Ongoing work focuses on utilizing the AI/ML-ready data such as target-disease, target-phenotype and PPI data to develop AI/ML models for prioritization of dark targets and better understanding of disease biology. Currently, we are evaluating ways to aggregate experimental data uncertainties, specifically data quality and reliability (48), similar to the in silico toxicology protocols (49). We continue to extend our efforts in enhancing the disease page to list associated targets, rank them by the consensus strength of association to a disease and further facilitate filtering to narrow down to targets of potential interest to researchers. The database can be expected to be further enriched with new data and data types that contribute to the ultimate goal of illuminating the dark targets.
