Improved predictions of time-dependent drug-drug interactions by determination of cytosolic drug concentrations

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.

Clinical Trial Data-Driven Risk Assessment of Drug-Drug Interactions: A Rapid and Accurate Decision-Making Tool

BACKGROUND

In clinical practice, the vast array of potential drug combinations necessitates swift and accurate assessments of pharmacokinetic drug-drug interactions (DDIs), along with recommendations for adjustments. Current methodologies for clinical DDI evaluations primarily rely on basic extrapolations from clinical trial data. However, these methods are limited in accuracy owing to their lack of a comprehensive consideration of various critical factors, including the inhibitory potency, dosage, and type of the inhibitor, as well as the metabolic fraction and intestinal availability of the substrate.

OBJECTIVE

This study aims to propose an efficient and accurate clinical pharmacokinetic-mediated DDI assessment tool, which comprehensively considers the effects of inhibitory potency and dosage of inhibitors, intestinal availability and fraction metabolized of substrates on DDI outcomes.

METHODS

This study focuses on DDIs caused by cytochrome P450 3A4 enzyme inhibition, utilizing extensive clinical trial data to establish a methodology to calculate the metabolic fraction and intestinal availability for substrates, as well as the concentration and inhibitory potency for inhibitors ( K i ork inact / K I ). These parameters were then used to predict the outcomes of DDIs involving 33 substrates and 20 inhibitors. We also defined the risk index for substrates and the potency index for inhibitors to establish a clinical DDI risk scale. The training set for parameter calculation consisted of 73 clinical trials. The validation set comprised 89 clinical DDI trials involving 53 drugs. which was used to evaluate the reliability of in vivo values of K i andk inact / K I , the accuracy of DDI predictions, and the false-negative rate of risk scale.

RESULTS

First, the reliability of the in vivo K i andk inact / K I values calculated in this study was assessed using a basic static model. Compared with values obtained from other methods, this study values showed a lower geometric mean fold error and root mean square error. Additionally, incorporating these values into the physiologically based pharmacokinetic-DDI model facilitated a good fitting of the C-t curves when the substrate's metabolic enzymes are inhibited. Second, area under the curve ratio predictions of studied drugs were within a 1.5 × margin of error in 81% of cases compared with clinical observations in the validation set. Last, the clinical DDI risk scale developed in this study predicted the actual risks in the validation set with only a 5.6% incidence of serious false negatives.

CONCLUSIONS

This study offers a rapid and accurate approach for assessing the risk of pharmacokinetic-mediated DDIs in clinical practice, providing a foundation for rational combination drug use and dosage adjustments.

Evaluation of Cytochrome P450-Mediated Cannabinoid-Drug Interactions in Healthy Adult Participants

Understanding cannabis-drug interactions is critical given regulatory changes that have increased access to and use of cannabis. Cannabidiol (CBD) and Δ-9-tetrahydrocannabinol (Δ9-THC), the most abundant phytocannabinoids, are in vitro reversible and time-dependent (CBD only) inhibitors of several cytochrome P450 (CYP) enzymes. Cannabis extracts were used to evaluate quantitatively potential pharmacokinetic cannabinoid-drug interactions in 18 healthy adults. Participant received, in a randomized cross-over manner (separated by ≥ 1 week), a brownie containing (i) no cannabis extract (ethanol/placebo), (ii) CBD-dominant cannabis extract (640 mg CBD + 20 mg Δ9-THC), or (iii) Δ9-THC-dominant cannabis extract (20 mg Δ9-THC and no CBD). After 30 minutes, participants consumed a cytochrome P450 (CYP) drug cocktail consisting of caffeine (CYP1A2), losartan (CYP2C9), omeprazole (CYP2C19), dextromethorphan (CYP2D6), and midazolam (CYP3A). Plasma and urine samples were collected (0-24 hours). The CBD + Δ9-THC brownie inhibited CYP2C19 > CYP2C9 > CYP3A > CYP1A2 (but not CYP2D6) activity, as evidenced by an increase in the geometric mean ratio of probe drug area under the plasma concentration-time curve (AUC) relative to placebo (AUCGMR ) of omeprazole, losartan, midazolam, and caffeine by 207%, 77%, 56%, and 39%, respectively. In contrast, the Δ9-THC brownie did not inhibit any of the CYPs. The CBD + Δ9-THC brownie increased Δ9-THC AUCGMR by 161%, consistent with CBD inhibiting CYP2C9-mediated oral Δ9-THC clearance. Except for caffeine, these interactions were well-predicted by our physiologically-based pharmacokinetic model (within 26% of observed interactions). Results can be used to help guide dose adjustment of drugs co-consumed with cannabis products and the dose of CBD in cannabis products to reduce interaction risk with Δ9-THC.

Applications, Challenges, and Outlook for PBPK Modeling and Simulation: A Regulatory, Industrial and Academic Perspective

Several regulatory guidances on the use of physiologically based pharmacokinetic (PBPK) analyses and physiologically based biopharmaceutics model(s) (PBBM(s)) have been issued. Workshops are routinely held, demonstrating substantial interest in applying these modeling approaches to address scientific questions in drug development. PBPK models and PBBMs have remarkably contributed to model-informed drug development (MIDD) such as anticipating clinical PK outcomes affected by extrinsic and intrinsic factors in general and specific populations. In this review, we proposed practical considerations for a "base" PBPK model construction and development, summarized current status, challenges including model validation and gaps in system models, and future perspectives in PBPK evaluation to assess a) drug metabolizing enzyme(s)- or drug transporter(s)- mediated drug-drug interactions b) dosing regimen prediction, sampling timepoint selection and dose validation in pediatric patients from newborns to adolescents, c) drug exposure in patients with renal and/or and hepatic organ impairment, d) maternal-fetal drug disposition during pregnancy, and e) pH-mediated drug-drug interactions in patients treated with proton pump inhibitors/acid-reducing agents (PPIs/ARAs) intended for gastric protection. Since PBPK can simulate outcomes in clinical studies with enrollment challenges or ethical issues, the impact of PBPK models on waivers and how to strengthen study waiver is discussed.

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.

Influence of Proteome Profiles and Intracellular Drug Exposure on Differences in CYP Activity in Donor-Matched Human Liver Microsomes and Hepatocytes

Human liver microsomes (HLM) and human hepatocytes (HH) are important in vitro systems for studies of intrinsic drug clearance (CLint) in the liver. However, the CLint values are often in disagreement for these two systems. Here, we investigated these differences in a side-by-side comparison of drug metabolism in HLM and HH prepared from 15 matched donors. Protein expression and intracellular unbound drug concentration (Kpuu) effects on the CLint were investigated for five prototypical probe substrates (bupropion-CYP2B6, diclofenac-CYP2C9, omeprazole-CYP2C19, bufuralol-CYP2D6, and midazolam-CYP3A4). The samples were donor-matched to compensate for inter-individual variability but still showed systematic differences in CLint. Global proteomics analysis outlined differences in HLM from HH and homogenates of human liver (HL), indicating variable enrichment of ER-localized cytochrome P450 (CYP) enzymes in the HLM preparation. This suggests that the HLM may not equally and accurately capture metabolic capacity for all CYPs. Scaling CLint with CYP amounts and Kpuu could only partly explain the discordance in absolute values of CLint for the five substrates. Nevertheless, scaling with CYP amounts improved the agreement in rank order for the majority of the substrates. Other factors, such as contribution of additional enzymes and variability in the proportions of active and inactive CYP enzymes in HLM and HH, may have to be considered to avoid the use of empirical scaling factors for prediction of drug metabolism.

Cytochrome P450 3A Time-Dependent Inhibition Assays Are Too Sensitive for Identification of Drugs Causing Clinically Significant Drug-Drug Interactions: A Comparison of Human Liver Microsomes and Hepatocytes and Definition of Boundaries for Inactivation Rate Constants

Time-dependent inhibition (TDI) of CYP3A is an important mechanism underlying numerous drug-drug interactions (DDIs), and assays to measure this are done to support early drug research efforts. However, measuring TDI of CYP3A in human liver microsomes (HLMs) frequently yields overestimations of clinical DDIs and thus can lead to the erroneous elimination of many viable drug candidates from further development. In this investigation, 50 drugs were evaluated for TDI in HLMs and suspended human hepatocytes (HHEPs) to define appropriate boundary lines for the TDI parameter rate constant for inhibition (k_obs) at a concentration of 30 µM. In HLMs, a k_obs value of 0.002 minute^-1 was statistically distinguishable from control; however, many drugs show k_obs greater than this but do not cause DDI. A boundary line defined by the drug with the lowest k_obs that causes a DDI (diltiazem) was established at 0.01 minute^-1 Even with this boundary, of the 33 drugs above this value, only 61% cause a DDI (true positive rate). A corresponding analysis was done using HHEPs; k_obs of 0.0015 minute^-1 was statistically distinguishable from control, and the boundary was established at 0.006 minute^-1 Values of k_obs in HHEPs were almost always lower than those in HLMs. These findings offer a practical guide to the use of TDI data for CYP3A in early drug-discovery research. SIGNIFICANCE STATEMENT: Time-dependent inhibition of CYP3A is responsible for many drug interactions. In vitro assays are employed in early drug research to identify and remove CYP3A time-dependent inhibitors from further consideration. This analysis demonstrates suitable boundaries for inactivation rates to better delineate drug candidates for their potential to cause clinically significant drug interactions.

Assessment of the in vitro cytochrome P450 (CYP) inhibition potential of nafithromycin, a next generation lactone ketolide antibiotic

Nafithromycin is a next generation lactone ketolide antibiotic slated to enter phase III clinical development in India for the treatment of CABP as a shorter 800 mg-OD X3 day therapeutic regimen. Nafithromycin exhibits potent activity against MDR Streptococcus pneumoniae including erythromycin and telithromycin-resistant resistant strains. Older macrolides/ketolides are reported to be potent inhibitors of CYP3A4/5. To facilitate comparative assessment of drug-drug interaction potential, CYP inhibitory activities of nafithromycin was evaluated in comparison with clarithromycin, telithromycin, cethromycin and solithromycin. CYP inhibitory activities were assessed against key CYP isoforms (CYP1A2, 2B6, 2C8, 2C9, 2C19, 2D6 and CYP3A4/5) using human liver microsomes. Additionally, time-dependent inhibition (TDI), metabolism-based inhibition (MBI) and k _inact /K _I activities were also investigated for CYP3A4/5. Nafithromycin did not inhibit key CYP enzymes and was found to be a weak inhibitor of CYP3A4/5. Comparator antibiotics were found to be potent inhibitors with 2- to 50-fold leftward shifts in CYP3A4/5 IC50 values, while such shift was not noted for nafithromycin. k _inact /K _I ratio of nafithromycin was 3- to 153-fold lower than comparator drugs, further substantiating its lower affinity for CYP3A4/5. In sum, weaker inhibition and lower k _inact /K _I ratio for CYP3A4/5, points towards nafithromycin's lower propensities towards clinical drug-drug interactions as compared to other macrolides/ketolides antibiotics.

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.

How precise is quantitative prediction of pharmacokinetic effects due to drug-drug interactions and genotype from in vitro data? A comprehensive analysis on the example CYP2D6 and CYP2C19 substrates

Drug-drug interactions (DDI) and genomic variation (PG) can lead to dangerously high blood and tissue concentrations with some drugs but may be negligible with other drugs. Using a quantitative metaanalysis, we analyzed on the example of CYP2D6 and CYP2C19 substrates, how well the effects of DDI and PG can be predicted by in vitro methods. In addition, we analyzed the quantitative effect of prototypic inhibitors of the two enzymes in relation to their genetic deficiency. More than 600 published studies were screened which compared either human pharmacokinetics with and without comedication, or which compared human pharmacokinetics of deficient with extensive metabolizers, or which assessed metabolism by in vitro approaches. With human liver microsomes, the in vitro to in vivo agreement of fractional clearances was reasonably high if loss of substrate was quantified in the in vitro assays performed with and without enzyme specific inhibitors. Also a generally very high correlation between the clinical pharmacokinetic effects of inherited deficiency and inhibition by drug-drug interactions could be demonstrated. Most cases of poor correlation were explained by the lack of CYP2D6 versus CYP2C19 specificity of fluoxetine or by a poor knowledge of the quantitative contribution of the metabolic pathways if metabolite formation was quantified in the in vitro assays. The good correspondence of the in vitro data with clinical DDI and clinical PG studies may be a good basis for future application of these methods in drug development and drug therapy.

Impact of Intracellular Concentrations on Metabolic Drug-Drug Interaction Studies

Accurate prediction of drug-drug interactions (DDI) is a challenging task in drug discovery and development. It requires determination of enzyme inhibition in vitro which is highly system-dependent for many compounds. The aim of this study was to investigate whether the determination of intracellular unbound concentrations in primary human hepatocytes can be used to bridge discrepancies between results obtained using human liver microsomes and hepatocytes. Specifically, we investigated if Kp_uu could reconcile differences in CYP enzyme inhibition values (K_i or IC₅₀). Firstly, our methodology for determination of Kp_uu was optimized for human hepatocytes, using four well-studied reference compounds. Secondly, the methodology was applied to a series of structurally related CYP2C9 inhibitors from a Roche discovery project. Lastly, the Kp_uu values of three commonly used CYP3A4 inhibitors—ketoconazole, itraconazole, and posaconazole—were determined and compared to compound-specific hepatic enrichment factors obtained from physiologically based modeling of clinical DDI studies with these three compounds. Kp_uu obtained in suspended human hepatocytes gave good predictions of system-dependent differences in vitro. The Kp_uu was also in fair agreement with the compound-specific hepatic enrichment factors in DDI models and can therefore be used to improve estimations of enrichment factors in physiologically based pharmacokinetic modeling.