Development of the neurovascular unit (NVU) is a complex, multistage process that requires orchestrated cell signaling mechanisms across several cell types and ultimately results in formation of the blood-brain barrier. Typical high-throughput screening (HTS) assays investigate single biochemical or single cell responses following chemical insult. As the NVU comprises multiple cell types interacting at various stages of development, a methodology combining high-throughput results across pertinent cell-based assays is needed to investigate potential chemical-induced disruption to the development of this complex cell system. To this end, we implemented a novel method for screening putative NVU disruptors across diverse assay platforms to predict chemical perturbation of the developing NVU. HTS assay results measuring chemical-induced perturbations to cellular key events across angiogenic and neurogenic outcomes in vitro were combined to create a cell-based prioritization of NVU hazard. Chemicals were grouped according to similar modes of action to train a logistic regression literature model on a training set of 38 chemicals. This model utilizes the chemical-specific pairwise mutual information score for PubMed MeSH annotations to represent a quantitative measure of previously published results. Taken together, this study presents a methodology to investigate NVU developmental hazard using cell-based HTS assays and literature evidence to prioritize screening of putative NVU disruptors towards a knowledge-driven characterization of neurovascular developmental toxicity. The results from these screening efforts demonstrate that chemicals representing a range of putative vascular disrupting compound (pVDC) scores can also produce effects on neurogenic outcomes and characterizes possible modes of action for disrupting the developing NVU.

神经血管单元 (NVU) 的发育是一个复杂的多阶段过程，需要跨多种细胞类型的协调细胞信号传导机制，并最终导致血脑屏障的形成。典型的高通量筛选 (HTS) 测定研究化学损伤后的单一生化或单细胞反应。由于 NVU 包含在不同发展阶段相互作用的多种细胞类型，因此需要一种结合相关细胞检测的高通量结果的方法来研究潜在的化学诱导破坏这一复杂细胞系统的发展。为此，我们实施了一种新方法，用于在不同的检测平台上筛选假定的 NVU 干扰物，以预测正在发展的 NVU 的化学扰动。体外结合起来创建基于细胞的 NVU 危害优先级排序。根据相似的作用模式对化学品进行分组，以在 38 种化学品的训练集上训练逻辑回归文献模型。该模型利用 PubMed MeSH 注释的特定化学成对互信息评分来表示先前发表结果的定量测量。综上所述，本研究提出了一种使用基于细胞的 HTS 测定和文献证据来调查 NVU 发育危害的方法，以优先筛选假定的 NVU 干扰物，以对神经血管发育毒性进行知识驱动的表征。