J Chem Inf Model - How experimental errors influence drug metabolism and pharmacokinetic QSAR/QSPR models.

Tópicos

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Resumo

We consider the impact of gross, systematic, and random experimental errors in relation to their impact on the predictive ability of QSAR/QSPR DMPK models used within early drug discovery. Models whose training sets contain fewer but repeatedly measured data points, with a defined threshold for the random error, resulted in prediction improvements ranging from 3.3% to 23.0% for an external test set, compared to models built from training sets in which the molecules were defined by single measurements. Similarly, models built on data with low experimental uncertainty, compared to those built on data with higher experimental uncertainty, gave prediction improvements ranging from 3.3% to 27.5%.

Resumo Limpo

consid impact gross systemat random experiment error relat impact predict abil qsarqspr dmpk model use within earli drug discoveri model whose train set contain fewer repeat measur data point defin threshold random error result predict improv rang extern test set compar model built train set molecul defin singl measur similar model built data low experiment uncertainti compar built data higher experiment uncertainti gave predict improv rang

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