Optimizing Coordinated Combination Drug Therapy
优化协调联合药物治疗
基本信息
- 批准号:7667429
- 负责人:
- 金额:$ 58万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2006
- 资助国家:美国
- 起止时间:2006-07-01 至 2011-04-30
- 项目状态:已结题
- 来源:
- 关键词:AddressAdherenceAdolescentAminoglycosidesAnti-Retroviral AgentsAntiepileptic AgentsAntifungal TherapyBehaviorBlood PlateletsBusulfanCardiacCardiovascular DiseasesChemicalsChildChildhoodCitiesClinicalClinical InvestigatorClinical ResearchCollaborationsCollectionCombination Drug TherapyCombined AntibioticsCombined Modality TherapyComplexComputational ScienceComputer softwareCost SavingsDevelopmentDiabetes MellitusDigoxinDiseaseDistrict of ColumbiaDoctor of PharmacyDoctor of PhilosophyDoseDrug CombinationsDrug InteractionsDrug KineticsEffectivenessElderlyEnsureEpilepsyEquationEventFailureFeedbackFranceFundingGoalsHIVHeart failureHospitalsInstitutesLaboratoriesMalignant NeoplasmsMedicalMedical centerMedicineMethodsModelingMonitorMoscowMycobacterium InfectionsMycosesOutcomePatientsPediatric HospitalsPharmaceutical PreparationsPharmacodynamicsPharmacotherapyPhasePilot ProjectsPlasmaPlatelet TransfusionPopulationPopulation AnalysisResearchResearch InstituteResearch PersonnelResistanceRussiaSafetySerumSiteSolutionsSystemTechnologyTextTherapeuticToxic effectTransplantationTreatment ProtocolsUniversitiesViral Load resultWeightWorkantiretroviral therapycancer radioimmunotherapyclinical research sitecompliance behaviordesigndosagehospice environmentimprovedinnovationmathematical modelmedical schoolsnovelpharmacodynamic modelresearch clinical testingresponsesoftware developmenttherapeutic targettool
项目摘要
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、所给联合方案的共同治疗和毒性作用以及患者结果之间的高度可变关系。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已经开发了参数,特别是非参数(NP)人口建模软件,以捕捉这些关系的统计一致性和精度。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群体模型,并以最大的精度实现目标。我们还拥有NP软件,可以为多种药物联合治疗的更大,非线性和复杂的相互作用系统及其共同的联合治疗和毒性作用建立模型。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MM联合用药方案的剂量设计。初步结果非常令人鼓舞。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、需要联合抗生素和抗真菌治疗的患者,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个性化,但相互作用从未被考虑过,每种药物似乎都是可变的和反复无常的,因为其他药物的剂量变化及其影响未被考虑,并且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联合药物治疗的个体化和协调,基本上是最佳的贝叶斯MM反馈和剂量调整。随后的反馈应该倾向于更加证实,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、其他反应的效果,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,也是临床上最急需的。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,其他在场外。这项工作应大大提高我们的理解和控制的组合和相互作用的药物的关系,以及质量和精度的组合药物治疗的患者谁必须接受潜在的毒性药物。
项目成果
期刊论文数量(2)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Predictability of individualized dosage regimens of carbamazepine and valproate mono- and combination therapy.
卡马西平和丙戊酸盐单药和联合治疗个体化剂量方案的可预测性。
- DOI:10.1111/j.1365-2710.2010.01215.x
- 发表时间:2011
- 期刊:
- 影响因子:2
- 作者:Bondareva,IB;Jelliffe,RW;Andreeva,OV;Bondareva,KI
- 通讯作者:Bondareva,KI
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Roger W. Jelliffe其他文献
A Stochastic Control Program to Predict Outcome and to Support Therapeutic Decisions: A Preliminery Report
- DOI:
10.1007/s10877-005-5870-5 - 发表时间:
2005-06-01 - 期刊:
- 影响因子:2.200
- 作者:
William C. Shoemaker;David S. Bayard;Charles C. J. Wo;Andreas Botnen;Nasarolla Ahmedpour;Ashutosth Gandhi;Demetrios Demetriades;Roger W. Jelliffe - 通讯作者:
Roger W. Jelliffe
Computer Programs for Drug Therapy: A Tool for Teaching Pharmacokinetics
- DOI:
10.1016/s0002-9459(24)05083-6 - 发表时间:
1974-05-01 - 期刊:
- 影响因子:
- 作者:
Frank J. Goicoechea;Roger W. Jelliffe - 通讯作者:
Roger W. Jelliffe
Administration of Digoxin
- DOI:
10.1378/chest.56.1.56 - 发表时间:
1969-07-01 - 期刊:
- 影响因子:
- 作者:
Roger W. Jelliffe - 通讯作者:
Roger W. Jelliffe
Author’s reply to Veloso HH Comment on “The Role of Digitalis Pharmacokinetics in Converting Atrial Fibrillation and Flutter to Sinus Rhythm”
- DOI:
10.1007/s40262-016-0381-8 - 发表时间:
2016-03-21 - 期刊:
- 影响因子:4.000
- 作者:
Roger W. Jelliffe - 通讯作者:
Roger W. Jelliffe
Author’s Reply to Proost: “Challenges in Individualizing Drug Dosage for Intensive Care Unit Patients”
- DOI:
10.1007/s40262-016-0482-4 - 发表时间:
2016-12-29 - 期刊:
- 影响因子:4.000
- 作者:
Roger W. Jelliffe - 通讯作者:
Roger W. Jelliffe
Roger W. Jelliffe的其他文献
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{{ truncateString('Roger W. Jelliffe', 18)}}的其他基金
Population Pharmacokinetic Modeling and Optimal Control
群体药代动力学建模和最优控制
- 批准号:
6900308 - 财政年份:2003
- 资助金额:
$ 58万 - 项目类别:
Population Pharmacokinetic Modeling and Optimal Control
群体药代动力学建模和最优控制
- 批准号:
6756435 - 财政年份:2003
- 资助金额:
$ 58万 - 项目类别:
Populaton Pharmacokinetic Modeling and Optimal Control
群体药代动力学建模和最优控制
- 批准号:
7683166 - 财政年份:2003
- 资助金额:
$ 58万 - 项目类别:
Population Pharmacokinetic Modeling and Optimal Control
群体药代动力学建模和最优控制
- 批准号:
6687987 - 财政年份:2003
- 资助金额:
$ 58万 - 项目类别:
Populaton Pharmacokinetic Modeling and Optimal Control
群体药代动力学建模和最优控制
- 批准号:
7473264 - 财政年份:2003
- 资助金额:
$ 58万 - 项目类别:
Populaton Pharmacokinetic Modeling and Optimal Control
群体药代动力学建模和最优控制
- 批准号:
7317917 - 财政年份:2003
- 资助金额:
$ 58万 - 项目类别:
Population Pharmacokinetic Modeling and Optimal Control
群体药代动力学建模和最优控制
- 批准号:
7071649 - 财政年份:2003
- 资助金额:
$ 58万 - 项目类别:
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