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As global health services respond to the coronavirus pandemic, many prescribers are turning to experimental drugs. This review aims to assess the risk of drug-drug interactions in the severely ill COVID-19 patient. Experimental therapies were identified by searching ClinicalTrials.gov for 'COVID-19', '2019-nCoV', '2019 novel coronavirus' and 'SARS-CoV-2'. The last search was performed on 30 June 2020. Herbal medicines, blood-derived products and in vitro studies were excluded. We identified comorbidities by searching PubMed for the MeSH terms 'COVID-19', 'Comorbidity' and 'Epidemiological Factors'. Potential drug-drug interactions were evaluated according to known pharmacokinetics, overlapping toxicities and QT risk. Drug-drug interactions were graded GREEN and YELLOW: no clinically significant interaction; AMBER: caution; RED: serious risk. A total of 2378 records were retrieved from ClinicalTrials.gov, which yielded 249 drugs that met inclusion criteria. Thirteen primary compounds were screened against 512 comedications. A full database of these interactions is available at www.covid19-druginteractions.org. Experimental therapies for COVID-19 present a risk of drug-drug interactions, with lopinavir/ritonavir (10% RED, 41% AMBER; mainly a perpetrator of pharmacokinetic interactions but also risk of QT prolongation particularly when given with concomitant drugs that can prolong QT), chloroquine and hydroxychloroquine (both 7% RED and 27% AMBER, victims of some interactions due to metabolic profile but also perpetrators of QT prolongation) posing the greatest risk. With management, these risks can be mitigated. We have published a drug-drug interaction resource to facilitate medication review for the critically ill patient., (© The Author(s) 2020. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Aims: Direct-acting antiviral agents (DAAs) for the treatment of hepatitis C (HCV) can be associated with drug-drug interactions (DDIs) with concomitant medications. The practical clinical implications of such DDIs are poorly understood. We assessed the clinical impact of possible pharmacokinetic (PK) interactions between simeprevir and frequently prescribed concomitant medications., Methods: This post hoc analysis pooled data from nine studies which evaluated simeprevir (SMV)-based interferon-free HCV treatment. Three classes of frequently used concomitant medications of interest (CMOIs) were analysed [antihypertensive drugs (AHDs), anxiolytic drugs (AXDs) and lipid-lowering drugs (LLDs)] and categorized as amber or green according to their DDI potential with SMV (green: no DDIs; amber: potential/known PK interactions). Concomitant medications not recommended to be coadministered with SMV were not included. The composite primary endpoint was defined as the frequency of either discontinuation, interruption or dose modification of the CMOI during 12 weeks of SMV treatment., Results: Few patients met the composite endpoint in the various subgroups. Patients on amber CMOIs tended to experience CMOI modification more often (13.4-19.4%) than those on green CMOIs (3.1-10.8%). There was no difference in the frequency of adverse events between patients taking green and those taking amber CMOIs., Conclusions: In this large pooled analysis, coadministration of the evaluated commonly prescribed medications with known or potential PK interactions with SMV was manageable and resulted in few adjustments of concomitant medications. Our method could serve as a blueprint for the evaluation of the impact of DDIs., (© 2018 The Authors. British Journal of Clinical Pharmacology published by John Wiley & Sons Ltd on behalf of British Pharmacological Society.)

Background: HIV-positive women receiving efavirenz-based ART and levonorgestrel contraceptive implants are at risk of low levonorgestrel exposure and unintended pregnancy., Objectives: To investigate clinically applicable dose-adjustment strategies to overcome the known drug-drug interaction (DDI) between levonorgestrel and efavirenz, using a physiologically based pharmacokinetic (PBPK) modelling-based approach., Methods: A PBPK model was qualified against clinical data to predict levonorgestrel plasma concentrations when standard-dose (150 mg) levonorgestrel implants were administered alone (control group), as well as when standard-dose or increased-dose (300 mg) levonorgestrel implants were coadministered with either 600 or 400 mg of efavirenz., Results: No difference was seen between in vivo clinical and PBPK-model-simulated levonorgestrel plasma concentrations (P > 0.05). Simulated levonorgestrel plasma concentrations were ∼50% lower at 48 weeks post-implant-placement in virtual individuals receiving standard-dose levonorgestrel with either 600 or 400 mg of efavirenz compared with the control group (efavirenz:control geometric mean ratio = 0.42 and 0.49, respectively). Conversely, increased-dose levonorgestrel in combination with either 600 or 400 mg of efavirenz was sufficient to restore levonorgestrel concentrations to levels similar to those observed in the 150 mg levonorgestrel control group 48 weeks post-implant-placement (efavirenz:control geometric mean ratio = 0.86 and 1.03, respectively)., Conclusions: These results suggest that the clinically significant DDI between efavirenz and levonorgestrel is likely to persist despite efavirenz dose reduction, whereas dose escalation of implantable levonorgestrel may represent a successful clinical strategy to circumvent efavirenz-levonorgestrel DDIs and will be of use to inform clinical trial design to assess coadministration of efavirenz and levonorgestrel implants.

Background: Co-administration of antineoplastics with ART is challenging due to potential drug-drug interactions (DDIs). However, trials specifically assessing such DDIs are lacking. Our objective was to simulate DDIs between the antineoplastics erlotinib and gefitinib with key antiretroviral drugs and to predict dose adjustments using a physiologically based pharmacokinetic (PBPK) model., Methods: In vitro data describing chemical properties and pharmacokinetic processes of each drug and their effect on cytochrome P450 isoforms were obtained from the literature. Plasma drug-concentration profiles were simulated in a virtual population of 50 individuals receiving erlotinib or gefitinib alone or with darunavir/ritonavir, efavirenz or etravirine. Simulated pharmacokinetic parameters and the magnitude of DDIs with probe drugs (midazolam, maraviroc) were compared with literature values. Erlotinib and gefitinib pharmacokinetics with and without antiretrovirals were compared and dose-adjustment strategies were evaluated., Results: Simulated parameters of each drug and the magnitude of DDIs with probe drugs were in agreement with reference values. Darunavir/ritonavir increased erlotinib and gefitinib exposure, while efavirenz and etravirine decreased erlotinib and gefitinib concentrations. Based on our predictions, dose-adjustment strategies may consist of once-daily dosing erlotinib at 25 mg and gefitinib at 125 mg with darunavir/ritonavir; or erlotinib at 200 mg and gefitinib at 375 mg with etravirine. The interaction with efavirenz was not overcome even after doubling erlotinib or gefitinib doses., Conclusions: PBPK models predicted the in vivo pharmacokinetics of erlotinib, gefitinib and the antiretrovirals darunavir/ritonavir, efavirenz and etravirine, and the DDIs between them. The simulated dose-adjustments may represent valuable strategies to optimize antineoplastic therapy in HIV-infected patients., (© The Author 2016. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Objectives: Treatment of HIV/TB coinfection is challenging due to potent drug-drug interactions between antiretrovirals and rifampicin. The effect of rifampicin on darunavir/ritonavir has not been studied. Population pharmacokinetic modelling was applied to investigate the interaction and generate alternative doses to inform clinical trial design., Patients and Methods: Darunavir/ritonavir concentrations were modelled simultaneously, including data from three studies in HIV patients (n = 51, 7 female). The darunavir/ritonavir-rifampicin interaction was assumed to mimic that previously observed with lopinavir/ritonavir. Daily darunavir/ritonavir 800/100 mg was simulated as a reference (n = 1000; -rifampicin). Simulations with apparent oral clearance increased by 71% and 36% and relative bioavailability decreased by 20% and 45% for darunavir and ritonavir, respectively, were performed for +rifampicin, 600 mg once daily (n = 1000). Darunavir/ritonavir 1200/200 mg once daily, 1600/200 mg once daily, 800/100 mg twice daily and 1200/150 mg twice daily +rifampicin were simulated. Darunavir parameters for each dose +rifampicin were compared with -rifampicin by geometric mean ratio (90% CI)., Results: A maximum effect model, with ritonavir inhibiting darunavir clearance, best described the relationship between the drugs. Compared with -rifampicin, simulated darunavir AUC0-24 was 57%, 26%, 1% and 16% lower for 800/100 mg once daily, 1200/200 mg once daily, 1600/200 mg once daily and 800/100 mg twice daily +rifampicin, respectively; but 39% higher with 1200/150 mg twice daily +rifampicin., Conclusions: Darunavir/ritonavir 1600/200 mg once daily, 800/100 mg twice daily and 1200/150 mg twice daily could potentially overcome reduced darunavir concentrations with rifampicin. In the absence of clinical data, modelling and simulation may be useful to predict drug-drug interactions and aid optimal dose selection., (© The Author 2015. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

With the licensing of the direct acting antivirals telaprevir and boceprevir the topic of drug-drug interactions has come to the forefront. These first generation hepatitis C virus protease inhibitors are metabolized by and inhibit the key drug metabolizing enzyme CYP3A4, which means that knowledge of drug-drug interactions has become an essential component of the evaluation of a patient starting triple therapy. The number of potential co-medications means that many drugs will be used in hepatitis C virus patients where there are no pharmacokinetic study data. Here we have to use the data that are available and seek to extrapolate to unstudied drugs using key principles of clinical pharmacology (disposition characteristics, concentration-effect relationships, therapeutic window) in order to give some guidance for management of patients. This is a rapidly moving area in hepatitis C therapy, both in terms of understanding the drug interaction profile of telaprevir and boceprevir, interaction mechanisms that sometimes appear counterintuitive and that may involve enzymes other than CYP3A4 or transporters, but then seeking to understand the interaction potential of the next wave of drugs that will soon be with us., (Copyright © 2013 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.)

Objectives: Co-administration of artemether/lumefantrine with antiretroviral therapy has potential for pharmacokinetic drug interactions. We investigated drug-drug interactions between artemether/lumefantrine and efavirenz or nevirapine., Methods: We performed a cross-over study in which HIV-infected adults received standard six-dose artemether/lumefantrine 80/480 mg before and at efavirenz or nevirapine steady state. Artemether, dihydroartemisinin, lumefantrine, efavirenz and nevirapine plasma concentrations were measured and compared., Results: Efavirenz significantly reduced artemether maximum concentration (C(max)) and plasma AUC (median 29 versus 12 ng/mL, P < 0.01, and 119 versus 25 ng · h/mL, P < 0.01), dihydroartemisinin C(max) and AUC (median 120 versus 26 ng/mL, P < 0.01, and 341 versus 84 ng · h/mL, P < 0.01), and lumefantrine C(max) and AUC (median 8737 versus 6331 ng/mL, P = 0.03, and 280 370 versus 124 381 ng · h/mL, P < 0.01). Nevirapine significantly reduced artemether C(max) and AUC (median 28 versus 11 ng/mL, P < 0.01, and 123 versus 34 ng · h/mL, P < 0.01) and dihydroartemisinin C(max) and AUC (median 107 versus 59 ng/mL, P < 0.01, and 364 versus 228 ng · h/mL, P < 0.01). Lumefantrine C(max) and AUC were non-significantly reduced by nevirapine. Artemether/lumefantrine reduced nevirapine C(max) and AUC (median 8620 versus 4958 ng/mL, P < 0.01, and 66 329 versus 35 728 ng · h/mL, P < 0.01), but did not affect efavirenz exposure., Conclusions: Co-administration of artemether/lumefantrine with efavirenz or nevirapine resulted in a reduction in artemether, dihydroartemisinin, lumefantrine and nevirapine exposure. These drug interactions may increase the risk of malaria treatment failure and development of resistance to artemether/lumefantrine and nevirapine. Clinical data from population pharmacokinetic and pharmacodynamic trials evaluating the impact of these drug interactions are urgently needed.

Background: Treatment of HIV/malaria-coinfected patients with antiretroviral therapy (ART) and artemisinin-based combination therapy has potential for drug interactions. We investigated the pharmacokinetics of artemether, dihydroartemisinin and lumefantrine after administration of a single dose of 80/480 mg of artemether/lumefantrine to HIV-infected adults, taken with and without lopinavir/ritonavir., Methods: A two-arm parallel study of 13 HIV-infected ART-naive adults and 16 HIV-infected adults stable on 400/100 mg of lopinavir/ritonavir plus two nucleoside reverse transcriptase inhibitors (ClinicalTrials.gov, NCT 00619944). Each participant received a single dose of 80/480 mg of artemether/lumefantrine under continuous cardiac function monitoring. Plasma concentrations of artemether, dihydroartemisinin and lumefantrine were measured., Results: Co-administration of artemether/lumefantrine with lopinavir/ritonavir significantly reduced artemether maximum concentration (C(max)) and area under the concentration-time curve (AUC) [median (range): 112 (20-362) versus 56 (17-236) ng/mL, P = 0.03; and 264 (92-1129) versus 151 (38-606) ng · h/mL, P < 0.01]. Dihydroartemisinin C(max) and AUC were not affected [66 (10-111) versus 73 (31-224) ng/mL, P = 0.55; and 213 (68-343) versus 175 (118-262) ng · h/mL P = 0.27]. Lumefantrine C(max) and AUC increased during co-administration [2532 (1071-5957) versus 7097 (2396-9462) ng/mL, P < 0.01; and 41,119 (12,850-125,200) versus 199,678 (71,205-251,015) ng · h/mL, P < 0.01]., Conclusions: Co-administration of artemether/lumefantrine with lopinavir/ritonavir significantly increases lumefantrine exposure, but decreases artemether exposure. Population pharmacokinetic and pharmacodynamic trials will be highly valuable in evaluating the clinical significance of this interaction and determining whether dosage modifications are indicated.

Background: Clinically significant drug-drug interactions (CSDIs) involving antiretrovirals are frequent and under-recognized in developed countries, but data are lacking for developing countries., Methodology and Principal Findings: To investigate the prevalence of CSDIs between antiretrovirals and coadministered drugs, we surveyed prescriptions dispensed in a large HIV clinic in Kenya. Of 1040 consecutive patients screened, 996 were eligible for inclusion. CSDIs were defined as 'major' (capable of causing severe or permanent damage, contraindicated, avoid or not recommended by the manufacturer, or requiring dose modification) or 'moderate' (manufacturers advise caution, or close monitoring, or capable of causing clinical deterioration). A total of 334 patients (33.5%) were at risk for a CSDI, potentially lowering antiretroviral drug concentrations in 120 (12%) patients. Major interactions most frequently involved rifampicin (12.4%, mostly with efavirenz) and azoles (2.7%) whereas moderate interactions were frequently azoles (13%), steroids (11%), and antimalarials (3%). Multivariable analyses suggested that patients at risk for CSDIs had lower CD4 counts (P = 0.006) and baseline weight (P = 0.023) and WHO Stage 3 or 4 disease (P≤0.007). Risk for CSDIs was not associated with particular regimens, although only 116 (11.6%) patients were receiving WHO second line regimens., Conclusions: One in three patients receiving antiretrovirals in our programme were at risk of CSDIs. Strategies need to be urgently developed to avoid important drug interactions, to identify early markers of toxicity and to manage unavoidable interactions safely in order to reduce risk of harm, and to maximize the effectiveness of mass antiretroviral deployment in Africa.

Current antiretroviral treatment has allowed HIV infection to become a chronic manageable condition with many HIV patients living longer. However, available antiretrovirals are not without limitations, for example the development of resistance and adverse effects. Consequently, new drugs in existing and novel classes are urgently required to provide viable treatment options to patients with few remaining choices. Darunavir, etravirine, maraviroc and raltegravir have been recently approved for treatment-experienced patients and other agents such as rilpivirine, vicriviroc and elvitegravir are currently under phase III study. Clinical studies are necessary to optimise potential treatment combinations and to manage drug-drug interactions to help avoid toxicity or therapy failure. This review aims to summarise the pharmacokinetics and key drug-drug interaction studies for newly available antiretrovirals and those in development. Further information regarding drug-drug interactions of well established antiretrovirals and those recently approved are readily available online at sites such as http://www.hiv-druginteractions.org, http://www.clinicaloptions.com/hiv, http://hivinsite.ucsf.edu. This article forms part of a special issue of Antiviral Research marking the 25th anniversary of antiretroviral drug discovery and development, Vol 85, issue 1, 2010., (Copyright 2009 Elsevier B.V. All rights reserved.)

Background: Potential drug-drug interactions (PDDIs) might expand with new combination antiretroviral therapies (ART) and polypharmacy related to increasing age and comorbidities. We investigated the prevalence of comedications and PDDIs within a large HIV cohort, and their effect on ART efficacy and tolerability., Methods: All medications were prospectively recorded in 1,497 ART-treated patients and screened for PDDIs using a customized version of the Liverpool drug interactions database., Results: Overall, 68% (1,013/1,497) of patients had a comedication and 40% (599/1,497) had > or = 1 PDDI. Among patients with comedication, 2% (21/1,013) had red-flag interactions (contraindicated) and 59% (597/1,013) had orange-flag interactions (potential dose adjustment and/or close monitoring required). The latter involved mainly central nervous system drugs (49%), cardiovascular drugs (34%) and methadone (19%). In the multivariate analysis, factors associated with having a comedication were advanced age, female gender, obesity and HCV infection. Independent risk factors for PDDIs were regimens combining protease inhibitors and non-nucleoside reverse transcriptase inhibitors (odds ratio [OR] 3.06, 95% confidence interval [CI] 1.44-6.48), > or = 2 comedications (OR 1.89, 95% CI 1.32-2.70), current illicit drug use (OR 2.00, 95% CI 1.29-3.10) and patients with HCV infection (OR 1.74, 95% CI 1.19-2.56). Viral response was similar in patients with and without PDDIs (84.5% versus 86.4%; P=0.386). During follow-up, ART was modified in 134 patients with comedication regardless of the presence of PDDIs (P=0.524)., Conclusions: PDDIs increase with complex ART and comorbidities. No adverse effect was noted on ART efficacy or tolerability; however, most PDDIs affected comedication but were manageable through dose adjustment or monitoring.

Patients with HIV who are receiving antiretroviral (ARV) therapy are at high risk for drug-drug interactions (DDIs), which can significantly impact patient care and represent a substantial opportunity cost for healthcare systems. DDIs are prevalent in the developed world and in resource-poor settings, with the cost being potentially greater in the latter. Although practically unavoidable in HIV care, many DDIs can be better managed, reducing the risks to patients and the burden on resources. The scope for DDI management is likely to be greater in the developed world, due to the availability of new agents and second-line drugs, which allow greater flexibility of ARV regimens and co-administered drug choice. The advent of electronic prescribing and patient medication records represents an opportunity to aid the identification and management of DDIs. Searchable electronic databases of HIV drug interactions are available, which are a useful tool for HIV healthcare professionals and non-specialists for managing DDIs involving ARVs. Although general active systems that alert prescribers to DDIs currently exist, there is an indication for the development of specialist active databases to be incorporated into electronic prescribing or dispensing systems, with the aim of improving the quality of prescribing and the safe dispensing of the therapeutically risky drugs and complicated regimens used in HIV management.

Darunavir (TMC114) is a new HIV protease inhibitor that has demonstrated substantial antiretroviral activity against wild-type HIV-1 virus and multidrug-resistant strains. Darunavir inhibits and is primarily metabolized by cytochrome P450 3A (CYP3A) isoenzymes and is coadministered with low-dose ritonavir (darunavir/r); ritonavir is an inhibitor of CYP3A isoenzymes and pharmacologically enhances darunavir, resulting in increased plasma concentrations and allowing for a lower daily dose. The t1/2 (terminal elimination half-life) of darunavir is 15 h in the presence of ritonavir. An extensive darunavir/r drug-drug interaction programme has been undertaken, covering a wide range of therapeutic areas. Studies conducted in HIV-negative healthy volunteers and in HIV-infected patients show that the potential for interactions is well characterized and the interactions are manageable. For most drugs investigated, no dose adjustments of darunavir/r or the co-administered drug are required. This article reviews all the pharmacokinetic and drug-drug interaction studies conducted to date for darunavir/r, providing guidance on how to co-administer darunavir/r with many other antiretroviral or non-antiretroviral medications commonly used in HIV-infected individuals.

It is increasingly difficult to keep track of information on drug-drug interactions in HIV therapeutics, and the clinical implications of much of the data reported are not immediately evident. Nevertheless, knowledge of drug-drug interactions is necessary to preserve antiretroviral efficacy and to avoid undue risk of toxicity. The following article reviews important drug-drug interactions and accumulating data on newer antiretroviral agents.

The coronavirus disease 2019 (COVID‐19) antiviral nirmatrelvir/ritonavir (Paxlovid) has been granted authorization or approval in several countries for the treatment of patients with mild to moderate COVID‐19 at high risk of progression to severe disease and with no requirement for supplemental oxygen. Nirmatrelvir/ritonavir will be primarily administered outside the hospital setting as a 5‐day course oral treatment. The ritonavir component boosts plasma concentrations of nirmatrelvir through the potent and rapid inhibition of the key drug‐metabolizing enzyme cytochrome P450 (CYP) 3A4. Thus nirmatrelvir/ritonavir, even given as a short treatment course, has a high potential to cause harm from drug–drug interactions (DDIs) with other drugs metabolized through this pathway. Options for mitigating risk from DDIs with nirmatrelvir/ritonavir are limited due to the clinical illness, the short window for intervention, and the related difficulty of implementing clinical monitoring or dosage adjustment of the comedication. Pragmatic options are largely confined to preemptive or symptom‐driven pausing of the comedication or managing any additional risk through counseling. This review summarizes the effects of ritonavir on drug disposition (i.e., metabolizing enzymes and transporters) and discusses factors determining the likelihood of having a clinically significant DDI. Furthermore, it provides a comprehensive list of comedications likely to be used in COVID‐19 patients which are categorized according to their potential DDI risk with nirmatrelvir/ritonavir. It also discusses recommendations for the management of DDIs which balance the risk of harm from DDIs with a short course of ritonavir, against unnecessary denial of nirmatrelvir/ritonavir treatment. [ABSTRACT FROM AUTHOR]

Global use of dexamethasone in COVID-19 patients has revealed a poor understanding of the drug-drug interaction (DDI) potential of dexamethasone, particularly with antiretroviral agents (ARVs). Dexamethasone is both a substrate and a dose-dependent inducer of cytochrome P450 3A4 (CYP3A4). As many ARVs are substrates and/or inhibitors or inducers of CYP3A4, there is concern about DDIs with dexamethasone either as a perpetrator or a victim. Assessment of DDIs that involve dexamethasone is complex as dexamethasone is used at a range of daily doses (generally 0.5 up to 40 mg) and a treatment course can be short, long, or intermittent. Moreover, DDIs with dexamethasone have been evaluated only for a limited number of drugs. Here, we summarize the available in vitro and in vivo data on the interaction potential of dexamethasone and provide recommendations for the management of DDIs with ARVs, considering various dexamethasone dosages and treatment durations. [ABSTRACT FROM AUTHOR]

Combined antiretroviral treatments have significantly improved the morbidity and mortality related to HIV infection, thus transforming HIV infection into a chronic disease; however, the efficacy of antiretroviral treatments is highly dependent on the ability of infected individuals to adhere to life-long drug combination therapies. A major milestone in HIV treatment is the marketing of the long-acting intramuscular antiretroviral drugs cabotegravir and rilpivirine, allowing for infrequent drug administration, with the potential to improve adherence to therapy and treatment satisfaction. Intramuscular administration of cabotegravir and rilpivirine leads to differences in pharmacokinetics and drug–drug interaction (DDI) profiles compared with oral administration. A notable difference is the long elimination half-life with intramuscular administration, which reaches 5.6–11.5 weeks for cabotegravir and 13–28 weeks for rilpivirine, compared with 41 and 45 h, respectively, with their oral administration. Cabotegravir and rilpivirine have a low potential to cause DDIs, however these drugs can be victims of DDIs. Cabotegravir is mainly metabolized by UGT1A1, and rilpivirine is mainly metabolized by CYP3A4, therefore these agents are susceptible to DDIs with inhibitors, and particularly inducers of drug-metabolizing enzymes. Intramuscular administration of cabotegravir and rilpivirine has the advantage of eliminating DDIs occurring at the gastrointestinal level, however interactions can still occur at the hepatic level. This review provides insight on the intramuscular administration of drugs and summarizes the pharmacology of long-acting cabotegravir and rilpivirine. Particular emphasis is placed on DDI profiles after oral and intramuscular administration of these antiretroviral drugs. [ABSTRACT FROM AUTHOR]

Although direct‐acting antivirals (DAAs) for chronic hepatitis C virus (HCV) infection are highly efficacious and safe, treatment initiation is often limited in patients with neuropsychiatric disorders due to concerns over reduced treatment adherence and drug–drug interactions. Here, we report adherence, efficacy, safety and patient‐reported outcomes (PROs) from an integrated analysis of registrational studies using the pangenotypic DAA regimen of glecaprevir and pibrentasvir (G/P). Patients with chronic HCV genotypes 1‐6 infection with compensated liver disease (with or without cirrhosis) receiving G/P for 8, 12 or 16 weeks were included in this analysis. Patients were classified as having a psychiatric disorder based on medical history and/or co‐medications. Primary analyses assessed treatment adherence, efficacy (sustained virologic response at post‐treatment week 12; SVR12), safety and PROs. Among 2522 patients receiving G/P, 789 (31%) had a psychiatric disorder with the most common diagnoses being depression (64%; 506/789) and anxiety disorders (27%; 216/789). Treatment adherence was comparably high (>95%) in patients with and without psychiatric disorders. SVR12 rates were 97.3% (768/789; 95% CI = 96.2‐98.5) and 97.5% (1689/1733; 95% CI = 96.7‐98.2) in patients with and without psychiatric disorders, respectively. Among patients with psychiatric disorders, SVR12 rates remained >96% by individual psychiatric diagnoses and co‐medication classes. Overall, most adverse events (AEs) were mild‐to‐moderate in severity with serious AEs and AEs leading to G/P discontinuation occurring at similarly low rates in both patient populations. In conclusion, G/P treatment was highly efficacious, well‐tolerated and demonstrated high adherence rates in patients with chronic HCV infection and psychiatric disorders. [ABSTRACT FROM AUTHOR]

Background: HIV-positive women receiving efavirenz-based ART and levonorgestrel contraceptive implants are at risk of low levonorgestrel exposure and unintended pregnancy.Objectives: To investigate clinically applicable dose-adjustment strategies to overcome the known drug-drug interaction (DDI) between levonorgestrel and efavirenz, using a physiologically based pharmacokinetic (PBPK) modelling-based approach.Methods: A PBPK model was qualified against clinical data to predict levonorgestrel plasma concentrations when standard-dose (150 mg) levonorgestrel implants were administered alone (control group), as well as when standard-dose or increased-dose (300 mg) levonorgestrel implants were coadministered with either 600 or 400 mg of efavirenz.Results: No difference was seen between in vivo clinical and PBPK-model-simulated levonorgestrel plasma concentrations (P > 0.05). Simulated levonorgestrel plasma concentrations were ∼50% lower at 48 weeks post-implant-placement in virtual individuals receiving standard-dose levonorgestrel with either 600 or 400 mg of efavirenz compared with the control group (efavirenz:control geometric mean ratio = 0.42 and 0.49, respectively). Conversely, increased-dose levonorgestrel in combination with either 600 or 400 mg of efavirenz was sufficient to restore levonorgestrel concentrations to levels similar to those observed in the 150 mg levonorgestrel control group 48 weeks post-implant-placement (efavirenz:control geometric mean ratio = 0.86 and 1.03, respectively).Conclusions: These results suggest that the clinically significant DDI between efavirenz and levonorgestrel is likely to persist despite efavirenz dose reduction, whereas dose escalation of implantable levonorgestrel may represent a successful clinical strategy to circumvent efavirenz-levonorgestrel DDIs and will be of use to inform clinical trial design to assess coadministration of efavirenz and levonorgestrel implants. [ABSTRACT FROM AUTHOR]

Background: Antiretroviral drugs are among the therapeutic agents with the highest potential for drug-drug interactions (DDIs). In the absence of clinical data, DDIs are mainly predicted based on preclinical data and knowledge of the disposition of individual drugs. Predictions can be challenging, especially when antiretroviral drugs induce and inhibit multiple cytochrome P450 (CYP) isoenzymes simultaneously.Methods: This study predicted the magnitude of the DDI between efavirenz, an inducer of CYP3A4 and inhibitor of CYP2C8, and dual CYP3A4/CYP2C8 substrates (repaglinide, montelukast, pioglitazone, paclitaxel) using a physiologically based pharmacokinetic (PBPK) modeling approach integrating concurrent effects on CYPs. In vitro data describing the physicochemical properties, absorption, distribution, metabolism, and elimination of efavirenz and CYP3A4/CYP2C8 substrates as well as the CYP-inducing and -inhibitory potential of efavirenz were obtained from published literature. The data were integrated in a PBPK model developed using mathematical descriptions of molecular, physiological, and anatomical processes defining pharmacokinetics. Plasma drug-concentration profiles were simulated at steady state in virtual individuals for each drug given alone or in combination with efavirenz. The simulated pharmacokinetic parameters of drugs given alone were compared against existing clinical data. The effect of efavirenz on CYP was compared with published DDI data.Results: The predictions indicate that the overall effect of efavirenz on dual CYP3A4/CYP2C8 substrates is induction of metabolism. The magnitude of induction tends to be less pronounced for dual CYP3A4/CYP2C8 substrates with predominant CYP2C8 metabolism.Conclusion: PBPK modeling constitutes a useful mechanistic approach for the quantitative prediction of DDI involving simultaneous inducing or inhibitory effects on multiple CYPs as often encountered with antiretroviral drugs. [ABSTRACT FROM AUTHOR]

Background: In all settings, there are challenges associated with safely treating patients with multimorbidity and polypharmacy. The need to characterise, understand and limit harms resulting from medication use is therefore increasingly important. Drug-drug interactions (DDIs) are prevalent in patients taking antiretrovirals (ARVs) and if unmanaged, may pose considerable risk to treatment outcome. One of the biggest challenges in preventing DDIs is the substantial gap between theory and clinical practice. There are no robust methods published for formally assessing quality of evidence relating to DDIs, despite the diverse sources of information. We defined a transparent, structured process for developing evidence quality summaries in order to guide therapeutic decision making. This was applied to a systematic review of DDI data with considerable public health significance: HIV and malaria. Methods and findings: This was a systematic review of DDI data between antiretrovirals and drugs used in prophylaxis and treatment of malaria. The data comprised all original research in humans that evaluated pharmacokinetic data and/or related adverse events when antiretroviral agents were combined with antimalarial agents, including healthy volunteers, patients with HIV and/or malaria, observational studies, and case reports. The data synthesis included 36 articles and conference presentations published via PubMed and conference websites/abstract books between 1987-August 2016. There is significant risk of DDIs between HIV protease inhibitors, or NNRTIs and artemesinin-containing antimalarial regimens. For many antiretrovirals, DDI studies with antimalarials were lacking, and the majority were of moderate to very low quality. Quality of evidence and strength of recommendation categories were defined and developed specifically for recommendations concerning DDIs. Conclusions: There is significant potential for DDIs between antiretrovirals and antimalarials. The application of quality of evidence and strength of recommendation criteria to DDI data is feasible, and allows the assessment of DDIs to be robust, consistent, transparent and evidence-based. [ABSTRACT FROM AUTHOR]

Nearly all HIV PIs and the integrase inhibitor elvitegravir require a pharmacokinetic enhancer in order to achieve therapeutic plasma concentrations at the desired dose and frequency. Whereas ritonavir has been the only available pharmacokinetic enhancer for more than a decade, cobicistat has recently emerged as an alternative boosting agent. Cobicistat and ritonavir are equally strong inhibitors of cytochrome P450 (CYP) 3A4 and consequently were shown to be equivalent pharmacokinetic enhancers for elvitegravir and for the PIs atazanavir and darunavir. Since cobicistat is a more selective CYP inhibitor than ritonavir and is devoid of enzyme-inducing properties, differences are expected in their interaction profiles with some co-medications. Drugs whose exposure might be altered by ritonavir but unaltered by cobicistat are drugs primarily metabolized by CYP1A2, CYP2B6, CYP2C8, CYP2C9 and CYP2C19 or drugs undergoing mainly glucuronidation. Thus, co-medications should be systematically reviewed when switching the pharmacokinetic enhancer to anticipate potential dosage adjustments. [ABSTRACT FROM AUTHOR]

Background. With the approval of direct-acting antivirals (DAAs), the management of drug-drug interactions (DDIs) has become an important challenge while treating individuals with hepatitis C. To date, the potential of causing DDIs for the recently approved DAAs has not been systematically investigated. We aimed to assess the clinical significance of DDI between the regular outpatient medications and DAA therapies in a large real-world cohort. Methods. Overall, 261 hepatitis C virus monoinfected patients who were selected for DAA therapy at 2 intervals between 2011 and 2014 were asked about their regular outpatient medications. The potential for DDIs between all these drugs and sofosbuvir/ribavirin, ledipasvir/sofosbuvir, sofosbuvir/daclatasvir, sofosbuvir/simeprevir, ombitasvir/paritaprevir/ritonavir ± dasabuvir as well as boceprevir and telaprevir triple therapy was assessed using www.hep-druginteractions.org and the relevant prescribing information. Results. The 261 patients took a median number of 2 drugs (range 0-15); 20% of patients did not take any medication. Sofosbuvir/ ribavirin had the lowest risk to cause a potentially significant DDI (9.6%). In contrast, for ombitasvir/paritaprevir/ritonavir ± dasabuvir potentially significant DDIs could be expected in 66.3% of the patients. Significant DDIs for sofosbuvir/simeprevir would be expected in 31.4%, for sofosbuvir/daclatasvir in 36.8%, and for sofosbuvir/ledipasvir in 40.2%. Proton pump inhibitors, thyroid hormones, and dihydropyridine derivatives were frequently used and presented a risk of interacting with the antiviral regimen. Conclusions. A significant number of patients are at risk for DDIs if treated with the recently approved DAA regimens. A careful evaluation of potential DDI is essential to prevent adverse effects or unnecessary risk of treatment failure. [ABSTRACT FROM AUTHOR]

Background St John's wort (SJW; Hypericum perforatum) induces CYP3A4 that is involved in the metabolism of the hepatitis C virus (HCV) protease inhibitor boceprevir. Reduced boceprevir exposure and efficacy would contribute to therapeutic failure and increase the risk for resistance development. Boceprevir is co-administered with interferon/ribavirin, and depression has been described frequently in patients undergoing HCV treatment. Patients may purchase over-the-counter herbals to manage depression, and knowing the interaction between SJW and boceprevir is desirable. Methods This Phase I, open-label, three-period, cross-over pharmacokinetic study enrolled healthy males and females who, following consent and screening procedures, were randomized to receive SJW on days 1–14, SJW plus boceprevir (SJW on days 22–35 and together on days 31–35) and boceprevir on days 52–56, separated by 7 day washout periods, or the same treatment in the opposite order. Pharmacokinetic sampling was performed at the end of each phase. Results Seventeen (11 female) subjects completed the study and no serious adverse events were reported. Geometric mean ratios (GMRs) and 90% CIs for boceprevir (with SJW versus alone) AUC0–8, Cmax and C8 were 0.91 (0.87–0.96), 0.94 (0.82–1.07) and 1.00 (0.79–1.27), respectively. GMRs and 90% CIs for hypericin, the active component of SJW, (with boceprevir versus alone) AUC0–8, Cmax and C8 were 1.23 (1.10–1.38), 1.32 (1.16–1.52) and 1.37 (1.19–1.58), respectively. Conclusions SJW did not have a clinically significant effect on boceprevir plasma concentrations (or those of its metabolite), suggesting that SJW and boceprevir can be safely co-administered. [ABSTRACT FROM PUBLISHER]

Background and Objective: The rate of depression in patients with HIV is higher than in the general population. The use of antidepressants can have a beneficial effect, improving antiretroviral therapy adherence and consequently their efficacy and safety. Efavirenz and protease inhibitor boosted with ritonavir are major components of the antiretroviral therapy and are inducers and/or inhibitors of several cytochrome P450 (CYP) isoforms. Although antidepressants are prescribed to a significant proportion of patients treated with antiretrovirals, there are limited clinical data on drug-drug interactions. The aim of this study was to predict the magnitude of drug-drug interactions among efavirenz, boosted protease inhibitors and the most commonly prescribed antidepressants using an in vitro-in vivo extrapolation (IVIVE) model simulating virtual clinical trials. Methods: In vitro data describing the chemical characteristics, and absorption, distribution, metabolism and elimination (ADME) properties of efavirenz, boosted protease inhibitors and the most commonly prescribed antidepressants were obtained from published literature or generated by standard methods. Pharmacokinetics and drug-drug interaction were simulated using the full physiologically based pharmacokinetic model implemented in the Simcyp™ ADME simulator. The robustness of our modeling approach was assessed by comparing the magnitude of simulated drug-drug interactions using probe drugs to that observed in clinical studies. Results: Simulated pharmacokinetics and drug-drug interactions were in concordance with available clinical data. Although the simulated drug-drug interactions with antidepressants were overall weak to moderate according to the classification of the US FDA, fluoxetine and venlafaxine represent better candidates from a pharmacokinetic standpoint for patients on efavirenz and venlafaxine or citalopram for patients on boosted protease inhibitors. Conclusion: The modest magnitude of interaction could be explained by the fact that antidepressants are substrates of multiple isoforms and thus metabolism can still occur through CYPs that are weakly impacted by efavirenz or boosted protease inhibitors. These findings indicate that IVIVE is a useful tool for predicting drug-drug interactions and designing prospective clinical trials, giving insight into the variability of exposure, sample size and time-dependent induction or inhibition. [ABSTRACT FROM AUTHOR]

Summary: Hepatitis C virus (HCV) infected patients often take multiple co-medications to treat adverse events related to HCV therapy, or to manage other co-morbidities. Drug–drug interactions associated with this polypharmacy are relatively new to the field of HCV pharmacotherapy. With the advent of the direct-acting antivirals telaprevir and boceprevir, which are both substrates and inhibitors of the cytochrome P450 (CYP) 3A iso-enzyme, knowledge and awareness of drug–drug interactions have become a cornerstone in the evaluation of patients starting and continuing HCV combination therapy. In our opinion, an overview of conducted drug–drug interaction studies and a list of contraindicated medications is not enough for the clinical management of these drug–drug interactions. Knowledge of pharmacokinetic profiles and concentration–effect relationships is key for the interpretation of these data, and insight into how to manage these interactions (e.g., dose adjustments, safe alternatives and therapeutic drug monitoring) is of equal importance. This review provides a practical overview of the safe and effective management of these clinical challenges. [ABSTRACT FROM AUTHOR]

Objectives To assess the pharmacokinetics (PK) of raltegravir and ezetimibe when co-administered to healthy volunteers. Methods This was a prospective, open-label, crossover study, with subjects randomly assigned to group 1 (raltegravir 400 mg twice daily, raltegravir plus ezetimibe 10 mg once daily, wash-out period, ezetimibe) or group 2 (ezetimibe, raltegravir plus ezetimibe, wash-out period, raltegravir); all phases lasted for 10 days. Steady-state full PK sampling was performed at days 10, 20 and 40. Raltegravir and ezetimibe PK parameters were determined by non-compartmental methods and comparisons in the presence of the potentially interactive drug measured by geometric mean ratio (GMR) and 95% confidence intervals (CIs). Results Twenty subjects (10 females) completed the study. Raltegravir PK parameters did not change significantly in the presence of ezetimibe: GMRs (95% CI) were 1.16 (0.89–1.51) for AUC0–12, 1.13 (0.81–1.58) for maximum plasma concentration (Cmax) and 1.12 (0.72–1.74) for trough concentration (Ctrough). Ezetimibe AUC0–24 and Ctrough were lower in the presence of raltegravir [GMRs (95% CI) were 0.79 (0.68–0.91) for AUC0–24 and 0.78 (0.60–0.99) for Ctrough], while ezetimibe glucuronide Cmax was 40% higher (90% CI 1.17–1.66). There was marked inter-individual variability in the PK of the two drugs, especially during co-administration. Conclusions There were no significant changes in raltegravir PK parameters with or without ezetimibe. However, in the presence of raltegravir, ezetimibe AUC0–24 and Ctrough were significantly lower (>20%) and ezetimibe glucuronide Cmax was higher. Clinical data to assess the importance of the change in ezetimibe concentrations are warranted. [ABSTRACT FROM PUBLISHER]

Grapefruit juice and grapefruit product consumption have potential health benefits; however, their intake is also associated with interactions with certain drugs, including calcium channel blockers, immunosuppressants and antihistamines. The primary mechanism through which interactions are mediated is mechanism-based intestinal cytochrome P450 3A4 inhibition by furanocoumarins resulting in increased bioavailability of administered medications that are substrates. Grapefruit products have also been associated with interactions with P-glycoprotein (P-gp) and uptake transporters (e.g. organic anion-transporting polypeptides [OATPs]). Polyphenolic compounds such as flavonoids have been proposed as the causative agents of the P-gp and OATP interactions. The mechanisms and magnitudes of the interactions can be influenced by the concentrations of furanocoumarins and flavonoids in the grapefruit product, the volume of juice consumed, and the inherent variability of specific enzymes and transporter components in humans. It is therefore challenging to predict the extent of grapefruit product-drug interactions and to compare available in vitro and in vivo data. The clinical significance of such interactions also depends on the disposition and toxicity profile of the drug being administered. The aim of this review is to outline the mechanisms of grapefruit-drug interactions and present a comprehensive summary of those agents affected and whether they are likely to be of clinical relevance. [ABSTRACT FROM AUTHOR]

Background: The protease inhibitors lopinavir and atazanavir are both recommended for treatment of HIV-infected patients. Considerable inter-individual variability in plasma concentration has been observed for both drugs. The aim of this study was to evaluate which demographic factors and concomitant drugs are associated with lopinavir and atazanavir plasma concentration. [ABSTRACT FROM PUBLISHER]

To investigate whether the administration of tenofovir diproxil fumarate 300 mg once daily alters the plasma pharmacokinetics of the saquinavir hard gel/ritonavir combination in HIV-1 infected individuals.On day 1, 12 h pharmacokinetic profiles for saquinavir/ritonavir (1000/100 mg given twice daily) were obtained for 18 subjects. All subjects were receiving ongoing treatment with a saquinavir/ritonavir-containing regimen. Tenofovir diproxil fumarate 300 mg given once daily was then added to the regimen and blood sampling was repeated at days 3 and 14. Saquinavir and ritonavir concentrations were measured by HPLC–MS/MS, and tenofovir concentrations by HPLC with UV detection.Following the addition of tenofovir diproxil fumarate to the regimen, saquinavir and ritonavir plasma concentrations were not significantly different compared with day 1. Thus the geometric mean ratios (95% confidence intervals) for the area under the concentration-time curve were 1.16 (0.97, 1.59) and 0.99 (0.87, 1.30) for saquinavir and 1.05 (0.92, 1.28) and 1.08 (0.97, 1.30) for ritonavir, on days 3 and 14, respectively.Tenofovir diproxil fumarate did not alter the pharmacokinetics of saquinavir hard gel/ritonavir. [ABSTRACT FROM AUTHOR]

Scale-up of HIV treatment services may have contributed to an increase in functional health facilities available in resource-limited settings and an increase in patient use of facilities and retention in care. As more patients are reached with medicines, monitoring patient safety is increasingly important. Limited data from resource-limited settings suggest that medication error and antiretroviral drug–drug interactions may pose a significant risk to patient safety. Commonly cited causes of medication error in the developed world include the speed and complexity of the medication use cycle combined with inadequate systems and processes. In resource-limited settings, specific factors may contribute, such as inadequate human resources and high disease burden. Management of drug–drug interactions may be complicated by limited access to alternative medicines or laboratory monitoring. Improving patient safety by addressing the issue of antiretroviral drug–drug interactions has the potential not just to improve healthcare for individuals, but also to strengthen health systems and improve vital communication among healthcare providers and with regulatory agencies. [ABSTRACT FROM PUBLISHER]

A letter to the editor is presented in response to the article "Communicating Information about Drug Interactions," by David J. Back and Sara E. Gibbons.

An abstract of the article "New drug interactions in HIV and HCV," by David Back is presented.

An abstract of the article " Drug-Drug Interactions: It Is Not Only CYP450's Which Matter," by David J. Back is presented.

To investigate the pharmacokinetics of darunavir/ritonavir and raltegravir, in HIV-infected subjects, in both plasma and at the intracellular (IC) site of action.HIV-infected patients on antiretroviral therapy received raltegravir 400 mg twice daily for 21 days (period 1); darunavir/ritonavir 800/100 mg once daily was added for 14 days (period 2), and patients were randomized to continue raltegravir twice daily (group 1) or to switch to 800 mg once daily (group 2), then they all stopped raltegravir intake and continued darunavir/ritonavir once daily for 14 days (period 3). Drug concentrations in plasma and cells (peripheral blood mononuclear cell) were measured, and differences in geometric mean ratios (GMR) and 90% confidence intervals (CI) between period 2 versus period 3 and period 2 versus period 1 were assessed.Twenty-four patients completed the study. Group 1 GMR (90% CI) of darunavir area under the curve (AUC) with and without raltegravir was 1.24 (1.13 to 1.45) for plasma and 1.24 (1.07 to 1.73) for cells and for group 2 was 1.14 (1.07 to 1.24) and 1.03 (0.94 to 1.16). GMR (90% CI) of raltegravir AUC without and with darunavir/ritonavir (plasma and cells) for group 1 was 0.90 (0.73 to 1.44) and 1.02 (0.81 to 1.67) and for group 2 was 1.21 (1.03 to 1.77) and 1.27 (1.07 to 1.94). Geometric mean IC to plasma AUC ratios were 5.3 and 4.9 for darunavir in groups 1 and 2 when darunavir/ritonavir was given alone and 4.9 and 5.6 for raltegravir when given alone. These ratios were not altered by the coadministered drug.No remarkable interactions between darunavir/ritonavir and raltegravir in plasma or cells were seen. Raltegravir IC concentrations are higher than previously reported; the difference being due to modified cell isolation procedures that reduced drug loss caused by washing. [ABSTRACT FROM AUTHOR]

Levonorgestrel (LNG) is a synthetic progestin that is available in oral contraceptive tablets, a subdermal implant, and an intrauterine system for contraception. LNG pharmacokinetics are a pivotal determinant of contraceptive efficacy and essential in assessing drug-drug interactions influencing LNG exposure following different routes of LNG administration. A highly sensitive LC-MS/MS method was developed and validated to quantify levonorgestrel in human plasma. Liquid-liquid extraction was utilized with a sample volume of 500 μL to extract levonorgestrel from plasma. Chromatographic separation of LNG was achieved with a Fortis™ C18 (3 μm: 100 mm × 2.1 mm) reverse phase analytical column. The mobile phases consisted of de-ionized water plus 0.1% NH 4 OH (100:0.1%, v/v) (A), and methanol plus 0.1% NH 4 OH (100:0.1%, v/v) (B) delivered as a gradient at a flow rate of 400 μL/min. Detection of LNG and internal standard (D-(−)-norgestrel-d7) was achieved using positive polarity mode monitoring at 313.2–245.2 amu and 320.1–251.2 amu, respectively. The assay was linear over the calibration range of 49.6 to 1500 pg/mL. This method was used to quantify plasma LNG released by subdermal implant in support of a drug interaction study among women with HIV receiving efavirenz- or nevirapine-based antiretroviral therapy. [ABSTRACT FROM AUTHOR]

The article offers information on a study related to Hepatitis C virus (HCV) treatment of patients on contraindicated anti-epileptic drugs and the role of drug level monitoring. It notes that the patients on strong inducing anti-epileptic drugs (AEDs) such as carbamazepine, phenytoin and phenobarbital requires additional treatment which is challenging.

The article presents a study that measures etravirine pharmacokinetics for once and twice a day with and without a preceding efavirenz intake phase in healthy volunteers. Volunteers were given etravirine 400 mg once or 200 mg twice a day for 14 days. Pharmacokinetic parameters comparisons were done through geometric mean ratios and 90 percent confidence intervals. Results show that efavirenz concentrations were noticeable in all subjects seven days after efavirenz was stopped.