AstraDx: Sub-Hour AST Via Computational Image Processing

项目总结/摘要 细菌性血流感染（BSI）的抗菌药物敏感性测试（AST）非常缓慢。 从阳性血培养开始，AST目前平均需要15小时，通常需要几天。直到 结果可用，别无选择，只能使用经验性抗生素治疗患者，并希望病原体 易受影响这是不可接受的。BSIs是严重的，迅速致命的感染，导致25万美国人死亡 包括三分之一的医院死亡。经验性抗生素会破坏患者正常的植物群， 使他们容易受到额外的无法治愈的感染。每小时就有一个病人用错抗生素 死亡风险增加7.6%。这一关键问题使快速、可负担得起的AST成为全球优先事项。 为了解决这个问题，AstraDx开发了一种低成本的新型AST设备，我们假设它可以执行 一个小时内。本提案的目的是检验这一假设。初步研究涉及 对19种菌株与8种标准抗生素进行的多项实验表明，在31±18 分钟（95%范围，20-63分钟）。检测的菌株包括耐甲氧西林的S.金黄色葡萄球菌（MRSA）， 万古霉素耐药肠球菌（VRE）、碳青霉烯类耐药A.鲍曼不动杆菌（CRAB），碳青霉烯类耐药 肠球菌（CRE）、耐多药铜绿假单胞菌-根据CDC，所有这些都是高度优先的-以及 相应的敏感菌株。使这些结果成为可能的创新是一种新的计算方法， 图像处理流水线，能够非常灵敏和强大地检测抗生素对 生长，往往在不到应变的倍增时间。第二个创新是使用廉价的标准 组件，从而产生负担得起的设备和消耗品。这些创新支持我们的长期目标 使快速AST普遍可用。我们将通过三个密切关注的具体问题来验证我们的假设。 目标。Aim 1将生成关于不同细菌-药物组合的训练数据，其中细菌来自模拟- 阳性血培养物在抗生素加倍稀释的情况下在384孔板上生长，类似于 目前的表型金标准，每个平板上有多种抗生素。目标2将使用目标1中的图像 创建一个统一的图片，每个菌株的行为在每种抗生素的存在，我们将使用， 完善我们如何确定最低抑菌浓度（MIC），以最大限度地提高分类一致性 CLSI黄金标准最后，目标3将通过检测其他细菌来验证目标2中的方法 根据FDA标准指南，菌株和测量与金标准的分类一致性。 预期的结果是一个设备被证明可以实现亚小时AST与FDA级的性能在广泛的 各种病原体，建立技术优点，可行性和商业潜力的SBIR第二阶段。 我们先进的技术，一个明确的产品，将有助于满足快速，高灵敏度的关键需求 感染性疾病诊断，以解决危及生命的BSI和败血症的抗菌素耐药性。

PROJECT SUMMARY/ABSTRACT Antimicrobial susceptibility testing (AST) for bacterial bloodstream infections (BSIs) is dangerously slow. Starting from a positive blood culture, AST currently takes a median of 15 hours, and often takes days. Until results are available, there is no choice but to treat patients with empiric antibiotics and hope the pathogen is susceptible. This is unacceptable. BSIs are serious, rapidly fatal infections that kill a quarter-million Americans each year, including a third of all hospital deaths. Empiric antibiotics destroy patients’ normal flora, predisposing them to additional, untreatable infections. Every hour a patient is on the wrong antibiotic increases risk of death by 7.6%. This key problem has made rapid, affordable AST a global priority. To address this problem, AstraDx has developed a low-cost new AST device that we hypothesize can perform AST in under an hour. The purpose of this proposal is to test this hypothesis. Preliminary studies involving multiple experiments on 19 strains vs. 8 standard antibiotics have demonstrated growth detection in 31±18 minutes (95% range, 20-63 minutes). Strains tested included methicillin-resistant S. aureus (MRSA), vancomycin-resistant Enterococci (VRE), carbapenem-resistant A. baumannii (CRAB), carbapenem-resistant Enterobacterales (CRE), multidrug-resistant P. aeruginosa—all high priority per the CDC—as well as corresponding susceptible strains. The innovation that makes these results possible is a new computational image-processing pipeline, which enables extremely sensitive and robust detection of an antibiotic’s effect on growth, often in less than the strain’s doubling time. A second innovation is the use of inexpensive standard components, leading to an affordable device and consumables. These innovations support our long-term goal of making rapid AST universally available. We will test our hypothesis through three tightly focused specific aims. Aim 1 will generate training data on diverse bug-drug combinations, with bacteria from simulated- positive blood cultures grown in the presence of doubling dilutions of antibiotic on 384-well plates, similar to the current phenotypic gold standard, with multiple antibiotics on each plate. Aim 2 will use the images from Aim 1 to create a unified picture of each strain’s behavior in the presence of each antibiotic, which we will use to refine how we determine minimum inhibitory concentrations (MICs) in order to maximize categorical agreement with the CLSI gold standard. Finally, Aim 3 will validate the method from Aim 2 by testing additional bacterial strains and measuring categorical agreement with the gold standard, per FDA standard guidelines. The expected outcome is a device proven to achieve sub-hour AST with FDA-level performance on a wide variety of pathogens, establishing technical merit, feasibility, and commercial potential for an SBIR Phase II. Our advanced technology, a clearly identified product, will help meet the critical need for rapid, highly sensitive infectious-disease diagnostics to address antimicrobial resistance for life-threatening BSIs and sepsis.