AIMC Topic: Drug Discovery

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Recent applications of deep learning and machine intelligence on in silico drug discovery: methods, tools and databases.

Briefings in bioinformatics
The identification of interactions between drugs/compounds and their targets is crucial for the development of new drugs. In vitro screening experiments (i.e. bioassays) are frequently used for this purpose; however, experimental approaches are insuf...

[Artificial Intelligence-based Drug Discovery and Drug Repositioning].

Brain and nerve = Shinkei kenkyu no shinpo
The methodologies of computational drug discovery and drug repositioning (DR) based on biomolecular profile information are reviewed systematically. For big data drug discovery and DR, 1) methods of comparing gene expression profiles of the diseased ...

Applications of machine learning in drug discovery and development.

Nature reviews. Drug discovery
Drug discovery and development pipelines are long, complex and depend on numerous factors. Machine learning (ML) approaches provide a set of tools that can improve discovery and decision making for well-specified questions with abundant, high-quality...

Opportunities and challenges using artificial intelligence in ADME/Tox.

Nature materials
A recent conference organized a panel of scientists representing small and big pharma companies, who work at the interface of machine learning (ML) and absorption, distribution, metabolism, excretion, and toxicology (ADME/Tox). With the recent rebirt...