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10.4 Absorption / Permeability
When a compound is crossing a membrane by purely passive diffusion, a reasonable permeability estimate can be made using single molecular properties such as log D
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or hydrogen bonding (see Chapters 1 and 3). Currently in vitro methods such as Caco-2 monolayers are widely used to make absorption estimates (see Chapter 3). The trend is to move to 24- and 96-well plates, but this is possibly the limit for this screen in its current form. New technologies need to be explored. Artificial membranes have been suggested for high throughput permeability assessment [19-23]. However, besides the purely physicochemical component contributing to membrane transport, many compounds are affected by biological events including the influence of transporters and metabolism. Many drugs appear to be substrates for transporter proteins, which either promote or are detrimental to permeability. Currently no theoretical SAR basis exists to account for these effects. Ultimately the fastest method is to make absorption estimates in silico (see Chapter 3) [24, 25]. Experience in the use of all the above approaches needs to be gathered before these systems can be considered to be reliable and truly predictive.
Important progress in terms of higher throughput in ADME/PK work was realized recently by wider use of liquid chromatography/mass spectrometry (LC/MS), which has now become a standard analytical tool . Flow NMR spectroscopy has become a routine method to resolve and identify mixtures of compounds and has found applications in drug metabolism and toxicology studies .
Mixture dosing (N-in-One dosing, or cocktail dosing, or cassette dosing) has been explored as a means of achieving higher throughput [28-30]. Efficient groupings may consist of 10-25 compounds. In order to avoid potential interactions the dose should be kept as low as possible. Another approach is the analysis of pooled plasma samples and the use of an abbreviated standard curve per compound . From an estimated AUC a ranking of compounds offers early PK information.
A rapid spectrofluorimetric technique for determining drug-serum protein binding in high throughput mode has been described .
P-glycoprotein-mediated efflux is a potential source of peculiarities in drug pharmacokinetics, such as non-linearity. This includes dose-dependent absorption, drug-drug interactions, intestinal secretion and limited access to the brain. Assays are in development to quantify the interaction between transporters and drugs. One of the first is a 96-well plate assay for P-gp binding [33, 34] and an MDR1 ATPase test .
The balance between renal clearance and metabolism is readily predicted by physicochemical properties . Rate of metabolism and formation of metabolic products can be screened for, using liver microsomal systems and mass spectrometry. The
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utility of pulsed ultrafiltration-mass spectrometry, where microsomal fractions are entrapped in stirred ultrafiltration chambers and the output of the chamber is introduced directly into an electrospray mass spectrometer shows particular promise .
Higher throughput screening with human cytochrome P450 to study P450-medi-ated metabolism is now available [38-40]. Similarly, rapid microtitre plate assays to conduct for example, P450 enzyme inhibition studies have been developed, using individually expressed CYP enzymes (Supersomes) .
Computational Approaches in PK and Metabolism
A number of approaches are available or under development to predict metabolism, including expert systems such as MetabolExpert (Compudrug), Meteor (Lhasa), MetaFore  and the databases Metabolite (MDL) and Metabolism (Synopsys) . Ultimately such programs may be linked to computer-aided toxicity prediction based on quantitative structure-toxicity relationships and expert systems for toxicity evaluation such as DEREK (Lhasa) (see also Chapter 8) .
QSAR and neural network approaches in combination with physiologically-based pharmacokinetic (PBPK) modelling hold promise in becoming a powerful tool in drug discovery . Below we briefly discuss some of these studies.
QSPR and QSMR
As a possible alternative to in vitro metabolism studies, QSAR and molecular modelling may play an increasing role. Quantitative structure-pharmacokinetic relationships (QSPR) have been studied for nearly three decades [42, 45-52]. These are often based on classical QSAR approaches based on multiple linear regression. In its most simple form, the relationship between PK properties and lipophilicity has been discussed by various workers in the field [36, 49, 50].
Similarly, quantitative structure-metabolism relationships (QSMR) have been studied . QSAR tools, such as pattern recognition analysis, have been used to e. g. predict phase II conjugation of substituted benzoic acids in the rat .