AIMC Topic: Drug Therapy, Combination
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[The development of model of prognostication and minimization of risk of by-effects under combined application of agents for treatment of chronic cardiac deficiency using AI].
Problemy sotsial'noi gigieny, zdravookhraneniia i istorii meditsiny
May 10, 2025
The chronic cardiac deficiency continues to be one of the leading health care problems requiring innovative solutions. The article presents mathematical algorithm to evaluate drug interactions and targeted to minimize side effects and to optimize chr...
DD-PRiSM: a deep learning framework for decomposition and prediction of synergistic drug combinations.
Briefings in bioinformatics
Nov 22, 2024
Combination therapies have emerged as a promising approach for treating complex diseases, particularly cancer. However, predicting the efficacy and safety profiles of these therapies remains a significant challenge, primarily because of the complex i...
RepurposeDrugs: an interactive web-portal and predictive platform for repurposing mono- and combination therapies.
Briefings in bioinformatics
May 23, 2024
RepurposeDrugs (https://repurposedrugs.org/) is a comprehensive web-portal that combines a unique drug indication database with a machine learning (ML) predictor to discover new drug-indication associations for approved as well as investigational mon...
Estimation of Mycophenolic Acid Exposure in Chinese Renal Transplant Patients by a Joint Deep Learning Model.
Therapeutic drug monitoring
Dec 1, 2022
BACKGROUND: To predict mycophenolic acid (MPA) exposure in renal transplant recipients using a deep learning model based on a convolutional neural network with bilateral long short-term memory and attention methods.
Multidrug representation learning based on pretraining model and molecular graph for drug interaction and combination prediction.
Bioinformatics (Oxford, England)
Sep 15, 2022
MOTIVATION: Approaches for the diagnosis and treatment of diseases often adopt the multidrug therapy method because it can increase the efficacy or reduce the toxic side effects of drugs. Using different drugs simultaneously may trigger unexpected ph...
SynPathy: Predicting Drug Synergy through Drug-Associated Pathways Using Deep Learning.
Molecular cancer research : MCR
May 4, 2022
UNLABELLED: Drug combination therapy has become a promising therapeutic strategy for cancer treatment. While high-throughput drug combination screening is effective for identifying synergistic drug combinations, measuring all possible combinations is...
Artificial intelligence and machine learning methods in predicting anti-cancer drug combination effects.
Briefings in bioinformatics
Nov 5, 2021
Drug combinations have exhibited promising therapeutic effects in treating cancer patients with less toxicity and adverse side effects. However, it is infeasible to experimentally screen the enormous search space of all possible drug combinations. Th...
Antimicrobial and synergistic activity of thiazoline derivatives in combination with conventional antibiotics against multidrug resistant Staphylococcus aureus isolated from abscess drainage samples.
Pakistan journal of pharmaceutical sciences
Sep 1, 2020
Emergence and spread of multidrug resistant (MDR) Staphylococcus aureus strains is becoming major challenge in treatment of soft tissue infections. This study aimed to explore antimicrobial and synergistic antimicrobial potential of three commerciall...
Artificial intelligence in drug combination therapy.
Briefings in bioinformatics
Jul 19, 2019
Currently, the development of medicines for complex diseases requires the development of combination drug therapies. It is necessary because in many cases, one drug cannot target all necessary points of intervention. For example, in cancer therapy, a...
Least-Squares Analysis
Drug Interactions
Expert Systems
Stochastic Processes
Drug Therapy, Combination
Gene Expression Regulation, Neoplastic
Drug Resistance
Humans
Support Vector Machine
Bayes Theorem
Machine Learning
Deep Learning
Neoplasms
Neural Networks, Computer
Computational Biology
Artificial Intelligence
Logistic Models
[A real-world study of paritaprevir/ritonavir-ombitasvir combined with dasabuvir in the treatment of genotype 1b chronic hepatitis C].
Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology
Dec 20, 2018
To recognize the efficacy and safety of paritaprevir/ritonavir-ombitasvir combined with dasabuvir (OBV/PTV/RTV+DSV) in the treatment of genotype 1b chronic hepatitis C. Patients with genotype 1b chronic hepatitis C who were admitted to the People's...
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