AIMC Topic: Molecular Targeted Therapy

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The case for AI-driven cancer clinical trials - The efficacy arm in silico.

Biochimica et biophysica acta. Reviews on cancer
Pharmaceutical agents in oncology currently have high attrition rates from early to late phase clinical trials. Recent advances in computational methods, notably causal artificial intelligence, and availability of rich clinico-genomic databases have ...

Target Prediction Model for Natural Products Using Transfer Learning.

International journal of molecular sciences
A large proportion of lead compounds are derived from natural products. However, most natural products have not been fully tested for their targets. To help resolve this problem, a model using transfer learning was built to predict targets for natura...

Towards the Interpretability of Machine Learning Predictions for Medical Applications Targeting Personalised Therapies: A Cancer Case Survey.

International journal of molecular sciences
Artificial Intelligence is providing astonishing results, with medicine being one of its favourite playgrounds. Machine Learning and, in particular, Deep Neural Networks are behind this revolution. Among the most challenging targets of interest in me...

Expanding the drug discovery space with predicted metabolite-target interactions.

Communications biology
Metabolites produced in the human gut are known modulators of host immunity. However, large-scale identification of metabolite-host receptor interactions remains a daunting challenge. Here, we employed computational approaches to identify 983 potenti...

Use of artificial intelligence to enhance phenotypic drug discovery.

Drug discovery today
Research and development (R&D) productivity across the pharmaceutical industry has received close scrutiny over the past two decades, especially taking into consideration reports of attrition rates and the colossal cost for drug development. The resp...

Strategies for Testing Intervention Matching Schemes in Cancer.

Clinical pharmacology and therapeutics
Personalized medicine, or the tailoring of health interventions to an individual's nuanced and often unique genetic, biochemical, physiological, behavioral, and/or exposure profile, is seen by many as a biological necessity given the great heterogene...

Automated design and optimization of multitarget schizophrenia drug candidates by deep learning.

European journal of medicinal chemistry
Complex neuropsychiatric diseases such as schizophrenia require drugs that can target multiple G protein-coupled receptors (GPCRs) to modulate complex neuropsychiatric functions. Here, we report an automated system comprising a deep recurrent neural ...

Computational inference of cancer-specific vulnerabilities in clinical samples.

Genome biology
BACKGROUND: Systematic in vitro loss-of-function screens provide valuable resources that can facilitate the discovery of drugs targeting cancer vulnerabilities.

Insight into potent leads for alzheimer's disease by using several artificial intelligence algorithms.

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie
Several proteins including S-nitrosoglutathione reductase (GSNOR), complement Factor D, complement 3b (C3b) and Protein Kinase R-like Endoplasmic Reticulum Kinase (PERK), have been demonstrated to be involved in pathogenesis pathways for Alzheimer's ...