Abstract

1. Variability of the unbound fraction in plasma (f_u) between labs, methods and conditions is known to exist. Variability and uncertainty of this parameter influence predictions of the overall pharmacokinetics of drug candidates and might jeopardise safety in early clinical trials. Objectives of this study were to evaluate the variability of human in vitro f_u-estimates between labs for a range of different drugs, and to develop and validate an in silico f_u-prediction method and compare the results to the lab variability.

2. A new in silico method with prediction accuracy (Q²) of 0.69 for log f_u was developed. The median and maximum prediction errors were 1.9- and 92-fold, respectively. Corresponding estimates for lab variability (ratio between max and min f_u for each compound) were 2.0- and 185-fold, respectively. Greater than 10-fold lab variability was found for 14 of 117 selected compounds.

3. Comparisons demonstrate that in silico predictions were about as reliable as lab estimates when these have been generated during different conditions. Results propose that the new validated in silico prediction method is valuable not only for predictions at the drug design stage, but also for reducing uncertainties of f_u-estimations and improving safety of drug candidates entering the clinical phase.

摘要

1. 已知实验室、方法和条件之间存在血浆中未结合部分 (f _u ) 的可变性。该参数的可变性和不确定性会影响候选药物整体药代动力学的预测，并可能危及早期临床试验的安全性。本研究的目的是评估实验室之间对一系列不同药物的人体体外f _u估计的变异性，并开发和验证计算机f _u预测方法并将结果与​​实验室变异性进行比较。

2. 开发了一种新的计算机模拟方法，对 log f _{u 的}预测精度 (Q ² ) 为 0.69 。中位数和最大预测误差分别为 1.9 倍和 92 倍。实验室变异性（每种化合物的最大和最小 f _{u 之}比）的相应估计值分别为 2.0 倍和 185 倍。在 117 种选定化合物中，有 14 种的实验室变异性超过 10 倍。

3. 比较表明，当这些是在不同条件下生成时，计算机预测与实验室估计一样可靠。结果表明，新验证的计算机预测方法不仅对药物设计阶段的预测有价值，而且对减少_u估计的不确定性和提高进入临床阶段的候选药物的安全性也很有价值。