AIMC Topic: Anti-HIV Agents
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Improving HIV preexposure prophylaxis uptake with artificial intelligence and automation: a systematic review.
AIDS (London, England)
May 23, 2024
OBJECTIVES: To identify studies promoting the use of artificial intelligence (AI) or automation with HIV preexposure prophylaxis (PrEP) care and explore ways for AI to be used in PrEP interventions.
DeepARV: ensemble deep learning to predict drug-drug interaction of clinical relevance with antiretroviral therapy.
NPJ systems biology and applications
May 6, 2024
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. Com...
A knowledge-guided pre-training framework for improving molecular representation learning.
Nature communications
Nov 21, 2023
Learning effective molecular feature representation to facilitate molecular property prediction is of great significance for drug discovery. Recently, there has been a surge of interest in pre-training graph neural networks (GNNs) via self-supervised...
Industrializing AI/ML during the end-to-end drug discovery process.
Current opinion in structural biology
Feb 1, 2023
Drug discovery aims to select proper targets and drug candidates to address unmet clinical needs. The end-to-end drug discovery process includes all stages of drug discovery from target identification to drug candidate selection. Recently, several ar...
Evaluation of the pharmacokinetic drug-drug interaction between the antiretroviral agents fostemsavir and maraviroc: a single-sequence crossover study in healthy participants.
HIV research & clinical practice
Mar 14, 2022
BACKGROUND: Fostemsavir is an oral prodrug of temsavir, a first-in-class attachment inhibitor that binds HIV-1 gp120, preventing initial HIV attachment and entry into host immune cells.
Switching to a NRTI-free 2 drug regimen (2DR) -a sub-analysis of the 48 weeks DUALIS study on metabolic and renal changes.
HIV research & clinical practice
Mar 2, 2022
Switching from a three-drug regimen (3DR: boosted darunavir [bDRV] and two nucleoside reverse transcriptase inhibitors [NRTIs]) to a two-drug regimen (2DR: bDRV and dolutegravir [DTG]) demonstrated non-inferiority with regard to viral suppression in...
Long-term safety and efficacy of rilpivirine in combination with nucleoside/nucleotide reverse transcriptase inhibitors in HIV-1 infected patients: 336-week rollover study of phase 2b and 3 clinical studies.
Antiviral therapy
Nov 26, 2021
BACKGROUND: To evaluate the long-term safety and efficacy of rilpivirine (RPV), a non-nucleoside reverse transcriptase inhibitor (NNRTI), in combination with nucleoside/nucleotide reverse transcriptase inhibitors (NRTIs) in human immunodeficiency vir...
Using machine learning and big data to explore the drug resistance landscape in HIV.
PLoS computational biology
Aug 26, 2021
Drug resistance mutations (DRMs) appear in HIV under treatment pressure. DRMs are commonly transmitted to naive patients. The standard approach to reveal new DRMs is to test for significant frequency differences of mutations between treated and naive...
Predicting HIV drug resistance using weighted machine learning method at target protein sequence-level.
Molecular diversity
Jul 9, 2021
Acquired immune deficiency syndrome (AIDS) is a fatal disease caused by human immunodeficiency virus (HIV). Although 23 different drugs have been available, the treatment of AIDS remains challenging because the virus mutates very quickly which can le...
Application of deep learning and molecular modeling to identify small drug-like compounds as potential HIV-1 entry inhibitors.
Journal of biomolecular structure & dynamics
Apr 15, 2021
A generative adversarial autoencoder for the rational design of potential HIV-1 entry inhibitors able to block CD4-binding site of the viral envelope protein gp120 was developed. To do this, the following studies were carried out: (i) an autoencoder ...
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