Not all therapeutics are created equal in regards to individual patients. The problem of identifying which compound will work best with which patient is a significant burden across all disease contexts. In the context of autoimmune diseases such as alopecia areata, several formulations of JAK/STAT inhibitors have demonstrated efficacy in clinical trials. All of these compounds demonstrate different rates of response, and here we observed that this coincided with different molecular effects on patients undergoing treatment. Using these data, we have developed a computational model that is capable of predicting which patient-drug pairs have the highest likelihood of response. We achieved this by integrating inferred mechanism of action data and gene regulatory networks derived from an independent patient cohort with baseline patient data prior to beginning treatment.

并非所有疗法都对个体患者而言是平等的。确定哪种化合物最适合哪种患者的问题是所有疾病背景下的重大负担。在自身免疫性疾病（如斑秃）的背景下，JAK/STAT 抑制剂的几种制剂已在临床试验中证明有效。所有这些化合物都表现出不同的反应率，在这里我们观察到这与对接受治疗的患者的不同分子效应相吻合。使用这些数据，我们开发了一种计算模型，能够预测哪些患者-药物对具有最高的反应可能性。