Multiparametric Sensor Arrays for High Information Content Separations

用于高信息含量分离的多参数传感器阵列

• 批准号: 1508656
• 负责人: Ryan Bailey
• 金额: $ 42万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-01 至 2017-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1508656&HistoricalAwards=false
• 关键词: Multiparametric; Sensor; Arrays; Information; Content

With support from the Chemical Measurement and Imaging Program in the Division of Chemistry, Professor Ryan Bailey and his group at University of Illinois at Urbana-Champaign aim to perform high information content separations using a silicon photonic microring resonator platform. The focus of this work is to improve analysis of polymers and small molecules, for example, with applications in consumer goods quality control and pharmaceutical drug development. The inherent versatility, quantitative nature, and dynamic range of this analytical platform make it applicable to a wide range of chromatographic detection challenges. In conjunction with the scientific goals of the project, the award will also support the training and development of young scientists, particularly those students from traditionally underrepresented minorities. Furthermore, the group will continue participation in outreach activities within the local community, including an innovative Spanish language science outreach program developed in collaboration with the campus chapter of the Society for the Advancement of Chicanos and Native Americans in Science (SACNAS).Modified sensor arrays for multiparametric separations can be applied to polymer characterization using tunable organic sensor surfaces, to pharmaceutical biologics validation using immune-affinity characterization, and to integrated on-chip separations with electrophoresis for a lab-on-a-chip devices. The current methods for the analysis of polymer and small molecules suffer from slow product validation and often require multiple analytical methods for complete characterization. This project seeks to simplify the validation process by incorporating rapid and chemically informative separations into a single device, representing a new capability for the separations field. Such a device will prove particularly important in the separation and analysis of the next generation of pharmaceuticals, including antibody-based therapeutics. Unlike more conventional small molecule drugs these biological therapeutics demand unique analytical characterization tools.

在化学系化学测量和成像项目的支持下，伊利诺伊大学厄巴纳-香槟分校的Ryan Bailey教授和他的团队旨在使用硅光子微环谐振器平台进行高信息量的分离。这项工作的重点是改进聚合物和小分子的分析，例如，在消费品质量控制和药物开发中的应用。该分析平台固有的多功能性，定量性质和动态范围使其适用于广泛的色谱检测挑战。与该项目的科学目标相结合，该奖项还将支持年轻科学家的培训和发展，特别是那些来自传统上代表性不足的少数民族的学生。此外，该小组将继续参与当地社区的外展活动，包括与奇卡诺人和美洲原住民科学促进会（SACNAS）校园分会合作制定的一项创新的西班牙语科学外展计划。用于多参数分离的改进传感器阵列可以应用于使用可调有机传感器表面的聚合物表征，使用免疫亲和表征的药物生物制品验证，以及集成的芯片上分离与电泳的芯片上实验室设备。目前用于聚合物和小分子分析的方法存在产品验证缓慢的问题，并且通常需要多种分析方法才能完成表征。该项目旨在通过将快速和化学信息分离结合到单个设备中来简化验证过程，代表分离领域的新能力。这种设备将被证明在分离和分析下一代药物，包括基于抗体的疗法中特别重要。与更传统的小分子药物不同，这些生物疗法需要独特的分析表征工具。