126.96.36.199 Transporter- and Paracellular-Mediated Absorption
PAMPA is a high-throughput, non-cell-based permeability model that provides estimates of the passive transcellular permeability property. The lack of any functional drug transporters and paracellular pores in PAMPA makes it an inappropriate model for compounds that are absorbed via transporter- and pore-mediated processes. However, the lack of transporter- and pore-mediated permeability might be an advantage of the PAMPA model. Because the PAMPA provides an
Figure 5.5. Correlation of PAMPA permeability with lipophilicity. Log D (pH 7.4) value was calculated using ACD/Log D module
uncontaminated transcellular passive permeability data, it could be more useful in constructing the structure-permeability relationship at the chemistry bench. Lipophilicity (most commonly expressed as Log P or Log D values) plays a major role in passive diffusion. An adequate lipophilicity is required for a permeant to travel across the phospholipid membrane. However, as shown in the Fig. 5.5, the PAMPA permeability of 22 marketed drugs (listed in Table 5.3) did not demonstrate any correlation with lipophilicity alone. As expected, several other factors (e.g., polar surface area, molecular volume/flexibility, hydrogen bonding, etc.) in addition to lipophilicity are involved in dictating the overall passive permeability of any compound. Although pharmaceutically important drug transporters (e.g., PEPT1, OCT, OAT, etc.) are functionally expressed in Caco-2 cells (Sun et al., 2002; Anderle et al., 2004; Behrens et al., 2004), they are quantitatively under-expressed when compared to in vivo situation. For example, beta-lactam antibiotics (e.g., cephalexin, amoxicillin) and ACE inhibitors, that are known unequivocal substrates of dipeptide transporters, are poorly permeable across the Caco-2 cell monolayer despite the fact that they are completely absorbed in vivo (Chong et al., 1996). This model is likely to generate false negatives with drug candidates that are transported by carrier-mediated process. Caco-2 cells have tight junctions that are significantly tighter compared to human intestine, and it does not differentiate drugs that are absorbed primarily via paracellular pathway. The low molecular weight hydrophilic compounds (e.g., metformin, ranitidine, atenolol, furosemide, hydrochlorothiazide, etc.) showed poor permeability (i.e., equal or less than mannitol) in Caco-2 cells despite adequate absorption (greater than 50% of dose) in humans. Therefore, models such as PAMPA and Caco-2 cells can only serve as a one-way screen such that compounds with high permeability in these models are typically well absorbed, however, compounds with low permeability cannot be ruled out as poorly absorbed compounds in humans.
188.8.131.52 Incomplete Mass-Balance Due to Nonspecific Binding
Nonspecific drug binding to plastic devices and cells during the permeability study is a common problem which often makes the data interpretation difficult. Permeability is calculated based on several factors: the amount of drugs appeared in the receiver compartment, the initial concentration in the donor compartment, and the surface area of the physical barrier (e.g., lipid bilayers and cell monolayer). When significant drug loss occurs during the incubation due to a nonspecific binding, two things occur (1) the concentration in the donor compartment (a driving force) is reduced and (2) the concentration in the receiver compartment is artifac-tually reduced. This will lead to an underestimation of permeability estimates, and potentially lead to false negatives. "Cacophilicty" or "membrane retention" has been used as a term to describe the drug binding to Caco-2 cell monolayer, and the significant binding results in an incomplete recovery. Incomplete recovery is particularly common with lipophilic drug candidates. A few approaches may be able to minimize the nonspecific binding. Rather than using the initial donor concentration, the final donor concentration at the termination of incubation can be used. Assumption is that the nonspecific binding occurs relatively quickly, therefore, the final donor concentration is a better estimate for the concentration gradient between two compartments. For certain drug candidates with poor recovery, the results can be significantly different depending on the calculation method used. Another approach involves addition of serum proteins (bovine serum albumin in case of Caco-2 cells) or surfactants (in case of PAMPA) to the receiver compartment to minimize nonspecific binding, therefore, improving the assay recovery and overall predictability of the model (Aungst et al., 2000; Krishna et al., 2001; Saha and Kou, 2002).
Drug candidates at the early discovery stage are often optimized in terms of SAR around potency and pharmacological activity, and the SAR generally lead to rather lipophilic and poorly soluble candidates (solubility in aqueous buffer <0.01 mg/mL). As a result, significant percentage of new drug candidates cannot be evaluated in the permeability models due to their poor aqueous solubility. This is particularly problematic in the cell-based model because the cells do not tolerate the typical organic cosolvents (e.g., DMSO, PG, etc.) very well. Beyond a small percentage of cosolvent (>1%), the cell tight junction is easily compromised making the data interpretation difficult or impossible (Dimitrijevic et al., 2000; Rege et al., 2001, 2002). Consequently, for some discovery programs, the permeability data cannot be provided for a majority (> 95%) of new compounds because they tend to come from a similar chemotype which may share a problematic
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