Optimizing Coordinated Combination Drug Therapy

描述(申请人提供)：最佳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、所给联合方案的共同治疗和毒性效果以及患者结果之间的高度可变的关系。联合治疗现在是许多临床环境中的标准。我们的跨学科实验室开发了参数，特别是非参数(NP)人口建模软件，以统计一致性和精确度捕捉这些关系。我们还开发了新的剂量设计的“多模型”(MM)方法，以最大精度(最小加权平方误差)达到预期的治疗目标，用于单个药物的模型，其微分方程式具有解析解。我们现在已经开始在试点合作项目中进行临床测试，以建立NP人口模型，并以最高精度实现目标目标。我们还拥有NP软件来建立更大、非线性和复杂的多种药物联合治疗相互作用系统的模型，以及它们共享的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。初步结果是最令人鼓舞的。我们将开发集成软件，以确保对艾滋病毒、癌症、移植、心力衰竭、结核病、癫痫、那些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，进行最精确的协调联合药物治疗。未能考虑联合用药意味着，虽然每种药物都可以单独使用，但从未考虑过相互作用，每种药物看起来都是可变和反复无常的，因为没有考虑其他药物的变化剂量及其影响，而且剂量调整总是在事件的背后。我们令人兴奋的新工具现在应该优化患者联合药物治疗的个性化和协调性，本质上是最优的贝叶斯MM反馈和剂量调整。随后的反馈应该更具验证性，剂量调整应该更少和更小。人们还可以监测效果，如Hb、WBC、血小板、病毒载量、CD-4、其他反应，然后进行剂量调整，以最准确地击中所有选定的治疗目标，包括可耐受的毒性程度(例如，Hb=10，WBC=1200，PLTS=100,000)。所有这些都是高度可行的，也是临床上最迫切需要的。目标3：这项工作将在几个合作的试点临床项目中进行研究和评估，一个在现场，其他在现场。这项工作将大大提高我们对联合和相互作用药物关系的理解和控制，以及必须接受潜在毒性药物的患者联合药物治疗的质量和精确度。

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.