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: 1914796
• 负责人: Krishnendu Chakrabarty
• 金额: $ 44.99万
• 依托单位: Duke University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-01 至 2023-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1914796&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.

基于液滴（“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，生物测定方案可缩小至液滴尺寸，并通过基于软件的图案化电极阵列上的纳升液滴控制来执行。然而，向工业的技术转型一直充满挑战，因为当今的 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了实时电容传感来检测液滴的特性和位置。这种“传感图”为网络物理 MEDA 生物芯片带来了令人兴奋的机会，它可以动态响应生物测定结果，执行实时错误恢复，并执行支持下一代生物化学所必需的“if-then-else”协议。具有紧密集成的片上实验室传感技术的网络物理系统（CPS）。尽管前景如此巨大，但在将 MEDA 用于现实生物化学方面的一个重大障碍是需要手动控制生物芯片上的生化方案。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测定。为了充分利用 MEDA 的动态适应能力，需要一个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，拟议的研究是实现基于 MEDA 的 CPS 的全面努力，从而产生新的应用，例如，在癌症治疗或智能城市污染监测的大气气溶胶测量方面取得突破。 MEDA 的系统解决方案，包括硬件和软件方面的进步。具体研究产品包括以下创新：（1）建模和鲁棒控制器设计，其中将涉及基于离线模型的协议综合和基于在线学习的协议/模型自适应； (2) 综合结合所有MEDA特定液滴操作的自适应弹性合成技术； (3) 多反应物合成的优化方法，其中涉及片上样品制备以及与稀释、混合和浓度梯度生成相关的流体步骤的优化； (4) 通过基于实时传感、液滴跟踪和自适应 MEDA 特定流体操作的错误恢复实现容错； (5) MEDA 生物芯片设计、制造和测试台设置，以及在软件控制下实时适应个性化癌症治疗中细胞分析的演示。这些突破将使 MEDA 从用于演示液滴操作的探索性平台发展成为微生物学家和生物化学家可用于实施现实方案的成熟平台。该项目还具有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，在新的本科生和研究生课程中展示嵌入式控制和信息物理系统的建模、设计和分析的实时适应。顶级会议上的教程和基准传播活动将使更广泛的研究界受益。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力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

Enhancing the Reliability of MEDA Biochips Using IJTAG and Wear Leveling

使用 IJTAG 和磨损均衡增强 MEDA 生物芯片的可靠性

• DOI: 10.1109/tcad.2020.3032629
• 发表时间: 2020
• 期刊: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
• 影响因子: 2.9
• 作者: Zhong, Zhanwei;Liang, Tung-Che;Chakrabarty, Krishnendu
• 通讯作者: Chakrabarty, Krishnendu

IJTAG-based Fault Recovery and Robust Microelectrode-Cell Design for MEDA Biochips

适用于 MEDA 生物芯片的基于 IJTAG 的故障恢复和鲁棒微电极单元设计

• DOI: 10.1109/tcad.2020.2986741
• 发表时间: 2020
• 期刊: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
• 影响因子: 2.9
• 作者: Zhong, Zhanwei;Chakrabarty, Krishnendu
• 通讯作者: Chakrabarty, Krishnendu

Multi-Target Sample Preparation Using MEDA Biochips

使用 MEDA 生物芯片制备多目标样品

• DOI: 10.1109/tcad.2019.2942002
• 发表时间: 2019
• 期刊: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
• 影响因子: 2.9
• 作者: Liang, Tung-Che;Chan, Yun-Sheng;Ho, Tsung-Yi;Chakrabarty, Krishnendu;Lee, Chen-Yi
• 通讯作者: Lee, Chen-Yi

Adaptive Droplet Routing for MEDA Biochips via Deep Reinforcement Learning

通过深度强化学习实现 MEDA 生物芯片的自适应液滴路由

• DOI: 10.23919/date54114.2022.9774737
• 发表时间: 2022
• 期刊: Automation and Test in Europe (DATE
• 作者: Elfar, Mahmoud;Liang, Tung-Che;Chakrabarty, Krishnendu;Pajic, Miroslav
• 通讯作者: Pajic, Miroslav

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