Prediction of Drug Absorption Using Multivariate Statistics

Abstract

Literature data on compounds both well- and poorly-absorbed in humans were used to build a statistical pattern recognition model of passive intestinal absorption. Robust outlier detection was utilized to analyze the well-absorbed compounds, some of which were intermingled with the poorly-absorbed compounds in the model space. Outliers were identified as being actively transported. The descriptors chosen for inclusion in the model were PSA and AlogP98, based on consideration of the physical processes involved in membrane permeability and the interrelationships and redundancies between available descriptors. These descriptors are quite straightforward for a medicinal chemist to interpret, enhancing the utility of the model. Molecular weight, while often used in passive absorption models, was shown to be superfluous, as it is already a component of both PSA and AlogP98. Extensive validation of the model on hundreds of known orally delivered drugs, "drug-like" molecules, and Pharmacopeia, Inc. compounds, which had been assayed for Caco-2 cell permeability, demonstrated a good rate of successful predictions (74-92%, depending on the dataset and exact criterion used).

A BOILED‐Egg To Predict Gastrointestinal Absorption and Brain Penetration of Small Molecules

“…An elegant compromise between these two types of models was proposed by Egan et al.,8 who developed a descriptive representation to discriminate between well‐absorbed and poorly absorbed molecules based on their lipophilicity and polarity, described by the n ‐octanol/water partition coefficient (log  P ) and the polar surface area (PSA). The delineation exists in a region of favorable properties for gastrointestinal absorption on a plot of two computed descriptors: ALOGP989 versus PSA 10.…”

“…As lipophilicity and polarity are often inversely correlated properties, the sometimes‐tricky chemical modifications simultaneously impacting log  P and PSA are efficiently supported by the model, which is rapid enough to allow trial‐and‐error iterations. These practical benefits make the Egan egg widely used in industrial and academic contexts, as indicated by its implementation in commercial packages (e.g., Discovery Studio, Dassault Systèmes BIOVIA, San Diego, CA, USA) and numerous citations of the seminal articles 8, 11. Successful applications include, for example, the discovery and development of the groundbreaking drug against hepatitis C, telaprevir,12 and a detailed pharmacokinetic analysis leading to anti‐tuberculosis agents 13…”

Incorporating physiologically relevant mobile phases in micellar liquid chromatography for the prediction of human intestinal absorption

“…Based on previous research, PSA has been reported to be a successful parameter in the prediction of intestinal absorption (Clark, 1999; Palm, Stenberg, Luthman, & Artursson, 1997; Stenberg et al, 1999). Furthermore, drug absorption‐relevant information has been shown to be sufficiently encoded in lipophilicity, along with PSA, without explicit reference to molecular weight (Egan, Merz, & Baldwin, 2000). These findings further corroborate that the current model displays superiority over the previously developed one for predicting intestinal absorption.…”

Rational hopping of a peptidic scaffold into non-peptidic scaffolds: structurally novel potent proteasome inhibitors derived from a natural product, belactosin A

“…21 To clarify the impact of the scaffold hopping on the molecular properties as leads, we calculated binding efficiency index (BEI) and surface-binding efficiency index (SEI) of these compounds (Table 1): BEI and SEI indicate binding efficiency per molecular weight and polar surface area (PSA), respectively. 22 Because molecular weight and PSA are well known physicochemical properties wellrelated to membrane permeability and bioavailability, [23][24][25][26][27] 22 Fig . 3 shows the plot of BEI vs. SEI of the newly identified nonpeptide inhibitors 5-12 and the previously developed inhibitors with the peptide scaffold identical to that of 4.…”