Soldatos Theodoros G, Taglang Guillaume, Jackson David B
Molecular Health GmbH, Kurfuersten Anlage 21, 69115 Heidelberg, Germany.
High Throughput. 2018 Nov 23;7(4):37. doi: 10.3390/ht7040037.
We present a novel approach for the molecular transformation and analysis of patient clinical phenotypes. Building on the fact that drugs perturb the function of targets/genes, we integrated data from 8.2 million clinical reports detailing drug-induced side effects with the molecular world of drug-target information. Using this dataset, we extracted 1.8 million associations of clinical phenotypes to 770 human drug-targets. This collection is perhaps the largest phenotypic profiling reference of human targets to-date, and unique in that it enables rapid development of testable molecular hypotheses directly from human-specific information. We also present validation results demonstrating analytical utilities of the approach, including drug safety prediction, and the design of novel combination therapies. Challenging the long-standing notion that molecular perturbation studies cannot be performed in humans, our data allows researchers to capitalize on the vast tomes of clinical information available throughout the healthcare system.
我们提出了一种用于患者临床表型分子转化和分析的新方法。基于药物会干扰靶点/基因功能这一事实，我们将来自820万份详细描述药物副作用的临床报告的数据与药物靶点信息的分子世界进行了整合。利用该数据集，我们提取了180万个临床表型与770个人类药物靶点之间的关联。该集合可能是迄今为止最大的人类靶点表型分析参考，其独特之处在于它能够直接从人类特异性信息中快速开发可测试的分子假说。我们还展示了验证结果，证明了该方法的分析效用，包括药物安全性预测和新型联合疗法的设计。我们的数据挑战了长期以来认为无法在人类中进行分子扰动研究的观念，使研究人员能够利用整个医疗系统中大量可用的临床信息。
