Sigawi Tal, Israeli Adir, Ilan Yaron
Faculty of Medicine, Hebrew University and Department of Medicine, Hadassah Medical Center, Jerusalem, Israel.
Immunotargets Ther. 2024 Oct 14;13:525-539. doi: 10.2147/ITT.S477841. eCollection 2024.
Lack of response to immunotherapies poses a significant challenge in treating immune-mediated disorders and cancers. While the mechanisms associated with poor responsiveness are not well defined and change between and among subjects, the current methods for overcoming the loss of response are insufficient. The Constrained Disorder Principle (CDP) explains biological systems based on their inherent variability, bounded by dynamic boundaries that change in response to internal and external perturbations. Inter and intra-subject variability characterize the immune system, making it difficult to provide a single therapeutic regimen to all patients and even the same patients over time. The dynamicity of the immune variability is also a significant challenge for personalizing immunotherapies. The CDP-based second-generation artificial intelligence system is an outcome-based dynamic platform that incorporates personalized variability signatures into the therapeutic regimen and may provide methods for improving the response and overcoming the loss of response to treatments. The signatures of immune variability may also offer a method for identifying new biomarkers for early diagnosis, monitoring immune-related disorders, and evaluating the response to treatments.
对免疫疗法缺乏反应在治疗免疫介导的疾病和癌症方面构成了重大挑战。虽然与反应不佳相关的机制尚未明确界定，且在不同个体之间存在差异，但目前克服反应丧失的方法并不充分。约束紊乱原理（CDP）基于生物系统固有的变异性来解释生物系统，这种变异性受到动态边界的限制，这些边界会根据内部和外部扰动而变化。个体间和个体内的变异性是免疫系统的特征，这使得难以对所有患者甚至同一患者在不同时间提供单一的治疗方案。免疫变异性的动态性也是个性化免疫疗法的重大挑战。基于CDP的第二代人工智能系统是一个基于结果的动态平台，它将个性化的变异性特征纳入治疗方案，并可能提供改善反应和克服治疗反应丧失的方法。免疫变异性特征还可能提供一种方法，用于识别早期诊断的新生物标志物、监测免疫相关疾病以及评估治疗反应。
