Mechanisms of pharmacokinetic enhancement between ritonavir and saquinavir; micro/small dosing tests using midazolam (CYP3A4), fexofenadine (p-glycoprotein), and pravastatin (OATP1B1) as probe drugs

Pathophysiology and Clinical Management of Dyslipidemia in People Living with HIV: Sailing through Rough Seas

Infections with human immunodeficiency virus (HIV) and acquired immune deficiency syndrome (AIDS) represent one of the greatest health burdens worldwide. The complex pathophysiological pathways that link highly active antiretroviral therapy (HAART) and HIV infection per se with dyslipidemia make the management of lipid disorders and the subsequent increase in cardiovascular risk essential for the treatment of people living with HIV (PLHIV). Amongst HAART regimens, darunavir and atazanavir, tenofovir disoproxil fumarate, nevirapine, rilpivirine, and especially integrase inhibitors have demonstrated the most favorable lipid profile, emerging as sustainable options in HAART substitution. To this day, statins remain the cornerstone pharmacotherapy for dyslipidemia in PLHIV, although important drug-drug interactions with different HAART agents should be taken into account upon treatment initiation. For those intolerant or not meeting therapeutic goals, the addition of ezetimibe, PCSK9, bempedoic acid, fibrates, or fish oils should also be considered. This review summarizes the current literature on the multifactorial etiology and intricate pathophysiology of hyperlipidemia in PLHIV, with an emphasis on the role of different HAART agents, while also providing valuable insights into potential switching strategies and therapeutic options.

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.

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.

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.

Quantitative prediction of pharmacokinetic properties of drugs in humans: Recent advance in in vitro models to predict the impact of efflux transporters in the small intestine and blood-brain barrier

Efflux transport systems are essential to suppress the absorption of xenobiotics from the intestinal lumen and protect the critical tissues at the blood-tissue barriers, such as the blood-brain barrier. The function of drug efflux transport is dominated by various transporters. Accumulated clinical evidences have revealed that genetic variations of the transporters, together with coadministered drugs, affect the expression and/or function of transporters and subsequently the pharmacokinetics of substrate drugs. Thus, in the preclinical stage of drug development, quantitative prediction of the impact of efflux transporters as well as that of uptake transporters and metabolic enzymes on the pharmacokinetics of drugs in humans has been performed using various in vitro experimental tools. Various kinds of human-derived cell systems can be applied to the precise prediction of drug transport in humans. Mathematical modeling consisting of each intrinsic metabolic or transport process enables us to understand the disposition of drugs both at the organ level and at the level of the whole body by integrating a variety of experimental results into model parameters. This review focuses on the role of efflux transporters in the intestinal absorption and brain distribution of drugs, in addition to recent advances in predictive tools and methodologies.

Pharmacokinetics, Safety, and Efficacy of Trastuzumab Deruxtecan with Concomitant Ritonavir or Itraconazole in Patients with HER2-Expressing Advanced Solid Tumors

PURPOSE

To evaluate drug-drug interactions between the human epidermal growth factor receptor 2 (HER2)-targeted antibody-drug conjugate trastuzumab deruxtecan (T-DXd; DS-8201a) and the OATP1B/CYP3A inhibitor ritonavir or the strong CYP3A inhibitor itraconazole.

PATIENTS AND METHODS

Patients with HER2-expressing advanced solid tumors were enrolled in this phase I, open-label, single-sequence crossover study (NCT03383692) and received i.v. T-DXd 5.4 mg/kg every 3 weeks. Patients received ritonavir (cohort 1) or itraconazole (cohort 2) from day 17 of cycle 2 through the end of cycle 3. Primary endpoints were maximum serum concentration (C max) and partial area under the concentration-time curve from beginning of cycle through day 17 (AUC17d) for T-DXd and deruxtecan (DXd) with (cycle 3) and without (cycle 2) ritonavir or itraconazole treatment.

RESULTS

Forty patients were enrolled (cohort 1, n = 17; cohort 2, n = 23). T-DXd C max was similar whether combined with ritonavir [cohort 1, cycle 3/cycle 2; 90% confidence interval (CI): 1.05 (0.98-1.13)] or itraconazole [cohort 2, 1.03 (0.96-1.09)]. T-DXd AUC17d increased from cycle 2 to 3; however, the cycle 3/cycle 2 ratio upper CI bound remained at ≤1.25 for both cohorts. For DXd (cycle 3/cycle 2), C max ratio was 0.99 (90% CI, 0.85-1.14) for cohort 1 and 1.04 (0.92-1.18) for cohort 2; AUC17d ratio was 1.22 (1.08-1.37) and 1.18 (1.11-1.25), respectively. The safety profile of T-DXd plus ritonavir or itraconazole was consistent with previous studies of T-DXd monotherapy. T-DXd demonstrated promising antitumor activity across HER2-expressing solid-tumor types.

CONCLUSIONS

T-DXd was safely combined with ritonavir or itraconazole without clinically meaningful impact on T-DXd or DXd pharmacokinetics.

Phase 0/microdosing approaches: time for mainstream application in drug development?

Phase 0 approaches - which include microdosing - evaluate subtherapeutic exposures of new drugs in first-in-human studies known as exploratory clinical trials. Recent progress extends phase 0 benefits beyond assessment of pharmacokinetics to include understanding of mechanism of action and pharmacodynamics. Phase 0 approaches have the potential to improve preclinical candidate selection and enable safer, cheaper, quicker and more informed developmental decisions. Here, we discuss phase 0 methods and applications, highlight their advantages over traditional strategies and address concerns related to extrapolation and developmental timelines. Although challenges remain, we propose that phase 0 approaches be at least considered for application in most drug development scenarios.

Methamphetamine administration increases hepatic CYP1A2 but not CYP3A activity in female guinea pigs

Methamphetamine use has increased over the past decade and the first use of methamphetamine is most often when women are of reproductive age. Methamphetamine accumulates in the liver; however, little is known about the effect of methamphetamine use on hepatic drug metabolism. Methamphetamine was administered on 3 occassions to female Dunkin Hartley guinea pigs of reproductive age, mimicking recreational drug use. Low doses of test drugs caffeine and midazolam were administered after the third dose of methamphetamine to assess the functional activity of cytochrome P450 1A2 and 3A, respectively. Real-time quantitative polymerase chain reaction was used to quantify the mRNA expression of factors involved in glucocorticoid signalling, inflammation, oxidative stress and drug transporters. This study showed that methamphetamine administration decreased hepatic CYP1A2 mRNA expression, but increased CYP1A2 enzyme activity. Methamphetamine had no effect on CYP3A enzyme activity. In addition, we found that methamphetamine may also result in changes in glucocorticoid bioavailability, as we found a decrease in 11β-hydroxysteroid dehydrogenase 1 mRNA expression, which converts inactive cortisone into active cortisol. This study has shown that methamphetamine administration has the potential to alter drug metabolism via the CYP1A2 metabolic pathway in female guinea pigs. This may have clinical implications for drug dosing in female methamphetamine users of reproductive age.

Drug Interactions of Psychiatric and COVID-19 Medications

INTRODUCTION

Coronavirus disease 2019 (COVID-19) has become a pandemic with 1771514 cases identified in the world and 70029 cases in Iran until April 12, 2020. The co-prescription of psychotropics with COVID-19 medication is not uncommon. Healthcare providers should be familiar with many Potential Drug-Drug Interactions (DDIs) between COVID-19 therapeutic agents and psychotropic drugs based on cytochrome P450 metabolism. This review comprehensively summarizes the current literature on DDIs between antiretroviral drugs and chloroquine/hydroxychloroquine, and psychotropics, including antidepressants, antipsychotics, mood stabilizers, and anxiolytics.

METHODS

Medical databases, including Google Scholar, PubMed, Web of Science, and Scopus were searched to identify studies in English with keywords related to psychiatric disorders, medications used in the treatment of psychiatric disorders and COVID-19 medications.

RESULTS

There is a great potential for DDIs between psychiatric and COVID-19 medications ranging from interactions that are not clinically apparent (minor) to those that produce life-threatening adverse drug reactions, or loss of treatment efficacy. The majority of interactions are pharmacokinetic interactions via the cytochrome P450 enzyme system.

CONCLUSION

DDIs are a major concern in the comorbidity of psychiatric disorders and COVID-19 infection resulting in the alteration of expected therapeutic outcomes. The risk of toxicity or lack of efficacy may occur due to a higher or lower plasma concentration of medications. However, psychiatric medication can be safely used in combination with COVID-19 pharmacotherapy with either a wise selection of medication with the least possibility of interaction or careful patient monitoring and management.

Variability in In Vitro OATP1B1/1B3 Inhibition Data: Impact of Incubation Conditions on Variability and Subsequent Drug Interaction Predictions

As the research into the organic anion transporting polypeptides (OATPs) continues to grow, it is important to ensure that the data generated are accurate and reproducible. In the in vitro evaluation of OATP1B1/1B3 inhibition, there are many variables that can contribute to variability in the resulting inhibition constants, which can then, in turn, contribute to variable results when clinical predictions (R-values) are performed. Currently, the only experimental condition recommended by the US Food and Drug Administration (FDA) is the inclusion of a pre-incubation period.¹ To identify other potential sources of variability, a descriptive analysis of available in vitro inhibition data was completed. For each of the 21 substrate/inhibitor pairs evaluated, cell type and pre-incubation were found to have the greatest effect on half-maximal inhibitory concentration (IC₅₀ ) variability. Indeed, when only HEK293 cells and co-incubation conditions were included, the observed variability for the entire data set (highest IC₅₀ /lowest) was reduced from 12.4 to 5.2. The choice of probe substrate used in the study also had a significant effect on inhibitor constant variability. Interestingly, despite the broad range of inhibitory constants identified, these two factors showed little effect on the calculated R-values relative to the FDA evaluation cutoff of 1.1 triggering a clinical evaluation for the inhibitors evaluated. However, because of the small data set available, further research is needed to confirm these preliminary results and define best practice for the study of OATPs.

Drug-drug interactions and clinical considerations with co-administration of antiretrovirals and psychotropic drugs

Psychotropic medications are frequently co-prescribed with antiretroviral therapy (ART), owing to a high prevalence of psychiatric illness within the population living with HIV, as well as a 7-fold increased risk of HIV infection among patients with psychiatric illness. While ART has been notoriously associated with a multitude of pharmacokinetic drug interactions involving the cytochrome P450 enzyme system, the magnitude and clinical impact of these interactions with psychotropics may range from negligible effects on plasma concentrations to life-threatening torsades de pointes or respiratory depression. This comprehensive review summarizes the currently available information regarding drug-drug interactions between antiretrovirals and pharmacologic agents utilized in the treatment of psychiatric disorders-antidepressants, stimulants, antipsychotics, anxiolytics, mood stabilizers, and treatments for opioid use disorder and alcohol use disorder-and provides recommendations for their management. Additionally, overlapping toxicities between antiretrovirals and the psychotropic classes are highlighted. Knowledge of the interaction and adverse effect potential of specific antiretrovirals and psychotropics will allow clinicians to make informed prescribing decisions to better promote the health and wellness of this high-risk population.

Phase 0, including microdosing approaches: Applying the Three Rs and increasing the efficiency of human drug development

Phase 0 approaches, including microdosing, involve the use of sub-therapeutic exposures to the tested drugs, thus enabling safer, more-relevant, quicker and cheaper first-in-human (FIH) testing. These approaches also have considerable potential to limit the use of animals in human drug development. Recent years have witnessed progress in applications, methodology, operations, and drug development culture. Advances in applications saw an expansion in therapeutic areas, developmental scenarios and scientific objectives, in, for example, protein drug development and paediatric drug development. In the operational area, the increased sensitivity of Liquid Chromatography Tandem Mass Spectrometry (LC-MS/MS), expansion of the utility of Positron Emission Tomography (PET) imaging, and the introduction of Cavity Ring-Down Spectroscopy (CRDS), have led to the increased accessibility and utility of Phase 0 approaches, while reducing costs and exposure to radioactivity. PET has extended the application of microdosing, from its use as a predominant tool to record pharmacokinetics, to a method for recording target expression and target engagement, as well as cellular and tissue responses. Advances in methodology include adaptive Phase 0/Phase 1 designs, cassette and cocktail microdosing, and Intra-Target Microdosing (ITM), as well as novel modelling opportunities and simulations. Importantly, these methodologies increase the predictive power of extrapolation from microdose to therapeutic level exposures. However, possibly the most challenging domain in which progress has been made, is the culture of drug development. One of the main potential values of Phase 0 approaches is the opportunity to terminate development early, thus not only applying the principle of 'kill-early-kill-cheap' to enhance the efficiency of drug development, but also obviating the need for the full package of animal testing required for therapeutic level Phase 1 studies. Finally, we list developmental scenarios that utilised Phase 0 approaches in novel drug development.

Simultaneous Determination of Five Cytochrome P450 Probe Substrates and Their Metabolites and Organic Anion Transporting Polypeptide Probe Substrate in Human Plasma Using Liquid Chromatography-Tandem Mass Spectrometry

A rapid and selective liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for the simultaneous determination of organic anion transporting polypeptide 1B1 (OATP1B1) and cytochrome P450 (P450) probe substrates and their phase I metabolites in human plasma was developed. The OATP1B1 (pitavastatin) and five P450 probe substrates, caffeine (CYP1A2), losartan (CYP2C9), omeprazole (CYP2C19), dextromethorphan (CYP2D6), and midazolam (CYP3A) and their metabolites were extracted from human plasma (50 µL) using methanol. Analytes were separated on a C18 column followed by selected reaction monitoring detection using MS/MS. All analytes were separated simultaneously within a 9 min run time. The developed method was fully validated over the expected clinical concentration range for all analytes tested. The intra- and inter-day precisions for all analytes were lower than 11.3% and 8.82%, respectively, and accuracy was 88.5–117.3% and 96.1–109.2%, respectively. The lower limit of quantitation was 0.05 ng/mL for dextromethorphan, dextrorphan, midazolam, and 1′-hydroxymidazolam; 0.5 ng/mL for losartan, EXP-3174, omeprazole, 5′-hydroxyomeprazole, and pitavastatin; and 5 ng/mL for caffeine and paraxanthine. The method was successfully used in a pharmacokinetic study in healthy subjects after oral doses of five P450 and OATP1B1 probes. This analytical method provides a simple, sensitive, and accurate tool for the determination of OATP1B1 and five major P450 activities in vivo drug interaction studies.

Relationships of Changes in Pharmacokinetic Parameters of Substrate Drugs in Drug-Drug Interactions on Metabolizing Enzymes and Transporters

A general objective of drug-drug interaction (DDI) studies is to determine whether potential interactions of new molecular entities with concomitantly administered other drugs exist and, if DDIs occur, whether dosage adjustments are required. A typical end point for DDI evaluations is the ratio of area under the plasma concentration-time curve (AUC) of substrate drugs (AUCR), whereas the ratios of maximal plasma concentration (C_max ) and terminal half-life (t_1/2 ) are also important to understand DDI mechanisms (C_max R and t_1/2 R, respectively). Because changes in substrate AUC by precipitant drugs ultimately result from alterations of C_max and t_1/2 , AUCR can be considered a hybrid parameter of C_max R and t_1/2 R, for example, AUCR ≈ C_max R  ×  t_1/2 R. The primary objective of this study was to investigate the relationships between AUCR, C_max R, and t_1/2 R in physiologically based pharmacokinetic model-predicted and clinically observed DDI results. First, the model-predicted results showed the excellent proportional relationship between AUCR and (C_max R × t_1/2 R) in DDI results of virtual substrates having a wide range of oral bioavailability with coadministration of ketoconazole, ritonavir, and rifampin. Second, the reasonable proportional relationships were also observed in the clinically observed DDI results of midazolam and statins (atorvastatin, cerivastatin, fluvastatin, lovastatin, pitavastatin, pravastatin, rosuvastatin, and simvastatin) with various inhibitors and inducers. Finally, these results suggest that utilization of the proportional relationship between AUCR and (C_max R × t_1/2 R) can provide an additional framework to further interpret DDI results reasonably and clearly. Furthermore, the proportional relationship can be purposely used to assess study design and pharmacokinetic analyses in DDI studies.

Mechanisms and Predictions of Drug-Drug Interactions of the Hepatitis C Virus Three Direct-Acting Antiviral Regimen: Paritaprevir/Ritonavir, Ombitasvir, and Dasabuvir

To assess drug-drug interaction (DDI) potential for the three direct-acting antiviral (3D) regimen of ombitasvir, dasabuvir, and paritaprevir, in vitro studies profiled drug-metabolizing enzyme and transporter interactions. Using mechanistic static and dynamic models, DDI potential was predicted for CYP3A, CYP2C8, UDP-glucuronosyltransferase (UGT) 1A1, organic anion-transporting polypeptide (OATP) 1B1/1B3, breast cancer resistance protein (BCRP), and P-glycoprotein (P-gp). Perpetrator static model DDI predictions for metabolizing enzymes were within 2-fold of the clinical observations, but additional physiologically based pharmacokinetic modeling was necessary to achieve the same for drug transporters. When perpetrator interactions were assessed, ritonavir was responsible for the strong increase in exposure of sensitive CYP3A substrates, whereas paritaprevir (an OATP1B1/1B3 inhibitor) greatly increased the exposure of sensitive OATP1B1/1B3 substrates. The 3D regimen drugs are UGT1A1 inhibitors and are predicted to moderately increase plasma exposure of sensitive UGT1A1 substrates. Paritaprevir, ritonavir, and dasabuvir are BCRP inhibitors. Victim DDI predictions were qualitatively in line with the clinical observations. Plasma exposures of the 3D regimen were reduced by strong CYP3A inducers (paritaprevir and ritonavir; major CYP3A substrates) but were not affected by strong CYP3A4 inhibitors, since ritonavir (a CYP3A inhibitor) is already present in the regimen. Strong CYP2C8 inhibitors increased plasma exposure of dasabuvir (a major CYP2C8 substrate), OATP1B1/1B3 inhibitors increased plasma exposure of paritaprevir (an OATP1B1/1B3 substrate), and P-gp or BCRP inhibitors (all compounds are substrates of P-gp and/or BCRP) increased plasma exposure of the 3D regimen. Overall, the comprehensive mechanistic assessment of compound disposition along with mechanistic and PBPK approaches to predict victim and perpetrator DDI liability may enable better clinical management of nonstudied drug combinations with the 3D regimen.

Evidence-based review of statin use in patients with HIV on antiretroviral therapy

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Cardiovascular disease is up to two times more prevalent in patient with HIV.

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Based on pharmacokinetic and clinical data, atorvastatin and pravastatin are generally considered safe for HIV patients receiving ART.

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Rosuavstatin is generally safe if started at a low dose and a maximum 20 mg per day.

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Fluvastatin, lovastatin, and simvastatin should be avoided in patients with HIV receiving ART.

Introduction

As a result of improved safe and effective therapeutic options for human immunodeficiency virus (HIV), life expectancy of those living with HIV is increasing leading to new challenges (e.g., management of chronic diseases). Some chronic diseases (e.g., cardiovascular disease [CVD]), are up to two times more prevalent in patients with HIV. Statins are a mainstay of therapy for prevention of CVD; but, clinicians should be aware that not all statins are appropriate for use in the HIV population, especially those receiving antiretroviral therapy (ART). The purpose of this article is to review the pharmacokinetic and clinical data for statin therapy in HIV-infected patients receiving ART.

Methods

A systematic literature search using PubMed and MEDLINE databases was performed using each statin drug name combined with HIV, pharmacokinetics, AIDS, and/or human immunodeficiency virus. English language trials published from 1946 to November 2016 were considered, and results were limited to clinical efficacy trials.

Results

In general, atorvastatin and pravastatin are safe and effective for patients treated with protease-inhibitor (PI) or non-nucleoside reverse transcriptase inhibitor-based ART. Rosuvastatin is generally considered safe if started at a low dose, but should be avoided if possible in patients receiving PI-based ART. Pitavastatin has limited supporting evidence, but appears safe for use based on its pharmacokinetic properties and low number of drug interactions. Fluvastatin, lovastatin, and simvastatin should be avoided in patients receiving ART due to drug interactions, adverse events, and/or limited clinical data.

Conclusion

Clinicians need to be familiar with the intricacies of statin selection for the prevention of CVD in patients with HIV on ART.

Coadministration of ticagrelor and ritonavir: Toward prospective dose adjustment to maintain an optimal platelet inhibition using the PBPK approach

Ticagrelor is a potent antiplatelet drug metabolized by cytochrome (CYP)3A. It is contraindicated in patients with human immunodeficiency virus (HIV) because of the expected CYP3A inhibition by most protease inhibitors, such as ritonavir and an increased bleeding risk. In this study, a physiologically based pharmacokinetic (PBPK) model was created for ticagrelor and its active metabolite (AM). Based on the simulated interaction between ticagrelor 180 mg and ritonavir 100 mg, a lower dose of ticagrelor was calculated to obtain, when coadministered with ritonavir, the same pharmacokinetic (PK) and platelet inhibition as ticagrelor administered alone. A clinical study was thereafter conducted in healthy volunteers. Observed PK profiles of ticagrelor and its AM were successfully predicted with the model. Platelet inhibition was nearly complete in both sessions despite administration of a fourfold lower dose of ticagrelor in the second session. This PBPK model could be prospectively used to broaden the usage of ticagrelor in patients with ritonavir-treated HIV regardless of the CYP3A inhibition.

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.