GOLDILOKs: Project 2: Translational

将在以下方面使用的反应-暴露-剂量范例和“暴露递增”给药策略： GOLDILOKs项目1（临床）高度依赖于个体化给药的能力， 在儿童个人层面上的期望曝光。控制剂量-暴露关系 需要适当的药代动力学（PK）模型，该模型考虑了导致 观察到的暴露变化。基于生理学的药代动力学（PBPK）模型是 对儿科的兴趣相当大，因为他们有可能在一个特定的时间内考虑多种因素。 系统级。这些变化包括组织体积和成分的发育变化，器官血液 流动，胃酸，肠道通过时间，蛋白质结合，以及生长过程中发生的其他因素， 发展在构建和应用PBPK模型时， 与可能基于有限数据的参数估计和隐含假设相关-以及 需要考虑“变异性”-个体发育、遗传变异和环境因素。在这 翻译项目，我们将解决与建立个性化基因组相关的几个挑战， 个体发育PK（iGO-PK）模型，以告知个体患者在 GOLDILOKs倡议。AIM 1应用短读和长读下一代测序技术 在CYP 2D 6基因座内完善表型预测并解析长范围单倍型 具有远端（112 kb）调节性单核苷酸多态性（SNP）和CYP 2D 6编码区。 通过测定每克肝脏微粒体蛋白的含量和表征个体发育 （MPPGL），目标2将降低体外关键比例因子的不确定性 形成PBPK模型基础的体内外推。在目标2中，我们还建议使用Simcyp PBPK框架和我们的儿科肝脏库创建了一组iGO-PK“虚拟个体”，每个 利用他们自己独特的基因型数据，定量（蛋白质组学）丰度值>50种药物 代谢酶和转运蛋白以及相应的MPPGL比例因子。我们预计 根据基因型数据优化CYP 2D 6表型预测，并改进PBPK模型， 改进了儿童剂量个体化的给药算法。

The responseexposuredose paradigm and “exposure escalation” dosing strategy to be utilized in GOLDILOKs Project 1 (Clinical) is highly dependent on the ability to individualize dosing and achieve the desired exposure at the level of the individual child. Controlling the doseexposure relationship requires appropriate pharmacokinetic (PK) models that take into consideration factors contributing to the observed variability in exposure. Physiologically based pharmacokinetic (PBPK) models are of considerable interest in pediatrics due to their potential to take multiple factors into consideration at a systems level. These include developmental changes in tissue volumes and composition, organ blood flow, gastric acidity, intestinal transit time, protein binding, among others that occur during growth and development. In building and applying PBPK models, both “uncertainty” – potential vulnerabilities related to parameter estimates and implicit assumptions that may be based on limited data – and “variability” -- ontogeny, genetic variation and environmental factors – need to be considered. In this translational project, we will address several challenges relevant to building individualized Genome- Ontogeny PK (iGO-PK) models to inform optimal ATX dosing for an individual patient within the GOLDILOKs initiative. Aim 1 applies short read and long read next generation sequencing technology to refine phenotype predictions within the CYP2D6 gene locus and to resolve long range haplotypes with a distal (112kb) regulatory single nucleotide polymorphism (SNP) and the CYP2D6 coding region. By determining the content and characterizing the ontogeny of microsomal protein per gram liver (MPPGL) in pediatric liver tissue, Aim 2 will reduce uncertainty in a critical scaling factor for in vitro-in vivo extrapolations that form the basis of PBPK models. In Aim 2 we also propose to use the Simcyp PBPK framework and our pediatric liver bank to create a group of iGO-PK “virtual individuals”, each with their own unique genotype data, quantitative (proteomic) abundance values for >50 drug metabolizing enzymes and transporters and corresponding MPPGL scaling factor. We anticipate that optimized CYP2D6 phenotype prediction from genotype data and improved PBPK models will result in improved dosing algorithms for dose individualization in children.