DeepARV: ensemble deep learning to predict drug-drug interaction of clinical relevance with antiretroviral therapy.

Drug-drug interaction (DDI) may result in clinical toxicity or treatment failure of antiretroviral therapy (ARV) or comedications. Despite the high number of possible drug combinations, only a limited number of clinical DDI studies are conducted. Computational prediction of DDIs could provide key evidence for the rational management of complex therapies.

Physiologically-based pharmacokinetic modelling of long-acting injectable cabotegravir and rilpivirine in pregnancy.

Aims: Long-acting cabotegravir and rilpivirine have been approved to manage HIV in adults, but data regarding safe use in pregnancy are limited. Physiologically-based pharmacokinetic (PBPK) modelling was used to simulate the approved dosing regimens in pregnancy and explore if C was maintained above cabotegravir and rilpivirine target concentrations (664 and 50 ng/mL, respectively).

Methods: An adult PBPK model was validated using clinical data of cabotegravir and rilpivirine in nonpregnant adults.

General Framework to Quantitatively Predict Pharmacokinetic Induction Drug-Drug Interactions Using In Vitro Data.

Introduction: Metabolic inducers can expose people with polypharmacy to adverse health outcomes. A limited fraction of potential drug-drug interactions (DDIs) have been or can ethically be studied in clinical trials, leaving the vast majority unexplored. In the present study, an algorithm has been developed to predict the induction DDI magnitude, integrating data related to drug-metabolising enzymes.

Prevalence of Potentially Clinically Significant Drug-Drug Interactions With Antiretrovirals Against HIV Over Three Decades: A Systematic Review of the Literature.

Background: Contemporary first-line antiretrovirals have considerably reduced liability for clinically significant drug-drug interactions (DDI). This systematic review evaluates the prevalence of DDI among people receiving antiretrovirals across 3 decades.

Methods: We searched 3 databases for studies reporting the prevalence of clinically significant DDIs in patients receiving antiretrovirals published between January 1987 and July 2022.

Evaluation of drug-drug interaction between rilpivirine and rifapentine using PBPK modelling.

Tuberculosis remains the leading cause of death among people living with HIV. Rifapentine is increasingly used to treat active disease or prevent reactivation, in both cases given either as weekly or daily therapy. However, rifapentine is an inducer of CYP3A4, potentially interacting with antiretrovirals like rilpivirine.

PBPK Modelling of Dexamethasone in Patients With COVID-19 and Liver Disease.

The aim of the study was to apply Physiologically-Based Pharmacokinetic (PBPK) modelling to predict the effect of liver disease (LD) on the pharmacokinetics (PK) of dexamethasone (DEX) in the treatment of COVID-19. A whole-body PBPK model was created to simulate 100 adult individuals aged 18-60 years. Physiological changes (e.

Drug-Drug Interactions in People Living With HIV at Risk of Hepatic and Renal Impairment: Current Status and Future Perspectives.

Despite the advancement of antiretroviral therapy (ART) for the treatment of human immunodeficiency virus (HIV), drug-drug interactions (DDIs) remain a relevant clinical issue for people living with HIV receiving ART. Antiretroviral (ARV) drugs can be victims and perpetrators of DDIs, and a detailed investigation during drug discovery and development is required to determine whether dose adjustments are necessary or coadministrations are contraindicated. Maintaining therapeutic ARV plasma concentrations is essential for successful ART, and changes resulting from potential DDIs could lead to toxicity, treatment failure, or the emergence of ARV-resistant HIV.