PBTK modeling and simulation framework to identify critical data requirements for efficient and effective pediatric risk assessment

环境污染物暴露是一个日益严重的问题，评估与这种暴露有关的人类风险仍然是一门不精确的科学。风险主要基于动物接触和影响对人类的外推。外推法通常采用简单的形式，其中将动物研究得出的阈值剂量除以调整因子（AF），以说明毒代动力学（TK）和毒理学的种间和人群变异性。一个有前途的方法来完善默认AF是基于生理毒代动力学（PBTK）模型。这些数学模型有助于理解化合物暴露或摄入剂量如何转化为全身（血浆）和靶器官（器官）暴露，并基于生物体生理学、化合物物理化学和生物化学过程之间的相互作用。 由于不成熟，儿童是污染物暴露的潜在易感人群，他们可能会或可能不会使用默认AF充分覆盖。然而，预测性儿科PBTK建模存在相当大的数据负担，这可能导致在没有进一步研究的情况下无法使用该方法进行AF细化。尚未努力定义哪些化合物特定数据要求对于准确的儿科剂量测定估计至关重要。该项目的目标是开发一个PBTK建模和模拟框架，以确定高效和有效的儿科风险评估的关键数据要求。该框架的目标是尽量减少数据负担，同时最大限度地提高对结果的信心。 该计划将侧重于开发或进一步扩展机械吸入和口服吸收模型，以适应生命阶段。此外，将开发使用各种假设化合物的儿科PBTK模型，并在当地和全球敏感性分析方法的帮助下，提供一种检查关键数据输入的方法，这些关键数据输入依赖于生成准确的儿科暴露量。此外，风险评估期间用于模型开发的真实的数据将位于文献中或通过实验获得。完整和精简的数据集将用于模型开发，这将有助于确认对先前强调的特定情景至关重要的数据，并评估在不太重要的数据不可用时对预测准确性的影响。 该框架将允许行业针对新发现的污染物进行实验，仅针对那些对实现可接受的儿科暴露预测至关重要的数据要求。 可接受的预测将降低设定限制的可能性，过高的限制将使儿科健康处于危险之中，过低的限制则是过度保护，并对风险管理人员提出挑战。

Environmental contaminant exposure is an escalating concern and assessing the human risks associated with such exposure continues to be an inexact science. Risks are largely based upon the extrapolation of exposure and effect in animals to those in humans. Extrapolation customarily takes a simplistic form, wherein a threshold dose derived from animal studies is divided by adjustment factors (AFs) to account for interspecies and human population variability in toxicokinetics (TK) and toxicodynamics. One promising method to refine default AFs is based on physiologically based toxicokinetic (PBTK) models. These mathematical models facilitate the understanding of how exposure to a compound, or ingested dose, translates into systemic (plasma) and target (organ) exposure and are based on the interplay between organism physiology, compound physicochemistry and biochemical processes. Due to immaturity, children represent a potentially susceptible population to contaminant exposure and they may, or may not, be adequately covered using default AFs. There is however a considerable data burden for predictive pediatric PBTK modeling that may lead to an inability to use this method for AF refinement without further research. There have been no efforts to define what compound-specific data requirements are critical for accurate pediatric dosimetry estimation. The objective of this program is to develop a PBTK modeling and simulation framework to identify critical data requirements for efficient and effective pediatric risk assessment. The framework would aim to minimize data burden while maximizing confidence in outcomes. The program will focus on developing or further extending mechanistic inhalation and oral absorption models to be life-stage appropriate. Further, pediatric PBTK models using a wide range of hypothetical compounds will be developed and, with the aid of local and global sensitivity analysis methods, offer a means to examine those critical data inputs that are relied upon to generate accurate pediatric exposures. Further, real data that would be used for model development during a risk assessment will be located in literature or experimentally derived. Complete and reduced datasets will be used for model development and this will provide for both a confirmation of those data pieces that are critical for a particular scenario as highlighted previously and an assessment of the impact on prediction accuracy when less critical data pieces are unavailable. The framework will allow industry to target experimentation for newly identified contaminants to only those data requirements that will be important for achieving acceptable pediatric exposure prediction. Acceptable predictions will reduce the probability of setting limits that are either too high, which will put pediatric health at risk, or too low, which is overprotective and presents challenges to risk managers.