BIOLOGICAL MONITORING OF CONTROLLED TOLUENE EXPOSURE: TOXICOKINETICS

群体药代动力学模型已被用作中心 暴露反应关系的部分描述， 抗感染剂。 我们已经建立了一种关系 患者个体暴露量相对于 将病原体感染至氟喹诺酮类抗生素左氧氟沙星， 患者具有成功临床或 微生物结果（患者情况良好/微生物 从原发感染部位根除）（1）。 这些关系 在22个不同的中心同时开发。 为了 为实现这一目标，提出了总体最优抽样策略 并建立了数据库。 血浆浓度-时间曲线 在272例患者中获得，其中134例有 有微生物记录的感染 群体药代动力学 建模后进行MAP-Bayesian估计， 模拟产生峰/MIC比的药效学变量， AUC/MIC比值和血浆浓度超过MIC的时间。 这些（在其他协变量中）在一项单独的分析中进行了检查， 一个逻辑回归分析，这样一个暴露的措施， 与结果的可能性有关。 虽然这表明， 许多相对复杂的技术可以与生产联系起来 药物暴露与前瞻性研究结果之间的关系 以（2-4）的方式，期望以类似的方式执行类似的分析。 完全集成的单步方式。 然而， 这些复杂的模型并在相对较大的数据库上运行它们 会使现有人口的效用 药代动力学建模程序超过临界点。 抗病毒 化疗提供了一个特别有吸引力的机会， 展示建模过程的力量。 的重要性 临床结果的干预是明确的（5，6）。 几乎没有 - 有指导这些药剂的剂量，以实现 期望的效果。 对于许多代理，代理标记是可用的 这已被证明与临床结果有关。 示例 包括用于HIV RNA PCR，以及最近用于丙型肝炎的RNA PCR 巨细胞病毒的DNA PCR（以及pp 65抗原测定） （7，8）. 这些测定中的每一种都提供药物的定量测量。 对病原体复制的影响。 这允许 使用人口提出和回答的重要问题 动力学/动力学建模作为核心工具。

Population pharmacokinetic modeling has been employed as a central part of the delineation of exposure response relationships for anti-infective agents. We have prospectively developed a relationship between the patient-individual exposure relative to the MIC of the infecting pathogen to the fluoroquinolone antibiotic levofloxacin and the probability of that patient having a successful clinical or microbiological outcome (the patient did well/the organism was eradicated from the primary infection site) (1). These relationships were developed in 22 separate centers simultaneously. In order to accomplish this, a population optimal sampling strategy was developed and the data base was developed. Plasma concentration-time profiles were obtained in 272 patients, of whom 134 had a microbiologically-documented infection. Population pharmacokinetic modeling was followed by MAP-Bayesian estimation and patient simulation produced the pharmacodynamic variables of Peak/MIC ratio, AUC/MIC ratio a nd the Time Plasma Concentrations Exceed the MIC. These (among other covariates) were examined in a separate analysis in a logistic regression analysis, so that a measure of exposure could be linked to the probability of outcome. While this demonstrates that a number of relatively sophisticated techniques can be linked to produce a relationship between drug exposure and outcome in a prospective fashion (2-4), it would be desirable to perform similar analyses in a fully integrated, single step manner. However, the ability to build such sophisticated models and run them on relatively large data bases would stretch the utility of the currently extant population pharmacokinetic modeling programs past the breaking point. Antiviral chemotherapy provides a particularly attractive opportunity to demonstrate the power of the modeling process. The importance of the intervention for clinical outcome is clear (5,6). Virtually no -guidance is available for dosing these agents in order to achieve the desired effect. For many agents, surrogate markers are available which have been demonstrably linked to clinical outcome. Examples include RNA PCR for HIV and, more recently, RNA PCR for Hepatitis C and DNA PCR (as well as a pp65 antigen assay) for Cytomegalovirus (7,8). Each of these assays provides quantitative measures of drug effect on the replication of the pathogen in question. This allows important questions to be asked and answered using population kinetic/dynamic modeling as the central tool.