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

An update on drug-drug interactions in older adults living with human immunodeficiency virus (HIV)

INTRODUCTION

People with HIV are living longer due to advances in antiretroviral therapy. With improved life expectancy comes an increased lifetime risk of comorbid conditions - such as cardiovascular disease and cancer - and polypharmacy. Older adults, particularly those living with HIV, are more vulnerable to drug interactions and adverse effects, resulting in negative health outcomes.

AREA COVERED

Antiretrovirals are involved in many potential drug interactions with medications used to treat common comorbidities and geriatric conditions in an aging population of people with HIV. We review the mechanisms and management of significant drug-drug interactions involving antiretroviral medications and non-antiretroviral medications commonly used among older people living with HIV. The management of these interactions may require dose adjustments, medication switches to alternatives, enhanced monitoring, and considerations of patient- and disease-specific factors.

EXPERT OPINION

Clinicians managing comorbid conditions among older people with HIV must be particularly vigilant to side effect profiles, drug-drug interactions, pill burden, and cost when optimizing treatment. To support healthier aging among people living with HIV, there is a growing need for antiretroviral stewardship, multidisciplinary care models, and advances that promote insight into the correlations between an individual, their conditions, and their medications.

Evaluation of the potential impact on pharmacokinetics of various cytochrome P450 substrates of increasing IL-6 levels following administration of the T-cell bispecific engager glofitamab

Glofitamab is a novel T cell bispecific antibody developed for treatment of relapsed-refractory diffuse large B cell lymphoma and other non-Hodgkin's lymphoma indications. By simultaneously binding human CD20-expressing tumor cells and CD3 on T cells, glofitamab induces tumor cell lysis, in addition to T-cell activation, proliferation, and cytokine release. Here, we describe physiologically-based pharmacokinetic (PBPK) modeling performed to assess the impact of glofitamab-associated transient increases in interleukin 6 (IL-6) on the pharmacokinetics of several cytochrome P450 (CYP) substrates. By refinement of a previously described IL-6 model and inclusion of in vitro CYP suppression data for CYP3A4, CYP1A2, and 2C9, a PBPK model was established in Simcyp to capture the induced IL-6 levels seen when glofitamab is administered at the intended dose and dosing regimen. Following model qualification, the PBPK model was used to predict the potential impact of CYP suppression on exposures of various CYP probe substrates. PBPK analysis predicted that, in the worst-case, the transient elevation of IL-6 would increase exposures of CYP3A4, CYP2C9, and CYP1A2 substrates by less than or equal to twofold. Increases for CYP3A4, CYP2C9, and CYP1A2 substrates were projected to be 1.75, 1.19, and 1.09-fold following the first administration and 2.08, 1.28, and 1.49-fold following repeated administrations. It is recommended that there are no restrictions on concomitant treatment with any other drugs. Consideration may be given for potential drug-drug interaction during the first cycle in patients who are receiving concomitant CYP substrates with a narrow therapeutic index via monitoring for toxicity or for drug concentrations.

Apixaban and rivaroxaban's physiologically-based pharmacokinetic model validation in hospitalized patients: A first step for larger use of a priori modeling approach at bed side

When used in real-world conditions, substantial interindividual variations in direct oral anticoagulant (DOAC) plasma concentrations are observed for a given dose, leading to a risk of over- or under-exposure and clinically significant adverse events. Physiologically-based pharmacokinetic (PBPK) models could help physicians to tailor DOAC prescriptions in vulnerable patient populations, such as those in the hospital setting. The present study aims to validate prospectively PBPK models for rivaroxaban and apixaban in a large cohort of elderly, polymorbid, and hospitalized patients. In using a model of geriatric population integrating appropriate physiological parameters into models first optimized with healthy volunteer data, observed plasma concentration collected in hospitalized patients on apixaban (n = 100) and rivaroxaban (n = 100) were adequately predicted (ratio predicted/observed area under the concentration curve for a dosing interval [AUCtau ] = 0.97 [0.96-0.99] geometric mean, 90% confidence interval, ratio predicted/observed AUCtau  = 1.03 [1.02-1.05]) for apixaban and rivaroxaban, respectively. Validation of the present PBPK models for rivaroxaban and apixaban in in-patients represent an additional step toward the feasibility of bedside use.

Drug-drug interactions and dose management of BTK inhibitors when initiating nirmatrelvir/ritonavir (paxlovid) based on physiologically-based pharmacokinetic models

OBJECTIVE

Co-administration of Bruton's tyrosine kinase (BTK) inhibitors with nirmatrelvir/ritonavir is challenging because of potential drug-drug interactions (DDIs). However, clinical trials specifically evaluating such DDIs are absent. To evaluate and quantify the DDIs between them and provide rational dose management strategies of BTK inhibitors, we conducted this study using physiologically-based pharmacokinetic (PBPK) models.

METHODS

Physicochemical properties and pharmacokinetic parameters were acquired from the published literature and databases. The PBPK models were developed using Simcyp® software. These models were validated by comparing with published literature values. The successfully validated PBPK models were used to simulate the plasma concentration-time profiles and DDIs in a virtual healthy population receiving BTK inhibitors alone or with ritonavir.

RESULTS

Simulated plasma concentration-time profiles and pharmacokinetic parameters of each drug were in agreement with clinically observed values from literatures. Ritonavir increased ibrutinib maximum plasma concentration (Cmax) and the area under plasma concentration-time curve (AUC) 33- and 53.88-fold, respectively, increased zanubrutinib Cmax and AUC 2.57- and 3.18-fold, respectively, and increased acalabrutinib Cmax and AUC 3.85- and 6.54-fold, respectively. Based on our simulations, dose-adjustment strategies may consist of ibrutinib at 25 mg q48h, zanubrutinib at 80 mg twice-daily and acalabrutinib at 25 mg twice-daily with nirmatrelvir/ritonavir.

CONCLUSIONS

The PBPK models predicted the in vivo pharmacokinetics and the DDIs of BTK inhibitors and ritonavir. The prospective simulations not only provided scientific evidence regarding rational dosing management strategies when initiating nirmatrelvir/ritonavir therapy but also provided a reference for the design of clinical DDIs study that may save resources and time.

SUMMARY

Paxlovid could increase Cmax and AUC0-τ of BTK inhibitors (ibrutinib, zanubrutinib and acalabrutinib), and dose adjustment strategy of ibrutinib (25 mg q48h), zanubrutinib (80 mg q12h) and acalabrutinib (25 mg q12h) should be considered when combination with nirmatrelvir/ritonavir.

2023 AHA/ACC/ACCP/ASPC/NLA/PCNA Guideline for the Management of Patients With Chronic Coronary Disease: A Report of the American Heart Association/American College of Cardiology Joint Committee on Clinical Practice Guidelines

AIM

The "2023 AHA/ACC/ACCP/ASPC/NLA/PCNA Guideline for the Management of Patients With Chronic Coronary Disease" provides an update to and consolidates new evidence since the "2012 ACCF/AHA/ACP/AATS/PCNA/SCAI/STS Guideline for the Diagnosis and Management of Patients With Stable Ischemic Heart Disease" and the corresponding "2014 ACC/AHA/AATS/PCNA/SCAI/STS Focused Update of the Guideline for the Diagnosis and Management of Patients With Stable Ischemic Heart Disease."

METHODS

A comprehensive literature search was conducted from September 2021 to May 2022. Clinical studies, systematic reviews and meta-analyses, and other evidence conducted on human participants were identified that were published in English from MEDLINE (through PubMed), EMBASE, the Cochrane Library, Agency for Healthcare Research and Quality, and other selected databases relevant to this guideline.

STRUCTURE

This guideline provides an evidenced-based and patient-centered approach to management of patients with chronic coronary disease, considering social determinants of health and incorporating the principles of shared decision-making and team-based care. Relevant topics include general approaches to treatment decisions, guideline-directed management and therapy to reduce symptoms and future cardiovascular events, decision-making pertaining to revascularization in patients with chronic coronary disease, recommendations for management in special populations, patient follow-up and monitoring, evidence gaps, and areas in need of future research. Where applicable, and based on availability of cost-effectiveness data, cost-value recommendations are also provided for clinicians. Many recommendations from previously published guidelines have been updated with new evidence, and new recommendations have been created when supported by published data.

2023 AHA/ACC/ACCP/ASPC/NLA/PCNA Guideline for the Management of Patients With Chronic Coronary Disease: A Report of the American Heart Association/American College of Cardiology Joint Committee on Clinical Practice Guidelines

AIM

The "2023 AHA/ACC/ACCP/ASPC/NLA/PCNA Guideline for the Management of Patients With Chronic Coronary Disease" provides an update to and consolidates new evidence since the "2012 ACCF/AHA/ACP/AATS/PCNA/SCAI/STS Guideline for the Diagnosis and Management of Patients With Stable Ischemic Heart Disease" and the corresponding "2014 ACC/AHA/AATS/PCNA/SCAI/STS Focused Update of the Guideline for the Diagnosis and Management of Patients With Stable Ischemic Heart Disease."

METHODS

A comprehensive literature search was conducted from September 2021 to May 2022. Clinical studies, systematic reviews and meta-analyses, and other evidence conducted on human participants were identified that were published in English from MEDLINE (through PubMed), EMBASE, the Cochrane Library, Agency for Healthcare Research and Quality, and other selected databases relevant to this guideline.

STRUCTURE

This guideline provides an evidenced-based and patient-centered approach to management of patients with chronic coronary disease, considering social determinants of health and incorporating the principles of shared decision-making and team-based care. Relevant topics include general approaches to treatment decisions, guideline-directed management and therapy to reduce symptoms and future cardiovascular events, decision-making pertaining to revascularization in patients with chronic coronary disease, recommendations for management in special populations, patient follow-up and monitoring, evidence gaps, and areas in need of future research. Where applicable, and based on availability of cost-effectiveness data, cost-value recommendations are also provided for clinicians. Many recommendations from previously published guidelines have been updated with new evidence, and new recommendations have been created when supported by published data.

Physiologically Based Pharmacokinetic Modeling of Bergamottin and 6,7-Dihydroxybergamottin to Describe CYP3A4 Mediated Grapefruit-Drug Interactions

Grapefruit is a moderate to strong inactivator of CYP3A4, which metabolizes up to 50% of marketed drugs. The inhibitory effect is mainly attributed to furanocoumarins present in the fruit, irreversibly inhibiting preferably intestinal CYP3A4 as suicide inhibitors. Effects on CYP3A4 victim drugs can still be measured up to 24 hours after grapefruit juice (GFJ) consumption. The current study aimed to establish a physiologically-based pharmacokinetic (PBPK) grapefruit-drug interaction model by modeling the relevant CYP3A4 inhibiting ingredients of the fruit to simulate and predict the effect of GFJ consumption on plasma concentration-time profiles of various CYP3A4 victim drugs. The grapefruit model was developed in PK-Sim and coupled with previously developed PBPK models of CYP3A4 substrates that were publicly available and already evaluated for CYP3A4-mediated drug-drug interactions. Overall, 43 clinical studies were used for model development. Models of bergamottin (BGT) and 6,7-dihydroxybergamottin (DHB) as relevant active ingredients in GFJ were established. Both models include: (i) CYP3A4 inactivation informed by in vitro parameters, (ii) a CYP3A4 mediated clearance estimated during model development, as well as (iii) passive glomerular filtration. The final model successfully describes interactions of GFJ ingredients with 10 different CYP3A4 victim drugs, simulating the effect of the CYP3A4 inactivation on the victims' pharmacokinetics as well as their main metabolites. Furthermore, the model sufficiently captures the time-dependent effect of CYP3A4 inactivation as well as the effect of grapefruit ingestion on intestinal and hepatic CYP3A4 concentrations.

Physiologically Based Pharmacokinetic Modelling-Guided Dose Management of Oral Anticoagulants when Initiating 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.

Evaluation of a Meropenem and Piperacillin Monitoring Program in Intensive Care Unit Patients Calls for the Regular Assessment of Empirical Targets and Easy-to-Use Dosing Decision Tools

The drug concentrations targeted in meropenem and piperacillin/tazobactam therapy also depend on the susceptibility of the pathogen. Yet, the pathogen is often unknown, and antibiotic therapy is guided by empirical targets. To reliably achieve the targeted concentrations, dosing needs to be adjusted for renal function. We aimed to evaluate a meropenem and piperacillin/tazobactam monitoring program in intensive care unit (ICU) patients by assessing (i) the adequacy of locally selected empirical targets, (ii) if dosing is adequately adjusted for renal function and individual target, and (iii) if dosing is adjusted in target attainment (TA) failure. In a prospective, observational clinical trial of drug concentrations, relevant patient characteristics and microbiological data (pathogen, minimum inhibitory concentration (MIC)) for patients receiving meropenem or piperacillin/tazobactam treatment were collected. If the MIC value was available, a target range of 1–5 × MIC was selected for minimum drug concentrations of both drugs. If the MIC value was not available, 8–40 mg/L and 16–80 mg/L were selected as empirical target ranges for meropenem and piperacillin, respectively. A total of 356 meropenem and 216 piperacillin samples were collected from 108 and 96 ICU patients, respectively. The vast majority of observed MIC values was lower than the empirical target (meropenem: 90.0%, piperacillin: 93.9%), suggesting empirical target value reductions. TA was found to be low (meropenem: 35.7%, piperacillin 50.5%) with the lowest TA for severely impaired renal function (meropenem: 13.9%, piperacillin: 29.2%), and observed drug concentrations did not significantly differ between patients with different targets, indicating dosing was not adequately adjusted for renal function or target. Dosing adjustments were rare for both drugs (meropenem: 6.13%, piperacillin: 4.78%) and for meropenem irrespective of TA, revealing that concentration monitoring alone was insufficient to guide dosing adjustment. Empirical targets should regularly be assessed and adjusted based on local susceptibility data. To improve TA, scientific knowledge should be translated into easy-to-use dosing strategies guiding antibiotic dosing.

Focal superior quadrant haemorrhages in post COVID-19 patient: A target for personalized medicine

PURPOSE

To report a case of multiple superior quadrant intraretinal haemorrhages in post-COVID-19 patient.

CASE DESCRIPTION

A 58-year-old male with a history of coronary artery disease and hypertension, presented with multiple superior quadrant intraretinal haemorrhages in the superonasal quadrant of the left eye 1 month after hospitalization for COVID-19. The right eye was normal. During his 10-day stay, he was treated with hydroxychloroquine, lopinavir + ritonavir, ceftriaxone, and his pre-existing antiplatelet therapy. During hospitalization, a complete medical work up showed an anomalous increase in D-dimer. He did not require intensive care support.

CONCLUSIONS

In this report, we focused on the origin of retinal bleeding in a post COVID-19 patient, likely due to a focal occlusion of a vessel. Considering the nature of SARS-CoV-2 infection, we hypothesize that retinal haemorrhages were caused by a combination of factors including the patient's antiplatelet therapy and the thrombotic microvascular injury caused by the virus.

The intersection of drug interactions and adverse reactions in contemporary antiretroviral therapy

PURPOSE OF REVIEW

Advances in antiretroviral therapy (ART) have transformed HIV infection into a chronic and manageable condition. The introduction of potent and more tolerable antiretrovirals (ARVs) with favorable pharmacokinetic profiles has changed the prevalence and nature of drug-drug interactions (DDIs). Here, we review the relevance of DDIs in the era of contemporary ART.

RECENT FINDINGS

Management of DDIs remains an important challenge with modern ART, primarily due to increased polypharmacy in older persons living with HIV. Significant DDIs exist between boosted ARVs or older nonnucleoside reverse transcriptase inhibitors and comedications for chronic comorbidities (e.g., anticoagulants, antiplatelets, statins) or complex conditions (e.g., anticancer agents, immunosuppressants). Newer ARVs such as unboosted integrase inhibitors, doravirine, and fostemsavir have reduced DDI potential, but there are clinically relevant DDIs that warrant consideration. Potential consequences of DDIs include increased toxicity and/or reduced efficacy of ARVs and/or comedications. Management approaches include switching to an ARV with less DDI potential, changing comedications, or altering medication dosage or dosing frequency. Deprescribing strategies can reduce DDIs and polypharmacy, improve adherence, minimize unnecessary adverse effects, and prevent medication-related errors.

SUMMARY

Management of DDIs requires close interdisciplinary collaboration from multiple healthcare disciplines (medicine, nursing, pharmacy) across a spectrum of care (community, outpatient, inpatient).

Physiologically-Based Pharmacokinetic Modelling of Entrectinib Parent and Active Metabolite to Support Regulatory Decision-Making

BACKGROUND AND OBJECTIVE

Entrectinib is a selective inhibitor of ROS1/TRK/ALK kinases, recently approved for oncology indications. Entrectinib is predominantly cleared by cytochrome P450 (CYP) 3A4, and modulation of CYP3A enzyme activity profoundly alters the pharmacokinetics of both entrectinib and its active metabolite M5. We describe development of a combined physiologically based pharmacokinetic (PBPK) model for entrectinib and M5 to support dosing recommendations when entrectinib is co-administered with CYP3A4 inhibitors or inducers.

METHODS

A PBPK model was established in Simcyp^® Simulator. The initial model based on in vitro-in vivo extrapolation was refined using sensitivity analysis and non-linear mixed effects modeling to optimize parameter estimates and to improve model fit to data from a clinical drug-drug interaction study with the strong CYP3A4 inhibitor, itraconazole. The model was subsequently qualified against clinical data, and the final qualified model used to simulate the effects of moderate to strong CYP3A4 inhibitors and inducers on entrectinib and M5 pharmacokinetics.

RESULTS

The final model showed good predictive performance for entrectinib and M5, meeting commonly used predictive performance acceptance criteria in each case. The model predicted that co-administration of various moderate CYP3A4 inhibitors (verapamil, erythromycin, clarithromycin, fluconazole, and diltiazem) would result in an average increase in entrectinib exposure between 2.2- and 3.1-fold, with corresponding average increases for M5 of approximately 2-fold. Co-administration of moderate CYP3A4 inducers (efavirenz, carbamazepine, phenytoin) was predicted to result in an average decrease in entrectinib exposure between 45 and 79%, with corresponding average decreases for M5 of approximately 50%.

CONCLUSIONS

The model simulations were used to derive dosing recommendations for co-administering entrectinib with CYP3A4 inhibitors or inducers. PBPK modeling has been used in lieu of clinical studies to enable regulatory decision-making.

Pharmacokinetic Modeling of Morphine's Effect on Plasma Concentrations of Ticagrelor and Its Metabolite in Healthy Volunteers

This study aimed to build a mathematical model describing the pharmacokinetics of ticagrelor and its active metabolite (AR-C124910XX) in a stable setting with concomitant administration of morphine. The model consists of a set of four differential equations prepared upon the available knowledge regarding the biological processes in the pharmacokinetics of ticagrelor. The set of equations was solved numerically using the Runge–Kutta method. The data were obtained in a double-blind, randomized, placebo-controlled, crossover trial. Twenty-four healthy volunteers received a 180-mg ticagrelor loading dose together with either 5-mg morphine or placebo. Blood samples were analyzed with liquid chromatography–tandem mass spectrometry to assess plasma concentrations of ticagrelor and AR-C124910XX before ticagrelor loading dose and after that 1, 2, 3, 4, and 6 h. The model allowed us to reproduce the experimental results accurately and led us to conclusions consistent with clinical observations that morphine delays the time of maximum drug concentration and that the morphine effect occurs due to decreased gastrointestinal motility. Based on the model, we were able to predict the effect of drug dose on receptor blocking efficacy.

Lopinavir-Ritonavir in SARS-CoV-2 Infection and Drug-Drug Interactions with Cardioactive Medications

Lopinavir-ritonavir combination is being used for the treatment of SARS-CoV-2 infection. A low dose of ritonavir is added to other protease inhibitors to take advantage of potent inhibition of cytochrome (CYP) P450 3A4, thereby significantly increasing the plasma concentration of coadministered lopinavir. Ritonavir also inhibits CYP2D6 and induces CYP2B6, CYP2C19, CYP2C9, and CYP1A2. This potent, time-dependent interference of major hepatic drug-metabolizing enzymes by ritonavir leads to several clinically important drug-drug interactions. A number of patients presenting with acute coronary syndrome and acute heart failure may have SARS-CoV-2 infection simultaneously. Lopinavir-ritonavir is added to their prescription of multiple cardiac medications leading to potential drug-drug interactions. Many cardiology, pulmonology, and intensivist physicians have never been exposed to clinical scenarios requiring co-prescription of cardiac and antiviral therapies. Therefore, it is essential to enumerate these drug-drug interactions, to avoid any serious drug toxicity, to consider alternate and safer drugs, and to ensure better patient care.

Stroke in SARS-CoV-2 Infection: A Pictorial Overview of the Pathoetiology

Since the early days of the pandemic, there have been several reports of cerebrovascular complications during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Numerous studies proposed a role for SARS-CoV-2 in igniting stroke. In this review, we focused on the pathoetiology of stroke among the infected patients. We pictured the results of the SARS-CoV-2 invasion to the central nervous system (CNS) via neuronal and hematogenous routes, in addition to viral infection in peripheral tissues with extensive crosstalk with the CNS. SARS-CoV-2 infection results in pro-inflammatory cytokine and chemokine release and activation of the immune system, COVID-19-associated coagulopathy, endotheliitis and vasculitis, hypoxia, imbalance in the renin-angiotensin system, and cardiovascular complications that all may lead to the incidence of stroke. Critically ill patients, those with pre-existing comorbidities and patients taking certain medications, such as drugs with elevated risk for arrhythmia or thrombophilia, are more susceptible to a stroke after SARS-CoV-2 infection. By providing a pictorial narrative review, we illustrated these associations in detail to broaden the scope of our understanding of stroke in SARS-CoV-2-infected patients. We also discussed the role of antiplatelets and anticoagulants for stroke prevention and the need for a personalized approach among patients with SARS-CoV-2 infection.

Implications of the Antiplatelet Therapy Gap Left With Discontinuation of Prasugrel in Canada

Background

The current Canadian Cardiovascular Society antiplatelet therapy guidelines recommend the use of ticagrelor or prasugrel over clopidogrel as first-line platelet P2Y12 receptor antagonists for treatment of moderate- to high-risk acute coronary syndromes. Recently, Effient (prasugrel [Eli Lilly Canada Inc, Toronto, Canada]) was discontinued by its distributor in Canada.

Methods

Five members of the Canadian Cardiovascular Society antiplatelet therapy 2018 guidelines committee undertook an independent, evidence-based review to outline patients for whom prasugrel should be the optimal P2Y12 agent and discuss alternative strategies to consider without prasugrel.

Results

Several clinical scenarios where prasugrel should be indicated are identified and discussed. Considerations to be undertaken for alternative therapies are summarized, including a review of national and international guidelines for de-escalation of P2Y12 receptor antagonists.

Conclusions

The discontinuation of prasugrel poses a challenge for clinicians. Clinicians must consider key factors in determining the best alternate therapy.

A Model Averaging/Selection Approach Improves the Predictive Performance of Model-Informed Precision Dosing: Vancomycin as a Case Study

Many important drugs exhibit substantial variability in pharmacokinetics and pharmacodynamics leading to a loss of the desired clinical outcomes or significant adverse effects. Forecasting drug exposures using pharmacometric models can improve individual target attainment when compared with conventional therapeutic drug monitoring (TDM). However, selecting the "correct" model for this model-informed precision dosing (MIPD) is challenging. We derived and evaluated a model selection algorithm (MSA) and a model averaging algorithm (MAA), which automates model selection and finds the best model or combination of models for each patient using vancomycin as a case study, and implemented both algorithms in the MIPD software "TDMx." The predictive performance (based on accuracy and precision) of the two algorithms was assessed in (i) a simulation study of six distinct populations and (ii) a clinical dataset of 180 patients undergoing TDM during vancomycin treatment and compared with the performance obtained using a single model. Throughout the six virtual populations the MSA and MAA (imprecision: 9.9-24.2%, inaccuracy: less than ± 8.2%) displayed more accurate predictions than the single models (imprecision: 8.9-51.1%; inaccuracy: up to 28.9%). In the clinical dataset, the predictive performance of the single models applying at least one plasma concentration varied substantially (imprecision: 28-62%, inaccuracy: -16 to 25%), whereas the MSA or MAA utilizing these models simultaneously resulted in unbiased and precise predictions (imprecision: 29% and 30%, inaccuracy: -5% and 0%, respectively). MSA and MAA approaches implemented in TDMx might thereby lower the burden of fit-for-purpose validation of individual models and streamline MIPD.

Towards Personalized Antithrombotic Treatments: Focus on P2Y12 Inhibitors and Direct Oral Anticoagulants

Oral anticoagulants and antiplatelet drugs are commonly prescribed to lower the risk of cardiovascular diseases, such as venous and arterial thrombosis, which represent the leading causes of mortality worldwide. A significant percentage of patients taking antithrombotics will nevertheless experience bleeding or recurrent ischemic events, and this represents a major public health issue. Cardiovascular medicine is now questioning the one-size-fits-all policy, and more personalized approaches are increasingly being considered. However, the available tools are currently limited and they are only moderately able to predict clinical events or have a significant impact on clinical outcomes. Predicting concentrations of antithrombotics in blood could be an effective means of personalization as they have been associated with bleeding and recurrent ischemia. Target concentration interventions could take advantage of physiologically based pharmacokinetic (PBPK) and population-based pharmacokinetic (POPPK) models, which are increasingly used in clinical settings and have attracted the interest of governmental regulatory agencies, to propose dosages adapted to specific population characteristics. These models have the benefit of combining parameters from different sources, such as experimental in vitro data and patients' demographic, genetic, and physiological in vivo data, to characterize the dose-concentration relationships of compounds of interest. As such, they can be used to predict individual drug exposure. In the near future, these models could therefore be a valuable means of predicting personalized antithrombotic blood concentrations and, hopefully, of preventing clinical non-response or bleeding in a given patient. Existing approaches for personalization of antithrombotic prescriptions will be reviewed using practical examples for P2Y₁₂ inhibitors and direct oral anticoagulants. The review will additionally focus on the existing PBPK and POPPK models for these two categories of drugs. Lastly, we address potential scenarios for their implementation in clinics, along with the main limitations and challenges.

Thromboembolic events and Covid-19

The novel Corona virus infection (Covid-19) first identified in China in December 2019 has rapidly progressed in pandemic leading to significant mortality and unprecedented challenge for healthcare systems. Although the clinical spectrum of Covid-19 is variable, acute respiratory failure and systemic coagulopathy are common in severe Covid-19 patients. Lung is an important target of the SARS-CoV-2 virus causing eventually acute respiratory distress syndrome associated to a thromboinflammatory state. The cytokinic storm, thromboinflammation and pulmonary tropism are the bedrock of tissue lesions responsible for acute respiratory failure and for prolonged infection that may lead to multiple organ failure and death. The thrombogenicity of this infectious disease is illustrated by the high frequency of thromboembolic events observed even in Covid-19 patients treated with anticoagulation. Increased D-Dimers, a biomarker reflecting activation of hemostasis and fibrinolysis, and low platelet count (thrombocytopenia) are associated with higher mortality in Covid-19 patients. In this review, we will summarize our current knowledge on the thromboembolic manifestations, the disturbed hemostatic parameters, and the thromboinflammatory conditions associated to Covid-19 and we will discuss the modalities of anticoagulant treatment or other potential antithrombotic options.

Liquid Chromatography-Tandem Mass Spectrometry Method for Ticagrelor and its Active Metabolite Determination in Human Plasma: Application to a Pharmacokinetic Study

Background:

Ticagrelor is a highly recommended new antiplatelet agent for the treatment of patients with acute coronary syndrome at moderate or high ischemic risk. There is a real need for rapid and accurate analytical methods for ticagrelor determination in biological fluids for pharmacokinetic studies. In this study, a sensitive and specific LC-MS method was developed and validated for quantification of ticagrelor and its Active Metabolite (AM) in human plasma over expected clinical concentrations.

Methods:

Samples were handled by Liquid-Liquid Extraction (LLE). A linear gradient was applied with a mobile phase composed of formic acid 0.1% and acetonitrile with 0.1% of formic acid using a C18 reversed-phase column. MS spectra were obtained by electrospray ionization in negative mode and optimized at 521.4→360.9 m/z, 477.2→361.2 m/z and 528.1→367.9 m/z transitions for ticagrelor, AM and ticagrelor-d7, respectively.

Results:

This method allowed rapid elution, in less than 4 minutes, and quantification of concentrations as low as 2 ng/mL for ticagrelor and 1 ng/mL for AM using only 100 μL of human plasma. LLE using hexane/ethyl acetate (50/50) was an optimal compromise in terms of extraction recovery and endogenous compounds interference. Trueness values of 87.8% and 89.5% and precisions of 84.1% and 93.8% were obtained for ticagrelor and AM, respectively. Finally, the usefulness of the method was assessed in a clinical trial where a single 180 mg ticagrelor was orally administered to healthy male volunteers. Pharmacokinetic parameters of ticagrelor and its active metabolite were successfully determined.

Conclusion:

A sensitive and specific quantification LC-MS-MS method was developed and validated for ticagrelor and its active metabolite determination in human plasma. The method was successfully applied to a clinical trial where a single ticagrelor 180 mg dose was orally administered to healthy male volunteers. The described method allows quantification of concentrations as low as 2 ng/mL of ticagrelor and 1 ng/mL of the metabolite using only 100 μL of plasma.

Cardiovascular Risk Management and Hepatitis C: Combining Drugs

Direct-acting antivirals (DAAs) are known victims (substrate) and perpetrators (cause) of drug–drug interactions (DDIs). These DAAs are used for the treatment of hepatitis C virus (HCV) infections and are highly effective drugs. Drugs used for cardiovascular risk management are frequently used by HCV-infected patients, whom also are treated with DAAs. Therefore, the aim of this review was to describe DDIs between cardiovascular drugs (CVDs) and DAAs. An extensive literature search was performed containing search terms for the marketed DAAs and CVDs (β-blocking agents, ACE inhibitors, angiotensin II antagonists, renin inhibitors, diuretics, calcium channel blockers, statins/ezetimibe, fibrates, platelet aggregation inhibitors, vitamin K antagonists, heparins, direct Xa inhibitors, nitrates, amiodarone, and digoxin). In particular, the drug labels from the European Medicines Agency and the US Food and Drug Administration were used. A main finding of this review is that CVDs are mostly victims of DDIs with DAAs. Therefore, when possible, monitoring of pharmacodynamics is recommended when coadministering these drugs with DAAs. Nevertheless, it is sometimes better to discontinue a drug on a temporary basis (statins, ezetimide). The DAAs are victims of DDIs in combination with bisoprolol, carvedilol, labetalol, verapamil, and gemfibrozil. Despite there are many DDIs predicted in this review, most of these DDIs can be managed by monitoring the efficacy and toxicity of the victim drug or by switching to another CVD/DAA.

Utilization of Physiologically Based Pharmacokinetic Modeling in Clinical Pharmacology and Therapeutics: an Overview

The purpose of this review was to assess the advancement of applications for physiologically based pharmacokinetic (PBPK) modeling in various therapeutic areas. We conducted a PubMed search, and 166 articles published between 2012 and 2018 on FDA-approved drug products were selected for further review. Qualifying publications were summarized according to therapeutic area, medication(s) studied, pharmacokinetic model type utilized, simulator program used, and the applications of that modeling. The results showed a 13-fold increase in the number of papers published from 2012 to 2018, with the largest proportion of articles dedicated to the areas of infectious diseases, oncology, and neurology, and application extensions including prediction of drug-drug interactions due to metabolism and/or transporter-mediated effects and understanding drug kinetics in special populations. In addition, we profiled several high-impact studies whose results were used to guide package insert information and formulate dose recommendations. These results show that while utilization of PBPK modeling has drastically increased over the past several years, regulatory support, lack of easy-to-use systems for clinicians, and challenges with model validation remain major challenges for the widespread adoption of this practice in institutional and ambulatory settings. However, PBPK modeling will continue to be a useful tool in the future to assess therapeutic drug monitoring and the growing field of personalized medicine.

Polypharmacy, Drug-Drug Interactions, and Inappropriate Drugs: New Challenges in the Aging Population With HIV

Background

Antiretroviral therapy has transformed HIV infection from a deadly into a chronic condition. Aging people with HIV (PWH) are at higher risk of polypharmacy, potential drug-drug interactions (DDIs), and potentially inappropriate medications (PIMs). This study aims to compare prescribed drugs, polypharmacy, and potential DDIs between young (<65 years old) and elderly (≥65 years old) PWH. The prevalence of PIMs was assessed in elderly.

Methods

PWH from 2 centers within the Swiss HIV Cohort Study were asked to fill in a form with all their current medications. Polypharmacy was defined as being on ≥5 non-HIV drugs. PIMs were evaluated using Beers criteria. Potential DDIs for the most prescribed therapeutic classes were screened with the Liverpool interaction database.

Results

Among the 996 PWH included, 122 were ≥65 years old. Polypharmacy was more frequent in the elderly group (44% vs 12%). Medications and potential DDIs differed according to the age group: cardiovascular drugs and related potential DDIs were more common in the elderly group (73% of forms included ≥1 cardiovascular drug; 11% of cardiovascular drugs involved potential DDIs), whereas central nervous system drugs were more prescribed and involved in potential DDIs in younger PWH (26%, 11%). Potential DDIs were mostly managed through dosage adjustments. PIMs were found in 31% of the elderly group.

Conclusions

Potential DDIs remain common, and PIMs constitute an additional burden for the elderly. It is important that prescribers develop and maintain a proactive approach for the recognition and management of DDIs and other prescribing issues frequently encountered in geriatric medicine.

Impact of Boosted Antiretroviral Therapy on the Pharmacokinetics and Efficacy of Clopidogrel and Prasugrel Active Metabolites

BACKGROUND AND OBJECTIVES

Prasugrel and clopidogrel are inhibitors of the ADP-P₂Y₁₂ platelet receptor used in acute coronary syndrome patients. They require bioactivation via isoenzymes such as cytochrome P450 (CYP) 3A4, CYP2C19 and CYP2B6. Ritonavir and cobicistat are potent CYP3A inhibitors, prescribed as pharmacokinetic (PK) enhancers in the treatment of human immunodeficiency virus (HIV) infection.

METHODS

In this study, the impact of boosted antiretroviral therapies (ARTs) on the PK of clopidogrel and prasugrel active metabolites (AMs), and on the efficacy of prasugrel and clopidogrel, were evaluated in a randomized crossover clinical trial.

RESULTS

A significantly lower exposure to clopidogrel AM [3.2-fold lower area under the concentration-time curve (AUC) and maximum plasma concentration (C_max)] and prasugrel AM (2.1-fold and 1.7-fold lower AUC and C_max) were demonstrated in HIV-infected patients treated with boosted ARTs compared with healthy controls; however, a differential impact was observed on platelet inhibition between clopidogrel and prasugrel. Clopidogrel 300 mg induced adequate (although modest) platelet inhibition in all healthy subjects, while platelet inhibition was insufficient in 44% of HIV patients. On the contrary, prasugrel 60 mg induced a potent platelet inhibition in both healthy and HIV-infected subjects.

CONCLUSION

Prasugrel appears to remain an adequate antiplatelet agent in HIV-infected patients and could be preferred to clopidogrel in this context, regardless of the metabolic interaction and inhibition of its bioactivation pathways.

Prediction of Ticagrelor and its Active Metabolite in Liver Cirrhosis Populations Using a Physiologically Based Pharmacokinetic Model Involving Pharmacodynamics

Ticagrelor, a P2Y₁₂ receptor antagonist, has been highly recommended for use in acute coronary syndrome. The major active metabolite (AM) is similar to the parent drug, which exhibits antiplatelet activity. The inhibition of platelet aggregation (IPA) is used as an assay to demonstrate the anticoagulant efficacy of ticagrelor. In this study, we developed a physiologically based pharmacokinetic (PBPK) model to predict the pharmacokinetics of ticagrelor and its AM and combined this model with a pharmacodynamics model to reflect potential pharmacodynamic alterations in liver cirrhosis populations. The simulated results obtained using the PBPK model were validated by fold error values, which were all smaller than 2. Comparisons of exposure in different classifications of liver cirrhosis indicated that exposure to ticagrelor increased significantly with an increase in the degree of cirrhosis severity, whereas exposure to AM was decreased. The total concentration of ticagrelor and AM was related to the IPA included in the Sigmoid E_max model. The PBPK model of ticagrelor and AM could predict the pharmacokinetics of all populations, and a combination of PD models was used to extrapolate for predicting unknown scenarios. Liver cirrhosis may result in prolonged IPA, depending on the severity degree of this disease. The combined PBPK model including IPA can reveal changes in pharmacokinetics and pharmacodynamics in populations affected by liver cirrhosis and indicate the risk potential.

Complex Drug-Drug-Gene-Disease Interactions Involving Cytochromes P450: Systematic Review of Published Case Reports and Clinical Perspectives

Drug pharmacokinetics (PK) is influenced by multiple intrinsic and extrinsic factors, among which concomitant medications are responsible for drug-drug interactions (DDIs) that may have a clinical relevance, resulting in adverse drug reactions or reduced efficacy. The addition of intrinsic factors affecting cytochromes P450 (CYPs) activity and/or expression, such as genetic polymorphisms and diseases, may potentiate the impact and clinical relevance of DDIs. In addition, greater variability in drug levels and exposures has been observed when such intrinsic factors are present in addition to concomitant medications perpetrating DDIs. This variability results in poor predictability of DDIs and potentially dramatic clinical consequences. The present review illustrates the issue of complex DDIs using systematically searched published case reports of DDIs involving genetic polymorphisms, renal impairment, cirrhosis, and/or inflammation. Current knowledge on the impact of each of these factors on drug exposure and DDIs is summarized and future perspectives for the management of such complex DDIs in clinical practice are discussed, including the use of advanced Computerized Physician Order Entry (CPOE) systems, the development of model-based dose optimization strategies, and the education of healthcare professionals with respect to personalized medicine.