Abstract: Method(s), apparatus and system(s) are provided for generating and using an ensemble model. The ensemble may be generated by training a plurality of models based on a plurality of datasets associated with compounds; calculating model performance statistics for each of the plurality of trained models; selecting and storing a set of optimal trained model(s) from the trained models based on the calculated model performance statistics; and forming one or more ensemble models, each ensemble model comprising multiple models from the set of optimal trained model(s). The ensemble model may be used by retrieving the ensemble model and inputting, to the ensemble model, data representative of one or more labelled dataset(s) used to generate and/or train the model(s) of the ensemble model; and receiving, from the ensemble model, output data associated with labels of the one or more labelled dataset(s).

Abstract: Method(s), apparatus and system(s) are provided for designing a compound exhibiting one or more desired property(ies) using a machine learning (ML) technique. This may be achieved by generating a second compound using the ML technique to modify a first compound based on the desired property(ies) and a set of rules for modifying compounds; scoring the second compound based on the desired property(ies); determining whether to repeat the generating step based on the scoring; and updating the ML technique based on the scoring prior to repeating the generating step.

Abstract: Method(s), apparatus, and computer-implemented method(s) are provided for training a machine learning (ML) technique to generate a property model for predicting whether a compound has a particular property. An iterative procedure/feedback loop may be performed for generating the property model, the procedure including: generating a prediction result list for a plurality of compounds and their association with the particular property based on the property model; validating the property model based on compounds from the prediction result list having an association with the particular property; and updating the property model based on the property model validation. The procedure/loop may be repeated using the updated property model until it is determined the property model has been validly trained.

Abstract: Method(s) and apparatus are provided for generating a selection model based on a machine learning (ML) technique, the selection model for selecting a shortlist of compounds requiring validation with a particular property.