ADME assay

Drug candidates that are intended for oral dosing need to have good ADME properties so that they can be dosed once or twice daily. The drug should be well absorbed, survive first pass metabolism, and have sufficiently low clearance. At the lead identification stage, the primary in vitro ADME assays employed are those that assess permeability and metabolic stability. There are a variety of assays available for both parameters, as described in the previous chapter. 

It is also important to correlate PK data with in vitro ADME assay data for each series to validate the predictive potential for the in vitro assays within a series. Once this is done, one can rely on the in vitro assays with more confidence. 

Although ADME assays are usually performed by analytical chemists, medicinal chemists—the molecule makers—need to have some understanding of the physicochemical processes in which the molecules participate. Peter Taylor [17] states ... 

Jenkins, K.M. et al. 2004. Automated high throughput ADME assays for metabolic stability and cytochrome P450 inhibition profiling of combinatorial libraries. J. Pharm. Biomed. Anal. 34 989. 

BioPrint consists of a large database and a set of tools with which both the data and the models generated from the data can be accessed. The database contains structural information, in vivo and in vitro data on most of the marketed pharmaceuticals and a variety of other reference compounds. The in vitro data generated consist of panels of pharmacology and early ADME assays. The in vivo data consist of ADR data extracted from drug labels, mechanisms of action, associated therapeutic areas, pharmacokinetic (PK) data and route of administration data. 

Kassel, D. B. High throughput strategies for in vitro ADME assays how fast can we go in Using Mass Spectrometry for Drug Metabolism Studies, CRC Press, Boca Raton, 2005. 

With respect to compoimd management, the testing process, and assay and data validation, the BioPrint ADME assays are similar to the pharmacological assays. The test compounds are handled similarly with aliquots of prepared compounds set aside for the ADME screening. The only deviation... 

Figure 8. Heat map of a cluster of BioPrint compounds with similar in vitro ADME profiles. Eight ADME assays are clustered on the X-axis and 8 compounds are clustered on the Y-axis. Normalized data range from 0 (blue-green) to 2 (red). Clustering is performed using Pearson correlation and complete linkage using normalized dataset. Where available in literature, human in vivo oral absorption (oa) and oral bioavailability (ba) values (%) are presented after the compound name.

To meet the need of conducting HTS for ADME-Tox properties, many slow and expensive in vivo ADME assays are now being replaced by in vitro cell models. For intestinal absorption, Caco-2 cell lines and Madin Darby canine kidney (MDCK) cell lines are widely used to predict the absorption rate of candidate drug compounds across the intestinal epithelial cell barrier. A number of models for Caco-2 cell permeability and MDCK cell permeability have been reported that predict the oral absorption properties of drugs, mostly limited to small organic molecules. Caco-2 and MDCK permeability are related to "A" and "D" in the ADME-Tox. 

Early determination of PK properties (absorption, distribution, metabolism, excretion and toxicity, ADMET) has become a fundamental resource of medicinal chemistry in the LO phase. New technologies have been developed to perform a great number of in vitro and even in silico tests. Currently, the most common early-ADME assays evaluate both physicochemical properties (such as the solubility in an opportune medium, the lipophilicity, and the p K i) and biophysical properties (such as the permeability through cellular monolayers to predict oral absorption and the metabolic stability after treatment with liver or microsomal subcellular fraction that contains oxidative cytochromes). 

The introduction of several new technologies like protein crystallography, ADME assays, medicinal... 

It has to be pointed out that prediction failures of general ADME models are often related to two major sources namely the quality of experimental data used to derive the model and the interpretation of the final model. These problems are discussed in depth by Stouch et al. (2003). Some models fail as they were built from data collected from different sources and laboratories. Although this might work for some robust standardized ADME assay, it could produce incomparable data for others. Such problems have been reported for example for Caco-2 assays from different laboratories. Even if the experimental... 

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