Optimal design for 3D printed nasopharyngeal (NP) swabs for COVID-19 detection.

本研究项目旨在为新冠肺炎检测3D打印鼻咽拭子的优化设计提供资金支持。考虑到最近新冠肺炎大流行突出的需求，3D打印的NP棉签已被确定为大量生产NP棉签的可行方法。然而，NP棉签要推向市场并用于临床，在采集样本的质量和数量方面仍存在各种限制，患者不适，机械稳定性有限。在这里，我们建议开发数值模拟来改进当前的NP棉签设计特征，以优化样本收集。这一优化将考虑粘液的流变性和在NP拭子运动过程中对粘膜产生的局部应力，以采集样本。模拟而不是实验是进行这种优化的理想选择，因为粘液流变学和种群的外貌有很大的变异性。这种巨大的可变性使得实验方法既耗时又要求高。这种优化的设计将有利于新冠肺炎在加拿大的管理，减少a)假阴性的数量，b)合格人员的风险，以及c)相关个人防护装备的使用。

This research project seeks funds for developing optimal designs for 3D printed nasopharyngeal (NP) swabs for COVID-19 detection. 3D printed NP swabs have been identified as a viable methodology to manufacture NP swabs in large quantities considering the need highlighted by the recent COVID-19 pandemic. However, to be brought to the market and used clinically, NP swabs still suffers various limitations in quality and quantity of sample collected, patient discomfort and limited mechanical stability. Here we propose to develop numerical simulations to improve the current NP swab design features to optimize sample collections. This optimization will take into account the mucus rheological properties and the local stresses on the mucosa generated during the NP swab motion for sample collection. Simulations rather then experiments are ideal to perform this optimization because the large variability in mucus rheology and physiognomy of the population. This large variability makes an experimental approach time consuming and highly demanding. This optimized design will benefit the management of COVID-19 in Canada by reducing a) the number of false negatives, b) the risks for qualified personnel and c) the associated use of personal protective equipment.