ADME software packages

The present paper is organized as follows. First, a brief introduction is given for each ADME-Tox property, especially how it is related to ADME-Tox, and then the latest in silico models for that property are discussed. Further, some experts opinion is presented on how to model that property more accurately and reliably. This is followed by a discussion on how to build up predictable QSAR models with all kinds of statistical tools. Finally, the ADME-Tox resources, including both databases and software packages are summarized. 

Table 1 A list of ADME-Tox Software Packages and their major functions... 

Lion Biosciences is the supplier of the iDEA Metabolism software package as well as other ADME/T services (289). The iDEA software simulates metabolism and predicts a compound s metabolic behavior in humans. The Metabolism Module consists of a data expert module to perform data fitting and analysis of collected in vitro data and the physiological metabolism model. The physiological metabolism model is constructed from proprietary database of 64 clinically tested compounds. Additionally, the metabolism module automatically calculates the Michaelis-Menten constants Km and VjIiax for the kinetic analysis of metabolism turnover (289). 

The GRID force field represents the basis for several software packages specifically developed for application to pharmacodynamic aspects of drug research, including the programs ALMOND, Pathfinder, and FLAP or, in the ADME field, the programs VolSurf and MetaSite. 

Major reasons for drug candidates to fail in early clinical phases are unpropitious pharmaco-kinetic properties (such as a lack of bioavailability) or toxicity. Therefore, estimation of these properties is an important part of a combinatorial library profile. An increasing number of publications [6, 42-45] demonstrate the importance of ADME parameters (ADME = absorption, distribution, metaboHsm, and ehmina-tion). Several commercial software packages are available. The ways in which ADME parameters are derived are similar in most available software products. In a first step, simple descriptors are calculated and in a second step, these descriptors are correlated with experimental data [46]. The parameters must describe properties that are important for pharmaco-kinetics (lipophilicity, size, and polarity of molecules, etc.). Standard correlation methods can be used, because the type of correlation has only secondary effects on the results. Generally, the predictivity of classification methods (the output from which can only be good or bad ) is slightly better compared to a quantitative correlation. 

In spite of the high interest in the parameters and in spite of the fact that more and more software companies offer products to calculate them, reliable calculation of ADME properties remains difficult The results are only acceptable if the molecular structures of the training set (for which experimental data are known) and the structures of interest are similar. Typically, the methods achieve a high degree of predictivity (> 90% correct classification) within the training data. Nevertheless, most software packages fail completely in realistic tests [47]. 

Two software packages, ADMET predictor (Simulations plus) and ADME Boxes (Pharma Algorithms), were used to predict the potential absorption of the... 

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