This webinar gives insight into recent development of ChemAxon's Calculators and Predictors towards trainable models and new ADMET models. Trainable models give the opportunity to use input data including experimental values and chemical structures to build models automatically using machine learning techniques. The pipeline connects descriptor generation, model building and validation and delivers a model ready to be used. New ADMET models refers to our plans to extend predictions with additional end-points. The talk introduces the first version of the hERG pAct regression model, as the first element in the ADMET group.
Trainable models
Posted by
Ákos Tarcsay
on 13 09 2020
Related content
03 10 2022
< 1 minute
Calculate on the cloud
In order to increase the flexibility, access and integrability, Calculators and Predictors have...
30 08 2022
< 1 minute
Key Properties in Drug Design | Predicting Lipophilicity, pKa and Solubility
PhysChem properties are key descriptors in drug design Lipophilicity, pKa and solubility are key...
13 07 2022
< 1 minute
Local and Global Models For Predicting Properties of Small Molecules
Which type of model has the most potential for success? The obvious answer is all models that are...
13 07 2022
< 1 minute
ICCS 2022 - Translating data to predictive models
Biological, chemical and physical properties of molecules are encoded in their molecular structure....