吸收剂量分数的计算:基于一室稳态浓度近似和动态七室模型的解析解的比较

IF 0.4 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
K. Sugano
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引用次数: 21

摘要

药物的口服吸收是用溶解、渗透和胃肠道传递过程的微分方程来模拟的。本研究的目的是比较简单的近似解析解与完整的数值解,以计算吸收剂量的分数(Fa)。数值积分的GI分室模型由1个胃、7个肠和1个结肠分室组成,而解析解则使用一个简单的搅拌均匀的分室。通过对溶解、渗透和胃肠运输微分方程进行数值积分,得到了完整的数值解。在数值积分计算中,动态模拟了药物在胃肠道中的浓度变化、颗粒减小、药物转运等过程。没有考虑胃肠道的沉淀以及溶解度和渗透性的区域差异。总共进行了7056次数值积分,涵盖了溶解度(0.001 ~ 1mg /mL)、扩散系数(0.1 ~ 10 × 10 ~ 6cm2 /sec)、剂量(1 ~ 1000mg)、粒径(1 ~ 300 μm)和有效渗透率(0.03 ~ 10 × 10 ~ 4cm /sec)等实际药物参数范围。所研究的解析解为:(1)连续一阶近似(Fa = 1-Pn /(Pn - Dn)exp(- Dn) + Dn/(Pn - Dn)exp(- Pn)), Dn:溶解数,Do:剂量数和Pn:渗透数。Dn、Do和Pn为无量纲参数,分别代表溶解时间/GI传递时间比、溶解度/剂量比和渗透时间/GI传递时间比,(II)极限阶近似(Fa =1 - exp(-Pn)、Fa = Pn/Do和Fa =1 - exp(-Dn)的最小值),(III)溶解药物浓度的稳态近似(Fa =1 - exp(-1 /(1/Dn + Do/Pn)),如果Do < 1,对于低溶解度化合物,(I)和(II)法的Fa值高于数值积分法(r 2 = 0.80和0.98,均方根误差(RMSE)分别= 0.28和0.079)。采用稳态近似,提高了相关性(r2 = 0.99, RMSE = 0.047)。溶解药物浓度的稳态近似适于Fa的计算。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Calculation of fraction of dose absorbed: comparison between analytical solution based on one compartment steady state concentration approximation and dynamic seven compartment model
Oral absorption of a drug is modeled by the differential equations for dissolution, permeation and gastrointestinal transit processes. The purpose of the present study was to compare simple approximate analytical solutions with full numerical solutions for the calculation of the fraction of a dose absorbed (Fa). The GI compartment model for numerical integration consisted of 1 stomach, 7 intestine and 1 colon compartments, whereas for analytical solutions a simple one well-stirred compartment was used. Full numerical solutions were obtained by numerically integrating the dissolution, permeation and gastrointestinal transit differential equations. In the numerical integration calculation, the concentration change in the GI tract, particle size reduction, transit of drugs, etc., was dynamically simulated. Precipitation in the GI tract and regional differences of solubility and permeability were not considered. In total, 7056 numerical integrations were performed, sweeping practical drug parameter ranges of solubility (0.001 to 1 mg/mL), diffusion coefficient (0.1 – 10 x 10 -6 cm 2 /sec), dose (1 to 1000 mg), particle diameter (1 to 300 μm) and effective permeability (0.03 – 10 x 10 -4 cm/sec). The analytical solutions investigated were (I) a sequential first order approximation (Fa =1–Pn/(Pn – Dn)exp(–Dn) + Dn/(Pn – Dn)exp(–Pn), Dn: dissolution number, Do: dose number and Pn: permeation number. Dn, Do and Pn are the dimensionless parameters which represent the dissolution time/GI transit time ratio, the solubility/dose ratio, and the permeation time/GI transit time ratio, respectively), (II) a limiting step approximation (the minimum value of Fa = 1–exp(–Pn), Fa = Pn/Do and Fa = 1–exp(–Dn)) and (III) a steady state approximation for the dissolved drug concentration (Fa =1–exp(–1/(1/Dn + Do/Pn)), if Do < 1, Do = 1). Fa values by (I) and (II) were higher than those by numerical integration for low solubility compounds (r 2 = 0.80 and 0.98, root mean square error (RMSE) = 0.28 and 0.079, respectively). By applying the steady state approximation, the correlation was improved (r 2 = 0.99, RMSE = 0.047). The steady state approximation for the dissolved drug concentration was appropriate for Fa calculation.
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来源期刊
Chem-Bio Informatics Journal
Chem-Bio Informatics Journal BIOCHEMISTRY & MOLECULAR BIOLOGY-
CiteScore
0.60
自引率
0.00%
发文量
8
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