NSF/FDA SIR: The Role of Microbial Growth on Breast Implant Complications: Integration of Surface Properties, Extractable By-Product, and Biofilm Modeling
NSF/FDA SIR: The Role of Microbial Growth on Breast Implant Complications: Integration of Surface Properties, Extractable By-Product, and Biofilm Modeling
批准号:
2129311
负责人:
Stephen Arhin
金额:
$9.99万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-10-01 至 2023-09-30
中文摘要
美国食品和药物管理局(FDA)和世界卫生组织都发现了一种与乳房植入体相关的罕见的非霍奇金淋巴瘤。FDA的数据表明,毛面种植体更有可能发生这种类型的并发症。这种联系足够强烈,以至于FDA发布了一些毛面乳房植入体的自愿召回(I类召回)。然而,毛面植入物如何触发这种罕见的非霍奇金淋巴瘤的机制尚不清楚。因此,NSF/FDA学者驻留项目的目标是更好地了解这些纹理表面与光滑表面的区别,这可能有助于医疗器械制造商和监管机构防止美容和其他类型植入物的并发症。该项目将支持对霍华德大学的一名博士后研究员进行跨学科培训。与本研究相关的其他活动包括在霍华德大学与来自各个联邦和地方监管机构的专家一起讨论如何跨学科科学需要监管活动,标准制定,以及研究生毕业后在政府机构工作的机会。该项目的目标是评估乳房植入体脱落的表面特性和颗粒如何影响生物膜形成。BIA-ALCL(乳房植入体相关间变性大细胞淋巴瘤)与毛面植入体之间存在联系的证据确凿,最近在全球范围内引发了一系列监管行动。 这项工作的动机是研究表明这些毛面乳房植入体脱落颗粒,这导致了中心假设,即乳房植入体上的表面理化性质(如浸提物和颗粒脱落)影响生物膜形成。研究人员将采用实验系统和计算模型来测试这一假设,有两个目标。首先,生物膜反应器系统将用于评估具有各种理化性质的表面上的生物膜形成速率,例如,孔隙率、表面特征如何影响颗粒分布、以及在有颗粒和无颗粒的表面上细菌粘附和生物膜形成的水平。其次,将使用计算模型(COMSOL)评价表面特性和浸提物的影响。 将进行灵敏度分析,以确定哪些模型参数驱动结果,包括生物膜分离参数、Monod动力学生长参数和颗粒传输参数。在敏感性分析之后,将使用第一个目标中获得的实验结果来校准感兴趣的参数。 最后,将使用不同的实验条件(不同的表面粗糙度)对模型进行评价,以评估模型的预测能力。从该项目中获得的信息将通过为可能导致BIA-ALCL的生物膜生长提供更机械的解释来推进监管科学。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
Both the Food and Drug Administration (FDA) and the World Health Organization have identified a rare type of non-Hodgkin’s lymphoma associated with breast implants. FDA data indicate that textured implants are more likely to develop this type of complication. The link is strong enough that the FDA issued a voluntary recall of some textured breast implants (Class I recall). However, the mechanism between how textured implants may trigger this rare non-Hodgkin’s lymphoma is unknown. Thus, the goal of this NSF/FDA Scholar in Residence project is to better understand how these textured surfaces are distinct from smooth surfaces, which may help medical device makers and regulators prevent complications from cosmetic and other types of implants. The project will support the interdisciplinary training of a post-doctoral researcher at Howard University. Additional activities associated with this research include an event at Howard University with experts from various federal and local regulatory agencies to discuss how interdisciplinary science is needed for regulatory activities, standards development, and opportunities for graduate students to work in government agencies after graduation. The goal of this project is to assess how surface properties and particles that are shed from breast implants impact biofilm formation. Evidence of a link between BIA-ALCL (breast implant-associated anaplastic large cell lymphoma) and textured implants was conclusive enough to have recently triggered a series of regulatory actions worldwide. The work is motived by studies that have shown that these textured breast implants shed particles, which has led to the central hypothesis that the surface physicochemical properties such as extractables and particle shedding on breast implants influence biofilm formation. The investigators will employ experimental systems and computational models to test this hypothesis with two objectives. First, a biofilm reactor system will be used to evaluate biofilm formation rates on surfaces with various physiochemical properties, e.g., porosity, how surface features affect particle distribution, and the level of bacterial adhesion and biofilm formation on surfaces with and without particles. Second, a computational model (COMSOL) will to be used to evaluate the effects of surface properties and extractables. A sensitivity analysis will be conducted to determine which model parameters drive the results, including biofilm detachment parameters, Monod kinetic growth parameters, and particle transport parameters. Following sensitivity analysis, the parameters of interest will be calibrated using experimental results obtained in the first objective. Finally, the model will be evaluated using a different experimental condition (different surface roughness) to assess the predictive capability of the model. Information garnered from this project will advance regulatory science by providing a more mechanistic explanation for biofilm growth that may contribute to BIA-ALCL.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.
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