (2) to provide several case studies of drug disposition of important drug substrates, (3) to cover key analytical perspectives and key assay considerations to assess the role and involvement of CYP2D6, and (4) to elaborate some important considerations from the development point of view. Additionally, wherever applicable, special emphasis is provided on chiral drug substrates in the various subsections of the review.