In vitro and in vivo methods to assess pharmacokinetic drug– drug interactions in drug discovery and development

Prediction of Drug-Drug Interactions for Highly Plasma Protein Bound Compounds

Accurate prediction of drug-drug interactions (DDI) from in vitro data is important, as it provides insights on clinical DDI risk and study design. Historically, the lower limit of plasma fraction unbound (fu,p) is set at 1% for DDI prediction of highly bound compounds by the regulatory agencies due to the uncertainty of the fu,p measurements. This leads to high false positive DDI predictions for highly bound compounds. The recently published ICH M12 DDI guideline allows the use of experimental fu,p for DDI prediction of highly bound compounds. To further build confidence in DDI prediction of highly bound compounds using experimental fu,p values, we evaluated a set of drugs with fu,p < 1% and clinical DDI > 20% using both basic and mechanistic static models. All the compounds evaluated were flagged for DDI risk with the mechanistic model using experimental fu,p values. There was no false negative DDI prediction. Similarly, using the basic model, the DDI risk of all the compounds was identified except for CYP2D6 inhibition of almorexant. The totality of the data demonstrates that the DDI potential of highly bound compounds can be predicted accurately when actual protein binding numbers are measured.

Neuroimaging and the Investigation of Drug-Drug Interactions Involving Psychedelics

Psychedelic therapies are an emerging class of treatments in psychiatry with great potential, however relatively little is known about their interactions with other commonly used psychiatric medications. As psychedelic therapies become more widespread and move closer to the clinic, they likely will need to be integrated into existing treatment models which may include one or more traditional pharmacological therapies, meaning an awareness of potential drug-drug interactions will become vital. This commentary outlines some of the issues surrounding the study of drug-drug interactions of this type, provides a summary of some of the relevant key results to date, and charts a way forward which relies crucially on multimodal neuroimaging investigations. Studies in humans which combine Positron Emission Tomography (PET) and functional Magnetic Resonance Imaging (fMRI), plus ancillary measures, are likely to provide the most comprehensive assessment of drug-drug interactions involving psychedelics and the relevant effects at multiple levels of the drug response (molecular, functional, and clinical).

Mechanism-based inactivation of cytochromes P450: implications in drug interactions and pharmacotherapy

Cytochrome P40 (CYP) enzymes dominate the metabolism of numerous endogenous and xenobiotic substances. While it is commonly believed that CYP-catalysed reactions result in the detoxication of foreign substances, these reactions can also yield reactive intermediates that can bind to cellular macromolecules to cause cytotoxicity or irreversibly inactivate CYPs that create them.Mechanism-based inactivation (MBI) produces either irreversible or quasi-irreversible inactivation and is commonly caused by CYP metabolic bioactivation to an electrophilic reactive intermediate. Many drugs that have been known to cause MBI in CYPs have been discovered as perpetrators in drug-drug interactions throughout the last 20-30 years.This review will highlight the key findings from the recent literature about the mechanisms of CYP enzyme inhibition, with a focus on the broad mechanistic elements of MBI for widely used drugs linked to the phenomenon. There will also be a brief discussion of the clinical or pharmacokinetic consequences of CYP inactivation with regard to drug interaction and toxicity risk.Gaining knowledge about the selective inactivation of CYPs by common therapeutic drugs helps with the assessment of factors that affect the systemic clearance of co-administered drugs and improves comprehension of anticipated interactions with other drugs or xenobiotics.

Enzyme-mediated drug-drug interactions: a review of in vivo and in vitro methodologies, regulatory guidance, and translation to the clinic

Enzyme-mediated pharmacokinetic drug-drug interactions can be caused by altered activity of drug metabolizing enzymes in the presence of a perpetrator drug, mostly via inhibition or induction. We identified a gap in the literature for a state-of-the art detailed overview assessing this type of DDI risk in the context of drug development. This manuscript discusses in vitro and in vivo methodologies employed during the drug discovery and development process to predict clinical enzyme-mediated DDIs, including the determination of clearance pathways, metabolic enzyme contribution, and the mechanisms and kinetics of enzyme inhibition and induction. We discuss regulatory guidance and highlight the utility of in silico physiologically-based pharmacokinetic modeling, an approach that continues to gain application and traction in support of regulatory filings. Looking to the future, we consider DDI risk assessment for targeted protein degraders, an emerging small molecule modality, which does not have recommended guidelines for DDI evaluation. Our goal in writing this report was to provide early-career researchers with a comprehensive view of the enzyme-mediated pharmacokinetic DDI landscape to aid their drug development efforts.

Ontogeny of Human Liver Aldehyde Oxidase: Developmental Changes and Implications for Drug Metabolism

Despite the increasing importance of aldehyde oxidase (AO) in the drug metabolism of clinical candidates, ontogeny data for AO are limited. The objective of our study was to characterize the age-dependent AO content and activity in the human liver cytosolic fraction (HLC) and human hepatocytes (HH). HLC (n = 121 donors) and HH (n = 50 donors) were analyzed for (1) AO protein content by quantitative proteomics and (2) enzyme activity using carbazeran as a probe substrate. AO activity showed high technical variability and poor correlation with the content in HLC samples, whereas hepatocyte samples showed a strong correlation between the content and activity. Similarly, AO content and activity showed no significant age-dependent differences in HLC samples, whereas the average AO content and activity in hepatocytes increased significantly (∼20-40-fold) from the neonatal levels (0-28 days). Based on the hepatocyte data, the age at which 50% of the adult AO content is reached (age50) was 3.15 years (0.32-13.97 years, 95% CI). Metabolite profiling of carbazeran revealed age-dependent metabolic switching and the role of non-AO mechanisms (glucuronidation and desmethylation) in carbazeran elimination. The content-activity correlation in hepatocytes improved significantly (R2 = 0.95; p < 0.0001) in samples showing <10% contribution of glucuronidation toward the overall metabolism, confirming that AO-mediated oxidation and glucuronidation are the key routes of carbazeran metabolism. Considering the confounding effect of glucuronidation on AO activity, AO content-based ontogeny data are a more direct reflection of developmental changes in protein expression. The comprehensive ontogeny data of AO in HH samples are more reliable than HLC data, which are important for developing robust physiologically based pharmacokinetic models for predicting AO-mediated metabolism in children.

The cytotoxic and antiproliferative properties of ruthenium nitrosyl complexes and their modulation effect on cytochrome P450 in the HepG2 cell line

Ruthenium nitrosyl complexes are actively investigated as antitumor agents. Evaluation of potential interactions between cytochromes P450 (CYPs) with new compounds is carried out regularly during early drug development. In this study we have investigated the cytotoxic and antiproliferative activities of ruthenium nitrosyl complexes with methyl/ethyl esters of nicotinic and isonicotinic acids and γ-picoline against 2D and 3D cultures of human hepatocellular carcinoma HepG2 and non-cancer human lung fibroblasts MRC-5, assessed their photoinduced activity at λrad = 445 nm, and also evaluated their modulating effect on CYP3A4, CYP2C9, and CYP2C19. The study of cytotoxic and antiproliferative activities against 2D and 3D cell models was performed using phenotypic-based high content screening (HCS). The expression of CYP3A4, CYP2C9, and CYP2C19 mRNAs and CYP3A4 protein was examined using target-based HCS. The results of CYP3A4 mRNA expression were confirmed by real-time reverse transcription-polymerase chain reaction (RT-PCR). The ruthenium nitrosyl complexes exhibited a dose-dependent cytotoxic effect against HepG2 and MRC-5 cells. The cytotoxic activity of complexes with ethyl isonicotinate (1) and nicotinate (3, 4) was significantly lower for MRC-5 than for HepG2, for a complex with methyl isonicotinate (2) it was higher for MRC-5 than for HepG2, for a complex with γ-picoline (5) it was comparable for both lines. The antiproliferative effect of complexes 2 and 5 was one order of magnitude higher for MRC-5; for complexes 1, 3, and 4 it was comparable for both lines. The cytotoxic activity of all compounds for 3D HepG2 was lower than for 2D HepG2, with the exception of 4. Photoactivation affected the activity of complex 1 only. Its cytotoxic activity decreased, while the antiproliferative activity increased. The ruthenium nitrosyl complexes 1-4 acted as inducers of CYP3A4 and CYP2C19, while the complex with γ-picoline (5) induced of CYP3A4. Among the studied ruthenium nitrosyl complexes, the most promising potential antitumor compound is the ruthenium compound with methyl nicotinate (4).

A Review of CYP-Mediated Drug Interactions: Mechanisms and In Vitro Drug-Drug Interaction Assessment

Drug metabolism is a major determinant of drug concentrations in the body. Drug-drug interactions (DDIs) caused by the co-administration of multiple drugs can lead to alteration in the exposure of the victim drug, raising safety or effectiveness concerns. Assessment of the DDI potential starts with in vitro experiments to determine kinetic parameters and identify risks associated with the use of comedication that can inform future clinical studies. The diverse range of experimental models and techniques has significantly contributed to the examination of potential DDIs. Cytochrome P450 (CYP) enzymes are responsible for the biotransformation of many drugs on the market, making them frequently implicated in drug metabolism and DDIs. Consequently, there has been a growing focus on the assessment of DDI risk for CYPs. This review article provides mechanistic insights underlying CYP inhibition/induction and an overview of the in vitro assessment of CYP-mediated DDIs.

Update and Application of a Deep Learning Model for the Prediction of Interactions between Drugs Used by Patients with Multiple Sclerosis

Patients with multiple sclerosis (MS) often take multiple drugs at the same time to modify the course of disease, alleviate neurological symptoms and manage co-existing conditions. A major consequence for a patient taking different medications is a higher risk of treatment failure and side effects. This is because a drug may alter the pharmacokinetic and/or pharmacodynamic properties of another drug, which is referred to as drug-drug interaction (DDI). We aimed to predict interactions of drugs that are used by patients with MS based on a deep neural network (DNN) using structural information as input. We further aimed to identify potential drug-food interactions (DFIs), which can affect drug efficacy and patient safety as well. We used DeepDDI, a multi-label classification model of specific DDI types, to predict changes in pharmacological effects and/or the risk of adverse drug events when two or more drugs are taken together. The original model with ~34 million trainable parameters was updated using >1 million DDIs recorded in the DrugBank database. Structure data of food components were obtained from the FooDB database. The medication plans of patients with MS (n = 627) were then searched for pairwise interactions between drug and food compounds. The updated DeepDDI model achieved accuracies of 92.2% and 92.1% on the validation and testing sets, respectively. The patients with MS used 312 different small molecule drugs as prescription or over-the-counter medications. In the medication plans, we identified 3748 DDIs in DrugBank and 13,365 DDIs using DeepDDI. At least one DDI was found for most patients (n = 509 or 81.2% based on the DNN model). The predictions revealed that many patients would be at increased risk of bleeding and bradycardic complications due to a potential DDI if they were to start a disease-modifying therapy with cladribine (n = 242 or 38.6%) and fingolimod (n = 279 or 44.5%), respectively. We also obtained numerous potential interactions for Bruton's tyrosine kinase inhibitors that are in clinical development for MS, such as evobrutinib (n = 434 DDIs). Food sources most often related to DFIs were corn (n = 5456 DFIs) and cow's milk (n = 4243 DFIs). We demonstrate that deep learning techniques can exploit chemical structure similarity to accurately predict DDIs and DFIs in patients with MS. Our study specifies drug pairs that potentially interact, suggests mechanisms causing adverse drug effects, informs about whether interacting drugs can be replaced with alternative drugs to avoid critical DDIs and provides dietary recommendations for MS patients who are taking certain drugs.

DDI-GCN: Drug-drug interaction prediction via explainable graph convolutional networks

Drug-drug interactions (DDI) may lead to unexpected side effects, which is a growing concern in both academia and industry. Many DDIs have been reported, but the underlying mechanisms are not well understood. Predicting and understanding DDIs can help researchers to improve drug safety and protect patient health. Here, we introduce DDI-GCN, a method that utilizes graph convolutional networks (GCN) to predict DDIs based on chemical structures. We demonstrate that this method achieves state-of-the-art prediction performance on the independent hold-out set. It can also provide visualization of structural features associated with DDIs, which can help us to study the underlying mechanisms. To make it easy and accessible to use, we developed a web server for DDI-GCN, which is freely available at http://wengzq-lab.cn/ddi/.

Traditional medicinal plants in the treatment of gastrointestinal parasites in humans: A systematic review and meta-analysis of clinical and experimental evidence

Gastrointestinal (GI) parasites cause significant morbidity and mortality worldwide. The use of conventional antiparasitic drugs is often inhibited due to limited availability, side effects or parasite resistance. Medicinal plants can be used as alternatives or adjuncts to current antiparasitic therapies. This systematic review and meta-analysis aimed to critically synthesise the literature on the efficacy of different plants and plant compounds against common human GI parasites and their toxicity profiles. Searches were conducted from inception to September 2021. Of 5393 screened articles, 162 were included in the qualitative synthesis (159 experimental studies and three randomised control trials [RCTs]), and three articles were included in meta-analyses. A total of 507 plant species belonging to 126 families were tested against different parasites, and most of these (78.4%) evaluated antiparasitic efficacy in vitro. A total of 91 plant species and 34 compounds were reported as having significant in vitro efficacy against parasites. Only a few plants (n = 57) were evaluated for their toxicity before testing their antiparasitic effects. The meta-analyses revealed strong evidence of the effectiveness of Lepidium virginicum L. against Entamoeba histolytica with a pooled mean IC50 of 198.63 μg/mL (95% CI 155.54-241.72). We present summary tables and various recommendations to direct future research.

Comparative analysis of YAP/TEAD inhibitors in 2D and 3D cultures of primary human hepatocytes reveals a novel non-canonical mechanism of CYP induction

Induction of cytochrome P450 (CYP) genes constitutes an important cause of drug-drug interactions and preclinical evaluation of induction liability is mandatory for novel drug candidates. YAP/TEAD signaling has emerged as an attractive target for various oncological indications and multiple chemically distinct YAP/TEAD inhibitors are rapidly progressing towards clinical stages. Here, we tested the liability for CYP induction of a diverse set of YAP/TEAD inhibitors with different modes of action and TEAD isoform selectivity profiles in monolayers and 3D spheroids of primary human hepatocytes (PHH). We found that YAP/TEAD inhibition resulted in broad induction of CYPs in 2D monolayers, whereas, if at all, only marginal induction was seen in spheroid culture. Comprehensive RNA-Seq indicated that YAP/TEAD signaling was increased in 2D culture compared to spheroids, which was paralleled by elevated activities of the interacting transcription factors LXR and ESRRA, likely at least in part due to altered mechanosensing. Inhibition of this YAP/TEAD hyperactivation resulted in an overall reduction of hepatocyte dedifferentiation marked by increased hepatic functionality, including CYPs. These results thus demonstrate that the observed induction is due to on-target effects of the compounds rather than direct activation of xenobiotic sensing nuclear receptors. Combined, the presented data link hepatocyte dedifferentiation to YAP/TEAD dysregulation, reveal a novel non-canonical pathway of CYP induction and highlight the advantage of organotypic 3D cultures to predict clinically relevant pharmacokinetic properties, particularly for atypical induction mechanisms.

Recent advances in measurement of metabolic clearance, metabolite profile and reaction phenotyping of low clearance compounds

INTRODUCTION

Low metabolic clearance is usually a highly desirable property of drug candidates in order to reduce dose and dosing frequency. However, measurement of low clearance can be challenging in drug discovery. A number of new tools have recently been developed to address the gaps in the measurement of intrinsic clearance, identification of metabolites, and reaction phenotyping of low clearance compounds.

AREAS COVERED

The new methodologies of low clearance measurements are discussed, including the hepatocyte relay, HepatoPac®, HμREL®, and spheroid systems. In addition, metabolite formation rate determination and in vivo allometric scaling approaches are covered as alternative methods for low clearance measurements. With these new methods, measurement of ~ 20-fold lower limit of intrinsic clearance can be achieved. The advantages and limitations of each approach are highlighted.

EXPERT OPINION

Although several novel methods have been developed in recent years to address the challenges of low clearance, these assays tend to be time and labor intensive and costly. Future innovations focusing on developing systems with high enzymatic activities, ultra-sensitive universal quantifiable detectors, and artificial intelligence will further enhance our ability to explore the low clearance space.

Drug-drug interactions that alter the exposure of glucuronidated drugs: Scope, UDP-glucuronosyltransferase (UGT) enzyme selectivity, mechanisms (inhibition and induction), and clinical significance

Drug-drug interactions (DDIs) arising from the perturbation of drug metabolising enzyme activities represent both a clinical problem and a potential economic loss for the pharmaceutical industry. DDIs involving glucuronidated drugs have historically attracted little attention and there is a perception that interactions are of minor clinical relevance. This review critically examines the scope and aetiology of DDIs that result in altered exposure of glucuronidated drugs. Interaction mechanisms, namely inhibition and induction of UDP-glucuronosyltransferase (UGT) enzymes and the potential interplay with drug transporters, are reviewed in detail, as is the clinical significance of known DDIs. Altered victim drug exposure arising from modulation of UGT enzyme activities is relatively common and, notably, the incidence and importance of UGT induction as a DDI mechanism is greater than generally believed. Numerous DDIs are clinically relevant, resulting in either loss of efficacy or an increased risk of adverse effects, necessitating dose individualisation. Several generalisations relating to the likelihood of DDIs can be drawn from the known substrate and inhibitor selectivities of UGT enzymes, highlighting the importance of comprehensive reaction phenotyping studies at an early stage of drug development. Further, rigorous assessment of the DDI liability of new chemical entities that undergo glucuronidation to a significant extent has been recommended recently by regulatory guidance. Although evidence-based approaches exist for the in vitro characterisation of UGT enzyme inhibition and induction, the availability of drugs considered appropriate for use as 'probe' substrates in clinical DDI studies is limited and this should be research priority.

Drug-drug interaction potential of SH-1028, a third-generation EGFR-TKI: in vitro and clinical trials

SH-1028 is an irreversible third-generation EGFR tyrosine kinase inhibitor (EGFR-TKI) for the treatment of locally advanced or metastatic non-small cell lung cancer (NSCLC). Considering the possibility of combination therapy in patients with NSCLC, we investigated the drug-drug interaction (DDI) potential of SH-1028 both in vitro and in clinical trials. The in vitro studies were conducted to determine the potential of SH-1028 as a substrate, inducer, or inhibitor of cytochrome P450 (CYP) subtypes. A phase I drug-drug interaction study in healthy volunteers was performed to evaluate the impact of co-administering rifampicin (a strong CYP3A4 inducer) and itraconazole (a strong CYP3A4 inhibitor) on the pharmacokinetics of SH-1028. The in vitro experiments showed that SH-1028 was mainly metabolized by CYP3A4. The activities of CYP1A2, 2B6, 2C19, 2D6 and 3A4 enzymes were slightly inhibited in vitro with SH-1028. SH-1028 has no obvious induction effect on CYP1A2 and CYP2B6 activities, but has potential induction effect on CYP3A4 mRNA expression. However, SH-1028 may not induce or inhibit human CYPs significantly at the clinically expected dose (200 mg). The geometric mean ratios of pharmacokinetic parameters and their corresponding 90% confidence intervals for SH-1028 in combination and alone did not fall within the range of 80-125%. It is speculated that itraconazole and rifampicin affect the metabolism of SH-1028. In the clinical application of SH-1028, special attention should be paid to the interaction between SH-1028 and drugs or foods that affect the activity of CYP3A4. (Clinical trial registration number: CTR20210558).

Photomodulation Approaches to Overcome Antimicrobial Resistance

Photopharmacology is an approach that aims to be an alternative to classical chemotherapy. Herein, the different classes of photoswitches and photocleavage compounds and their biological applications are described. Proteolysis targeting chimeras (PROTACs) containing azobenzene moieties (PHOTACs) and photocleavable protecting groups (photocaged PROTACs) are also mentioned. Furthermore, porphyrins are referenced as successful photoactive compounds in a clinical context, such as in the photodynamic therapy of tumours as well as preventing antimicrobial resistance, namely in bacteria. Porphyrins combining photoswitches and photocleavage systems are highlighted, taking advantage of both photopharmacology and photodynamic action. Finally, porphyrins with antibacterial activity are described, taking advantage of the synergistic effect of photodynamic treatment and antibiotic therapy to overcome bacterial resistance.

General Framework to Quantitatively Predict Pharmacokinetic Induction Drug-Drug Interactions Using In Vitro Data

INTRODUCTION

Metabolic inducers can expose people with polypharmacy to adverse health outcomes. A limited fraction of potential drug-drug interactions (DDIs) have been or can ethically be studied in clinical trials, leaving the vast majority unexplored. In the present study, an algorithm has been developed to predict the induction DDI magnitude, integrating data related to drug-metabolising enzymes.

METHODS

The area under the curve ratio (AUC_ratio) resulting from the DDI with a victim drug in the presence and absence of an inducer (rifampicin, rifabutin, efavirenz, or carbamazepine) was predicted from various in vitro parameters and then correlated with the clinical AUC_ratio (N = 319). In vitro data including fraction unbound in plasma, substrate specificity and induction potential for cytochrome P450s, phase II enzymes and uptake, and efflux transporters were integrated. To represent the interaction potential, the in vitro metabolic metric (IVMM) was generated by combining the fraction of substrate metabolised by each hepatic enzyme of interest with the corresponding in vitro fold increase in enzyme activity (E) value for the inducer.

RESULTS

Two independent variables were deemed significant and included in the algorithm: IVMM and fraction unbound in plasma. The observed and predicted magnitudes of the DDIs were categorised accordingly: no induction, mild, moderate, and strong induction. DDIs were assumed to be well classified if the predictions were in the same category as the observations, or if the ratio between these two was < 1.5-fold. This algorithm correctly classified 70.5% of the DDIs.

CONCLUSION

This research presents a rapid screening tool to identify the magnitude of potential DDIs utilising in vitro data which can be highly advantageous in early drug development.

MecDDI: Clarified Drug-Drug Interaction Mechanism Facilitating Rational Drug Use and Potential Drug-Drug Interaction Prediction

Drug-drug interactions (DDIs) are a major concern in clinical practice and have been recognized as one of the key threats to public health. To address such a critical threat, many studies have been conducted to clarify the mechanism underlying each DDI, based on which alternative therapeutic strategies are successfully proposed. Moreover, artificial intelligence-based models for predicting DDIs, especially multilabel classification models, are highly dependent on a reliable DDI data set with clear mechanistic information. These successes highlight the imminent necessity to have a platform providing mechanistic clarifications for a large number of existing DDIs. However, no such platform is available yet. In this study, a platform entitled "MecDDI" was therefore introduced to systematically clarify the mechanisms underlying the existing DDIs. This platform is unique in (a) clarifying the mechanisms underlying over 1,78,000 DDIs by explicit descriptions and graphic illustrations and (b) providing a systematic classification for all collected DDIs based on the clarified mechanisms. Due to the long-lasting threats of DDIs to public health, MecDDI could offer medical scientists a clear clarification of DDI mechanisms, support healthcare professionals to identify alternative therapeutics, and prepare data for algorithm scientists to predict new DDIs. MecDDI is now expected as an indispensable complement to the available pharmaceutical platforms and is freely accessible at: https://idrblab.org/mecddi/.

Quantitative Cytochrome P450 3A4 Induction Risk Assessment Using Human Hepatocytes Complemented with Pregnane X Receptor-Activating Profiles

Reliable in vitro to in vivo translation of cytochrome P450 (CYP) 3A4 induction potential is essential to support risk mitigation for compounds during pharmaceutical discovery and development. In this study, a linear correlation of CYP3A4 mRNA induction potential in human hepatocytes with the respective pregnane-X receptor (PXR) activation in a reporter gene assay using DPX2 cells was successfully demonstrated for 13 clinically used drugs. Based on this correlation, using rifampicin as a positive control, the magnitude of CYP3A4 mRNA induction for 71 internal compounds at several concentrations up to 10 µM (n = 90) was predicted within 2-fold error for 64% of cases with only a few false positives (19%). Furthermore, the in vivo area under the curve reduction of probe CYP substrates was reasonably predicted for eight marketed drugs (carbamazepine, dexamethasone, enzalutamide, nevirapine, phenobarbital, phenytoin, rifampicin, and rufinamide) using the static net effect model using both the PXR activation and CYP3A4 mRNA induction data. The liver exit concentrations were used for the model in place of the inlet concentrations to avoid false positive predictions and the concentration achieving twofold induction (F2) was used to compensate for the lack of full induction kinetics due to cytotoxicity and solubility limitations in vitro. These findings can complement the currently available induction risk mitigation strategy and potentially influence the drug interaction modeling work conducted at clinical stages. SIGNIFICANCE STATEMENT: The established correlation of CYP3A4 mRNA in human hepatocytes to PXR activation provides a clear cut-off to identify a compound showing an in vitro induction risk, complementing current regulatory guidance. Also, the demonstrated in vitro-in vivo translation of induction data strongly supports a clinical development program although limitations remain for drug candidates showing complex disposition pathways, such as involvement of auto-inhibition/induction, active transport and high protein binding.

Comparative pharmacokinetics of seven bioactive components after oral administration of crude and processed Qixue Shuangbu Prescription in chronic heart failure rats by microdialysis combined with UPLC-MS/MS

ETHNOPHARMACOLOGICAL RELEVANCE

Qixue Shuangbu Prescription (QSP) is a classical traditional Chinese medicine prescription, which has widely used for the treatment of chronic heart failure (CHF). Preliminary clinical studies have shown that the efficacy of processed QSP (P-QSP) in treating CHF is greater than crude QSP (C-QSP). However, the pharmacokinetic characteristics of its major bioactive components under pathological conditions are unclear.

AIM OF STUDY

This study aims to compare pharmacokinetics of seven bioactive components after oral administration of C-QSP and P-QSP in CHF model rats.

MATERIALS AND METHODS

Ginsenoside Rb1, ginsenoside Re, ginsenoside Rg1, ferulic acid, astragaloside IV, calycosin-7-O-β-D-glucoside, and paeoniflorin in QSP were used as the target components. CHF model in rats was induced by the intraperitoneal injection of doxorubicin. A microdialysis combined with UPLC-MS/MS method was first established to compare the pharmacokinetics of seven major bioactive components in CHF model rats after oral administration of C-QSP and P-QSP.

RESULTS

This method was successfully applied to the pharmacokinetic investigation of seven major components of C-QSP and P-QSP following oral administration in CHF model rats. Compared with the C-QSP group, the C_max, AUC_0-t and AUC_0-∞ of ginsenoside Rb1, ginsenoside Re, ginsenoside Rg1, ferulic acid, astragaloside IV and paeoniflorin significantly increased (P < 0.05) in the P-QSP group, which suggested that the absorptivity and bioavailability were increased. Lower T_1/2, MRT_0-t of ginsenoside Rb1, gerulic acid and higher T_1/2, MRT_0-t of ginsenoside Rb1, astragaloside IV, paeoniflorin in the P-QSP group, which indicated that eliminated more quickly or slowly, respectively.

CONCLUSIONS

The pharmacokinetic parameters of bioactive components were significantly changed for better bioavailability and absorption, longer lasting time elimination, which were beneficial for enhancing therapeutic efficacy in the P-QSP group. This study will provide a new perspective to explain the pharmacokinetic-pharmacodynamic correlation of P-QSP on the treatment of CHF.

Inhibitory effect of Selaginella doederleinii hieron on human cytochrome P450

Introduction: Selaginella doederleinii Hieron is a traditional Chinese herbal medicine, the ethyl acetate extract from Selaginella doederleinii (SDEA) showed favorable anticancer potentials. However, the effect of SDEA on human cytochrome P450 enzymes (CYP450) remains unclear. To predict the herb-drug interaction (HDI) and lay the groundwork for further clinical trials, the inhibitory effect of SDEA and its four constituents (Amentoflavone, Palmatine, Apigenin, Delicaflavone) on seven CYP450 isoforms were investigated by using the established CYP450 cocktail assay based on LC-MS/MS. Methods: Appropriate substrates for seven tested CYP450 isoforms were selected to establish a reliable cocktail CYP450 assay based on LC-MS/MS. The contents of four constituents (Amentoflavone, Palmatine, Apigenin, Delicaflavone) in SDEA were determined as well. Then, the validated CYP450 cocktail assay was applied to test the inhibitory potential of SDEA and four constituents on CYP450 isoforms. Results: SDEA showed strong inhibitory effect on CYP2C9 and CYP2C8 (IC₅₀ ≈ 1 μg/ml), moderate inhibitory effect against CYP2C19, CYP2E1 and CYP3A (IC₅₀ < 10 μg/ml). Among the four constituents, Amentoflavone had the highest content in the extract (13.65%) and strongest inhibitory effect (IC₅₀ < 5 μM), especially for CYP2C9, CYP2C8 and CYP3A. Amentoflavone also showed time-dependent inhibition on CYP2C19 and CYP2D6. Apigenin and Palmatine both showed concentration-dependent inhibition. Apigenin inhibited CYP1A2, CYP2C8, CYP2C9, CYP2E1 and CYP3A. Palmatine inhibited CYP3A and had a weak inhibitory effect on CYP2E1. As for Delicaflavone, which has the potential to develop as an anti-cancer agent, showed no obvious inhibitory effect on CYP450 enzymes. Conclusion: Amentoflavone may be one of the main reasons for the inhibition of SDEA on CYP450 enzymes, the potential HDI should be considered when SDEA or Amentoflavone were used with other clinical drugs. On the contrast, Delicaflavone is more suitable to develop as a drug for clinical use, considering the low level of CYP450 metabolic inhibition.

Modulating effect of Cu(II) complexes with enamine and tetrazole derivatives on CYP2C and CYP3A and their cytotoxic and antiproliferative properties in HepG2 spheroids

CYP2C and CYP3A cytochromes are induced by a variety of compounds and affect the pharmacokinetics and pharmacodynamics of a large number of drugs. Currently, the possibility of using copper coordination compounds in antitumor therapy is being actively studied. Evaluation of potential interactions between new molecules and P450 cytochromes is necessary at an early stage of drug design.The aim. To study the modulating effect of Cu(II) complexes with enamine and tetrazole derivatives on CYP2C9, CYP2C19 and CYP3A4 and their cytotoxic and antiproliferative properties on normal human lung fibroblasts MRC-5 and a 3D model of hepatocellular carcinoma HepG2.Materials and methods. Cytotoxic and antiproliferative activities of copper(II) complexes – [CuL2] (1), [Cu2(bipy)2(PT)4] (2), [Cu2(phen)2(PT)4] (3), {[Cu(phen)(MT)2]∙H2O}n (4) (L – anion of 2-anilinomethylidene-5,5-dimethylcyclohexane-1,3-dione; PT – 5-phenyltetrazolate anion; MT – 5-methyltetrazolate anion; bipy – 2,2’-bipyridine; phen – 1,10-phenanthroline) – were examined in 2D and 3D models using fluorescence-based phenotypic screening. The modulating effect on CYP2C9, CYP2C19 and CYP3A4 was studied using fluorescence-based targeted screening. The results of CYP3A4 expression were confirmed by real-time reverse transcription polymerase chain reaction (RT-PCR).Results. Complex (1) increases the CYP3A4 expression and does not affect CYP2C9 and CYP2C19 expression. Complex (2) has no modulating effect on CYP2C and CYP3A. Complexes with 1,10-phenatrolin (3) and (4) induce CYP3A4, inhibit CYP2C9 and do not affect CYP2C19 expression. All compounds have a dose-dependent cytotoxic effect on HepG2 and MRC-5: the compound with 5-methyltetrazolate anion (4) has the same effect on cell lines, compounds with 5-phenyltetrazolate anion (2) and (3) have selective effect. Complexes with 1,10-phenatrolin are effective on both 2D and 3D models.Conclusion. The [Cu2(phen)2(FT)4] complex (3) can be used as a basis for creating an antitumor compound, but further modification of the structure is required to increase the selectivity to tumor cells.

Epigenetics in drug disposition & drug therapy: symposium report of the 24th North American meeting of the International Society for the Study of Xenobiotics (ISSX)

The 24th North American International Society for the Study of Xenobiotics (ISSX) meeting, held virtually from September 13 to 17, 2021, embraced the theme of "Broadening Our Horizons." This reinforces a key mission of ISSX: striving to share innovative science related to drug discovery and development. Session speakers and the ISSX New Investigators Group, which supports the scientific and professional development of student and early career ISSX members, elected to highlight the scientific content presented during the captivating session titled, "Epigenetics in Drug Disposition & Drug Therapy." The impact genetic variation has on drug response is well established; however, this session underscored the importance of investigating the role of epigenetics in drug disposition and drug discovery. Session speakers, Drs. Ning, McClay, and Lazarus, detailed mechanisms by which epigenetic players including long non-coding RNA (lncRNAs), microRNA (miRNAs), DNA methylation, and histone acetylation can alter the expression of genes involved in pharmacokinetics, pharmacodynamics, and toxicity. Dr. Ning detailed current knowledge about miRNAs and lncRNAs and the mechanisms by which they can affect the expression of drug metabolizing enzymes (DMEs) and nuclear receptors. Dr. Lazarus discussed the potential role of miRNAs on UDP-glucuronosyltransferase (UGT) expression and activity. Dr. McClay provided evidence that aging alters methylation and acetylation of DMEs in the liver, affecting gene expression and activity. These topics, compiled by the symposium organizers, presenters, and the ISSX New Investigators Group, are herein discussed, along with exciting future perspectives for epigenetics in drug disposition and drug discovery research.

Computer-Aided (In Silico) Modeling of Cytochrome P450-Mediated Food–Drug Interactions (FDI)

Modifications of the activity of Cytochrome 450 (CYP) enzymes by compounds in food might impair medical treatments. These CYP-mediated food–drug interactions (FDI) play a major role in drug clearance in the intestine and liver. Inter-individual variation in both CYP expression and structure is an important determinant of FDI. Traditional targeted approaches have highlighted a limited number of dietary inhibitors and single-nucleotide variations (SNVs), each determining personal CYP activity and inhibition. These approaches are costly in time, money and labor. Here, we review computational tools and databases that are already available and are relevant to predicting CYP-mediated FDIs. Computer-aided approaches such as protein–ligand interaction modeling and the virtual screening of big data narrow down hundreds of thousands of items in databanks to a few putative targets, to which the research resources could be further directed. Structure-based methods are used to explore the structural nature of the interaction between compounds and CYP enzymes. However, while collections of chemical, biochemical and genetic data are available today and call for the implementation of big-data approaches, ligand-based machine-learning approaches for virtual screening are still scarcely used for FDI studies. This review of CYP-mediated FDIs promises to attract scientists and the general public.

Characterisation of seven medications approved for attention-deficit/hyperactivity disorder using in vitro models of hepatic metabolism

The metabolism of most medications approved for the treatment of attention deficit/hyperactivity disorder (ADHD) is not fully understood.In vitro studies using cryopreserved, plated human hepatocytes (cPHHs) and pooled human liver microsomes (HLMs) were performed to more thoroughly characterise the metabolism of several ADHD medications.The use of enzyme-specific chemical inhibitors indicated a role for CYP2D6 in atomoxetine (ATX) metabolism, and roles for CYP3A4/5 in guanfacine (GUA) metabolism.The 4-hydroxy-atomoxetine and N-desmethyl-atomoxetine pathways represented 98.4% and 1.5% of ATX metabolism in cPHHs, respectively. The 3-OH-guanfacine pathway represented at least 2.6% of GUA metabolism in cPHHs, and 71% in HLMs.The major metabolising enzyme for methylphenidate (MPH) and dexmethylphenidate (dMPH) could not be identified using these methods because these compounds were too unstable. Hydrolysis of these medications was spontaneous and did not require the presence of protein to occur.Clonidine (CLD), amphetamine (AMPH), and dextroamphetamine (dAMPH) did not deplete substantially in cPHHs nor HLMs, suggesting that these compounds may not undergo considerable hepatic metabolism. The major circulating metabolites of AMPH and dAMPH (benzoic acid and hippuric acid) were not observed in either system, and therefore could not be characterised. Additionally, inhibition experiments suggested a very minimal role for CYP2D6 in CLD and AMPH metabolism.

ZY12201, A Potent TGR5 Agonist: Identification of a Novel Pan CYP450 Inhibitor Tool Compound for In-Vitro Assessment

BACKGROUND

Identification of clinical drug-drug interaction (DDI) risk is an important aspect of drug discovery and development owing to poly-pharmacy in present-day clinical therapy. Drug metabolizing enzymes (DME) plays important role in the efficacy and safety of drug candidates. Hence evaluation of a New Chemical Entity (NCE) as a victim or perpetrator is very crucial for DDI risk mitigation. ZY12201 (2-((2-(4-(1H-imidazol-1-yl) phenoxy) ethyl) thio)-5-(2-(3, 4- dimethoxy phenyl) propane-2-yl)-1-(4-fluorophenyl)-1H-imidazole) is a novel and potent Takeda-G-protein-receptor-5 (TGR-5) agonist. ZY12201 was evaluated in-vitro to investigate the DDI liabilities.

OBJECTIVE

The key objective was to evaluate the CYP inhibition potential of ZY12201 for an opportunity to use it as a tool compound for pan CYP inhibition activities.

METHOD

In-vitro drug metabolizing enzymes (DME) inhibition potential of ZY12201 was evaluated against major CYP isoforms (1A2, 2B6, 2C8, 2C9, 2C19, 2D6, 2E1, and 3A4/5), aldehyde oxidase (AO), monoamine oxidase (MAO), and flavin-containing monooxygenase (FMO in human liver cytosol/mitochondrial preparation/ microsomes using probe substrates and Liquid Chromatography with tandem mass spectrometry (LC-MS-MS) method.

RESULTS

The study conducted on ZY12201 at 100 µM ZY12201 was found to reduce the metabolism of vanillin (AO probe substrate), tryptamine (MAO probe substrate), and benzydamine (FMO probe substrate) by 49.2%, 14.7%, and 34.9%, respectively. ZY12201 Ki values were 0.38, 0.25, 0.07, 0.01, 0.06, 0.02, 7.13, 0.03 and 0.003 μM for CYP1A2, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP2E1, CYP3A4/5 (substrate: testosterone) and CYP3A4/5 (substrate: midazolam), respectively. Time-dependant CYP inhibition potential of ZY12201 was assessed against CYP1A2, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP2E1, and CYP3A4/5 and no apparent IC50 shift was observed.

CONCLUSIONS

ZY12201, at 100 µM concentration showed low inhibition potential of AO, MAO, and FMO. ZY12201 was found as a potent inhibitor of CYP1A2, 2B6, 2C8, 2C9, 2C19, 2D6, and 3A4/5 while moderately inhibits to CYP2E1. Inhibition of CYP1A2, CYP2B6, CYP2C19, and CYP2E1 by ZY12201 was competitive, while inhibition of CYP2C8, CYP2C9, CYP2D6, and CYP3A4/5 was of mixed-mode. ZY12201 is a non-time-dependent inhibitor of CYP1A2, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP2E1, CYP3A4/5. In summary, the reported Ki values unequivocally support that ZY12201 has a high potential to inhibit all major CYP isoforms. ZY12201 can be effectively used as a tool compound for in-vitro evaluation of CYP-based metabolic contribution to total drug clearance in the lead optimization stage of Drug Discovery Research.

An efficient strategy based on two-stage chromatography and in vitro evaluation for rapid screening and isolation of acetylcholinesterase inhibitors from Scutellaria baicalensis Georgi

The extraction of Scutellaria baicalensis Georgi was investigated using the response surface methodology-genetic algorithm mathematical regression model, and the extraction variables were optimized to maximize the flavonoid yield. Furthermore, a simple and efficient ultrafiltration-liquid chromatography-mass spectrometry and molecular docking methods was developed for the rapid screening and identification of acetylcholinesterase inhibitors present in Scutellaria baicalensis Georgi. Subsequently, four major chemical constituents, namely baicalein, norwogonin, wogonin, and oroxylin A, were identified as potent acetylcholinesterase inhibitors. This novel approach, involving the use of ultrafiltration-liquid chromatography-mass spectrometry and molecular docking methods combined with stepwise flow rate counter-current chromatography and semi-preparative high-performance liquid chromatography, could potentially provide a powerful tool for the screening and extraction of acetylcholinesterase inhibitors from complex matrices and be a useful platform for the production of bioactive and nutraceutical ingredients. This article is protected by copyright. All rights reserved.

Prediction of metabolizing enzyme-mediated clinical drug interactions using in vitro information

Evaluation of drug interactions is an essential step in the new drug development process. Regulatory agencies, including U.S. Food and Drug Administrations and European Medicines Agency, have been published documents containing guidelines to evaluate potential drug interactions. Here, we have streamlined in vitro experiments to assess metabolizing enzyme-mediated drug interactions and provided an overview of the overall process to evaluate potential clinical drug interactions using in vitro data. An experimental approach is presented when an investigational drug (ID) is either a victim or a perpetrator, respectively, and the general procedure to obtain in vitro drug interaction parameters is also described. With the in vitro inhibitory and/or inductive parameters of the ID, basic, static, and/or dynamic models were used to evaluate potential clinical drug interactions. In addition to basic and static models which assume the most conservative conditions, such as the concentration of perpetrators as C_max, dynamic models including physiologically-based pharmacokinetic models take into account changes in in vivo concentrations and metabolizing enzyme levels over time.

Ionic-liquid-based ultrasound-assisted extraction combined with counter-current chromatography and semi-preparative-LC for the preparation of monoamine oxidase B inhibitors from Pueraria thomsonii

A simple and efficient method was developed for the rapid screening and identification of ligands for monoamine oxidase B. A new ionic-liquid-based ultrasound-assisted extraction method for medicinal herbs was also developed and validated. In addition, the hyphenated technique of counter-current chromatography and semi-preparative-LC was developed and applied to the isolation of the chemical constituents for Pueraria thomsonii Benth. Three potent monoamine oxidase B inhibitors, viz. daidzein-4',7-diglucoside (42.2 mg), puerarin 6''-O-xyloside (88.3 mg), and 3'-hydroxypuerarin (48.5 mg) with purities of 98.2%, 96.3%, and 97.1%, respectively, were obtained from 500 g of P. thomsonii raw material using semi-HPLC, whereas 3'-methoxypuerarin (76.2 mg), daidzein-8-C-apiosyl (1→6) glucoside (84.2 mg), and tectorigenin (75.1 mg) with purities of 98.5%, 96.4%, and 96.8%, respectively, were obtained from 500 g raw material via counter-current chromatography using a two-phase solvent system comprising n-hexane-ethyl acetate-methanol-water at a volume ratio of 1.85:1.00:0.86:3.69 (v/v). Then, the anti-Alzheimer activity of the phytochemicals was assessed using a PC12 cell model. Treatment with tectorigenin, daidzein-4',7-diglucoside, puerarin 6''-O-xyloside, 3'-hydroxypuerarin, 3'-methoxypuerarin, and daidzein-8-C-apiosyl (1→6) glucoside (100 μg/mL), resulted in cell viabilities of 69.00%, 65.81%, 59.69%, 57.90%, 55.61%, and 54.59%, respectively (P < 0.001). The protocol was proved to be very accurate and efficient. This article is protected by copyright. All rights reserved.

The role of DMPK science in improving pharmaceutical research and development efficiency

The successful regulatory authority approval rate of drug candidates in the drug development pipeline is crucial for determining pharmaceutical research and development (R&D) efficiency. Regulatory authorities include the US Food and Drug Administration (FDA), European Medicines Agency (EMA), and Pharmaceutical and Food Safety Bureau Japan (PFSB), among others. Optimal drug metabolism and pharmacokinetics (DMPK) properties influence the progression of a drug candidate from the preclinical to the clinical phase. In this review, we provide a comprehensive assessment of essential concepts, methods, improvements, and challenges in DMPK science and its significance in drug development. This information provides insights into the association of DMPK science with pharmaceutical R&D efficiency.

MicroRNAs: Crucial Players in the Differentiation of Human Pluripotent and Multipotent Stem Cells into Functional Hepatocyte-Like Cells

Hepatic disease negatively impacts liver function and metabolism. Primary human hepatocytes are the gold standard for the prediction and successful treatment of liver disease. However, the sources of hepatocytes for drug toxicity testing and disease modeling are limited. To overcome this issue, pluripotent stem cells (PSCs) have emerged as an alternative strategy for liver disease therapy. Human PSCs, including embryonic stem cells (ESC) and induced pluripotent stem cells (iPSC) can self-renew and give rise to all cells of the body. Human PSCs are attractive cell sources for regenerative medicine, tissue engineering, drug discovery, and developmental studies. Several recent studies have shown that mesenchymal stem cells (MSCs) can also differentiate (or trans-differentiate) into hepatocytes. Differentiation of human PSCs and MSCs into functional hepatocyte-like cells (HLCs) opens new strategies to study genetic diseases, hepatotoxicity, infection of hepatotropic viruses, and analyze hepatic biology. Numerous in vitro and in vivo differentiation protocols have been established to obtain human PSCs/MSCs-derived HLCs and mimic their characteristics. It was recently discovered that microRNAs (miRNAs) play a critical role in controlling the ectopic expression of transcription factors and governing the hepatocyte differentiation of human PSCs and MSCs. In this review, we focused on the role of miRNAs in the differentiation of human PSCs and MSCs into hepatocytes.

Cytochrome P450 enzymes: a review on drug metabolizing enzyme inhibition studies in drug discovery and development

Assessment of drug candidate's potential to inhibit cytochrome P450 (CYP) enzymes remains crucial in pharmaceutical drug discovery and development. Both direct and time-dependent inhibition of drug metabolizing CYP enzymes by the concomitant administered drug is the leading cause of drug-drug interactions (DDIs), resulting in the increased toxicity of the victim drug. In this context, pharmaceutical companies have grown increasingly diligent in limiting CYP inhibition liabilities of drug candidates in the early stages and examining risk assessments throughout the drug development process. This review discusses different strategies and decision-making processes for assessing the drug-drug interaction risks by enzyme inhibition and lays particular emphasis on in vitro study designs and interpretation of CYP inhibition data in a stage-appropriate context.

Novel Bruton's Tyrosine Kinase inhibitor remibrutinib: Drug-drug interaction potential as a victim of CYP3A4 inhibitors based on clinical data and PBPK modeling

Remibrutinib, a novel oral Bruton’s Tyrosine Kinase inhibitor (BTKi) is highly selective for BTK, potentially mitigating the side effects of other BTKis. Enzyme phenotyping identified CYP3A4 to be the predominant elimination pathway of remibrutinib. The impact of concomitant treatment with CYP3A4 inhibitors, grapefruit juice and ritonavir (RTV), was investigated in this study in combination with an intravenous microtracer approach. Pharmacokinetic (PK) parameters, including the fraction absorbed, the fractions escaping intestinal and hepatic first‐pass metabolism, the absolute bioavailability, systemic clearance, volume of distribution at steady‐state, and the fraction metabolized via CYP3A4 were evaluated. Oral remibrutinib exposure increased in the presence of RTV 4.27‐fold, suggesting that remibrutinib is not a sensitive CYP3A4 substrate. The rich PK dataset supported the building of a robust physiologically‐based pharmacokinetic (PBPK) model, which well‐described the therapeutic dose range of 25–100 mg. Simulations of untested scenarios revealed an absence of drug‐drug interaction (DDI) risk between remibrutinib and the weak CYP3A4 inhibitor fluvoxamine (area under the concentration‐time curve ratio [AUCR] <1.25), and a moderate effect with the CYP3A4 inhibitor erythromycin (AUCR: 2.71). Predictions with the moderate and strong CYP3A4 inducers efavirenz and rifampicin, suggested a distinct remibrutinib exposure decrease of 64% and 89%. Oral bioavailability of remibrutinib was 34%. The inclusion of an intravenous microtracer allowed the determination of all relevant remibrutinib PK parameters, which facilitated construction of the PBPK model. This will provide guidance on the selection or restriction of comedications and prediction of DDI risks.

Translational aspects of cytochrome P450-mediated drug-drug interactions: A case study with clopidogrel

Multimorbidity, polypharmacotherapy and drug interactions are increasingly common in the ageing population. Many drug-drug interactions (DDIs) are caused by perpetrator drugs inhibiting or inducing cytochrome P450 (CYP) enzymes, resulting in alterations of the plasma concentrations of a victim drug. DDIs can have a major negative health impact, and in the past, unrecognized DDIs have resulted in drug withdrawals from the market. Signals to investigate DDIs may emerge from a variety of sources. Nowadays, standard methods are widely available to identify and characterize the mechanisms of CYP-mediated DDIs in vitro. Clinical pharmacokinetic studies, in turn, provide experimental data on pharmacokinetic outcomes of DDIs. Physiologically based pharmacokinetic (PBPK) modelling utilizing both in vitro and in vivo data is a powerful tool to predict different DDI scenarios. Finally, epidemiological studies can provide estimates on the health outcomes of DDIs. Thus, to fully characterize the mechanisms, clinical effects and implications of CYP-mediated DDIs, translational research approaches are required. This minireview provides an overview of translational approaches to study CYP-mediated DDIs, going beyond regulatory DDI guidelines, and an illustrative case study of how the DDI potential of clopidogrel was unveiled by combining these different methods.

Evolving approaches on measurements and applications of intracellular free drug concentration and Kpuu in drug discovery

Introduction: Intracellular-free drug concentration (C_u,cell) and unbound partition coefficient (Kp_uu) are two important parameters to develop pharmacokinetic and pharmacodynamic relationships, predict drug-drug interaction potentials and estimate therapeutic indices.Area covered: Methods on measurements of C_u,cell, Kp_uu, partition coefficient (Kp) and fraction unbound of cells (f_uc) are discussed. Advantages and limitations of several f_uc methods are reviewed. Applications highlighted here are bridging the potency gaps between biochemical and cell-based assays, in vitro hepatocyte assay to predict in vivo liver-to-plasma Kp_uu, the role of Kp_uu in prediction of hepatic clearance for enzyme- and transporter-mediated mechanisms using extended clearance equation, and structural attributes governing tissue Kp_uu.Expert opinion: C_u,cell and Kp_uu are of growing applications in drug discovery. Methods for measurements of these properties continue to evolve in order to achieve higher precision/accuracy and obtain more detailed information at the subcellular levels. Future directions of the field include the development of in vitro and in silico models to predict tissue Kp_uu, direct measurement of free drug concentration in subcellular organelles, and further investigations into the critical elements governing cell and tissue Kp_uu. Significant innovation is needed to advance this complex, but highly impactful and exciting area of science.

Enantioselective inhibition of human CYP2C19 by the chiral pesticide ethofumesate: Prediction of pesticide-drug interactions in humans

Ethofumesate is a chiral herbicide that may display enantioselective behavior in humans. For this reason, the enantioselective potential of ethofumesate and its main metabolite ethofumesate-2-hydroxy to cause pesticide-drug interactions on cytochrome P450 forms (CYPs) has been evaluated by using human liver microsomes. Among the evaluated CYPs, CYP2C19 had its activity decreased by the ethofumesate racemic mixture (rac-ETO), (+)-ethofumesate ((+)-ETO), and (-)-ethofumesate ((-)-ETO). CYP2C19 inhibition was not time-dependent, but a strong inhibition potential was observed for rac-ETO (IC₅₀ = 5 ± 1 μmol L^-1), (+)-ETO (IC₅₀ = 1.6 ± 0.4 μmol L^-1), and (-)-ETO (IC₅₀ = 1.8 ± 0.4 μmol L^-1). The reversible inhibition mechanism was competitive, and the inhibition constant (K_i) values for rac-ETO (2.6 ± 0.4 μmol L^-1), (+)-ETO (1.5 ± 0.2 μmol L^-1), and (-)-ETO (0.7 ± 0.1 μmol L^-1) were comparable to the K_i values of strong CYP2C19 inhibitors. Inhibition of CYP2C19 by ethofumesate was enantioselective, being almost twice higher for (-)-ETO than for (+)-ETO, which indicates that this enantiomer may be a more potent inhibitor of this CYP form. For an in vitro-in vivo correlation, the Food and Drug Administration's (FDA) guideline on the assessment of drug-drug interactions used in the early stages of drug development was used. The FDA's R₁ values were estimated on the basis of the obtained ethofumesate K_i and distribution volume, metabolism, unbound plasma fraction, gastrointestinal and dermal absorption data available in the literature. The correlation revealed that ethofumesate probably inhibits CYP2C19 in vivo for both chronic (oral) and occupational (dermal) exposure scenarios.

Advancement in predicting interactions between drugs used to treat psoriasis and its comorbidities by integrating molecular and clinical resources

OBJECTIVE

Drug-drug interactions (DDIs) can result in adverse and potentially life-threatening health consequences; however, it is challenging to predict potential DDIs in advance. We introduce a new computational approach to comprehensively assess the drug pairs which may be involved in specific DDI types by combining information from large-scale gene expression (984 transcriptomic datasets), molecular structure (2159 drugs), and medical claims (150 million patients).

MATERIALS AND METHODS

Features were integrated using ensemble machine learning techniques, and we evaluated the DDIs predicted with a large hospital-based medical records dataset. Our pipeline integrates information from >30 different resources, including >10 000 drugs and >1.7 million drug-gene pairs. We applied our technique to predict interactions between 37 611 drug pairs used to treat psoriasis and its comorbidities.

RESULTS

Our approach achieves >0.9 area under the receiver operator curve (AUROC) for differentiating 11 861 known DDIs from 25 750 non-DDI drug pairs. Significantly, we demonstrate that the novel DDIs we predict can be confirmed through independent data sources and supported using clinical medical records.

CONCLUSIONS

By applying machine learning and taking advantage of molecular, genomic, and health record data, we are able to accurately predict potential new DDIs that can have an impact on public health.

Designing Out PXR Activity on Drug Discovery Projects: A Review of Structure-Based Methods, Empirical and Computational Approaches

This perspective discusses the role of pregnane xenobiotic receptor (PXR) in drug discovery and the impact of its activation on CYP3A4 induction. The use of structural biology to reduce PXR activity on drug discovery projects has become more common in recent years. Analysis of this work highlights several important molecular interactions, and the resultant structural modifications to reduce PXR activity are summarized. The computational approaches undertaken to support the design of new drugs devoid of PXR activation potential are also discussed. Finally, the SAR of empirical design strategies to reduce PXR activity is reviewed, and the key SAR transformations are discussed and summarized. In conclusion, this perspective demonstrates that PXR activity can be greatly diminished or negated on active drug discovery projects with the knowledge now available. This perspective should be useful to anyone who seeks to reduce PXR activity on a drug discovery project.

Rapid screening and purification of potential inhibitors from Medicago sativa by ultrafiltration-liquid chromatography combined with stepwise flow rate counter-current chromatography

INTRODUCTION

Medicago sativa contains flavonoids, saponins, coumarins, sterols, monoterpenes, and organic acids, with flavonoids being the main active constituents. Flavonoids naturally contain a 2-phenylchromone structure with antioxidant, free radical scavenging, cardiovascular, and trace estrogen-like effects.

OBJECTIVE

Screening and isolation of neuraminidase, lipoxidase, and lactate dehydrogenase inhibitors from M. sativa via ultrafiltration-liquid chromatography-mass spectrometry (UF-LC-MS) combined with stepwise flow rate counter-current chromatography (CCC).

METHOD

Utilising the medicinal plants M. sativa as the research objects and UF-LC-MS was used for activity screening followed by isolation and purification of the inhibitors by stepwise flow rate CCC. Finally, identification of the three active compounds was achieved by MS and nuclear magnetic resonance.

RESULTS

Three major compounds, viz. quercetin, genistein, and formononetin, were identified as potent neuraminidase, lipoxidase, and lactate dehydrogenase inhibitors, respectively. A two-phase solvent system of ethyl acetate/methanol/n-butanol/water (5.0:1.5:5.0:10; v/v/v/v) was subsequently selected for separation by stepwise flow rate CCC.

CONCLUSION

This novel approach based on UF-LC-MS and stepwise flow rate CCC represents a powerful tool for the screening and isolation of neuraminidase, lipoxidase, and lactate dehydrogenase inhibitors from complex matrices. Therefore, a useful platform for the large-scale production of bioactive and nutraceutical ingredients was developed herein.

Immunization and Drug Metabolizing Enzymes: Focus on Hepatic Cytochrome P450 3A

OBJECTIVE

Infectious disease emergencies like the 2013-2016 Ebola epidemic and the 2009 influenza and current SARS-CoV-2 pandemics illustrate that vaccines are now given to diverse populations with preexisting pathologies requiring pharmacological management. Many natural biomolecules (steroid hormones, fatty acids, vitamins) and ~60% of prescribed medications are processed by hepatic cytochrome P450 (CYP) 3A4. The objective of this work was to determine the impact of infection and vaccines on drug metabolism.

METHODS

The impact of an adenovirus-based vaccine expressing Ebola glycoprotein (AdEBO) and H1N1 and H3N2 influenza viruses on hepatic CYP 3A4 and associated nuclear receptors was evaluated in human hepatocytes (HC-04 cells) and in mice.

RESULTS

CYP3A activity was suppressed by 55% in mice 24 h after administration of mouse-adapted H1N1, while ˂10% activity remained in HC-04 cells after infection with H1N1 and H3N2 due to global suppression of cellular translation capacity, indicated by reduction (70%, H1N1, 56%, H3N2) of phosphorylated eukaryotic translation initiation factor 4e (eIF4E). AdEBO suppressed CYP3A activity in vivo (44%) and in vitro (26%) 24 hours after infection.

CONCLUSION

As the clinical evaluation of vaccines for SARS-CoV-2 and other global pathogens rise, studies to evaluate the impact of new vaccines and emerging pathogens on CYP3A4 and other metabolic enzymes are warranted to avoid therapeutic failures that could further compromise the public health during infectious disease emergencies.

Innovation in bioanalytical strategies and in vitro drug-drug interaction study approaches in drug discovery

Failure to evaluate actual toxicities of investigational molecules in drug discovery is majorly due to inadequate evaluation of their pharmacokinetics. Limitation of conventional drug metabolism profiling procedure demands advancement of existing approaches. Various techniques such as 3D cell culture system, bio microfluidic OoC model, sandwich culture model is in pipeline to be employed at their full potential in drug discovery phase. Although they outweigh the conventional techniques in various aspects, a more detailed exploration of applicability in terms of automation and high throughput analysis is required. This review extensively discusses various ongoing innovations in bioanalytical techniques. The review also proposed various scientific strategies to be adopted for prior assessment of interaction possibilities in translational drug discovery research.

Evaluation of Pharmacokinetic Drug-Drug Interactions: A Review of the Mechanisms, In Vitro and In Silico Approaches

Pharmacokinetic drug–drug interactions (DDIs) occur when a drug alters the absorption, transport, distribution, metabolism or excretion of a co-administered agent. The occurrence of pharmacokinetic DDIs may result in the increase or the decrease of drug concentrations, which can significantly affect the drug efficacy and safety in patients. Enzyme-mediated DDIs are of primary concern, while the transporter-mediated DDIs are less understood but also important. In this review, we presented an overview of the different mechanisms leading to DDIs, the in vitro experimental tools for capturing the factors affecting DDIs, and in silico methods for quantitative predictions of DDIs. We also emphasized the power and strategy of physiologically based pharmacokinetic (PBPK) models for the assessment of DDIs, which can integrate relevant in vitro data to simulate potential drug interaction in vivo. Lastly, we pointed out the future directions and challenges for the evaluation of pharmacokinetic DDIs.

Inhibition and induction of CYP enzymes in humans: an update

The cytochrome P450 (CYP) enzyme family is the most important enzyme system catalyzing the phase 1 metabolism of pharmaceuticals and other xenobiotics such as herbal remedies and toxic compounds in the environment. The inhibition and induction of CYPs are major mechanisms causing pharmacokinetic drug–drug interactions. This review presents a comprehensive update on the inhibitors and inducers of the specific CYP enzymes in humans. The focus is on the more recent human in vitro and in vivo findings since the publication of our previous review on this topic in 2008. In addition to the general presentation of inhibitory drugs and inducers of human CYP enzymes by drugs, herbal remedies, and toxic compounds, an in-depth view on tyrosine-kinase inhibitors and antiretroviral HIV medications as victims and perpetrators of drug–drug interactions is provided as examples of the current trends in the field. Also, a concise overview of the mechanisms of CYP induction is presented to aid the understanding of the induction phenomena.

2020 FDA Drug-drug Interaction Guidance: A Comparison Analysis and Action Plan by Pharmaceutical Industrial Scientists

Background:

In January 2020, the US FDA published two final guidelines, one entitled “In vitro Drug Interaction Studies - Cytochrome P450 Enzyme- and Transporter-Mediated Drug Interactions Guidance for Industry” and the other entitled “Clinical Drug Interaction Studies - Cytochrome P450 Enzyme- and Transporter-Mediated Drug Interactions Guidance for Industry”. These were updated from the 2017 draft in vitro and clinical DDI guidance.

Methods:

This study is aimed to provide an analysis of the updates along with a comparison of the DDI guidelines published by the European Medicines Agency (EMA) and Japanese Pharmaceuticals and Medical Devices Agency (PMDA) along with the current literature.

Results:

The updates were provided in the final FDA DDI guidelines and explained the rationale of those changes based on the understanding from research and literature. Furthermore, a comparison among the FDA, EMA, and PMDA DDI guidelines are presented in Tables 1, 2 and 3.

Conclusion:

The new 2020 clinical DDI guidance from the FDA now has even higher harmonization with the guidance (or guidelines) from the EMA and PMDA. A comparison of DDI guidance from the FDA 2017, 2020, EMA, and PMDA on CYP and transporter based DDI, mathematical models, PBPK, and clinical evaluation of DDI is presented in this review.

Prediction of Cyclosporin-Mediated Drug Interaction Using Physiologically Based Pharmacokinetic Model Characterizing Interplay of Drug Transporters and Enzymes

Uptake transporter organic anion transporting polypeptides (OATPs), efflux transporters (P-gp, BCRP and MRP2) and cytochrome P450 enzymes (CYP450s) are widely expressed in the liver, intestine or kidney. They coordinately work to control drug disposition, termed as "interplay of transporters and enzymes". Cyclosporine A (CsA) is an inhibitor of OATPs, P-gp, MRP2, BCRP and CYP3As. Drug-drug interaction (DDI) of CsA with victim drugs occurs via disordering interplay of transporters and enzymes. We aimed to establish a whole-body physiologically-based pharmacokinetic (PBPK) model which predicts disposition of CsA and nine victim drugs including atorvastatin, cerivastatin, pravastatin, rosuvastatin, fluvastatin, simvastatin, lovastatin, repaglinide and bosentan, as well as drug-drug interactions (DDIs) of CsA with nine victim drugs to investigate the integrated effect of enzymes and transporters in liver, intestinal and kidney on drug disposition. Predictions were compared with observations. Most of the predictions were within 0.5-2.0 folds of observations. Atorvastatin was represented to investigate individual contributions of transporters and CYP3As to atorvastatin disposition and their integrated effect. The contributions to atorvastatin disposition were hepatic OATPs >> hepatic CYP3A > intestinal CYP3As ≈ efflux transporters (P-gp/BCRP/MRP2). The results got the conclusion that the developed PBPK model characterizing the interplay of enzymes and transporters was successfully applied to predict the pharmacokinetics of 10 OATP substrates and DDIs of CsA with 9 victim drugs.

Microengineered systems with iPSC-derived cardiac and hepatic cells to evaluate drug adverse effects

Hepatic and cardiac drug adverse effects are among the leading causes of attrition in drug development programs, in part due to predictive failures of current animal or in vitro models. Hepatocytes and cardiomyocytes differentiated from human induced pluripotent stem cells (iPSCs) hold promise for predicting clinical drug effects, given their human-specific properties and their ability to harbor genetically determined characteristics that underlie inter-individual variations in drug response. Currently, the fetal-like properties and heterogeneity of hepatocytes and cardiomyocytes differentiated from iPSCs make them physiologically different from their counterparts isolated from primary tissues and limit their use for predicting clinical drug effects. To address this hurdle, there have been ongoing advances in differentiation and maturation protocols to improve the quality and use of iPSC-differentiated lineages. Among these are in vitro hepatic and cardiac cellular microsystems that can further enhance the physiology of cultured cells, can be used to better predict drug adverse effects, and investigate drug metabolism, pharmacokinetics, and pharmacodynamics to facilitate successful drug development. In this article, we discuss how cellular microsystems can establish microenvironments for these applications and propose how they could be used for potentially controlling the differentiation of hepatocytes or cardiomyocytes. The physiological relevance of cells is enhanced in cellular microsystems by simulating properties of tissue microenvironments, such as structural dimensionality, media flow, microfluidic control of media composition, and co-cultures with interacting cell types. Recent studies demonstrated that these properties also affect iPSC differentiations and we further elaborate on how they could control differentiation efficiency in microengineered devices. In summary, we describe recent advances in the field of cellular microsystems that can control the differentiation and maturation of hepatocytes and cardiomyocytes for drug evaluation. We also propose how future research with iPSCs within engineered microenvironments could enable their differentiation for scalable evaluations of drug effects.

Imbalance of Drug Transporter-CYP450s Interplay by Diabetes and Its Clinical Significance

The pharmacokinetics of a drug is dependent upon the coordinate work of influx transporters, enzymes and efflux transporters (i.e., transporter-enzyme interplay). The transporter-enzyme interplay may occur in liver, kidney and intestine. The influx transporters involving drug transport are organic anion transporting polypeptides (OATPs), peptide transporters (PepTs), organic anion transporters (OATs), monocarboxylate transporters (MCTs) and organic cation transporters (OCTs). The efflux transporters are P-glycoprotein (P-gp), multidrug/toxin extrusions (MATEs), multidrug resistance-associated proteins (MRPs) and breast cancer resistance protein (BCRP). The enzymes related to drug metabolism are mainly cytochrome P450 enzymes (CYP450s) and UDP-glucuronosyltransferases (UGTs). Accumulating evidence has demonstrated that diabetes alters the expression and functions of CYP450s and transporters in a different manner, disordering the transporter-enzyme interplay, in turn affecting the pharmacokinetics of some drugs. We aimed to focus on (1) the imbalance of transporter-CYP450 interplay in the liver, intestine and kidney due to altered expressions of influx transporters (OATPs, OCTs, OATs, PepTs and MCT6), efflux transporters (P-gp, BCRP and MRP2) and CYP450s (CYP3As, CYP1A2, CYP2E1 and CYP2Cs) under diabetic status; (2) the net contributions of these alterations in the expression and functions of transporters and CYP450s to drug disposition, therapeutic efficacy and drug toxicity; (3) application of a physiologically-based pharmacokinetic model in transporter-enzyme interplay.