Optimizing Immunosuppression Drug Dosing via Phenotypic Precision Medicine

项目总结 作者开发了一个计算平台来快速确定最佳药物和剂量组合 从无数可能性中脱颖而出。通过测试这项名为表型个性化医学(PPM)的技术 在代表不同疾病的各种实验系统中，他们发现 生物系统对药物的响应可以用一个低阶、光滑的多维曲面来描述。 这样做的主要结果是，可以在少量的测试中找到最佳的药物组合。这 投入产出关系总是基于实验数据，而不是建模，这将导致 在处理药物剂量需求的人类多样性方面的直接解决方案，以及其他临床问题。 他们将测试PPM可以开发并验证为临床使用的假设，方法是进行 前瞻性临床试验，比较这种方法的可行性和有效性与医生的护理标准 给药。该小组此前曾在体外使用基于PPM的优化方法寻找新的药物组合 癌症和感染的体内模型。 在最近的一项首次人类研究中，他们比较了4名服用PPM的患者和4名对照组(标准护理剂量)。 病人。他们使用PPM过程计算了他克莫司的剂量方案，结果显示 可变性的改善和提高疗效的趋势。对于此应用程序，它们的目标是在 临床试验表明，PPM比无辅助医生给药更有效。这将允许生成数据以 证明多中心验证性研究的合理性，并探索更广泛的临床结果以进行优化。

PROJECT SUMMARY The authors have developed a computational platform to rapidly identify optimal drug and dose combinations from the innumerable possibilities. By testing this technique termed Phenotypic Personalized Medicine (PPM) in a diverse number of experimental systems representing different diseases, they have found that the response of biological systems to drugs can be described by a low order, smooth multidimensional surface. The main consequence of this is that optimal drug combinations can be found in a small number of tests. This input–output relationship is always based on experimental data, not modeling, and it would lead to a straightforward solution for handling human diversity in drug dosing needs, among other clinical problems. They will test the hypothesis that PPM can be developed and validated for clinical use by conducting a prospective clinical trial to compare the feasibility and efficacy of this approach to standard of care physician dosing. This group has previously used PPM-based optimization to find novel drug combinations in in vitro and in vivo models of cancer and infection. In a first-in-human study, they recently compared 4 PPM-dosed patients and 4 control (standard of care dosed) patients. They calculated the tacrolimus dosing regimen using the PPM process and showed significant improvement in variability and a trend toward improved efficacy. For this application, they aim to show in a clinical trial, that PPM is more effective than unaided physician dosing. This will allow the generation of data to justify a multi-center confirmatory study and to explore a wider array of clinical outcomes to optimize.