AIMC Topic: Drug Combinations

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Improving the therapeutic ratio of radiotherapy against radioresistant cancers: Leveraging on novel artificial intelligence-based approaches for drug combination discovery.

Cancer letters
Despite numerous advances in cancer radiotherapy, tumor radioresistance remain one of the major challenges limiting treatment efficacy of radiotherapy. Conventional strategies to overcome radioresistance involve understanding the underpinning molecul...

TranSynergy: Mechanism-driven interpretable deep neural network for the synergistic prediction and pathway deconvolution of drug combinations.

PLoS computational biology
Drug combinations have demonstrated great potential in cancer treatments. They alleviate drug resistance and improve therapeutic efficacy. The fast-growing number of anti-cancer drugs has caused the experimental investigation of all drug combinations...

Predicting adverse drug reactions of two-drug combinations using structural and transcriptomic drug representations to train an artificial neural network.

Chemical biology & drug design
Adverse drug reactions (ADRs) are pharmacological events triggered by drug interactions with various sources of origin including drug-drug interactions. While there are many computational studies that explore models to predict ADRs originating from s...

The role of sacubitril/valsartan in the treatment of chronic heart failure with reduced ejection fraction in hypertensive patients with comorbidities: From clinical trials to real-world settings.

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie
BACKGROUND: Sacubitril/valsartan, the first agent to be approved in a new class of drugs called angiotensin receptor neprilysin inhibitors (ARNIs), has been shown to reduce cardiovascular mortality and morbidity compared to enalapril in outpatient su...

Detecting asthma exacerbations using daily home monitoring and machine learning.

The Journal of asthma : official journal of the Association for the Care of Asthma
OBJECTIVE: Acute exacerbations contribute significantly to the morbidity of asthma. Recent studies have shown that early detection and treatment of asthma exacerbations leads to improved outcomes. We aimed to develop a machine learning algorithm to d...

Making Sense of Pharmacovigilance and Drug Adverse Event Reporting: Comparative Similarity Association Analysis Using AI Machine Learning Algorithms in Dogs and Cats.

Topics in companion animal medicine
Drug-associated adverse events cause approximately 30 billion dollars a year of added health care expense, along with negative health outcomes including patient death. This constitutes a major public health concern. The US Food and Drug Administratio...

Predict effective drug combination by deep belief network and ontology fingerprints.

Journal of biomedical informatics
The synergistic effect of drug combination is one of the most desirable properties for treating cancer. However, systematically predicting effective drug combination is a significant challenge. We report here a novel method based on deep belief netwo...

Artificial neural networks (ANNs) and partial least squares (PLS) regression in the quantitative analysis of cocrystal formulations by Raman and ATR-FTIR spectroscopy.

Journal of pharmaceutical and biomedical analysis
The present work describes the development of an efficient, fast and accurate method for the quantification of polymer-based cocrystal formulations. Specifically, the content of carbamazepine-nicotinamide (CBZ/NIC) and ibuprofen-nicotinamide (IBU/NIC...

A systematic and prospectively validated approach for identifying synergistic drug combinations against malaria.

Malaria journal
BACKGROUND: Nearly half of the world's population (3.2 billion people) were at risk of malaria in 2015, and resistance to current therapies is a major concern. While the standard of care includes drug combinations, there is a pressing need to identif...

Population pharmacokinetics of continuous infusion of piperacillin in critically ill patients.

International journal of antimicrobial agents
Dosing recommendations for continuous infusion of piperacillin, a broad-spectrum beta-lactam antibiotic, are mainly guided by outputs from population pharmacokinetic models constructed with intermittent infusion data. However, the probability of targ...