Adaptive Protocol Synthesis and Error Recovery in Micro-Electrode-Dot-Array (MEDA) Microfluidic Biochips

微电极点阵列 (MEDA) 微流控生物芯片中的自适应协议合成和错误恢复

• 批准号: 2313498
• 负责人: Krishnendu Chakrabarty
• 金额: $ 44.99万
• 依托单位: Arizona State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-15 至 2025-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2313498&HistoricalAwards=false
• 关键词: Adaptive; Protocol; Synthesis; Error; Recovery

Droplet-based ("digital") microfluidic biochips (DMFBs) are revolutionizing high-throughput DNA sequencing and point-of-care clinical diagnosis. Using DMFBs, bioassay protocols are scaled down to droplet size and executed through software-based control of nanoliter droplets on a patterned electrode array. However, technology transition to industry has been challenging as today's DMFBs suffer from several key limitations: (1) constraints on droplet size; (2) difficulty of sensor integration for real-time detection and monitoring; and (3) reliability/yield concerns. To overcome these limitations, micro-electrode-dot-array (MEDA) biochips have been recently developed, incorporating real-time capacitive sensing on every microelectrode to detect the property and location of a droplet. Such 'sensing maps' open up the exciting opportunity of cyber-physical MEDA biochips that can dynamically respond to bioassay outcomes, perform real-time error recovery, and execute "if-then-else" protocols from biochemistry necessary to support the next generation of cyber-physical systems (CPS) with tightly integrated lab-on-chip sensing technology. Despite such tremendous promise, a significant barrier in the exploitation of MEDA for realistic biochemistry arises from the need to manually control biochemical protocols on the biochip. This research is thus motivated by the need to enable the execution of biomolecular assays on programmable and cyber-physical MEDA biochips. To take full advantage of the dynamic adaptation capabilities of MEDA, there is a need for a synthesis and run-time optimization framework that can be agile in its ability to respond to real-time sensor feedback. The proposed research therefore constitutes a comprehensive effort towards the realization of MEDA-based CPS, resulting in new applications that would, for instance, enable breakthroughs in cancer treatment or atmospheric aerosol measurements for pollution monitoring in smart cities.This is aimed at developing an integrated system solution for MEDA that includes advances in both hardware and software. Specific research products include the following innovations: (1) Modeling and robust controller design, which will involve offline model-based protocol synthesis and online learning-based protocol/model adaptation; (2) Adaptive and elastic synthesis techniques that comprehensively incorporate all the MEDA-specific droplet operations; (3) Optimization methods for multiple-reactant synthesis, which will involve on-chip sample preparation and optimization of the fluidic steps associated with dilution, mixing, and the generation of concentration gradients; (4) Fault tolerance through error recovery based on real-time sensing, droplet tracking, and adaptive MEDA-specific fluidic operations; and (5) MEDA biochip design, fabrication, and testbed setup, and the demonstration of real-time adaptation under software control for cell analysis in personalized cancer treatment. These breakthroughs will advance MEDA from an exploratory platform used to demonstrate droplet manipulation, to a mature platform that microbiologists and biochemists can use for implementing realistic protocols. The project also has an extensive education and outreach component, including curriculum development, expansion of hands-on research opportunities for undergraduate and graduate students, and international collaboration. For instance, MEDA-CPS will be used as an important example to showcase real-time adaptation in new undergraduate and graduate courses on modeling, design, and analysis of embedded control and cyber-physical systems. Tutorials at top conferences and benchmark dissemination activities will benefit the broader research community.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.

基于微滴（“数字”）的微流控生物芯片（dmfb）正在彻底改变高通量DNA测序和即时临床诊断。使用dmfb，生物测定方案被缩小到液滴大小，并通过基于软件的控制纳米升液滴在图案电极阵列上执行。然而，技术向工业的转变一直具有挑战性，因为今天的dmfb受到几个关键限制：(1)液滴尺寸的限制；(2)传感器集成难以实现实时检测和监控；(3)可靠性/良率问题。为了克服这些限制，最近开发了微电极点阵列（MEDA）生物芯片，在每个微电极上结合实时电容传感来检测液滴的性质和位置。这种“传感地图”为网络物理MEDA生物芯片开辟了令人兴奋的机会，它可以动态响应生物测定结果，执行实时错误恢复，并执行生物化学中的“if-then-else”协议，以支持下一代网络物理系统（CPS），具有紧密集成的芯片实验室传感技术。尽管有如此巨大的前景，但MEDA在现实生物化学中的开发存在一个重大障碍，即需要手动控制生物芯片上的生化协议。因此，这项研究的动机是需要在可编程和网络物理MEDA生物芯片上执行生物分子分析。为了充分利用MEDA的动态适应能力，需要一种能够灵活响应实时传感器反馈的综合和运行时优化框架。因此，拟议的研究构成了实现基于meda的CPS的全面努力，从而产生新的应用，例如，在癌症治疗或用于智能城市污染监测的大气气溶胶测量方面取得突破。该项目旨在为MEDA开发一个集成的系统解决方案，包括硬件和软件的进步。具体研究成果包括以下创新：(1)建模和鲁棒控制器设计，这将涉及离线基于模型的协议综合和在线基于学习的协议/模型自适应；(2)综合了所有meda特异性液滴操作的自适应和弹性合成技术；(3)优化多反应物合成方法，这将涉及芯片上样品制备和优化与稀释、混合和浓度梯度产生相关的流体步骤；(4)基于实时传感、液滴跟踪和自适应meda特定流体操作的纠错容错；(5) MEDA生物芯片的设计、制造、试验台搭建，并在软件控制下演示用于个性化癌症治疗中细胞分析的实时适应。这些突破将推动MEDA从一个用于演示液滴操作的探索性平台，发展成为一个成熟的平台，微生物学家和生物化学家可以使用它来实施现实的方案。该项目还包括广泛的教育和推广内容，包括课程开发，扩大本科生和研究生的实践研究机会，以及国际合作。例如，MEDA-CPS将作为一个重要的例子，在嵌入式控制和网络物理系统建模、设计和分析的新本科和研究生课程中展示实时适应性。顶级会议上的教程和基准传播活动将使更广泛的研究社区受益。该奖项反映了美国国家科学基金会的法定使命，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。

项目成果

Formal Synthesis of Adaptive Droplet Routing for MEDA Biochips

MEDA 生物芯片自适应液滴路由的正式合成

• DOI: 10.1109/tcad.2021.3110190
• 发表时间: 2022
• 期刊: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
• 影响因子: 2.9
• 作者: Elfar, Mahmoud;Liang, Tung-Che;Chakrabarty, Krishnendu;Pajic, Miroslav
• 通讯作者: Pajic, Miroslav

Deep Reinforcement Learning-Based Approach for Efficient and Reliable Droplet Routing on MEDA Biochips

基于深度强化学习的方法，在 MEDA 生物芯片上实现高效可靠的液滴路由

• DOI: 10.1109/tcad.2022.3194808
• 发表时间: 2023
• 期刊: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
• 影响因子: 2.9
• 作者: Elfar, Mahmoud;Chang, Yi-Chen;Ku, Harrison Hao-Yu;Liang, Tung-Che;Chakrabarty, Krishnendu;Pajic, Miroslav
• 通讯作者: Pajic, Miroslav