Continuous measurement of cell growth as an optimal tool in drug toxicity testing (Supplement)

 描述（由申请人提供）：在筛选具有治疗潜力的药物的过程中，通常会出现几种候选药物作为具有相似疗效的主要候选药物，并且很难选择先导化合物。然而，人们的生命和数十亿美元可能取决于选择哪种化合物进行临床研究， 审判由于药物引起的任何毒性水平都将禁止选择其作为先导化合物，因此检测到非常低的毒性水平可以形成以客观方式对此类化合物进行排序的基础。因此，该提案的总体目标是建立一种新的超灵敏体外毒性测量与临床毒性相关的算法，该算法将用于对被视为临床试验先导化合物的候选药物进行排名。我们推断，即使是长期服用药物引起的细胞死亡速度非常缓慢，也可能在多年的时间里杀死相当大比例的器官或细胞类型。然而，仅几个百分点的细胞数量变化低于当前体外测试的检测限。 我们假设，如果药物足够敏感，体内发生的一些副作用可以在体外试验中发现。我们已经建立了独特的方法来测量细胞数量和代谢活力，这通过连续测量所需灵敏度的耗氧量来反映。建立我们的方法的效用的关键将是使用一组相关的基准化合物来证明与体内安全性和毒理学的强相关性，其中先前的体内数据是众所周知的，并且包含从高度“安全”的药物到具有已知毒性的药物的范围。我们将优化方法，以测量各种选定细胞类型中耗氧量（细胞数量的测量）的微小变化，并通过测试具有不同毒性程度的化合物来验证方法。这将为最终构建客观算法奠定基础， 可用于基于长期给药引起的毒性对先导化合物的潜力进行分级。

 DESCRIPTION (provided by applicant): During the process of screening for drugs with therapeutic potential, often times several candidates emerge as prime candidates with similar efficacy and the choice for a lead compound is difficult to make. However, people's lives and billions of dollars may rest on the choice of which compound to bring to clinical investigation and trials. Since any levels of toxicity caused the by drug would contra-indicate its choice as a lead compound, detection of very low-level toxicity could form the basis for ranking such groups of compounds in an objective fashion. Accordingly, the overall goal of the proposal is to build an algorithm relating a novel ultra-sensitive in vitro measure of toxicity to clinical toxicity, whichwill be used to rank candidate drugs being considered as lead compound of clinical trials. We reasoned that even a very slow rate of cell death induced by a chronically administered drug might -- over the years -- kill off a significant proportion of an organ or cell type. However, a change in cell number of only a few percent is below the detection limit of current in vitro tests. We hypothesize that some side effects of drugs occurring in vivo could be revealed in in vitro tests if they were sensitive enough. We have established unique methods to measure cell number and metabolic viability as reflected by continuous measurement of oxygen consumption with the required sensitivity. The key to establishing the utility of our approach will be to demonstrate strong correlation with in vivo safety and toxicology using a relevant panel of benchmark compounds about which prior in vivo data is well known, and that contains a spectrum from highly "safe" drugs to those with known toxicity. We will optimize methods to measure small changes in oxygen consumption (a measure of cell number) in various selected cell types, and verify the methods by testing with compounds that have varying degrees of toxicity. This will lay the foundation for the eventual construction of an objective algorithm that can be used to rank the potential of lead compounds on the basis of toxicity caused by chronic administration.