Enslein K
J Environ Pathol Toxicol. 1978 Sep-Oct;2(1):115-21.
A statistical model has been developed for estimation of acute toxicity. The model, currently operational for rat oral LD50, permits the estimation of rat oral LD50 for untested chemical compounds. Only the chemical structure, partition coefficient, and molecular weight for a compound are needed for estimation purposes. The chemical structure is partitioned into substructural fragments using the CIDS fragment keys. A regression model is developed on the basis of 425 compounds. A test of the regression equation with 100 compounds not used in its design shows that 56 percent of the compounds are predicted with less than 0.4 log unit deviation between extimated and measured LD50. This toxicity estimation model can be readily adapted to other species and to other measures of toxicity by the use of suitable design data bases. The model also identifies the contribution to toxicity of the fragments and physical characteristics. The use of this model can materially reduce the amount of toxicological testing for new compounds. It also permits the ranking of potentially toxic compounds to allow the most likely candidates to be tested. The method may also prove applicable to the determination of optimum dosages for new drugs.
已开发出一种用于估算急性毒性的统计模型。该模型目前用于大鼠口服半数致死剂量（LD50）的估算，能够对未经测试的化合物估算大鼠口服LD50。估算时仅需化合物的化学结构、分配系数和分子量。使用CIDS片段键将化学结构划分为子结构片段。基于425种化合物建立了回归模型。用100种未用于模型设计的化合物对回归方程进行检验，结果表明，56%的化合物预测值与实测LD50之间的偏差小于0.4对数单位。通过使用合适的设计数据库，这种毒性估算模型可轻松适用于其他物种和其他毒性指标。该模型还能确定片段和物理特性对毒性的贡献。使用此模型可大幅减少新化合物的毒理学测试量。它还能对潜在有毒化合物进行排序，以便对最有可能的候选化合物进行测试。该方法也可能适用于新药最佳剂量的确定。
