OncoDrug+ data 2.0

Combinations of cancer drugs have the potential to overcome resistance, improve the response rate of existing drugs and reduce dose-limiting toxicity associated with single agents. Existing drug combination databases only provide response data, such as synergy scores between two drugs, without important contextual information to assist oncologists in matching their patients with these combinations in an evidence-based way. To address this gap, we constructed an unique dataset by manually collecting and integrating drug combinations and corresponding evidences from FDA databases, clinical guidelines, clinical trials, clinical case reports, patient-derived tumor xenograft models, cell line models and bioinformatics predictions.Records classified into Level A were derived from professional clinical guidelines or included in the FDA database.Records classified into Level B were collected from clinical trials and individual case reports in electronic medical records.Records classified into Level C were obtained from in vivo or in vitro experiments, including PDX mouse models, cell line models and high-throughput drug screening experiments.Records classified into Level D dataset were derived from drug combination predictions based on bioinformatic algorithms.Our manuscript about this dataset has been submitted.