Drug discovery could be significantly sped up by the integration of in silico methods. To this end, LLNL scientists along with other ATOM Consortium members created the ATOM Modeling PipeLine (AMPL). AMPL is an open-source, modular, extensible, end-to-end software pipeline for building and sharing models. It extends the functionality of DeepChem and supports an array of machine learning and molecular featurization tools. AMPL has been benchmarked on a large collection of pharmaceutical datasets covering a wide range of parameters and has been shown to generate machine learning models that can predict key safety and pharmacokinetic-relevant parameters. By integrating in silico methods such as AMPL into the drug discovery process, patients can obtain safer, more effective drugs faster.
AMPL, Open-sourced software licensed under the MIT license (LLNL internal case # CP02227)