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

FDA 学者计划：表征聚合生物材料中有害物质的浸出

• 批准号: 2149517
• 负责人: Martin Tanaka
• 金额: $ 9.98万
• 依托单位: Western Carolina University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-01 至 2023-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2149517&HistoricalAwards=false
• 关键词: FDA; Scholar; Program; Characterizing; Leaching; FDA; Scholar; Program; Characterizing; Leaching

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.

如果植入的医疗设备中包含的潜在危险化学物质，如果将其从设备迁移到周围的组织中，则可能对人类健康构成风险。但是，如果一天内释放的化学物质量很低，则暴露可能几乎没有受到负面影响的风险。从历史上看，预测暴露量的主要方法是通过化学液体中的实验室测试。但是，科学和计算机技术的最新进展支持开发新的基于计算机的工具来预测风险。在这项研究中，开发了数学方程式和计算机模拟，以预测潜在的危险材料被释放到体内的速度。对先前模拟的进步是将医疗设备和周围组织都包含在两个组成模型中，旨在更好地预测暴露风险。预测模型可以降低开发成本，降低动物测试，并使产品能够在不牺牲公共保护的情况下更快地到达市场。将模型用于初步风险评估将是行业的重要资产，尤其是在与监管机构互动之前可能缺乏资源预测结果的小型公司。作为另一个组成部分，首席研究人员将访问医疗设备公司，以分享有关产品评估过程的知识，开发新课程，并为本科生提供资助的研究机会。该研究的目的是更准确地量化可渗出材料通过通过聚合物矩阵和接触生物学组织建模的医疗设备从医疗设备中释放出的可浸出材料的速度。研究包括通过汇总来自多个来源的数据并使用群集分析来近似生物组织中浸润物的运输特性来表征生物组织中可浸泡物的运输特性。使用这些传输属性的数学模型和计算机模拟将创建使用扩散限制的两个组件系统来预测可浸泡物的迁移。 此外，将开发一种新型的生物材料系统模型的方法，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。这种新方法将推进该领域可用的建模工具。总体而言，这项研究将提高对与人体接触的聚合物生物材料中包含的渗出物命运的基本理解。与提取研究相比，基于物理学的模型可以更好地捕获该系统的复杂性，这将产生更多的临床相关结果，扩大我们对这些复杂的生物动力系统的理解。该奖项反映了NSF的法定任务，并且认为值得通过基金会的智力优点评估来支持，并具有更广泛的影响。