Population Pharmacokinetic and Pharmacodynamic Models in the Presence of Outliers

描述（由申请人提供）：重症监护室（ICU）中的几乎每个危重患者都接受强效精神活性药物，如镇静剂和阿片类镇痛药，以缓解疼痛和不适。在危重病期间，老年患者通常与年轻患者接受相同的高剂量镇静剂和镇痛剂。几乎没有关于这些药物的剂量或浓度与临床结果之间关系的数据，以允许ICU团队适当地滴定治疗。我们已经证明，如果暴露不优化，镇静剂和镇痛剂会对谵妄和长期认知障碍（LTCI）的风险产生不利影响。老年患者特别容易受到镇静剂和止痛剂暴露的风险。我们正在进行的NIA申办的R 01（称为BRAIN-ICU研究）的未满足需求是通过开发最佳统计方法来研究这些药物在ICU患者中的复杂药代动力学（PK）和药效学（PD）关系，以确定最佳治疗。我们的初步工作表明，必须克服统计方面的挑战。首先，为了患者安全，只能抽取少量血液样本用于测量药物浓度。在这种稀疏采样的情况下，平均血浆浓度和血浆浓度曲线下面积不能提供药物暴露的良好测量。第二，我们需要避免PK参数的偏倚估计，这可能是由于在真实的复杂ICU环境中从被输注药物污染的静脉或管路中意外采血而导致的人为离群值。因此，我们将开发和使用一种新的、稳健的群体PK和PK/PD模型，该模型可以适应稀疏采样和人为离群值的存在，并允许我们检查镇静和镇痛药物暴露与药物暴露相关的不良结局（如谵妄和LTCI）之间的相关性。此外，它将确定改变动力学的患者特征和具有不同代谢速率的亚群，这将支持更大规模的药物遗传学研究。因此，这项工作将为干预提供基础，以优化强效药物的剂量，以减少急性和长期的脑功能障碍，并将产生深远的影响，最终导致镇静剂和镇痛剂的个性化治疗。 公共卫生相关性：在老年（和年轻）患者中，越来越多的证据表明，如果患者的暴露量未得到优化，镇静剂和镇痛剂（几乎普遍提供给重症监护室（ICU）中的重症患者的药物）是谵妄和长期认知障碍（LTCI）的主要风险因素。我们建议首次开发一种新的群体PK和PK/PD模型，该模型可以适应由于器官功能和遗传因素的变化而存在的患者个体间代谢差异，以及通过在NIA申办的大型观察性研究中获得的样本获得的药物水平的人为离群值。使用这种新方法，这项重要的研究将研究暴露于镇静和镇痛药物与药物暴露导致的结果之间的相关性，例如谵妄和LTCI的发展，这些疾病在危重病期间严重致残老年患者并阻止他们完全康复。

DESCRIPTION (provided by applicant): Virtually every critically ill patient in an intensive care unit (ICU) receives potent psychoactive medications such as sedatives and opiate analgesics to relieve pain and discomfort. During critical illness, older patients are often given the same high doses of these sedatives and analgesics that younger patients receive. There are virtually no data about the relationships between dose or concentration of these drugs and clinical outcomes to allow ICU teams to titrate therapy appropriately. We have documented that sedatives and analgesics contribute adversely to the risk of delirium and long-term cognitive impairment (LTCI) if exposure is not optimized. Older patients are particularly prone to the risks posed by sedative and analgesic exposure. A driving unmet need of our ongoing NIA-sponsored R01 called the BRAIN-ICU study is to investigate the complicated pharmacokinetic (PK) and pharmacodynamic (PD) relationships of these medications in ICU patients by developing the best statistical methods in order to define optimal therapy. Our preliminary work has shown us that there are statistical challenges that must be overcome. First, only a small number of blood samples can be drawn for measurement of drug concentrations for patient safety. With such sparse sampling, mean plasma concentration and area under the plasma concentration curve do not provide a good measure of drug exposure. Second, we need to avoid biased estimates of PK parameters that might result from artifactual outlying values due to inadvertent blood sampling from a vein or line contaminated with infused drug as occurs in the real life complex ICU setting. Thus, we will develop and use a novel and robust population PK and PK/PD model that can accommodate sparse sampling and the presence of artifactual outliers, and allow us to examine the associations between exposure to sedative and analgesic medications and adverse outcomes related to drug exposure such as delirium and LTCI. In addition, it will identify patient characteristics altering kinetics, and subpopulations with different rates of metabolism, which would support a larger scale of pharmacogenetic study. Therefore, this work will provide a basis for intervention to optimize doses of potent medications in order to reduce acute and long-term brain dysfunction and will have far reaching implications, ultimately leading to individualized therapy with sedatives and analgesics. PUBLIC HEALTH RELEVANCE: There is increasing evidence in older (and younger) patients that sedatives and analgesics, medications nearly universally provided to critically ill patients in Intensive Care Units (ICUs), are leading risk factors for delirium and long-term cognitive impairment (LTCI) if patients' exposure is not optimized. We propose to develop, for the first time, a novel population PK and PK/PD model that can accommodate both the presence of patients' inter-individual differences in metabolism due to variations in organ function and genetic factors and artifactual outliers in drug levels through samples obtained in a large NIA-sponsored observational study. Using the novel method, this important study will examine the associations between exposure to sedative and analgesic medications and outcomes due to drug exposure such as development of delirium and LTCI that are so profoundly disabling older patients during critical illness and preventing their complete recovery.