As the U.S. FDA has begun accepting recommendations for the waiver of BE requirement, protocols that prove extremely expensive in the drug development cycle, there is a greater need to develop surrogate models that one day may prove useful in securing waivers for all classes of drugs. Generally, the methods available currently show that the complexity of assay is directly proportional to its correlation with absorption of drugs in humans (Fig. 1). In this chapter, we examine more complex assay systems.
Data from both complex biological and artificial permeation assays can provide valuable information regarding the absorption of a drug (Courtesy of Millipore Corporation, Billerica, Massachusetts, U.S.A.).
Drug transport across epithelial cell barriers, especially the human small intestine, is difficult to predict. The intestinal epithelial cell barrier is a sophisticated organ that has evolved over hundreds of millions of years to become a smart, effective, and selective xenobiotic screen. Nevertheless, there is large interindividual variability in the intestinal transport of drugs. Genetic variability in key proteins is believed to be causal. There is a pressing need to better understand the key processes and how the system components interact at the molecular, cellular, and tissue level to control drug transport and determine drug absorption in the small intestine.
Is it feasible to construct an in silico framework to represent the drug absorption in the small intestine at the cellular level with internal dynamic property and concert with the update molecular biochemical mechanism? This new generation of models and computational tools might integrate the available and emerging information at different levels to better account for and predict observed experimental results. Predicting aqueous solubility with in silico tools solubility is a key drug property. It is however difficult to measure accurately, especially for poorly soluble compounds, and thus numerous in silico models have been developed for its prediction. Some in silico models can predict aqueous solubility of simple, uncharged organic chemicals reasonably well; however, solubility prediction for charged species and drug-like chemicals is not very accurate. However, extrapolating solubility data to intestinal absorption
FIGURE 1 Assay complexity versus correlation with ^ human absorption. Abbreviation: PAMPA, parallel artificial membrane permeability analysis.
Assay complexity from pharmacokinetic and physicochemical data and elucidating crucial parameters for absorption and the potential for improvement of BA are important at the preformulation stages.
The poor oral BA of drugs is generally assumed to be due to physiochemical problems, which result in poor solubility in GI tract or difficulty in diffusion through the small intestine epithelial membrane. Furthermore, the biochemical process also contributes to oral BA. The in vitro cell culture models of the intestinal epithelial cell barrier have evolved to become widely used experimental devices.
In the previous chapter, the log P factor was discussed in detail; in this chapter, we examine other methods of testing transport across membranes.
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