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Targeted Drug Delivery by Gemtuzumab Ozogamicin: Mechanism-Based Mathematical Model for Treatment Strategy Improvement and Therapy Individualization

机译:Gemtuzumab Ozogamicin靶向药物递送:改善治疗策略和个体化治疗的基于机制的数学模型

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摘要

Gemtuzumab ozogamicin (GO) is a chemotherapy-conjugated anti-CD33 monoclonal antibody effective in some patients with acute myeloid leukemia (AML). The optimal treatment schedule and optimal timing of GO administration relative to other agents remains unknown. Conventional pharmacokinetic analysis has been of limited insight for the schedule optimization. We developed a mechanism-based mathematical model and employed it to analyze the time-course of free and GO-bound CD33 molecules on the lekemic blasts in individual AML patients treated with GO. We calculated expected intravascular drug exposure (I-AUC) as a surrogate marker for the response to the drug. A high CD33 production rate and low drug efflux were the most important determinants of high I-AUC, characterizing patients with favorable pharmacokinetic profile and, hence, improved response. I-AUC was insensitive to other studied parameters within biologically relevant ranges, including internalization rate and dissociation constant. Our computations suggested that even moderate blast burden reduction prior to drug administration enables lowering of GO doses without significantly compromising intracellular drug exposure. These findings indicate that GO may optimally be used after cyto-reductive chemotherapy, rather than before, or concomitantly with it, and that GO efficacy can be maintained by dose reduction to 6 mg/m2 and a dosing interval of 7 days. Model predictions are validated by comparison with the results of EORTC-GIMEMA AML19 clinical trial, where two different GO schedules were administered. We suggest that incorporation of our results in clinical practice can serve identification of the subpopulation of elderly patients who can benefit most of the GO treatment and enable return of the currently suspended drug to clinic.
机译:Gemtuzumab ozogamicin(GO)是一种化学疗法偶联的抗CD33单克隆抗体,对某些急性髓细胞白血病(AML)患者有效。相对于其他药物而言,GO治疗的最佳治疗方案和最佳时机仍然未知。常规药代动力学分析对时间表优化的了解有限。我们建立了一个基于机制的数学模型,并用它来分析接受GO治疗的单个AML患者的白血病细胞上游离和GO结合的CD33分子的时程。我们计算了预期的血管内药物暴露(I-AUC)作为对药物反应的替代指标。高CD33产生率和低药物流出是高I-AUC的最重要决定因素,其特征是患者的药代动力学特征良好,因此改善了反应。 I-AUC对生物学相关范围内的其他研究参数不敏感,包括内在化速率和解离常数。我们的计算表明,即使在给药前适度降低冲击负荷,也可以降低GO剂量,而不会显着损害细胞内药物的暴露。这些发现表明,GO可以在减细胞化疗后最佳使用,而不是之前或与其同时使用,并且可以通过降低剂量至6 mg / m2和7天的给药间隔来维持GO疗效。通过与EORTC-GIMEMA AML19临床试验的结果进行比较,验证了模型预测,在该试验中,两个不同的GO计划被管理。我们建议将我们的研究结果纳入临床实践中可用于鉴定老年人患者的亚群,这些患者可从大多数GO治疗中受益,并使当前停药的药物返回临床。

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