A simulation-based technology for stochastic modeling, sensitivity analysis and design optimization, aimed at development of next-generation micro-fluidic devices for biomedical applications.

一种用于随机建模、灵敏度分析和设计优化的模拟技术，旨在开发用于生物医学应用的下一代微流体设备。

• 批准号: 10323474
• 负责人: GAURAV KEWLANI
• 金额: $ 23.21万
• 依托单位: SOFTWORTHY LLC
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-30 至 2023-09-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10323474
• 关键词: Accounting; Address; Adopted; Affect; Air; Algorithms; Artificial Intelligence; Automobile Driving; Biology; Biomedical Engineering; Cells; Cessation of life; Characteristics; Chemicals; Chemistry; Complex; Comprehensive Health Care; Computer software; Development; Device Designs; Devices; Diagnosis; Diagnostic; Discipline; Disease; Disease Outbreaks; Drug Delivery Systems; Elements; Engineering; Ensure; Environmental Risk Factor; Epidemic; Equipment Malfunction; Evaluation; Exhibits; Fiber; Finite Element Analysis; Food Safety; Formulation; Fostering; Genes; Guidelines; Health; Health Care Sector; Industry; Infection; Investigation; Knowledge; Lead; Methodology; Methods; Microfluidic Microchips; Microfluidics; Modeling; Monte Carlo Method; Morbidity - disease rate; Outcome; Output; Pathogen detection; Patients; Performance; Pharmaceutical Preparations; Physics; Play; Polynomial Models; Primary Health Care; Probability; Process; Productivity; Public Health; Quality Control; Rapid screening; Resolution; Resources; Role; Scheme; Sensitivity and Specificity; Software Design; Space Explorations; Specific qualifier value; System; Techniques; Technology; Temperature; Testing; Therapeutic; Thermal Conductivity; Uncertainty; Variant; Work; base; clinical decision-making; clinically relevant; commercial application; cost; design; detection limit; detection sensitivity; digital; disability; disability-adjusted life years; drug discovery; drug synthesis; effective therapy; engineering design; global health; graphical user interface; improved; innovation; insight; knowledge base; microfluidic technology; mortality; multidisciplinary; next generation; novel; point-of-care diagnostics; portability; practical application; prospective; prototype; rapid detection; reconstitution; recurrent neural network; research and development; response; scientific computing; screening; simulation; simulation software; software systems; therapeutically effective; tool

During an epidemic, testing numerous patients puts a heavy burden on the healthcare sector, while infections continue to rise in the absence of a treatment. In such a scenario, micro-fluidics technology can be used to develop affordable point-of-care diagnostic tools for detecting infected patients early, and effective drug discovery platforms for synthesizing therapeutic drugs. The development of such devices is extremely challenging, needing expertise in multiple disciplines (e.g. physics, chemistry, biology), and understanding the interplay between variables that influence operating performance requires computational assistance. While advanced design software may be adopted to simulate the performance of such devices, precise knowledge of prediction reliability is of paramount importance to ensure their suitability for clinical decision-making. Therefore, the long term objectives of this project are to commercially introduce a new paradigm of digital engineering design that focuses on evaluating the fluctuations in performance outputs due to variability in input parameters and to demonstrate the relevance of such a simulation-based technology through specific application to development of micro-fluidic biomedical devices. The envisioned proof-of-concept is a modular computational system with practical commercial applications in the healthcare sector that demonstrates how scientific computing, numerical simulation & artificial intelligence modeling approaches can lead to an increased understanding of the performance of a micro-fluidic system subject to operating uncertainty, and enable robust design optimization. The proposed approach is to employ innovative stochastic spectral methods & advanced numerical schemes to conduct computationally efficient, high fidelity simulations involving uncertainty quantification & propagation, model sensitivity analysis, and finite element analysis for the engineering evaluation of progressively complex micro-fluidic device designs, and to incorporate artificial intelligence based meta-modeling techniques to perform design space exploration for performance improvement of such devices. The R&D efforts would establish the technical merits & feasibility of a simulation- based technology for predictive stochastic analysis & multi-disciplinary engineering evaluation of novel micro- fluidic devices that addresses the need for efficient & accurate performance assessment of such devices in practical (often uncertain/variable) operating scenarios. It could subsequently be utilized by biomedical engineers to foster the rapid development of robust next-generation devices that operate reliably within desired operating performance specifications, such as diagnostic tools with improved detection sensitivity & specificity, and drug discovery platforms with enhanced reconstitution of complex cellular interactions. These can play a crucial role in rapid short-term response to control the spread of infections & to mitigate disease outbreaks, while also offering improved solutions for enhancing long-term access to primary healthcare & comprehensive disease treatment, thereby significantly improving public health, particularly in resource constrained settings.

在流行病期间，检测大量患者给医疗保健部门带来了沉重的负担， 在没有治疗的情况下继续上升。在这种情况下，微流体技术可以用于 开发负担得起的护理点诊断工具，以早期发现感染患者， 用于合成治疗药物的发现平台。这种设备的发展是非常重要的。 具有挑战性，需要多个学科的专业知识（例如物理，化学，生物学），并了解 影响操作性能的变量之间的相互作用需要计算辅助。而 可以采用先进的设计软件来模拟这种器件的性能， 预测的可靠性对于确保其适用于临床决策是至关重要的。 因此，该项目的长期目标是在商业上引入一种新的数字模式， 一种工程设计，其重点是评估由于输入可变性而导致的性能输出波动 参数，并通过具体的模拟技术来证明这种基于模拟的技术的相关性。 应用于微流体生物医学装置的开发。设想的概念验证是一个模块化的 计算系统与实际的商业应用，在医疗保健部门，展示了如何 科学计算，数值模拟和人工智能建模方法可以导致 增加对微流体系统在操作不确定性下的性能的理解，以及 实现稳健的设计优化。所提出的方法是采用创新的随机谱方法 和先进的数值方案进行计算效率，高保真度模拟，包括 不确定性量化和传播，模型灵敏度分析，有限元分析， 工程评估日益复杂的微流体装置设计，并纳入人工 基于智能的元建模技术来执行设计空间探索以获得性能 这些设备的改进。研发工作将确定模拟的技术优点和可行性- 基于技术的预测随机分析和多学科工程评价的新的微观， 本发明涉及流体装置，其解决了对这种装置的有效和准确的性能评估的需要， 实际（通常不确定/可变）操作场景。它随后可以被生物医学 工程师促进快速开发强大的下一代设备，这些设备在所需的范围内可靠地运行 操作性能规范，例如具有改进的检测灵敏度和特异性的诊断工具， 以及具有增强的复杂细胞相互作用的重建的药物发现平台。这些可以起到 在控制感染蔓延和减轻疾病爆发的快速短期反应中发挥关键作用， 同时还提供改进的解决方案，以加强长期获得初级医疗保健和全面 疾病治疗，从而显着改善公共卫生，特别是在资源有限的环境中。