Because of the complexity of biological systems, cutting-edge machine-learning methods will be critical for future drug development. In particular, machine-vision methods to extract detailed information from imaging assays and active-learning methods to guide experimentation will be required to overcome the dimensionality problem in drug development.
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Acknowledgements
Much of the work from my group referred to here was supported by NIH grant GM075205.
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Murphy, R. An active role for machine learning in drug development. Nat Chem Biol 7, 327–330 (2011). https://doi.org/10.1038/nchembio.576
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DOI: https://doi.org/10.1038/nchembio.576
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