Optimizing Coordinated Combination Drug Therapy

描述（由申请人提供）：优化协调联合药物治疗的一个主要问题是无法量化和最小化各种药物剂量、患者依从性、血清浓度、药物-药物相互作用、给予联合方案的共同治疗和毒性作用以及患者结果之间高度可变的关系。联合治疗现在是许多临床环境的标准。我们的跨学科实验室开发了参数化，特别是非参数化（NP）人口建模软件，以统计一致性和准确性捕获这些关系。我们还开发了新的“多模型”（MM）剂量设计方法，以最大精度（最小加权平方误差）达到所需的治疗目标，用于具有微分方程解析解的单一药物模型。我们现在已经开始在试点合作项目中进行临床测试，以制作NP种群模型，并以最大的精度实现目标。我们也有NP软件来制作更大，非线性和复杂的相互作用系统的模型，与多种药物联合治疗，以及它们的共同联合治疗和毒性作用。目标1：我们将在一个新的Windows界面中实现上述所有功能。目的2：我们正在开发联合用药方案的MM剂量设计。初步结果非常令人鼓舞。我们将开发集成软件，以最大限度地确保艾滋病、癌症、移植、心力衰竭、结核病、癫痫、需要抗生素和抗真菌联合治疗的患者，甚至可能是糖尿病患者的精确协调联合药物治疗。如果不考虑联合用药，就意味着虽然每种药物都可以个体化，但它们之间的相互作用从来没有被考虑过，每种药物看起来都是可变的和反复无常的，因为其他药物的剂量变化及其作用都没有被考虑到，剂量调整总是落后于事件。我们令人兴奋的新工具现在应该优化患者的个体化和联合药物治疗的协调，本质上是最优的贝叶斯MM反馈和剂量调整。随后的反馈应该更加确认，剂量调整应该更少、更小。还可以监测诸如Hb、WBC、血小板、病毒载量、CD-4等效应，然后调整剂量以最精确地击中所有选定的治疗靶点，包括可耐受的毒性程度（例如Hb=10， WBC=1200, plts=100,000）。这些都是非常可行的，也是临床迫切需要的。目标3：这项工作将在几个合作试点临床项目中进行研究和评估，一个在现场，另一个在场外。这项工作将大大提高我们对联合用药和相互作用药物关系的理解和控制，以及对必须接受潜在毒性药物的患者进行联合用药治疗的质量和准确性。

DESCRIPTION (provided by applicant): A major problem in optimally coordinating combination drug therapy is the inability to quantify and minimize the highly variable relationships between dosage of the various drugs, patient adherence, serum concentrations, drug - drug interactions, shared therapeutic and toxic effects of the combination regimens given, and patient outcomes. Combination therapy is now the norm in many clinical settings. Our cross-disciplinary laboratory has developed parametric and especially nonparametric (NP) population modeling software to capture these relationships with statistical consistency and precision. We have also developed the new "multiple model" (MM) method of dosage design to hit desired therapeutic target goals with maximum precision (minimum weighted squared error), for models of single drugs having analytic solutions to their differential equations. We have now begun clinical testing in pilot collaborative projects, to make NP population models, and to achieve target goals with maximum precision. We also have NP software to make models of the larger, nonlinear and complex interacting systems of combination therapy with multiple drugs, and their shared combination therapeutic and toxic effects. Aim 1: We will implement all the above in a new Windows interface. Aim 2: We are developing MM dosage design for the combination drug regimens. Preliminary results are most encouraging. We will develop integrated software to ensure maximally precise coordinated combination drug therapy for patients with HIV, cancer, transplants, heart failure, TB, epilepsy, those requiring combination antibiotic and antifungal therapy, and even, perhaps, diabetes mellitus. Failure to consider drugs in combination means that while each drug can be individualized, the interactions are never considered, each drug appears variable and capricious, as the changing doses of the other drugs, and their effects, are not considered, and dosage adjustment is always behind the events. Our exciting new tool should now optimize the individualization and coordination of combination drug therapy for patients, with essentially optimal Bayesian MM feedback and dosage adjustment. Subsequent feedback should tend to be more confirmatory, and dosage adjustments should be fewer and smaller. One can also monitor effects such as Hb, WBC, platelets, viral load, CD-4, other responses, and then make adjustments of dosage to hit all selected therapeutic targets most precisely, including tolerable degrees of toxicity (Hb=10, WBC=1200, plts=100,000 for example). All this is highly feasible and most urgently needed clinically. Aim 3: This work will be studied and evaluated in several collaborating pilot clinical projects, one on- site, others off-site. This work should greatly improve our understanding and control of combination and interacting drug relationships, and the quality and precision of combination drug therapy for patients who must receive potentially toxic drugs.