Pfizer, Groton, CT, USA.
SLAS Technol. 2021 Dec;26(6):572-578. doi: 10.1177/24726303211023379. Epub 2021 Jun 19.
Since the advent of modern-day screening collections in the early 2000s, various aspects of our knowledge of good handling practices have continued to evolve. Some early practices, however, continue to prevail due to the absence of defining data that would bust the myths of tradition. The lack of defining data leads to a gap between plate-based screeners, on the one hand, and compound sample handling groups, on the other, with the latter being the default party to blame when an assay goes awry.In this paper, we highlight recommended practices that ensure sample integrity and present myth busting data that can help determine the root cause of an assay gone bad. We show how a strong and collaborative relationship between screening and sample handling groups is the better state that leads to the accomplishment of the common goal of finding breakthrough medicines.
自 21 世纪初现代筛选库出现以来，我们对良好处理方法的认识不断发展。然而，由于缺乏能够打破传统观念的定义性数据，一些早期的做法仍然存在。缺乏定义性数据导致基于平板的筛选器和化合物样品处理组之间存在差距，当测定出现问题时，后者往往成为默认的责任方。在本文中，我们强调了确保样品完整性的推荐做法，并提供了可以帮助确定测定出现问题的根本原因的破除神话数据。我们展示了筛选和样品处理小组之间建立强有力和协作关系的好处，这有助于实现找到突破性药物的共同目标。
