AMBROSIA: A Multiplexed Plasmo-Photonic Biosensing Platform For Rapid And Intelligent Sepsis Diagnosis At The Point- Of-Care

AMBROSIA旨在为败血症诊断提供多传感、面向未来的护理点单元（Point of Care Unit）基础，该单元由CMOS兼容工具包提供，并通过片上光子神经网络技术增强，以提供准确、快速的诊断。AMBROSIA将投资于已建立的集成等离子体光子传感器的超小尺寸和高灵敏度，这些传感器由众所周知的片上慢光效应和微转移印刷激光器和Si3N4上的光电二极管增强，以及集成光子神经网络引擎的功能处理和分类组合，以描绘传感器进化中下一个即将到来的中断的前景，在系统级封装原型组件中剪裁它们。这些传感器是廉价的一次性可插拔模块，可以在临床环境中快速准确地诊断败血症。AMBROSIA的目标是展示一个包含以下内容的护理点：i)可切换的传感器区域阵列，每个传感器区域便于可插拔的8通道无标签等离子体光子传感器，用于脓毒症诊断，灵敏度超过130.000nm/RIU，每个干涉传感器的检测限低于10-8 RIU； ii)嵌入式Si3N4光子神经网络同时处理和分类来自至少7个生物标志物的数据，零功率，在最初几分钟内提供准确快速的脓毒症诊断。iii)芯片上的微转移印刷激光器和光电探测器将大大降低传感和神经网络模块的成本，并使传感器阵列一次性使用。

AMBROSIA aims to provide the foundations for a multi-sensing future-proof Point of Care Unit for sepsis diagnosis offered by a CMOS compatible toolkit and enhanced by on-chip photonic neural network technology to provide an accurate and rapid diagnosis. AMBROSIA will be investing in the established ultra-small-footprint and elevated sensitivity of integrated plasmo-photonic sensors reinforced by the well-known on-chip slow-light effect and micro-transfer printed lasers and photodiodes on Si3N4, as well as the functional processing and classification portfolio of integrated photonic neural network engines, towards painting the landscape of the next-coming disruption in sensor evolution, tailoring them in System-in-Package prototype assemblies, with the sensors being cheap disposable pluggable modules that can rapidly and accurately diagnose sepsis at the bedside in clinical environments. AMBROSIA targets to demonstrate a Point of Care Unit incorporating: i) a switchable sensor area array, with each sensor area facilitating a pluggable, 8-channel label-free plasmo-photonic sensor for sepsis diagnosis with a sensitivity over 130.000nm/RIU and a Limit of Detection below 10-8 RIU for each interferometric sensor, ii) an embedded Si3N4 photonic neural network processing and classifying at the same time the data from at least 7 biomarkers with zero-power providing in the first minutes an accurate and rapid diagnosis for sepsis, iii) Micro transfer printed lasers and photodetectors on chip that will drastically decrease costs of both the sensing and neural network modules, and render the sensor arrays disposable.