AIMC Topic: Drug Repositioning
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Mechanism of baricitinib supports artificial intelligence-predicted testing in COVID-19 patients.
EMBO molecular medicine
Jun 24, 2020
Baricitinib is an oral Janus kinase (JAK)1/JAK2 inhibitor approved for the treatment of rheumatoid arthritis (RA) that was independently predicted, using artificial intelligence (AI) algorithms, to be useful for COVID-19 infection via proposed anti-c...
Sulfonamides
Drug Evaluation, Preclinical
Coronavirus Infections
COVID-19 Drug Treatment
Protein Serine-Threonine Kinases
Drug Repositioning
Female
Leukocytes
SARS-CoV-2
Intracellular Signaling Peptides and Proteins
Aged
Betacoronavirus
Adult
Pneumonia, Viral
Male
Azetidines
Middle Aged
Antiviral Agents
Liver
Artificial Intelligence
Pandemics
COVID-19
Cytokines
Humans
Pyrazoles
Protein Kinase Inhibitors
Purines
Spheroids, Cellular
Robot technology identifies a Parkinsonian therapeutics repurpose to target stem cells of glioblastoma.
CNS oncology
May 28, 2020
Glioblastoma is a heterogeneous lethal disease, regulated by a stem-cell hierarchy and the neurotransmitter microenvironment. The identification of chemotherapies targeting individual cancer stem cells is a clinical need. A robotic workstation was ...
Artificial intelligence approach fighting COVID-19 with repurposing drugs.
Biomedical journal
May 15, 2020
BACKGROUND: The ongoing COVID-19 pandemic has caused more than 193,825 deaths during the past few months. A quick-to-be-identified cure for the disease will be a therapeutic medicine that has prior use experiences in patients in order to resolve the ...
Artificial intelligence and machine learning to fight COVID-19.
Physiological genomics
Mar 27, 2020
HNet-DNN: Inferring New Drug-Disease Associations with Deep Neural Network Based on Heterogeneous Network Features.
Journal of chemical information and modeling
Mar 13, 2020
Drug research and development is a time-consuming and high-cost task, pressing an urgent demand to identify novel indications of approved drugs, referred to as drug repositioning, which provides an economical and efficient way for drug discovery. Wit...
Prediction of Side Effects Using Comprehensive Similarity Measures.
BioMed research international
Feb 27, 2020
Identifying the potential side effects of drugs is crucial in clinical trials in the pharmaceutical industry. The existing side effect prediction methods mainly focus on the chemical and biological properties of drugs. This study proposes a method th...
RefDNN: a reference drug based neural network for more accurate prediction of anticancer drug resistance.
Scientific reports
Feb 5, 2020
Cancer is one of the most difficult diseases to treat owing to the drug resistance of tumour cells. Recent studies have revealed that drug responses are closely associated with genomic alterations in cancer cells. Numerous state-of-the-art machine le...
Next-generation drug repurposing using human genetics and network biology.
Current opinion in pharmacology
Jan 22, 2020
Drug repurposing has attracted increased attention, especially in the context of drug discovery rates that remain too low despite a recent wave of approvals for biological therapeutics (e.g. gene therapy). These new biological entities-based treatmen...
Machine and deep learning approaches for cancer drug repurposing.
Seminars in cancer biology
Jan 3, 2020
Knowledge of the underpinnings of cancer initiation, progression and metastasis has increased exponentially in recent years. Advanced "omics" coupled with machine learning and artificial intelligence (deep learning) methods have helped elucidate targ...
Old drug repositioning and new drug discovery through similarity learning from drug-target joint feature spaces.
BMC bioinformatics
Dec 27, 2019
BACKGROUND: Detection of new drug-target interactions by computational algorithms is of crucial value to both old drug repositioning and new drug discovery. Existing machine-learning methods rely only on experimentally validated drug-target interacti...
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