Akere Millicent T, Zajac Kelsee K, Bretz James D, Madhavaram Anvitha R, Horton Austin C, Schiefer Isaac T
Department of Medicinal and Biological Chemistry, College of Pharmacy and Pharmaceutical Sciences, University of Toledo, Toledo, OH 43614, USA.
Center for Drug Design and Development, College of Pharmacy and Pharmaceutical Sciences, University of Toledo, Toledo, OH 43614, USA.
Brain Sci. 2024 Jul 30;14(8):770. doi: 10.3390/brainsci14080770.
The ability to screen for agents that can promote the development and/or maintenance of neuronal networks creates opportunities for the discovery of novel agents for the treatment of central nervous system (CNS) disorders. Over the past 10 years, advances in robotics, artificial intelligence, and machine learning have paved the way for the improved implementation of live-cell imaging systems for drug discovery. These instruments have revolutionized our ability to quickly and accurately acquire large standardized datasets when studying complex cellular phenomena in real-time. This is particularly useful in the field of neuroscience because real-time analysis can allow efficient monitoring of the development, maturation, and conservation of neuronal networks by measuring neurite length. Unfortunately, due to the relative infancy of this type of analysis, standard practices for data acquisition and processing are lacking, and there is no standardized format for reporting the vast quantities of data generated by live-cell imaging systems. This paper reviews the current state of live-cell imaging instruments, with a focus on the most commonly used equipment (IncuCyte systems). We provide an in-depth analysis of the experimental conditions reported in publications utilizing these systems, particularly with regard to studying neurite outgrowth. This analysis sheds light on trends and patterns that will enhance the use of live-cell imaging instruments in CNS drug discovery.
筛选能够促进神经网络发育和/或维持的药物的能力，为发现用于治疗中枢神经系统（CNS）疾病的新型药物创造了机会。在过去十年中，机器人技术、人工智能和机器学习的进步为改进用于药物发现的活细胞成像系统的实施铺平了道路。这些仪器彻底改变了我们在实时研究复杂细胞现象时快速准确获取大型标准化数据集的能力。这在神经科学领域特别有用，因为实时分析可以通过测量神经突长度来有效监测神经网络的发育、成熟和维持。不幸的是，由于这种类型分析尚处于起步阶段，缺乏数据采集和处理的标准做法，并且对于活细胞成像系统生成的大量数据没有标准化的报告格式。本文回顾了活细胞成像仪器的现状，重点关注最常用的设备（IncuCyte系统）。我们对利用这些系统的出版物中报告的实验条件进行了深入分析，特别是在研究神经突生长方面。该分析揭示了将加强活细胞成像仪器在中枢神经系统药物发现中应用的趋势和模式。
