As stated above, ADME/PK properties have to be incorporated into library design in order to increase the likelihood of successful optimization. PK parameters, which in that respect are crucial for good in vivo efficacy, are the systemic exposure of the compound (dependent on absorption, distribution, metabolism, and excretion), its bioavailability (dependent on absorption and metabolism), and its elimination, i.e. its half-life in the body (dependent on metabolism, distribution, and excretion). All these parameters are well defined in pharmacokinetic textbooks , but are only determined through expensive animal studies. Owing to the tremendous efforts required, animal data for absorption, distribution, metabolism, and excretion are measured for only a small number of the synthesized compounds during optimization, resulting in little information in terms of the structural space of the investigated compounds. First, in vitro PK measurements must be determined, assessing the absorption ability of compounds by measuring their permeation through tissue or cell layers or by assessing the metabolic stability via measurements with hepatocytes or microsomes. In addition, for permeation studies, new approaches have appeared very recently which focus on the use of artificial membrane layers consisting of either an organic liquid (hexadecane) or mixtures of such liquids with phospholipids [14, 15]. Although all the above-mentioned in vitro assays can be performed with relatively high throughput, quantitative structure-activity relationship (QSAR) models for these in vitro parameters over an appropriate structural space are rare in the scientific literature.
Therefore, models are needed that describe the majority of ADME/PK properties in terms of simple, easily accessible parameters, which can be measured and cal culated from the structure. For library design, these calculations have to be fast enough to calculate the property space even for very large virtual libraries.
Most of the ADME/PK properties - at least those which are driven by passive processes - can be explained by appropriate physiological and physicochemical models having physicochemical parameters as their input. Some ADME/PK parameters are partly or exclusively dependent on active processes with partially unclear or insufficient scientific background and, therefore, are not covered in this chapter. Physiological and physicochemical models have the advantage that they can be generalized much more easily than QSAR models and are less dependent on the molecular space of the compounds they are derived from.
The aim of this chapter is to describe briefly some of the models that explore the physicochemical parameter space in which ''drug-like'' molecules are found.
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