Abstract
Drug-repurposing technologies are growing in number and maturing. However, comparisons to each other and to reality are hindered because of a lack of consensus with respect to performance evaluation. Such comparability is necessary to determine scientific merit and to ensure that only meaningful predictions from repurposing technologies carry through to further validation and eventual patient use. Here, we review and compare performance evaluation measures for these technologies using version 2 of our shotgun repurposing Computational Analysis of Novel Drug Opportunities (CANDO) platform to illustrate their benefits, drawbacks, and limitations. Understanding and using different performance evaluation metrics ensures robust cross-platform comparability, enabling us to continue to strive toward optimal repurposing by decreasing the time and cost of drug discovery and development.
【저자키워드】 Drug repurposing, drug repositioning, Computational drug repurposing, validation, Performance evaluation, area under the curve, Computational drug repositioning, Biomedical Informatics, Performance metrics, Normalized discounted cumulative gain, 【초록키워드】 Drug discovery, drug, comparison, Patient, understanding, novel, platform, comparability, Consensus, measure, evaluation metrics, opportunity, limitations, robust, lack, determine, 【제목키워드】 Evaluating,