FDA Scholar Program: Characterizing Leaching of Hazardous Material from Polymeric Biomaterials

植入的医疗设备中包含的潜在危险化学物质如果从设备迁移到周围组织，可能会对人类健康构成威胁。然而，如果一天中释放的化学物质数量很少，暴露在这种环境中可能几乎没有负面影响的风险。从历史上看，预测接触量的主要方法是通过实验室在化学液体中进行测试。然而，最近科学和计算机技术的进步支持了新的基于计算机的工具的发展，以预测暴露风险。在这项研究中，开发了数学方程和计算机模拟来预测潜在危险物质释放到人体内的速度。与以前的模拟相比，一个进步是将医疗设备和周围组织都包括在一个旨在更好地预测暴露风险的双组分模型中。预测模型可以降低开发成本，减少动物试验，使产品在不牺牲公共保护的情况下更快地上市。使用该模型进行初步风险评估将是行业的一项巨大资产，特别是那些可能缺乏资源在与监管机构接触之前预测结果的小公司。作为一个额外的组成部分，首席研究员将访问医疗器械公司，分享产品评估过程的知识，开发一门新课程，并为本科生提供资助的研究机会。本研究的目标是通过模拟可浸出材料在聚合物基质和接触的生物组织中的迁移，更准确地量化可浸出材料从医疗器械中释放的速度。研究包括通过聚合来自多个来源的数据来表征生物组织中可浸出物的传输特性，并使用聚类分析来近似生物组织中可浸出物的传输特性。利用这些传输特性的数学模型和计算机模拟将被创建，以使用扩散受限的双组分系统来预测可浸出物的迁移。此外，还将开发一种新的方法来建模生物材料系统，该方法将模型参数表示为概率密度函数，而不是单个标量值。这一新方法将推动该领域可用的建模工具。总体而言，这项研究将提高对聚合物生物材料中与人体接触的可浸出物命运的基本理解。与提取研究相比，更好地捕捉这个系统的复杂性的基于物理的模型将产生更多临床相关的结果，扩大我们对这些复杂的生物动力学系统的理解。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Potentially hazardous chemicals contained within implanted medical devices can pose a risk to human health if they migrate from the device into surrounding tissues. However, if the amount of chemicals released in one day is low, the exposure may have little to no risk of negative effects. Historically, the primary method to predict the amount of exposure has been through laboratory testing in chemical liquids. However, recent advances in science and computer technology support the development of new computer-based tools to predict exposure risk. In this research, mathematical equations and computer simulations are developed to predict how quickly potentially hazardous materials are released into the body. An advancement over previous simulations is the inclusion of both the medical device and the surrounding tissue in a two-component model designed to better predict exposure risk. Predictive models can reduce development cost, decrease animal testing, and enable products to reach the market faster without sacrificing public protection. Use of the model for preliminary risk assessment would be a great asset to industry, especially small companies that may lack the resources to predict outcomes prior to engagement with regulatory bodies. As an additional component, the principal investigator will visit medical device companies to share knowledge about the product evaluation process, develop a new course, and provide undergraduates with funded research opportunities.The goal of this research is to more accurately quantify the rate that leachable materials are released from a medical device by modeling their migration through a polymeric matrix and the contacting biological tissue. Research includes characterizing the transport properties of leachables in biological tissue by aggregating data from multiple sources and using cluster analysis to approximate transport properties of leachables in biological tissue. Mathematical models and computer simulations that utilize these transport properties will be created to predict migration of leachables using a diffusion-limited two-component system. In addition, a novel approach to model biomaterial systems will be developed that represent model parameters as probability density functions rather than single scalar values. This new approach will advance modeling tools available in this field. Overall, this research will improve the fundamental understanding of the fate of leachables contained within polymeric biomaterials in contact with the body. Physics-based models that better capture the complexities of this system will yield more clinically relevant results than extraction studies, expanding our understanding of these complex biodynamic systems.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.