Inhibition of oral midazolam clearance by boosting doses of ritonavir, and by 4,4-dimethyl-benziso-(2H)-selenazine (ALT-2074), an experimental catalytic mimic of glutathione oxidase

No dose adjustment of metformin or substrates of organic cation transporters (OCT)1 and OCT2 and multidrug and toxin extrusion protein (MATE)1/2K with fostemsavir coadministration based on modeling approaches

Fostemsavir is an approved gp120-directed attachment inhibitor and prodrug for the treatment of human immunodeficiency virus type 1 infection in combination with other antiretrovirals (ARVs) in heavily treatment-experienced adults with multi-drug resistance, intolerance, or safety concerns with their current ARV regimen. Initial in vitro studies indicated that temsavir, the active moiety of fostemsavir, and its metabolites, inhibited organic cation transporter (OCT)1, OCT2, and multidrug and toxin extrusion transporters (MATEs) at tested concentration of 100 uM, although risk assessment based on the current Food and Drug Administration in vitro drug-drug interaction (DDI) guidance using the mechanistic static model did not reveal any clinically relevant inhibition on OCTs and MATEs. However, a DDI risk was flagged with EMA static model predictions. Hence, a physiologically based pharmacokinetic (PBPK) model of fostemsavir/temsavir was developed to further assess the DDI risk potential of OCT and MATEs inhibition by temsavir and predict changes in metformin (a sensitive OCT and MATEs substrate) exposure. No clinically relevant impact on metformin concentrations across a wide range of temsavir concentrations was predicted; therefore, no dose adjustment is recommended for metformin when co-administered with fostemsavir.

Physiologically-based pharmacokinetic modeling predicts the drug interaction potential of GLS4 in co-administered with ritonavir

GLS4 is a first-in-class hepatitis B virus (HBV) capsid assembly modulator (class I) that is co-administered with ritonavir to maintain the anticipated concentration required for the effective antiviral activity of GLS4. In this study, the first physiologically-based pharmacokinetic (PBPK) model for GLS4/ritonavir was successfully developed. The predictive performance of the PBPK model was verified using data from 39 clinical studies, including single-dose, multiple-dose, food effects, and drug-drug interactions (DDI). The PBPK model accurately described the PK profiles of GLS4 and ritonavir, with predicted values closely aligning with observed data. Based on the verified GLS4/ritonavir model, it prospectively predicts the effect of hepatic impairment (HI) and DDI on its pharmacokinetics (PK). Notably, CYP3A4 inducers significantly influenced GLS4 exposure when co-administered with ritonavir; co-administered GLS4 and ritonavir significantly influenced the exposure of CYP3A4 substrates. Additionally, with the severity of HI increased, there was a corresponding increase in the exposure to GLS4 when co-administered with ritonavir. The GLS4/ritonavir PBPK model can potentially be used as an alternative to clinical studies or guide the design of clinical trial protocols.

Physiologically based pharmacokinetic modeling of ritonavir-oxycodone drug interactions and its implication for dosing strategy

The concomitant administration of ritonavir and oxycodone may significantly increase the plasma concentrations of oxycodone. This study was aimed to simulate DDI between ritonavir and oxycodone, a widely used opioid, and to formulate dosing protocols for oxycodone by using physiologically based pharmacokinetic (PBPK) modeling. We developed a ritonavir PBPK model incorporating induction and competitive and time-dependent inhibition of CYP3A4 and competitive inhibition of CYP2D6. The ritonavir model was evaluated with observed clinical pharmacokinetic data and validated for its CYP3A4 inhibition potency. We then used the model to simulate drug interactions between oxycodone and ritonavir under various dosing scenarios. The developed model captured the pharmacokinetic characteristics of ritonavir from clinical studies. The model also accurately predicts exposure changes of midazolam, triazolam, and oxycodone in the presence of ritonavir. According to model simulations, the steady-state maximum, minimum and average concentrations of oxycodone increased by up to 166% after co-administration with ritonavir, and the total exposure increased by approximately 120%. To achieve similar steady-state concentrations, halving the dose with an unchanged dosing interval or doubling the dosing interval with an unaltered single dose should be practical for oxycodone, whether formulated in uncoated or controlled-release tablets during long-term co-medication with ritonavir. The results revealed exposure-related risks of oxycodone-ritonavir interactions that have not been studied clinically and emphasized PBPK as a workable method to direct judicious dosage.

Effect of Hepatic Impairment on the Pharmacokinetics of Nirmatrelvir/Ritonavir, the First Oral Protease Inhibitor for the Treatment of COVID-19

Nirmatrelvir, a novel, potent, orally bioavailable severe acute respiratory syndrome coronavirus 2 main protease inhibitor, coadministered with ritonavir for pharmacokinetic (PK) enhancement is licensed for the treatment of mild to moderate COVID-19 in individuals at increased risk of progression to severe disease. Cytochrome P450 3A4 is the primary metabolic enzyme responsible for nirmatrelvir metabolism; however, when cytochrome P450 3A4 is inhibited by ritonavir, nirmatrelvir is primarily excreted, unchanged, in urine. Because of intended use of nirmatrelvir among individuals with hepatic impairment, this Phase 1 study (NCT05005312) evaluated the effects of hepatic impairment on nirmatrelvir PK parameters to assess the potential need for any dose adjustments in this population. Participants with normal hepatic function or moderate hepatic impairment (n = 8 each) were administered a single 100-mg nirmatrelvir dose, with 100 mg of ritonavir administered 12 hours before, together with, and 12 and 24 hours after nirmatrelvir. Nirmatrelvir median plasma concentrations and systemic exposure measured by area under the plasma concentration-time curve from time zero extrapolated to infinite time and maximum observed plasma concentration values were comparable in both groups. Nirmatrelvir/ritonavir had an acceptable safety profile in both groups, and no clinically significant changes in laboratory measurements, vital signs, or electrocardiogram assessments were observed. Based on these results, no dose adjustment is deemed necessary in patients with moderate hepatic impairment and, by extension, in patients with mild hepatic impairment.

High concentrations of nirmatrelvir/ritonavir in critically ill patients receiving continuous renal replacement therapy

OBJECTIVES

Nirmatrelvir/ritonavir is a highly efficacious agent against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Although dose adjustment is recommended in patients with renal impairment according to the package insert for Paxlovid (Pfizer), there is no dose recommendation for patients with severe renal impairment who require continuous renal replacement therapy (CRRT).

METHODS

To characterise the features of nirmatrelvir/ritonavir in critically ill Chinese patients undergoing CRRT, therapeutic drug monitoring of nirmatrelvir/ritonavir was performed by high-performance liquid chromatography tandem mass spectrometry assay in eight patients.

RESULTS

Nirmatrelvir trough concentrations ranged from 3325.34 ng/mL to 15 625.46 ng/mL. Concentrations were up to 7-fold higher compared with patients with normal renal function and 2-fold higher compared with patients with end-stage renal disease undergoing haemodialysis.

CONCLUSIONS

These results suggest that a dose reduction should be implemented in the treatment of patients with CRRT.

Physiologically-Based Pharmacokinetic Modeling of PAXLOVID™ with First-Order Absorption Kinetics

PURPOSE

PAXLOVID™ is nirmatrelvir tablets co-packaged with ritonavir tablets. Ritonavir is used as a pharmacokinetics (PK) enhancer to reduce metabolism and increase exposure of nirmatrelvir. This is the first disclosure of Paxlovid physiologically-based pharmacokinetic (PBPK) model.

METHODS

Nirmatrelvir PBPK model with first-order absorption kinetics was developed using in vitro, preclinical, and clinical data of nirmatrelvir in the presence and absence of ritonavir. Clearance and volume of distribution were derived from nirmatrelvir PK obtained using a spray-dried dispersion (SDD) formulation where it is considered to be dosed as an oral solution, and absorption is near complete. The fraction of nirmatrelvir metabolized by CYP3A was estimated based on in vitro and clinical ritonavir drug-drug interaction (DDI) data. First-order absorption parameters were established for both SDD and tablet formulation using clinical data. Nirmatrelvir PBPK model was verified with both single and multiple dose human PK data, as well as DDI studies. Simcyp® first-order ritonavir compound file was also verified with additional clinical data.

RESULTS

The nirmatrelvir PBPK model described the observed PK profiles of nirmatrelvir well with predicted AUC and Cmax values within ± 20% of the observed. The ritonavir model performed well resulting in predicted values within twofold of observed.

CONCLUSIONS

Paxlovid PBPK model developed in this study can be applied to predict PK changes in special populations, as well as model the effect of victim and perpetrator DDI. PBPK modeling continues to play a critical role in accelerating drug discovery and development of potential treatments for devastating diseases such as COVID-19. NCT05263895, NCT05129475, NCT05032950 and NCT05064800.

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.

Interactions of the protease inhibitor, ritonavir, with common anesthesia drugs

The protease inhibitor, ritonavir, is a strong inhibitor of CYP 3A. The drug is used for management of the human immunovirus and is currently part of an oral antiviral drug combination (nirmatrelvir-ritonavir) for the early treatment of SARS-2 COVID-19-positive patients aged 12 years and over who have recognized comorbidities. The CYP 3A enzyme system is responsible for clearance of numerous drugs used in anesthesia (e.g., alfentanil, fentanyl, methadone, rocuronium, bupivacaine, midazolam, ketamine). Ritonavir will have an impact on drug clearances that are dependent on ritonavir concentration, anesthesia drug intrinsic hepatic clearance, metabolic pathways, concentration-response relationship, and route of administration. Drugs with a steep concentration-response relationship (ketamine, midazolam, rocuronium) are mostly affected because small changes in concentration have major changes in effect response. An increase in midazolam concentration is observed after oral administration because CYP 3A in the gastrointestinal wall is inhibited, causing a large increase in relative bioavailability. Fentanyl infusion may be associated with a modest increase in plasma concentration and effect, but the large between subject variability of pharmacokinetic and pharmacodynamic concentration changes suggests it will have little impact on an individual patient, especially when used with adverse effect monitoring. It has been proposed that drugs that have no or only a small metabolic pathway involving the CYP 3A enzyme be used during anesthesia, for example, propofol, atracurium, remifentanil, and the volatile agents. That anesthesia approach denies children of drugs with considerable value. It is better that the inhibitory changes in clearance of these drugs are understood so that rational drug choices can be made to tailor drug use to the individual patient. Altered drug dose, anticipation of duration of effect, timing of administration, use of reversal agents and perioperative monitoring would better behoove children undergoing anesthesia.

Clinically Relevant Interactions Between Ritonavir-Boosted Nirmatrelvir and Concomitant Antiseizure Medications: Implications for the Management of COVID-19 in Patients with Epilepsy

Ritonavir-boosted nirmatrelvir (RBN) has been authorized recently in several countries as an orally active anti-SARS-CoV-2 treatment for patients at high risk of progressing to severe COVID-19 disease. Nirmatrelvir is the active component against the SARS-CoV-2 virus, whereas ritonavir, a potent CYP3A inhibitor, is intended to boost the activity of nirmatrelvir by increasing its concentration in plasma to ensure persistence of antiviral concentrations during the 12-hour dosing interval. RBN is involved in many clinically important drug–drug interactions both as perpetrator and as victim, which can complicate its use in patients treated with antiseizure medications (ASMs). Interactions between RBN and ASMs are bidirectional. As perpetrator, RBN may increase the plasma concentration of a number of ASMs that are CYP3A4 substrates, possibly leading to toxicity. As victims, both nirmatrelvir and ritonavir are subject to metabolic induction by concomitant treatment with potent enzyme-inducing ASMs (carbamazepine, phenytoin, phenobarbital and primidone). According to US and European prescribing information, treatment with these ASMs is a contraindication to the use of RBN. Although remdesivir is a valuable alternative to RBN, it may not be readily accessible in some settings due to cost and/or need for intravenous administration. If remdesivir is not an appropriate option, either bebtelovimab or molnupiravir may be considered. However, evidence about the clinical efficacy of bebtelovimab is still limited, and molnupiravir, the only orally active alternative, is deemed to have appreciably lower efficacy than RBN and remdesivir.

Pharmacokinetics of asciminib in the presence of CYP3A or P-gp inhibitors, CYP3A inducers, and acid-reducing agents

Asciminib is a first‐in‐class inhibitor of BCR::ABL1, specifically targeting the ABL myristoyl pocket. Asciminib is a substrate of CYP3A4 and P‐glycoprotein (P‐gp) and possesses pH‐dependent solubility in aqueous solution. This report summarizes the results of two phase I studies in healthy subjects aimed at assessing the impact of CYP3A and P‐gp inhibitors, CYP3A inducers and acid‐reducing agents (ARAs) on the pharmacokinetics (PK) of asciminib (single dose of 40 mg). Asciminib exposure (area under the curve [AUC]) unexpectedly decreased by ~40% when administered concomitantly with the strong CYP3A inhibitor itraconazole oral solution, whereas maximum plasma concentration (C_max) decreased by ~50%. However, asciminib exposure was slightly increased in subjects receiving an itraconazole capsule (~3%) or clarithromycin (~35%), another strong CYP3A inhibitor. Macroflux studies showed that cyclodextrin (present in high quantities as excipient [40‐fold excess to itraconazole] in the oral solution formulation of itraconazole) decreased asciminib flux through a lipid membrane by ~80%. The AUC of asciminib was marginally decreased by concomitant administration with the strong CYP3A inducer rifampicin (by ~13–15%) and the strong P‐gp inhibitor quinidine (by ~13–16%). Concomitant administration of the ARA rabeprazole had little or no effect on asciminib AUC, with a 9% decrease in C_max. The treatments were generally well tolerated. Taking into account the large therapeutic window of asciminib, the observed changes in asciminib PK following multiple doses of P‐gp, CYP3A inhibitors, CYP3A inducers, or ARAs are not considered to be clinically meaningful. Care should be exercised when administering asciminib concomitantly with cyclodextrin‐containing drug formulations.

Pharmacokinetic Pharmacodynamic Modelling Contributions to Improve Paediatric Anaesthesia Practice

The use of pharmacokinetic-pharmacodynamic models has improved anaesthesia practice in children through a better understanding of dose-concentration-response relationships, developmental pharmacokinetic changes, quantification of drug interactions and insights into how covariates (e.g., age, size, organ dysfunction, pharmacogenomics) impact drug prescription. Simulation using information from these models has enabled the prediction and learning of beneficial and adverse effects and decision-making around clinical scenarios. Covariate information, including the use of allometric size scaling, age and consideration of fat mass, has reduced population parameter variability. The target concentration approach has rationalised dose calculation. Paediatric pharmacokinetic-pharmacodynamic insights have led to better drug delivery systems for total intravenous anaesthesia and an expectation about drug offset when delivery is stopped. Understanding concentration-dependent adverse effects have tempered dose regimens. Quantification of drug interactions has improved the understanding of the effects of drug combinations. Repurposed drugs (e.g., antiviral drugs used for COVID-19) within the community can have important effects on drugs used in paediatric anaesthesia, and the use of simulation educates about these drug vagaries.

A Mechanistic Absorption and Disposition Model of Ritonavir to Predict Exposure and Drug-Drug Interaction Potential of CYP3A4/5 and CYP2D6 Substrates

BACKGROUND AND OBJECTIVES

Due to health authority warnings and the recommended limited use of ketoconazole as a model inhibitor of cytochrome P450 (CYP) 3A4 in clinical drug-drug interaction (DDI) studies, there is a need to search for alternatives. Ritonavir is a strong inhibitor for CYP3A4/5-mediated DDIs and has been proposed as a suitable alternative to ketoconazole. It can also be used as a weak inhibitor for CYP2D6-mediated DDIs. Most of the currently available physiologically based pharmacokinetic (PBPK) inhibitor models developed for predicting DDIs use first-order absorption models, which do not mechanistically capture the effect of formulations on the systemic exposure of the inhibitor. Thus, the main purpose of the current study was to verify the predictive performance of a mechanistic absorption and disposition model of ritonavir when it was applied to the inhibition of CYP2D6 and CYP3A4/5 by ritonavir.

METHODS

A PBPK model that incorporates formulation characteristics and enzyme kinetic parameters for post-absorptive pharmacokinetic processes of ritonavir was constructed. Key absorption-related parameters in the model were determined using mechanistic modelling of in vitro biopharmaceutics experiments. The model was verified for systemic exposure and DDI risk assessment using clinical observations from 13 and 18 studies, respectively.

RESULTS

Maximal inhibition of hepatic (3.53% of the activity remaining) and gut (5.16% of the activity remaining) CYP3A4 activity was observed when ritonavir was orally administered in doses of 100 mg or higher. The PBPK model accurately described the concentrations of ritonavir in the different simulated studies. The prediction accuracy for maximum concentration (C_max) and area under the plasma concentration versus time curve (AUC) were assessed. The bias (average fold error, AFE) for the prediction of C_max and AUC was 0.92 and 1.06, respectively, and the precision (absolute average fold error, AAFE) was 1.29 and 1.23, respectively. The PBPK model predictions for all C_max and AUC ratios when ritonavir was used as an inhibitor of CYP metabolism fell within twofold of the clinical observations. The prediction accuracy for C_max and AUC ratios had a bias (AFE) of 0.85 and 0.99, respectively, and a precision (AAFE) of 1.21 and 1.33, respectively.

CONCLUSIONS

The current model, which incorporates formulation characteristics and mechanistic disposition parameters, can be used to assess the DDI potential of CYP3A4/5 and CYP2D6 substrates administered with a twice-daily dose of 100 mg of ritonavir for 14 days.

A Literature Review of Liver Function Test Elevations in Rifampin Drug-Drug Interaction Studies

Although rifampin drug–drug interaction (DDI) studies are routinely conducted, there have been instances of liver function test (LFT) elevations, warranting further evaluation. A literature review was conducted to identify studies in which combination with rifampin resulted in hepatic events and evaluate any similarities. Over 600 abstracts and manuscripts describing rifampin DDI studies were first evaluated, of which 30 clinical studies reported LFT elevations. Out of these, 11 studies included ritonavir in combination with other drug(s) in the rifampin DDI study. The number of subjects that were discontinued from treatment on these studies ranged from 0 to 71 (0–100% of subjects in each study). The number of subjects hospitalized for adverse events in these studies ranged from 0 to 41 (0–83.67% of subjects in each study). LFT elevations in greater than 50% of subjects were noted during the concomitant administration of rifampin with ritonavir‐boosted protease inhibitors and with lorlatinib; with labeled contraindication due to observed hepatotoxicity related safety findings only for saquinavir/ritonavir and lorlatinib. In the lorlatinib and ritonavir DDI studies, considerable LFT elevations were observed rapidly, typically within 24–72 h following co‐administration. A possible sequence effect has been speculated, where rifampin induction prior to administration of the combination may be associated with increased severity of the LFT elevations. The potential role of rifampin in the metabolic activation of certain drugs into metabolites with hepatic effects needs to be taken into consideration when conducting rifampin DDI studies, particularly those for which the metabolic profiles are not fully elucidated.

Foerster K, Terstegen T, Vogt C, Said A, Schulz M, E. Haefeli W. Oral Drugs Against COVID-19

BACKGROUND

Five-day oral therapies against early COVID-19 infection have recently been conditionally approved in Europe. In the drug combination nirmatrelvir + ritonavir (nirmatrelvir/r), the active agent, nirmatrelvir, is made bioavailable in clinically adequate amounts by the additional administration of a potent inhibitor of its first-pass metabolism by way of cytochrome P450 [CYP] 3A in the gut and liver. In view of the central role of CYP3A in the clearance of many different kinds of drugs, and the fact that many patients with COVID-19 are taking multiple drugs to treat other conditions, it is important to assess the potential for drug interactions when nirmatrelvir/r is given, and to minimize the risks associated with such interactions.

METHODS

We defined the interaction profile of ritonavir on the basis of information derived from two databases (Medline, GoogleScholar), three standard electronic texts on drug interactions, and manufacturer-supplied drug information. We compiled a list of drugs and their potentially relevant interactions, developed a risk min - imization algorithm, and applied it to the substances in question. We also compiled a list of commonly prescribed drugs for which there is no risk of interaction with nirmatrelvir/r.

RESULTS

Out of 190 drugs and drug combinations, 57 do not need any special measures when given in combination with brief, low-dose ritonavir treatment, while 15 require dose modification or a therapeutic alternative, 8 can be temporarily discontinued, 9 contraindicate ritonavir use, and 102 should preferably be combined with a different treatment.

CONCLUSION

We have proposed measures that are simple to carry out for the main types of drug that can interact with ritonavir. These measures can be implemented under quarantine conditions before starting a 5-day treatment with nirmatrelvir/r.

INTERSYSTEM EXTRAPOLATION FACTORS (ISEF) ARE SUBSTRATE-DEPENDENT FOR CYP3A4: IMPACT ON CYTOCHROME P450 REACTION PHENOTYPING

The use of intersystem extrapolation factors (ISEF) is required for the quantitative scaling of drug metabolism data generated in individually expressed cytochrome P450 enzymes when estimating fractional contribution to metabolism by P450 enzymes in vivo (f_m,_CYP). For successful prediction of f_m, ISEF values must be universal across all substrates for any individual enzyme. In this study, ISEF values were generated for ten CYP3A4 selective substrates using a common source of recombinant heterologously expressed CYP3A4 and a pool of human liver microsomes. The resulting ISEF values for CYP3A4 were substrate-dependent and ranged 8-fold, with the highest value generated from intrinsic clearance of midazolam depletion (0.36) and the lowest from quinidine depletion (0.044). Application of these ISEF values for estimation of the fractional contribution of CYP3A4 and CYP2C19 to omeprazole clearance yielded values that ranged from 0.21-0.63 and 0.37-0.79, respectively, as compared to back-extrapolated in vivo f_m values of 0.27 (CYP3A4) and 0.85 (CYP2C19) from clinical pharmacokinetic data. For risperidone, estimated f_m values for CYP3A4 and CYP2D6 ranged from 0.87-0.98 and 0.02-0.13, respectively, as compared to in vivo values of 0.36 (CYP3A4) and 0.63-0.88 (CYP2D6), showing that the importance of CYP3A4 was over-estimated and the importance of CYP2D6 under-estimated. Overall, these findings suggest that ISEF values for CYP3A4 can vary with the marker substrate used to derive them, thereby reducing the effectiveness of the approach of using metabolism data from rCYP3A4 with ISEF values for the prediction of f_m values in vivo. Significance Statement Intersystem extrapolation factors (ISEF) are utilized for assigning fractional contributions of individual enzymes to drug clearance (f_m) from drug metabolism data generated in recombinant P450s. The present data shows that ISEF values for cytochrome P4503A4 vary with the substrate. This can lead to variable and erroneous prediction of f_m.

An open-label, randomized, single intravenous dosing study to investigate the effect of fixed-dose combinations of tenofovir/lamivudine or atazanavir/ritonavir on the pharmacokinetics of remdesivir in Ugandan healthy volunteers (RemTLAR)

BACKGROUND

Remdesivir is a novel broad-spectrum antiviral therapeutic with activity against several viruses that cause emerging infectious diseases. The purpose of this study is to explore how commonly utilized antiretroviral therapy (tenofovir disoproxil fumarate/lamivudine [TDF/3TC] and atazanavir/ritonavir [ATV/r]) influence plasma and intracellular concentrations of remdesivir.

METHODS

This is an open-label, randomized, fixed sequence single intravenous dosing study to assess pharmacokinetic interactions between remdesivir and TDF/3TC (Study A, crossover design) or TDF/3TC plus ATV/r (Study B). Healthy volunteers satisfying study entry criteria will be enrolled in the study and randomized to either Study A; N=16 (Sequence 1 or Sequence 2) or Study B; N=8. Participants will receive standard adult doses of antiretroviral therapy for 7 days and a single 200mg remdesivir infusion administered over 60 min. Pharmacokinetic blood sampling will be performed relative to the start of remdesivir infusion; predose (before the start of remdesivir infusion) and 30 min after the start of remdesivir infusion. Additional blood samples will be taken at 2, 4, 6, 12, and 24 h after the end of remdesivir infusion.

DISCUSSION

This study will characterize the pharmacokinetics of remdesivir from a typical African population in whom clinical use is anticipated. Furthermore, this study will deliver pharmacokinetic datasets for remdesivir drug concentrations and demographic characteristics which could support pharmacometric approaches for simulation of remdesivir treatment regimens in patients concurrently using tenofovir/lamivudine and/or atazanavir/ritonavir.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04385719 . Registered 13 May 2020.

Model-Based Drug-Drug Interaction Extrapolation Strategy From Adults to Children: Risdiplam in Pediatric Patients With Spinal Muscular Atrophy

Risdiplam (Evrysdi) improves motor neuron function in patients with spinal muscular atrophy (SMA) and has been approved for the treatment of patients ≥2 months old. Risdiplam exhibits time‐dependent inhibition of cytochrome P450 (CYP) 3A in vitro. While many pediatric patients receive risdiplam, a drug–drug interaction (DDI) study in pediatric patients with SMA was not feasible. Therefore, a novel physiologically‐based pharmacokinetic (PBPK) model‐based strategy was proposed to extrapolate DDI risk from healthy adults to children with SMA in an iterative manner. A clinical DDI study was performed in healthy adults at relevant risdiplam exposures observed in children. Risdiplam caused an 1.11‐fold increase in the ratio of midazolam area under the curve with and without risdiplam (AUCR)), suggesting an 18‐fold lower in vivo CYP3A inactivation constant compared with the in vitro value. A pediatric PBPK model for risdiplam was validated with independent data and combined with a validated midazolam pediatric PBPK model to extrapolate DDI from adults to pediatric patients with SMA. The impact of selected intestinal and hepatic CYP3A ontogenies on the DDI susceptibility in children relative to adults was investigated. The PBPK analysis suggests that primary CYP3A inhibition by risdiplam occurs in the intestine rather than the liver. The PBPK‐predicted risdiplam CYP3A inhibition risk in pediatric patients with SMA aged 2 months–18 years was negligible (midazolam AUCR of 1.09–1.18) and included in the US prescribing information of risdiplam. Comprehensive evaluation of the sensitivity of predicted CYP3A DDI on selected intestinal and hepatic CYP3A ontogeny functions, together with PBPK model‐based strategy proposed here, aim to guide and facilitate DDI extrapolations in pediatric populations.

Management of COVID-19 in patients with seizures: Mechanisms of action of potential COVID-19 drug treatments and consideration for potential drug-drug interactions with anti-seizure medications

In regard to the global pandemic of COVID-19, it seems that persons with epilepsy (PWE) are not more vulnerable to get infected by SARS-CoV-2, nor are they more susceptible to a critical course of the disease. However, management of acute seizures in patients with COVID-19 as well as management of PWE and COVID-19 needs to consider potential drug-drug interactions between antiseizure drugs and candidate drugs currently assessed as therapeutic options for COVID-19. Repurposing of several licensed and investigational drugs is discussed for therapeutic management of COVID-19. While for none of these approaches, efficacy and tolerability has been confirmed yet in sufficiently powered and controlled clinical studies, testing is ongoing with multiple clinical trials worldwide. Here, we have summarized the possible mechanisms of action of drugs currently considered as potential therapeutic options for COVID-19 management along with possible and confirmed drug-drug interactions that should be considered for a combination of antiseizure drugs and COVID-19 candidate drugs. Our review suggests that potential drug-drug interactions should be taken into account with drugs such as chloroquine/hydroxychloroquine and lopinavir/ritonavir while remdesivir and tocilizumab may be less prone to clinically relevant interactions with ASMs.

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.

Clinically Significant Drug Interactions Between Psychotropic Agents and Repurposed COVID-19 Therapies

As many patients with underlying psychiatric disorders may be infected with COVID-19, and COVID-19-affected subjects may frequently experience a new onset of psychiatric manifestations, concomitant use of psychotropic medications and COVID-19 therapies is expected to be highly likely and raises concerns of clinically relevant drug interactions. In this setting, four major mechanisms responsible for drug interactions involving psychotropic agents and COVID-19 therapies may be identified: (1) pharmacokinetic drug-drug interactions mainly acting on cytochrome P450; (2) pharmacodynamic drug-drug interactions resulting in additive or synergistic toxicity; (3) drug-disease interactions according to stage and severity of the disease; and (4) pharmacogenetic issues associated with polymorphisms of cytochrome P450 isoenzymes. In this review, we summarise the available literature on relevant drug interactions between psychotropic agents and COVID-19 therapies, providing practical clinical recommendations and potential management strategies according to severity of illness and clinical scenario.

Therapeutic Protein Drug Interaction Potential in Subjects With Psoriasis: An Assessment Based on Population Pharmacokinetic Analyses of Sensitive Cytochrome P450 Probe Substrates

Elevated cytokine levels in inflammatory diseases are associated with downregulation of certain cytochrome P450 (CYP) enzymes. Upon treatment with some cytokine-targeting therapeutic proteins, the CYP enzymes levels may be restored resulting in therapeutic protein-mediated drug interactions (TP-DI). These analyses characterized the worst-case scenario for CYP1A2, 2C9, and 3A-based TP-DI potential in patients with psoriasis by comparing the pharmacokinetics of probe substrates between healthy volunteers and subjects with moderate to severe psoriasis. Data for the CYP probe substrates midazolam (CYP3A), caffeine (CYP1A2), and S-warfarin (CYP2C9) from 7 drug interaction studies (1 in patients with psoriasis and 6 in healthy subjects) were pooled to develop a population pharmacokinetics model for each substrate. A 2-compartment model with absorption lag time for midazolam, a 1-compartment model with 5 transit absorption compartments for caffeine, and a 3-compartment model with absorption lag time for S-warfarin best described the observed data. Apparent oral clearance and relative bioavailability for caffeine and S-warfarin were not significantly different between the subject populations. Psoriasis patients were estimated to have 17% lower midazolam oral bioavailability than healthy volunteers. Compounded with other covariate effects, the ratio of median post hoc area under the plasma concentration-time estimates in subjects with psoriasis relative to healthy subjects was 0.96, 1.13, and 0.65 for midazolam, caffeine, and S-warfarin, respectively. Therefore, inflammation in psoriasis had no relevant effect on reducing CYP1A2, 2C9, and 3A activities in vivo and no significant TP-DIs mediated through these enzymes are expected in patients with psoriasis. This approach can potentially be used in lieu of dedicated TP-DI studies to identify TP-DI risks within a disease area.

Doravirine and the Potential for CYP3A-Mediated Drug-Drug Interactions

Identifying and understanding potential drug-drug interactions (DDIs) are vital for the treatment of human immunodeficiency virus type 1 (HIV-1) infection. This article discusses DDIs between doravirine, a nonnucleoside reverse transcriptase inhibitor (NNRTI), and cytochrome P450 3A (CYP3A) substrates and drugs that modulate CYP3A activity. Consistent with previously published in vitro data and DDI trials with the CYP3A substrates midazolam and atorvastatin, doravirine did not have any meaningful impact on the pharmacokinetics of the CYP3A substrates ethinyl estradiol and levonorgestrel. Coadministration of doravirine with CYP3A inhibitors (ritonavir or ketoconazole) increased doravirine exposure approximately 3-fold. However, these increases were not considered clinically meaningful. Conversely, previously published trials showed that coadministered CYP3A inducers (rifampin and rifabutin) decreased doravirine exposure by 88% and 50%, respectively (K. L. Yee, S. G. Khalilieh, R. I. Sanchez, R. Liu, et al., Clin Drug Investig 37:659-667, 2017 [https://doi.org/10.1007/s40261-017-0513-4]; S. G. Khalilieh, K. L. Yee, R. I. Sanchez, R. Liu, et al., J Clin Pharmacol 58:1044-1052, 2018 [https://doi.org/10.1002/jcph.1103]), while doravirine exposure following prior efavirenz administration led to an initial reduction in doravirine exposure of 62%, but the reduction became less pronounced with time (K. L. Yee, R. I. Sanchez, P. Auger, R. Liu, et al., Antimicrob Agents Chemother 61:e01757-16, 2017 [https://doi.org/10.1128/AAC.01757-16]). Overall, the coadministration of doravirine with CYP3A inhibitors and substrates is, therefore, supported by these data together with efficacy and safety data from clinical trials, while coadministration with strong CYP3A inducers, such as rifampin, cannot be recommended. Concomitant dosing with rifabutin (a CYP3A inducer less potent than rifampin) is acceptable if doravirine dosing is adjusted from once to twice daily; however, the effect of other moderate inducers on doravirine pharmacokinetics is unknown.

Analysis of Clinical Drug-Drug Interaction Data To Predict Magnitudes of Uncharacterized Interactions between Antiretroviral Drugs and Comedications

Despite their high potential for drug-drug interactions (DDI), clinical DDI studies of antiretroviral drugs (ARVs) are often lacking, because the full range of potential interactions cannot feasibly or pragmatically be studied, with some high-risk DDI studies also being ethically difficult to undertake. Thus, a robust method to screen and to predict the likelihood of DDIs is required. We developed a method to predict DDIs based on two parameters: the degree of metabolism by specific enzymes, such as CYP3A, and the strength of an inhibitor or inducer. These parameters were derived from existing studies utilizing paradigm substrates, inducers, and inhibitors of CYP3A to assess the predictive performance of this method by verifying predicted magnitudes of changes in drug exposure against clinical DDI studies involving ARVs. The derived parameters were consistent with the FDA classification of sensitive CYP3A substrates and the strength of CYP3A inhibitors and inducers. Characterized DDI magnitudes (n = 68) between ARVs and comedications were successfully quantified, meaning 53%, 85%, and 98% of the predictions were within 1.25-fold (0.80 to 1.25), 1.5-fold (0.66 to 1.48), and 2-fold (0.66 to 1.94) of the observed clinical data. In addition, the method identifies CYP3A substrates likely to be highly or, conversely, minimally impacted by CYP3A inhibitors or inducers, thus categorizing the magnitude of DDIs. The developed effective and robust method has the potential to support a more rational identification of dose adjustment to overcome DDIs, being particularly relevant in an HIV setting, given the treatment's complexity, high DDI risk, and limited guidance on the management of DDIs.

Pharmacokinetic Interactions between Simeprevir and Ledipasvir in Treatment-Naive Hepatitis C Virus Genotype 1-Infected Patients without Cirrhosis Treated with a Simeprevir-Sofosbuvir-Ledipasvir Regimen

Interactions between simeprevir (hepatitis C virus [HCV] NS3/4A protease inhibitor) and ledipasvir (HCV NS5A replication complex inhibitor) were investigated in treatment-naive HCV genotype 1-infected patients without cirrhosis, treated with simeprevir-sofosbuvir-ledipasvir in a two-panel, phase 2, open-label study. Patients had stable background treatment with sofosbuvir (400 mg once daily [QD]). In panel 1 (n = 20), the effect of ledipasvir (90 mg QD) on simeprevir (150 mg QD) was studied. Patients received simeprevir and sofosbuvir from days 1 to 14; steady-state pharmacokinetics (PK) of simeprevir was assessed (day 14). On day 15, ledipasvir was added and steady-state PK of simeprevir in the combination was evaluated (day 28). In panel 2 (n = 20), the effect of simeprevir on ledipasvir was investigated. From days 1 to 14, patients received ledipasvir and sofosbuvir and steady-state PK of ledipasvir was assessed (day 14). On day 15, simeprevir was added and a full PK profile was obtained (day 28). The least-squares mean maximum plasma concentration and area under the concentration-time curve (90% confidence interval) increased 2.3-fold (2.0- to 2.8-fold) and 3.1-fold (2.4- to 3.8-fold) for simeprevir, respectively (panel 1), and 1.6-fold (1.4- to 1.9-fold) and 1.7-fold (1.6- to 2.0-fold) for ledipasvir, respectively (panel 2), in the presence versus the absence of the other drug. All patients achieved sustained virologic responses 12 weeks after treatment end. Adverse events, mainly grade 1/2, occurred in 80% of patients; the most common was photosensitivity (45%). Due to the magnitude of interaction and the limited amount of safety data available, the use of this treatment combination is not recommended. (This study has been registered at ClinicalTrials.gov under registration no. NCT02421211.).

Drug-Drug Interactions Between Direct-Acting Antivirals and Psychoactive Medications

Treatment options for chronic hepatitis C virus (HCV) infection have drastically changed since the development and licensing of new potent direct-acting antivirals (DAAs). The majority of DAAs are extensively metabolized by liver enzymes and have the ability to influence cytochrome P450 (CYP) enzymes. Additionally, these DAAs are both substrates and inhibitors of drug transporters, which makes the DAAs both possible victims or perpetrators of drug–drug interactions (DDIs). There is a high prevalence of mental illnesses such as depression or psychosis in HCV-infected patients; therefore, psychoactive medications are frequently co-administered with DAAs. The majority of these psychoactive medications are also metabolized by CYP enzymes but remarkably little information is available on DDIs between psychoactive medications and DAAs. Hence, the aim of this review is to provide an overview of the interaction mechanisms between DAAs and psychoactive agents. In addition, we describe evidenced-based interactions between DAAs and psychoactive drugs and identify safe options for the simultaneous treatment of mental illnesses and chronic HCV infection.

Simulations of Cytochrome P450 3A4-Mediated Drug-Drug Interactions by Simple Two-Compartment Model-Assisted Static Method

In order to predict cytochrome P450 3A4 (CYP3A4)-mediated drug-drug interactions (DDIs), a simple 2-compartment model-assisted, overall inhibition activity (A_i,overall) method was derived based on 2 concepts. One concept was that the increase in blood victim level and fold increase in the area under the blood victim level curve produced by DDI are determined entirely by A_i,overall, the hepatic availability of the victim and fraction of urinary excreted unchanged victim, where A_i,overall is determined by the perpetrator-specific CYP isoform inhibition activities (A_i,CYPs, DDI predictor-1) and victim-specific fractional CYP isoform contributions (f_m,CYPs, predictor-2). The other concept was that a DDI can be bridged to other DDIs, so that any possible DDI produced by a given victim or a given perpetrator can be predicted by using these predictors. The A_i,CYP3A4s of 12 common CYP3A4 inhibitors were able to be determined and shown to be useful for the prediction of CYP3A4-mediated DDIs wherein victims were metabolized by multiple CYP isoforms. Additionally, it was demonstrated that f_m,CYP values with high confidence can be estimated by bridging DDIs produced by the same victim and different perpetrators. This bridging approach will accelerate prediction of DDIs produced by new chemical entities from the existing DDI database.

Ritonavir is the best alternative to ketoconazole as an index inhibitor of cytochrome P450-3A in drug-drug interaction studies

AIMS

The regulatory prohibition of ketoconazole as a CYP3A index inhibitor in drug-drug interaction (DDI) studies has compelled consideration of alternative inhibitors.

METHODS

The biomedical literature was searched to identify DDI studies in which oral midazolam (MDZ) was the victim, and the inhibitory perpetrator was either ketoconazole, itraconazole, clarithromycin, or ritonavir. The ratios (RAUC ) of total area under the curve (AUC) for MDZ with inhibitor divided by MDZ AUC in the control condition were aggregated across individual studies for each inhibitor.

RESULTS

Mean (± SE) RAUC values were: ketoconazole (15 studies, 131 subjects), 11.5 (±1.2); itraconazole (five studies, 48 subjects), 7.3 (±1.0); clarithromycin (five studies, 73 subjects), 6.5 (±10.9); and ritonavir (13 studies, 159 subjects), 14.5 (±2.0). Differences among inhibitors were significant (F = 5.31, P < 0.005). RAUC values were not significantly related to inhibitor dosage or to duration of inhibitor pre-exposure prior to administration of MDZ.

CONCLUSIONS

Ritonavir produces CYP3A inhibition equivalent to or greater than ketoconazole, and is the best index CYP3A inhibitor alternative to ketoconazole. Cobicistat closely resembles ritonavir in structure and function, and can also be considered. Itraconazole and clarithromycin are not suitable alternatives since they do not produce inhibition comparable with ketoconazole or ritonavir, and have other significant disadvantages as well.

Concentration effect relationship of CYP3A inhibition by ritonavir in humans

PURPOSE

To investigate the dose and concentration dependency of CYP3A inhibition by ritonavir using the established limited sampling strategy with midazolam for CYP3A activity.

METHODS

An open, fixed-sequence study was carried out in 12 healthy subjects. Single ascending doses of ritonavir (0.1-300 mg) were evaluated for CYP3A inhibition in two cohorts using midazolam as a marker substance.

RESULTS

Ritonavir administered as a single oral dose produced a dose-dependent CYP3A inhibition with an ID50 of 3.4 mg. Using the measured ritonavir concentrations an exposure-inhibition effect curve was established with an IC50 of 600 h pmol/L (AUC2-4). Over the ritonavir dose range studied non-linear exposure of ritonavir was observed.

CONCLUSIONS

Ritonavir shows a dose and concentration effect relationship of CYP3A inhibition. In addition, a proposed auto-inhibition of ritonavir metabolism resulted in a non-linear exposure of ritonavir with sub-proportional concentrations at low doses. A time-dependent CYP3A activity may result when inhibitors of CYP3A with short elimination half-lives are used.

Effect of a herbal extract containing curcumin and piperine on midazolam, flurbiprofen and paracetamol (acetaminophen) pharmacokinetics in healthy volunteers

AIMS

Turmeric extract derived curcuminoids (curcumin, demethoxycurcumin and bisdemethoxycurcumin) are currently being evaluated for the treatment of cancer and Alzheimer's dementia. Previous in vitro studies indicate that curcuminoids and piperine (a black pepper derivative that enhances curcuminoid bioavailability) could inhibit human CYP3A, CYP2C9, UGT and SULT dependent drug metabolism. The aim of this study was to determine whether a commercially available curcuminoid/piperine extract alters the pharmacokinetic disposition of probe drugs for these enzymes in human volunteers.

METHODS

A randomized placebo-controlled six way crossover study was conducted in eight healthy volunteers. A standardized curcuminoid/piperine preparation (4 g curcuminoids plus 24 mg piperine) or matched placebo was given orally four times over 2 days before oral administration of midazolam (CYP3A probe), flurbiprofen (CYP2C9 probe) or paracetamol (acetaminophen) (dual UGT and SULT probe). Plasma and urine concentrations of drugs, metabolites and herbals were measured by HPLC. Subject sedation and electroencephalograph effects were also measured following midazolam dosing.

RESULTS

Compared with placebo, the curcuminoid/piperine treatment produced no meaningful changes in plasma C(max), AUC, clearance, elimination half-life or metabolite levels of midazolam, flurbiprofen or paracetamol (α = 0.05, paired t-tests). There was also no effect of curcuminoid/piperine treatment on the pharmacodynamics of midazolam. Although curcuminoid and piperine concentrations were readily measured in plasma following glucuronidase/sulfatase treatment, unconjugated concentrations were consistently below the assay thresholds (0.05-0.08 μM and 0.6 μM, respectively).

CONCLUSION

The results indicate that short term use of this piperine-enhanced curcuminoid preparation is unlikely to result in a clinically significant interaction involving CYP3A, CYP2C9 or the paracetamol conjugation enzymes.

Evaluation of limited sampling models for prediction of oral midazolam AUC for CYP3A phenotyping and drug interaction studies

BACKGROUND

The area under the concentration-time curve (AUC) after oral midazolam administration is commonly used for cytochrome P450 (CYP) 3A phenotyping studies. The aim of this investigation was to evaluate a limited sampling strategy for the prediction of AUC with oral midazolam.

METHODS

A total of 288 concentration-time profiles from 123 healthy volunteers who participated in four previously performed drug interaction studies with intense sampling after a single oral dose of 7.5 mg midazolam were available for evaluation. Of these, 45 profiles served for model building, which was performed by stepwise multiple linear regression, and the remaining 243 datasets served for validation. Mean prediction error (MPE), mean absolute error (MAE) and root mean squared error (RMSE) were calculated to determine bias and precision

RESULTS

The one- to four-sampling point models with the best coefficient of correlation were the one-sampling point model (8 h; r (2) = 0.84), the two-sampling point model (0.5 and 8 h; r (2) = 0.93), the three-sampling point model (0.5, 2, and 8 h; r (2) = 0.96), and the four-sampling point model (0.5,1, 2, and 8 h; r (2) = 0.97). However, the one- and two-sampling point models were unable to predict the midazolam AUC due to unacceptable bias and precision. Only the four-sampling point model predicted the very low and very high midazolam AUC of the validation dataset with acceptable precision and bias. The four-sampling point model was also able to predict the geometric mean ratio of the treatment phase over the baseline (with 90 % confidence interval) results of three drug interaction studies in the categories of strong, moderate, and mild induction, as well as no interaction.

CONCLUSION

A four-sampling point limited sampling strategy to predict the oral midazolam AUC for CYP3A phenotyping is proposed. The one-, two- and three-sampling point models were not able to predict midazolam AUC accurately.

Pharmacokinetic interaction between prasugrel and ritonavir in healthy volunteers

The new anti-aggregating agent prasugrel is bioactivated by cytochromes P450 (CYP) 3A and 2B6. Ritonavir is a potent CYP3A inhibitor and was shown in vitro as a CYP2B6 inhibitor. The aim of this open-label cross-over study was to assess the effect of ritonavir on prasugrel active metabolite (prasugrel AM) pharmacokinetics in healthy volunteers. Ten healthy male volunteers received 10 mg prasugrel. After at least a week washout, they received 100 mg ritonavir, followed by 10 mg prasugrel 2 hr later. We used dried blood spot sampling method to monitor prasugrel AM pharmacokinetics (C_max, t_1/2, t_max, AUC_{0–6 hr}) at 0, 0.25, 0.5, 1, 1.5, 2, 4 and 6 hr after prasugrel administration. A ‘cocktail’ approach was used to measure CYP2B6, 2C9, 2C19 and 3A activities. In the presence of ritonavir, prasugrel AM C_max and AUC were decreased by 45% (mean ratio: 0.55, CI 90%: 0.40–0.7, p = 0.007) and 38% (mean ratio: 0.62, CI 90%: 0.54–0.7, p = 0.005), respectively, while t_1/2 and t_max were not affected. Midazolam metabolic ratio (MR) dramatically decreased in presence of ritonavir (6.7 ± 2.6 versus 0.13 ± 0.07) reflecting an almost complete inhibition of CYP3A4, whereas omeprazole, flurbiprofen and bupropion MR were not affected. These data demonstrate that ritonavir is able to block prasugrel CYP3A4 bioactivation. This CYP-mediated drug–drug interaction might lead to a significant reduction of prasugrel efficacy in HIV-infected patients with acute coronary syndrome.

Quantification of femtomolar concentrations of the CYP3A substrate midazolam and its main metabolite 1'-hydroxymidazolam in human plasma using ultra performance liquid chromatography coupled to tandem mass spectrometry

The benzodiazepine midazolam is a probe drug used to phenotype cytochrome P450 3A activity. In this situation, effective sedative concentrations are neither needed nor desired, and in fact the use of very low doses is advantageous. We therefore developed and validated an assay for the femtomolar quantification of midazolam and 1'-hydroxymidazolam in human plasma. Plasma (0.25 mL) and 96-well-based solid-phase extraction were used for sample preparation. Extraction recoveries ranged between 75 and 92% for both analytes. Extracts were chromatographed within 2 min on a Waters BEH C18 1.7 μm UPLC® column with a fast gradient consisting of formic acid, ammonia, and acetonitrile. Midazolam and 1'-hydroxymidazolam were quantified using deuterium- and (13)C-labeled internal standards and positive electrospray tandem mass spectrometry in the multiple reaction monitoring mode, which yielded lower limits of quantification of 50 fg/mL (154 fmol/L) and 250 fg/mL (733 fmol/L) and a corresponding precision of <20%. The calibrated concentration ranges were linear for midazolam (0.05-250 pg/mL) and 1'-hydroxymidazolam (0.25-125 pg/mL), with correlation coefficients of >0.99. Within-batch and batch-to-batch precision in the calibrated ranges for both analytes were <14% and <12%. No ion suppression was detectable, and plasma matrix effects were minimized to <15% (<25%) for midazolam (1'-hydroxymidazolam). The assay was successfully applied to assess the kinetics of midazolam in two human volunteers after the administration of single oral microgram doses (1-100 μg). This ultrasensitive assay allowed us to quantify the kinetics of midazolam and 1'-hydroxymidazolam for at least 10 h, even after the administration of only 1 μg of midazolam.

Complex drug interactions of HIV protease inhibitors 1: inactivation, induction, and inhibition of cytochrome P450 3A by ritonavir or nelfinavir

Conflicting drug-drug interaction (DDI) studies with the HIV protease inhibitors (PIs) suggest net induction or inhibition of intestinal or hepatic CYP3A. As part of a larger DDI study in healthy volunteers, we determined the effect of extended administration of two PIs, ritonavir (RTV) or nelfinavir (NFV), or the induction-positive control rifampin on intestinal and hepatic CYP3A activity as measured by midazolam (MDZ) disposition after a 14-day treatment with the PI in either staggered (MDZ ∼12 h after PI) or simultaneous (MDZ and PI coadministered) manner. Oral and intravenous MDZ areas under the plasma concentration-time curves were significantly increased by RTV or NFV and were decreased by rifampin. Irrespective of method of administration, RTV decreased net intestinal and hepatic CYP3A activity, whereas NFV decreased hepatic but not intestinal CYP3A activity. The magnitude of these DDIs was more accurately predicted using PI CYP3A inactivation parameters generated in sandwich-cultured human hepatocytes rather than human liver microsomes.

Efflux transporters- and cytochrome P-450-mediated interactions between drugs of abuse and antiretrovirals

Multidrug regimens and corresponding drug interactions cause many adverse reactions and treatment failures. Drug efflux transporters: P-gp, MRP, BCRP in conjunction with metabolizing enzymes (CYPs) are major factors in such interactions. Most effective combination antiretrovirals (ARV) therapy includes a PI or a NNRTI or two NRTI. Coadministration of such ARV may induce efflux transporters and/or CYP3A4 resulting in sub-therapeutic blood levels and therapeutic failure due to reduced absorption and/or increased metabolism. A similar prognosis is true for ARV-compounds and drugs of abuse combinations. Morphine and nicotine enhance CYP3A4 and MDR1 expression in vitro. A 2.5 fold rise of cortisol metabolite was evident in smokers relative to nonsmokers. Altered functions of efflux transporters and CYPs in response to ARV and drugs of abuse may result in altered drug absorption and metabolism. Appropriate in vitro models can be employed to predict such interactions. Influence of genetic polymorphism, SNP and inter-individual variation in drug response has been discussed. Complexity underlying the relationship between efflux transporters and CYP makes it difficult to predict the outcome of HAART as such, particularly when HIV patients taking drugs of abuse do not adhere to HAART regimens. HIV(+) pregnant women on HAART medications, indulging in drugs of abuse, may develop higher viral load due to such interactions and lead to increase in mother to child transmission of HIV. A multidisciplinary approach with clear understanding of mechanism of interactions may allow proper selection of regimens so that desired therapeutic outcome of HAART can be reached without any side effects.