Robin Michelet, Klas Petersson, Marc C Huisman, C Willemien Menke-van der Houven van Oordt, Iris H C Miedema, Andrea Thiele, Ghazal Montaseri, Alejandro Pérez-Pitarch, David Busse
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Here, we present the development and application of a minimal physiologically-based pharmacokinetic (mPBPK) modeling approach to integrate biodistribution data in a quantitative platform to characterize and predict intratumor exposure and receptor occupancy (RO) of BI 754111, an IgG-based anti-lymphocyte-activation gene 3 (LAG-3) monoclonal antibody (mAb). Specifically, calibration and qualification of the predictions were performed using <sup>89</sup>Zr-labeled BI 754111 biodistribution data, that is, PET-derived intratumor drug concentration data, tumor-to-plasma ratios, and data from Patlak analyses. The model predictions were refined iteratively by the inclusion of additional biological processes into the model structure and the use of sensitivity analyses to assess the impact of model assumptions and parameter uncertainty on the predictions and model robustness. The developed mPBPK model allowed an adequate description of observed tumor radioactivity concentrations and tumor-to-plasma ratios leading to subsequent adequate prediction of LAG-3 RO at different dose levels. 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引用次数: 0
摘要
在肿瘤药物开发中,测量肿瘤部位和靶向受体的药物浓度仍然是一个持续的挑战。正电子发射断层扫描(PET)成像是一种很有前途的无创方法,可以量化肿瘤内放射性标记药物的暴露(生物分布数据)和体内治疗剂量的靶标饱和度。在这里,我们提出了一种基于最小生理的药代动力学(mPBPK)建模方法的开发和应用,将生物分布数据整合到定量平台中,以表征和预测BI 754111的肿瘤内暴露和受体占用(RO), BI 754111是一种基于igg的抗淋巴细胞活化基因3 (LAG-3)单克隆抗体(mAb)。具体来说,使用89zr标记的BI 754111生物分布数据(即pet衍生的肿瘤内药物浓度数据、肿瘤与血浆比率和Patlak分析数据)进行预测的校准和鉴定。通过在模型结构中加入额外的生物过程,并使用敏感性分析来评估模型假设和参数不确定性对预测和模型鲁棒性的影响,迭代地改进了模型预测。开发的mPBPK模型能够充分描述观察到的肿瘤放射性浓度和肿瘤与血浆的比率,从而在不同剂量水平下对LAG-3 RO进行充分的预测。在未来,开发的模型可以作为预测和分析其他单克隆抗体生物分布数据的平台,并可能最终通过确定导致饱和RO的剂量来支持剂量优化。
A minimal physiologically-based pharmacokinetic modeling platform to predict intratumor exposure and receptor occupancy of an anti-LAG-3 monoclonal antibody.
In oncology drug development, measuring drug concentrations at the tumor site and at the targeted receptor remains an ongoing challenge. Positron emission tomography (PET)-imaging is a promising noninvasive method to quantify intratumor exposure of a radiolabeled drug (biodistribution data) and target saturation by treatment doses in vivo. Here, we present the development and application of a minimal physiologically-based pharmacokinetic (mPBPK) modeling approach to integrate biodistribution data in a quantitative platform to characterize and predict intratumor exposure and receptor occupancy (RO) of BI 754111, an IgG-based anti-lymphocyte-activation gene 3 (LAG-3) monoclonal antibody (mAb). Specifically, calibration and qualification of the predictions were performed using 89Zr-labeled BI 754111 biodistribution data, that is, PET-derived intratumor drug concentration data, tumor-to-plasma ratios, and data from Patlak analyses. The model predictions were refined iteratively by the inclusion of additional biological processes into the model structure and the use of sensitivity analyses to assess the impact of model assumptions and parameter uncertainty on the predictions and model robustness. The developed mPBPK model allowed an adequate description of observed tumor radioactivity concentrations and tumor-to-plasma ratios leading to subsequent adequate prediction of LAG-3 RO at different dose levels. In the future, the developed model could be used as a platform for the prediction and analysis of biodistribution data for other mAbs and may ultimately support dose optimization by identifying dosages resulting in saturated RO.