Machine Learning For Drug Discovery

Machine learning algorithms are becoming greatly beneficial for drug development. According to a recent paper, 'Use of machine learning approaches for novel drug discovery', they can now be applied in several steps of the drug discovery methodology. These include'the prediction of target structure, prediction of biological activity of new ligands through model construction, discovery or optimization of hits, and construction of models that predict the pharmacokinetic and toxicological (ADMET) profile of compounds.' AstraZeneca's announcement today that they have joined forces with Human Longevity, a US sequencing and machine learning company, to sequence 2 million genomes is therefore not a surprise as such, but it does represent a step up in terms of the scale of such projects. AstraZeneca will be able to use Human Longevity's database of 1 million genomic and heath records alongside 500,000 DNA samples from their own clinical trials.