Optimizing Coordinated Combination Drug Therapy

优化协调联合药物治疗

• 批准号: 7248652
• 负责人: Roger W. Jelliffe
• 金额: $ 53.9万
• 依托单位: UNIVERSITY OF SOUTHERN CALIFORNIA
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-07-01 至 2010-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7248652
• 关键词: Address; Adherence; Adolescent; Aminoglycosides; Anti-Retroviral Agents; Antiepileptic Agents; Antifungal Antibiotics; Antifungal Therapy; Appendix; Behavior; Blood Platelets; Busulfan; Cardiac; Cardiovascular Diseases; Chemicals; Child; Childhood; Cities; Clinical; Clinical Investigator; Clinical Research; Collaborations; Collection; Combination Drug Therapy; Combined Antibiotics; Combined Modality Therapy; Complex; Computational Science; Computer software; Cost Savings; Development; Diabetes Mellitus; Digoxin; Disease; District of Columbia; Doctor of Pharmacy; Doctor of Philosophy; Dose; Drug Combinations; Drug Interactions; Drug Kinetics; Effectiveness; Elderly; Ensure; Epilepsy; Equation; Event; Failure; Feedback; France; Funding; Goals; HIV; Heart failure; Hospice Care; Hospitals; Institutes; Laboratories; Malignant Neoplasms; Medical; Medical center; Medicine; Methods; Modeling; Monitor; Moscow; Mycobacterium Infections; Mycoses; Outcome; Patients; Pediatric Hospitals; Pharmaceutical Preparations; Pharmacodynamics; Pharmacotherapy; Phase; Pilot Projects; Plasma; Platelet Transfusion; Population; Population Analysis; Research; Research Institute; Research Personnel; Resistance; Russia; Safety; Serum; Site; Solutions; System; Technology; Text; Therapeutic; Toxic effect; Transplantation; Treatment Protocols; Universities; Viral Load result; Weight; Work; antiretroviral therapy; cancer radioimmunotherapy; clinical research site; compliance behavior; design; desire; dosage; hospice environment; improved; innovation; mathematical model; medical schools; novel; pharmacodynamic model; research clinical testing; response; software development; therapeutic target; tool

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.

描述（由申请人提供）：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的剂量、患者依从性、血清浓度、药物-药物相互作用、联合治疗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。联合治疗现已成为许多临床环境中的常态。我们的跨学科实验室开发了参数尤其是非参数 (NP) 群体建模软件，以统计一致性和精确度捕获这些关系。我们还开发了新的剂量设计“多模型”（MM）方法，以最大精度（最小加权平方误差）达到所需的治疗目标，对于具有微分方程解析解的单一药物模型。我们现在已经开始试点合作项目的临床测试，制作 NP 群体模型，并以最高精度实现目标。我们还拥有 NP 软件，用于建立多种药物联合治疗的更大、非线性和复杂相互作用系统的模型，以及它们共同的联合治疗和毒性作用。目标 1：我们将在新的 Windows 界面中实现上述所有内容。目标 2：我们正在为联合用药方案开发 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，以确保为艾滋病毒、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，甚至糖尿病的患者提供最精确的协调联合药物治疗。未能考虑组合药物意味着虽然每种药物可以个体化，但从不考虑相互作用，每种药物都显得可变且反复无常，因为没有考虑其他药物的剂量变化及其作用，并且剂量调整总是在事件背后。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体化和协调，并具有最佳的贝叶斯 MM 反馈和剂量调整。随后的反馈应该更具有证实性，并且剂量调整应该更少、更小。人们还可以监测 Hb、WBC、血小板、病毒载量、CD-4 和其他反应等效应，然后调整剂量以最精确地达到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）。这一切都是高度可行的，也是临床上最迫切需要的。目标 3：这项工作将在几个合作试点临床项目中进行研究和评估，其中一个在现场，其他在场外。这项工作将极大地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联合用药治疗的质量和精确度。