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Computational prediction of oral drug absorption based on absorption rate constants in humans.

Abstract：

:Models for predicting oral drug absorption kinetics were developed by correlating absorption rate constants in humans (K(a)) with computational molecular descriptors. The K(a) values of a set of 22 passively absorbed drugs were derived from human plasma time-concentration profiles using a deconvolution approach. The K(a) values correlated well with experimental values of fraction of dose absorbed in humans (FA), better than the values of human jejunal permeability (P(eff)) which have previously been used to assess the in vivo absorption kinetics of drugs. The relationships between the K(a) values of the 22 structurally diverse drugs and computational molecular descriptors were established with PLS analysis. The analysis showed that the most important parameters describing log K(a) were polar surface area (PSA), number of hydrogen bond donors (HBD), and log D at a physiologically relevant pH. Combining log D at pH 6.0 with PSA or HBD resulted in models with Q(2) and R(2) values ranging from 0.74 to 0.76. An external data set of 169 compounds demonstrated that the models were able to predict K(a) values that correlated well with experimental FA values. Thus, it was shown that, using a combination of only two computational molecular descriptors, it is possible to predict with good accuracy the K(a) value for a new drug candidate.

journal_name

J Med Chem

journal_title

Journal of medicinal chemistry

authors

Linnankoski J,Mäkelä JM,Ranta VP,Urtti A,Yliperttula M

doi

10.1021/jm051231p

subject

Has Abstract

pub_date

2006-06-15 00:00:00

pages

3674-81

issue

12

eissn

0022-2623

issn

1520-4804

journal_volume

49

pub_type

杂志文章

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