There is an increasing number of public and private sector initiatives aimed at the generation and evaluation of prospective models to assist decision-making processes and to generate future innovations for predicting ADME-Tox properties. Initiatives are also underway to permit public use and comparison of ML/DL models to increase confidence in and acceptance of these predictions. For example, Therapeutics Data commons (TDC) was introduced as a platform to systematically access and evaluate ML models across the entire range of therapeutics, accessible via an open python library . TDC encompasses AI-ready datasets and learning tasks for therapeutics; sets of tools to support data processing, model development, validation, and evaluation; and a collection of 'leaderboards' to support model comparison and benchmarking.