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.

Physiologically-Based Pharmacokinetic Modeling-Guided Dose Management of Oral Anticoagulants when Initiating Nirmatrelvir/Ritonavir (Paxlovid) for COVID-19 Treatment.

Patients with coronavirus disease 2019 (COVID-19) with cardiovascular diseases who are at higher risk of progressing to critical illness should be treated with nirmatrelvir/ritonavir (Paxlovid). Ritonavir, the booster in nirmatrelvir/ritonavir, modulates multiple drug metabolizing enzymes and transporters, complicating its use in real-world clinics. We aimed to apply physiologically-based pharmacokinetic (PBPK) modeling to simulate the complex drug-drug interactions (DDIs) of ritonavir with two anticoagulants, rivaroxaban and racemic warfarin, to address this important clinical conundrum. Simulations were implemented within Simcyp Simulator. Compound and population models were adopted from Simcyp and our previous studies. Upon verification and validation of the PBPK model of ritonavir, prospective DDI simulations with the anticoagulants were performed in both the general population (20-65 years) and geriatric subjects (65-85 years) with or without moderate renal impairment. Elevated rivaroxaban concentrations were simulated with nirmatrelvir/ritonavir treatment, where the impact was more profound among geriatric subjects with renal impairment. The overexposure of rivaroxaban was restored to normal range on day 4 post-discontinuation of nirmatrelvir/ritonavir, corroborating with the recovery of enzyme activity. A lower 10 mg daily dose of rivaroxaban could effectively maintain acceptable systemic exposure of rivaroxaban during nirmatrelvir/ritonavir treatment. Treatment of ritonavir marginally declined simulated S-warfarin concentrations, but substantially elevated that of R-warfarin, resulting in a decrease in the international normalized ratio (INR). As INR only recovered 2 weeks post-nirmatrelvir/ritonavir treatment, a longer surveillance INR for warfarin becomes important. Our PBPK-guided simulations evaluated clinically important yet untested DDIs and supports clinical studies to ensure proper anticoagulation management of patients with COVID-19 with chronic coagulative abnormalities when initiating nirmatrelvir/ritonavir therapy.

Physiologically-Based Pharmacokinetic-Led Guidance for Patients With Cystic Fibrosis Taking Elexacaftor-Tezacaftor-Ivacaftor With Nirmatrelvir-Ritonavir for the Treatment of COVID-19.

Cystic fibrosis transmembrane conductance regulator (CFTR) modulating therapies, including elexacaftor-tezacaftor-ivacaftor, are primarily eliminated through cytochrome P450 (CYP) 3A-mediated metabolism. This creates a therapeutic challenge to the treatment of coronavirus disease 2019 (COVID-19) with nirmatrelvir-ritonavir in people with cystic fibrosis (CF) due to the potential for significant drug-drug interactions (DDIs). However, the population with CF is more at risk of serious illness following COVID-19 infection and hence it is important to manage the DDI risk and provide treatment options. CYP3A-mediated DDI of elexacaftor-tezacaftor-ivacaftor was evaluated using a physiologically-based pharmacokinetic modeling approach. Modeling was performed incorporating physiological information and drug-dependent parameters of elexacaftor-tezacaftor-ivacaftor to predict the effect of ritonavir (the CYP3A inhibiting component of the combination) on the pharmacokinetics of elexacaftor-tezacaftor-ivacaftor. The elexacaftor-tezacaftor-ivacaftor models were verified using independent clinical pharmacokinetic and DDI data of elexacaftor-tezacaftor-ivacaftor with a range of CYP3A modulators. When ritonavir was administered on Days 1 through 5, the predicted area under the curve (AUC) ratio of ivacaftor (the most sensitive CYP3A substrate) on Day 6 was 9.31, indicating that its metabolism was strongly inhibited. Based on the predicted DDI, the dose of elexacaftor-tezacaftor-ivacaftor should be reduced when coadministered with nirmatrelvir-ritonavir to elexacaftor 200 mg-tezacaftor 100 mg-ivacaftor 150 mg on Days 1 and 5, with delayed resumption of full-dose elexacaftor-tezacaftor-ivacaftor on Day 9, considering the residual inhibitory effect of ritonavir as a mechanism-based inhibitor. The simulation predicts a regimen of elexacaftor-tezacaftor-ivacaftor administered concomitantly with nirmatrelvir-ritonavir in people with CF that will likely decrease the impact of the drug interaction.

Physiologically Based Pharmacokinetic Modelling to Investigate the Impact of the Cytokine Storm on CYP3A Drug Pharmacokinetics in COVID-19 Patients.

Patients with coronavirus disease 2019 (COVID-19) may experience a cytokine storm with elevated interleukin-6 (IL-6) levels in response to severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2). IL-6 suppresses hepatic enzymes, including CYP3A; however, the effect on drug exposure and drug-drug interaction magnitudes of the cytokine storm and resulting elevated IL-6 levels have not been characterized in patients with COVID-19. We used physiologically-based pharmacokinetic (PBPK) modeling to simulate the effect of inflammation on the pharmacokinetics of CYP3A metabolized drugs. A PBPK model was developed for lopinavir boosted with ritonavir (LPV/r), using clinically observed data from people living with HIV (PLWH). The inhibition of CYPs by IL-6 was implemented by a semimechanistic suppression model and verified against clinical data from patients with COVID-19, treated with LPV/r. Subsequently, the verified model was used to simulate the effect of various clinically observed IL-6 levels on the exposure of LPV/r and midazolam, a CYP3A model drug. Clinically observed LPV/r concentrations in PLWH and patients with COVID-19 were predicted within the 95% confidence interval of the simulation results, demonstrating its predictive capability. Simulations indicated a twofold higher LPV exposure in patients with COVID-19 compared with PLWH, whereas ritonavir exposure was predicted to be comparable. Varying IL-6 levels under COVID-19 had only a marginal effect on LPV/r pharmacokinetics according to our model. Simulations showed that a cytokine storm increased the exposure of the CYP3A paradigm substrate midazolam by 40%. Our simulations suggest that CYP3A metabolism is altered in patients with COVID-19 having increased cytokine release. Caution is required when prescribing narrow therapeutic index drugs particularly in the presence of strong CYP3A inhibitors.

Pharmacokinetic interactions between the potential COVID-19 treatment drugs lopinavir/ritonavir and arbidol in rats.

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has occasioned worldwide alarm. Globally, the number of reported confirmed cases has exceeded 84.3 million as of this writing (January 2, 2021). Since there are no targeted therapies for COVID-19, the current focus is the repurposing of drugs approved for other uses. In some clinical trials, antiviral drugs such as remdesivir (Grein et al., 2020), lopinavir/ritonavir (LPV/r) (Cao et al., 2020), chloroquine (Gao et al., 2020), hydroxychloroquine (Gautret et al., 2020), arbidol (Wang et al., 2020), and favipiravir (Cai et al., 2020b) have shown efficacy in COVID-19 patients. LPV/r combined with arbidol, which is the basic regimen in some regional hospitals in China including Zhejiiang Province, has shown antiviral effects in COVID-19 patients (Guo et al., 2020; Xu et al., 2020). A retrospective cohort study also reported that this combination therapy showed better efficacy than LPV/r alone for the treatment of COVID-19 patients (Deng et al., 2020).

Population pharmacokinetics of lopinavir/ritonavir in Covid-19 patients.

OBJECTIVE: To develop a population pharmacokinetic model for lopinavir boosted by ritonavir in coronavirus disease 2019 (Covid-19) patients. METHODS: Concentrations of lopinavir/ritonavir were assayed by an accredited LC-MS/MS method. The population pharmacokinetics of lopinavir was described using non-linear mixed-effects modeling (NONMEM version 7.4). After determination of the base model that better described the data set, the influence of covariates (age, body weight, height, body mass index (BMI), gender, creatinine, aspartate aminotransferase (AST), alanine aminotransferase (ALT), C reactive protein (CRP), and trough ritonavir concentrations) was tested on the model. RESULTS: From 13 hospitalized patients (4 females, 9 males, age = 64 ± 16 years), 70 lopinavir/ritonavir plasma concentrations were available for analysis. The data were best described by a one-compartment model with a first-order input (KA). Among the covariates tested on the PK parameters, only the ritonavir trough concentrations had a significant effect on CL/F and improved the fit. Model-based simulations with the final parameter estimates under a regimen lopinavir/ritonavir 400/100 mg b.i.d. showed a high variability with median concentration between 20 and 30 mg/L (Cmin/Cmax) and the 90% prediction intervals within the range 1-100 mg/L. CONCLUSION: According to the estimated 50% effective concentration of lopinavir against SARS-CoV-2 virus in Vero E6 cells (16.7 mg/L), our model showed that at steady state, a dose of 400 mg b.i.d. led to 40% of patients below the minimum effective concentration while a dose of 1200 mg b.i.d. will reduce this proportion to 22%.

Physiologically-Based Pharmacokinetic Modeling to Predict the Clinical Efficacy of the Coadministration of Lopinavir and Ritonavir against SARS-CoV-2.

Lopinavir/ritonavir, originally developed for treating HIV, is currently undergoing clinical studies for treating the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although recent reports suggest that lopinavir exhibits in vitro efficacy against SARS-CoV-2, it is a highly protein-bound drug and it remains unknown if it reaches adequate in vivo unbound (free) concentrations in lung tissue. We built a physiologically-based pharmacokinetic model of lopinavir/ritonavir in white and Chinese populations. Our aim was to perform pharmacokinetic/pharmacodynamic correlations by comparing simulated free plasma and lung concentration values achieved using different dosing regimens of lopinavir/ritonavir with unbound half-maximal effective concentration (EC50,unbound ) and unbound effective concentration 90% values of lopinavir against SARS-CoV-2. The model was validated against multiple observed clinical datasets for single and repeated dosing of lopinavir/ritonavir. Predicted pharmacokinetic parameters, such as the maximum plasma concentration, area under the plasma concentration-time profile, oral clearance, half-life, and minimum plasma concentration at steady-state were within two-fold of clinical values for both populations. Using the current lopinavir/ritonavir regimen of 400/100 mg twice daily, lopinavir does not achieve sufficient free lung concentrations for efficacy against SARS-CoV-2. Although the Chinese population reaches greater plasma and lung concentrations as compared with whites, our simulations suggest that a significant dose increase from the current clinically used dosing regimen is necessary to reach the EC50,unbound value for both populations. Based on safety data, higher doses would likely lead to QT prolongation and gastrointestinal disorders (nausea, vomiting, and diarrhea), thus, any dose adjustment must be carefully weighed alongside these safety concerns.

Effect of Systemic Inflammatory Response to SARS-CoV-2 on Lopinavir and Hydroxychloroquine Plasma Concentrations.

Coronavirus disease 2019 (COVID-19) leads to inflammatory cytokine release, which can downregulate the expression of metabolizing enzymes. This cascade affects drug concentrations in the plasma. We investigated the association between lopinavir (LPV) and hydroxychloroquine (HCQ) plasma concentrations and the levels of the acute-phase inflammation marker C-reactive protein (CRP). LPV plasma concentrations in 92 patients hospitalized at our institution were prospectively collected. Lopinavir-ritonavir was administered every 12 hours, 800/200 mg on day 1 and 400/100 mg on day 2 until day 5 or 7. HCQ was given at 800 mg, followed by 400 mg after 6, 24, and 48 h. Hematological, liver, kidney, and inflammation laboratory values were analyzed on the day of drug level determination. The median age of study participants was 59 (range, 24 to 85) years, and 71% were male. The median durations from symptom onset to hospitalization and treatment initiation were 7 days (interquartile range [IQR], 4 to 10) and 8 days (IQR, 5 to 10), respectively. The median LPV trough concentration on day 3 of treatment was 26.5 µg/ml (IQR, 18.9 to 31.5). LPV plasma concentrations positively correlated with CRP values (r = 0.37, P < 0.001) and were significantly lower when tocilizumab was preadministered. No correlation was found between HCQ concentrations and CRP values. High LPV plasma concentrations were observed in COVID-19 patients. The ratio of calculated unbound drug fraction to published SARS-CoV-2 50% effective concentrations (EC50) indicated insufficient LPV concentrations in the lung. CRP values significantly correlated with LPV but not HCQ plasma concentrations, implying inhibition of cytochrome P450 3A4 (CYP3A4) metabolism by inflammation.

Severe COVID-19 in a renal transplant recipient: A focus on pharmacokinetics.

The current coronavirus disease 2019 (COVID-19) pandemic requires extra attention for immunocompromised patients, including solid organ transplant recipients. We report on a case of a 35-year-old renal transplant recipient who suffered from a severe COVID-19 pneumonia. The clinical course was complicated by extreme overexposure to the mammalian target of rapamycin inhibitor everolimus, following coadministration of chloroquine and lopinavir/ritonavir therapy. The case is illustrative for dilemmas that transplant professionals may face in the absence of evidence-based COVID-19 therapy and concurrent pressure for exploration of experimental pharmacological treatment options. However, the risk-benefit balance of experimental or off-label therapy may be weighed differently in organ transplant recipients than in otherwise healthy COVID-19 patients, owing to their immunocompromised status and potential drug interactions with immunosuppressive therapy. With this case report, we aimed to achieve increased awareness and improved management of drug-drug interactions associated with the various treatment options for COVID-19 in renal transplant patients.