Lean, mean, learning machines

Wheeler, Nicole E.; Sánchez-Busó, Leonor; Argimón, Silvia; Jeffrey, Benjamin

doi:10.1038/s41579-020-0357-4

Cited by 1 publication

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“…Drug resistant malaria and TB are common, with almost 500,000 new cases of multidrug-resistant tuberculosis in 2016 and a 45% mortality rate worldwide. ML methods are being used to predict resistance phenotypes (Wheeler et al, 2020) and the effects of multidrug dosing and drug synergies. A novel application of ML to predict synergistic combinations of antimalarial drugs was reported by Mason et al (Mason et al, 2018) The discovery of synergistic combinations of antimalarial drugs is potentially very important, but an exhaustive experimental screen of every antimalarial drug with all others is not tractable.…”

Section: Quantitative ML Models and Multitarget/ Multidrug Strategiesmentioning

confidence: 99%

Use of Artificial Intelligence and Machine Learning for Discovery of Drugs for Neglected Tropical Diseases

Winkler

2021

Front. Chem.

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Neglected tropical diseases continue to create high levels of morbidity and mortality in a sizeable fraction of the world’s population, despite ongoing research into new treatments. Some of the most important technological developments that have accelerated drug discovery for diseases of affluent countries have not flowed down to neglected tropical disease drug discovery. Pharmaceutical development business models, cost of developing new drug treatments and subsequent costs to patients, and accessibility of technologies to scientists in most of the affected countries are some of the reasons for this low uptake and slow development relative to that for common diseases in developed countries. Computational methods are starting to make significant inroads into discovery of drugs for neglected tropical diseases due to the increasing availability of large databases that can be used to train ML models, increasing accuracy of these methods, lower entry barrier for researchers, and widespread availability of public domain machine learning codes. Here, the application of artificial intelligence, largely the subset called machine learning, to modelling and prediction of biological activities and discovery of new drugs for neglected tropical diseases is summarized. The pathways for the development of machine learning methods in the short to medium term and the use of other artificial intelligence methods for drug discovery is discussed. The current roadblocks to, and likely impacts of, synergistic new technological developments on the use of ML methods for neglected tropical disease drug discovery in the future are also discussed.

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Section: Quantitative ML Models and Multitarget/ Multidrug Strategiesmentioning

confidence: 99%

Use of Artificial Intelligence and Machine Learning for Discovery of Drugs for Neglected Tropical Diseases

Winkler

2021

Front. Chem.

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show abstract

Lean, mean, learning machines

Cited by 1 publication

References 6 publications

Use of Artificial Intelligence and Machine Learning for Discovery of Drugs for Neglected Tropical Diseases

Use of Artificial Intelligence and Machine Learning for Discovery of Drugs for Neglected Tropical Diseases

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