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建立用于预测犬阿霉素暴露量的有限采样模型。

Development of a limited-sampling model for prediction of doxorubicin exposure in dogs.

作者信息

Wittenburg L A, Thamm D H, Gustafson D L

机构信息

Department of Clinical Sciences, Colorado State University Animal Cancer Center, Fort Collins, CO, USA.

出版信息

Vet Comp Oncol. 2014 Jun;12(2):114-9. doi: 10.1111/j.1476-5829.2012.00340.x. Epub 2012 Jul 3.

Abstract

Understanding the relationship between drug dose and exposure (pharmacokinetics, PK) and the relationship between exposure and effect (pharmacodynamics) is an important component of pharmacology when attempting to predict clinical effects of anticancer drugs. PK studies can provide a better understanding of these relationships; however, they often involve intensive sampling over an extended period of time, resulting in increased cost and decreased compliance. Doxorubicin (DOX), one of the most widely used antineoplastic agents in veterinary cancer therapy, is characterized by large interpatient variability in overall drug exposure and the development and degree of myelosuppression following equivalent dosages. We have developed and validated a limited-sampling strategy for DOX, in which three blood samples are obtained over 1 h post-treatment, that accurately predicts patient exposure. This strategy could allow for refining of dosing variables and utilization of therapeutic drug monitoring to ensure optimized dosing.

摘要

在试图预测抗癌药物的临床效果时,了解药物剂量与暴露(药代动力学,PK)之间的关系以及暴露与效应(药效动力学)之间的关系是药理学的一个重要组成部分。药代动力学研究可以更好地理解这些关系;然而,它们通常需要在较长时间内进行密集采样,从而导致成本增加和依从性降低。阿霉素(DOX)是兽医癌症治疗中使用最广泛的抗肿瘤药物之一,其特点是患者之间总体药物暴露以及等效剂量后骨髓抑制的发生和程度存在很大差异。我们已经开发并验证了一种针对DOX的有限采样策略,即在治疗后1小时内采集三份血样,该策略能够准确预测患者的暴露情况。这种策略可以优化给药变量并利用治疗药物监测来确保给药最优化。

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