Metabolic stability tests

Example 1 High-throughput Application for Metabolic Stability Tests... 

An important DMPK property of a NCE is oral bioavailability (F) of the compound in various pre-clinical species.3 The oral bioavailability of a compound is dependent on several factors including intestinal permeability (estimated by the Caco-2 assay) and hepatic clearance (estimated with an in vitro metabolic stability assay).3 30 The metabolic stability assay is typically performed by incubating test compounds in liver microsomes or hepatocytes. The results can provide estimates of in vivo stability in terms of metabolic liabilities.3 8 59 62 Several authors described this assay as an important tool for the rapid assessment of the DMPK properties of NCEs.3 6 8111819 26 44 59 62-65... 

Some authors searched for common oxidative metabolites as part of metabolic stability assays. Tong et al.75 described a highly automated microsomal metabolic stability assay that achieved a throughput of 50 compounds per day with each compound tested in rats, dogs, monkeys, and humans. In addition to assaying the test compound, they monitored M+16 metabolites by using the... 

Findings continue to accumulate in the field of endogenous opiates, as exemplified by two tetrapeptides isolated from mammalian brain and found to have high affinity and selectivity for p-opioid receptors. These tetrapeptides are endomorphin-1 (Tyr-Pro-Trp-Phe-NH2) and endomorphin-2 (Tyr-Pro-Phe-Phe-NH2). A number of synthetic analogues have been prepared with the view to improve their metabolic stability and, in some cases, to limit their access to peripheral opioid receptors. The three synthetic endomor-phin analogues Tyr-D-Ala-Phe-Phe-NH2 (6.84), Tyr-D-Arg-Phe-Phe-NH2 (6.85), and Tyr-D-Arg-Phe-Ape-NH2 (6.86), to be discussed in the next section, have potent antinociceptive effects in in vivo inflammatory tests but exhibit modest effects in the CNS. However, and despite the presence of a D-amino acid and a protected C-terminus, they remained sensitive to enzymatic hydrolysis [211][212],... 

Approximately 300 drugs were tested in aqueous solubility, log D, apparent permeability and metabolic stability assays. Compounds having low values for solubility, apparent permeability, or metabolic stability, or extreme log D values were flagged. The frequency of compounds with flags in each human bioavailability (%) bin is shown. 

Single Test Compound Clustering with Several Marketed Drugs on the Basis of the Similarity of In Vitro Profile Results Including Human Absorption, Oral Bioavailability, Permeability, Solubility, Log D, and Metabolic Stability Characteristics... 

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). 

Complementary to the simple adsorption test, the mass balance of the separation could be investigated. This method is more accurate to determine the loss of free drug, which may occur due to variations in sample preparations methods, non-specific protein binding and to metabolism. The latter may also be tested in separate stability tests in plasma or applied matrix. 

An example for an automated stability test in plasma is described by Linget and du Vignaud (1999). Incubations are performed on a 215 Gilson liquid handler. Incubation was done at substrate concentrations of 50 pM on 96 deep well plates. Each incubation tube contained 375 pL of a 200 pM test compound solution (in 0.1 M Tris buffer with 3% BSA, added to assist dissolution of compounds with poor solubility) and 1125 pL of plasma. Samples are taken after incubation times of 0, 1, 2, 3, 4 and 5 min. At each of these time points an aliquot of the incubation mixture was transferred from the incubation tube into a well in a 96 deep well plate containing an equal volume of acetonitrile for quenching by protein precipitation followed by centrifugation of the plates. Supernatants were analyzed by HPLC for metabolic screening. 

Figure 11-15. Flow diagram for performing intelligent metabolite ID studies. Compounds are incubated with liver microsomes or hepatocytes at a test concentration of 1 xM over a limited time course. The percent of substrate remaining after 30-min incubation is determined on-the-fly. Compounds exhibiting poor metabolic stability are automatically queued for detailed metabolite ID studies. This approach enables metabolic stability and metabolite ID data to be generated in a completely automated, independent manner.

Many types of modeling techniques are available in the discovery phase of drug development, from structure activity relationships (SAR) to physiology based pharmacokinetics (PBPK) and pharmacokinetics-/pharmacodynamics (PK/PD) to help choosing some of the lead compounds. Some tests that are carried out by discovery include techniques related to structure determination, metabolism, and permeability NMR, MS/MS, elemental analysis, PAMPA, CACO-2, and in vitro metabolic stability. Although they are important as a part of physicochemical molecular characterization under the biopharmaceutics umbrella, they will not be discussed here. The reader can find relevant information in numerous monographs [9,10]. 

The model can be used to evaluate the metabolic stability from the 3D structure of drug candidates prior to experimental measurements. Thus, we have used a test set of 1346 compounds from Johnson Johnson [20]. 

Figure 8.6 shows the projection of 1346 compounds from Johnson Johnson on the VolSurf metabolic stability model. The projected compounds are color-coded according to their percentage experimental metabolic stability (%MS) the red color defines compounds with %MS > 95, while the blue color defines compounds with %MS < 40. The figure shows that the great majority of projected compounds with %MS > 95 are predicted to be of medium or high stability for the metabolic activity of the CYP3A4, while compounds with low %MS < 40 are predicted to be unstable. The presence of outliers may be explained by the fact that the experimental %MS of the test set compounds is obtained from the activity of all CYP family enzymes (2C9, 3A4, 2D6 etc.), while the model uses only 3A4 mediated information. 

---