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Exploratory population pharmacokinetics (e-PPK) analysis for predicting human PK using exploratory ADME data during early drug discovery research

机译:探索性人群药代动力学(e-PPK)分析,用于在早期药物发现研究过程中使用探索性ADME数据预测人类PK

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We have proposed a novel method by population pharmacokinetics analysis for forecasting the drug concentration time-course in humans. This method is based on the non-linear mixed effect model (NONMEM) combined within vitro-in vivo extrapolation (IVIVE). Eleven clinically tested compounds were selected for retrospective analysis. Thein vivo pharmacokinetic (pk) profiles (rats, dogs, monkeys, and humans) andin vitro ADME data [intrinsic clearance (CLint), plasma unbound fraction (fp), and blood-plasma partition ratio (Rb)] for each compound was routinely tested via a screening system to account for inter-compound differences in pk properties. When evaluating the pk parameters, the hepatic plasma flow (Qph) and plasma volume (Vp) were taken into account to compensate for differences in body size among species. All these data were used to conduct population pk (PPK) analyses under the hypothesis that all species constituted one population. The two-compartment model (ADVAN4 TRANS3) and NONMEM software were used for this analysis. The fixed effect model for total body clearance (CL) and central distribution volume (Vd) were constructed as ?CLQph·Eh and ?Vd·Vp, respectively, where the hepatic extraction ratio Eh was calculated using the traditional dispersion model. NONMEM generates both fixed and random effects (η). The key point of this concept was to substitute the η values of each species (rats, dogs, and monkeys) into the human PPK model to simulate three kinds of pk profiles, compound by compound, for use as a general scaling factor. The NONMEM post hoc option was used to perform the simulation, after which the concentration vs. time courses were compared with actual clinical pk data. The true values were almost within the dynamic range. Thus, the advantage of this concept is that it can generate time-courses without the detail of drug-specific parameters, from which the elimination half time can be determined. This proposed exploratory population pharmacokinetic (e-PPK) approach is a useful and progressive tool that can be applied during the early stages of drug discovery research.
机译:我们已经通过群体药代动力学分析提出了一种预测人体内药物浓度时程的新方法。此方法基于在体外-体内外推法(IVIVE)中组合的非线性混合效应模型(NONMEM)。选择了11种经过临床测试的化合物进行回顾性分析。通常,每种化合物的体内药代动力学(pk)曲线(大鼠,狗,猴子和人)和体外ADME数据[内在清除率(CLint),血浆未结合分数(fp)和血血浆分配比(Rb)]通过筛选系统进行测试,以解释pk特性之间的化合物间差异。在评估pk参数时,要考虑肝血浆流量(Qph)和血浆体积(Vp),以补偿物种之间的体型差异。在所有物种都构成一个种群的假设下,所有这些数据都用于进行种群pk(PPK)分析。使用两室模型(ADVAN4 TRANS3)和NONMEM软件进行此分析。构建全身清除率(CL)和中央分布体积(Vd)的固定效应模型分别为ΔCL Qph·Eh和ΔVd·Vp,计算肝提取率Eh使用传统的色散模型。 NONMEM产生固定效应和随机效应(η)。这个概念的关键点是将每种物种(大鼠,狗和猴子)的η值代入人PPK模型中,以模拟三种PK曲线(逐个化合物)作为通用比例因子。使用NONMEM事后选项进行模拟,然后将浓度对时间的变化与实际临床pk数据进行比较。真实值几乎在动态范围内。因此,该概念的优点在于,它可以生成时程,而无需详细了解药物特异性参数,从而可以确定消除半衰期。这种拟议的探索性人群药代动力学(e-PPK)方法是一种有用且先进的工具,可以在药物发现研究的早期阶段应用。

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