The pursuit of accurate predictive models of the bioactivity of small molecules.

Property prediction is a key interest in chemistry. For several decades there has been a continued and incremental development of mathematical models to predict properties. As more data is generated and accumulated, there seems to be more areas of opportunity to develop models with increased accuracy.

School of cheminformatics in Latin America.

We report the major highlights of the School of Cheminformatics in Latin America, Mexico City, November 24-25, 2022. Six lectures, one workshop, and one roundtable with four editors were presented during an online public event with speakers from academia, big pharma, and public research institutions. One thousand one hundred eighty-one students and academics from seventy-nine countries registered for the meeting.

The OECD Principles for (Q)SAR Models in the Context of Knowledge Discovery in Databases (KDD).

The steps followed in the knowledge discovery in databases (KDD) process are well documented and are widely used in different areas where exploration of data is used for decision making. In turn, while different workflows for developing quantitative structure-activity relationship (QSAR) models have been proposed, including combinatorial use of QSAR, there is now agreement on common requirements for building trustable predictive models. In this work, we analyze and confront the steps involved in KDD and QSAR and present how they comply with the OECD principles for the validation, for regulatory purposes, of QSAR models.