AIMC Topic: Drug Therapy, Combination

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Leading predictors and their associations with combination opioid pain therapy in older adults with cancer: Application of machine learning approaches.

PloS one
Combined use of opioids and other pharmacological therapies used for pain management, such as non-steroidal anti-inflammatory drugs (NSAIDs), benzodiazepines, gabapentinoids, and/or skeletal muscle relaxants (SMRs), in older adult cancer survivors ca...

VCTatDot and VCTatMLP: novel deep learning models with triadic attention embeddings for synergistic drug combination prediction.

Scientific reports
Computational drug repurposing is vital in drug discovery research because it significantly reduces both the cost and time involved in the drug development process. Additionally, combination therapy-using more than one drug for treatment-can enhance ...

Synergistic analgesic effects of astaxanthin combined with celecoxib on a mouse bone cancer pain model: From behavioral validation to target prediction.

International immunopharmacology
Bone cancer pain (BCP) is a complex condition that severely affects patients' quality of life, and its treatment remains challenging. Astaxanthin, a potent antioxidant with anti-inflammatory and neuroprotective effects, and celecoxib, a selective COX...

DeepDrug as an expert guided and AI driven drug repurposing methodology for selecting the lead combination of drugs for Alzheimer's disease.

Scientific reports
Alzheimer's Disease (AD) significantly aggravates human dignity and quality of life. While newly approved amyloid immunotherapy has been reported, effective AD drugs remain to be identified. Here, we propose a novel AI-driven drug-repurposing method,...

Advanced AI and ML frameworks for transforming drug discovery and optimization: With innovative insights in polypharmacology, drug repurposing, combination therapy and nanomedicine.

European journal of medicinal chemistry
Artificial Intelligence (AI) and Machine Learning (ML) are transforming drug discovery by overcoming traditional challenges like high costs, time-consuming, and frequent failures. AI-driven approaches streamline key phases, including target identific...

Combination therapy synergism prediction for virus treatment using machine learning models.

PloS one
Combining different drugs synergistically is an essential aspect of developing effective treatments. Although there is a plethora of research on computational prediction for new combination therapies, there is limited to no research on combination th...

DrugSK: A Stacked Ensemble Learning Framework for Predicting Drug Combinations of Multiple Diseases.

Journal of chemical information and modeling
Combination therapy is an important direction of continuous exploration in the field of medicine, with the core goals of improving treatment efficacy, reducing adverse reactions, and optimizing clinical outcomes. Machine learning technology holds gre...

Antibiotic combinations prediction based on machine learning to multicentre clinical data and drug interaction correlation.

International journal of antimicrobial agents
BACKGROUND: With increasing antibiotic resistance and regulation, the issue of antibiotic combination has been emphasised. However, antibiotic combination prescribing lacks a rapid identification of feasibility, while its risk of drug interactions is...