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acids tend to be similar to the octanol values. This reflects the increased potential for partitioning of molecules with basic groups into membranes. Quantitative structure-activity relationship studies have found improved correlations with liposome-derived "surface ion pair" log P values.

The measurement of partitioning is only practical if the compound shows some solubility; insoluble compounds are difficult to characterize and often prove less valuable anyway. A relationship between log P and the observed biology is frequently found in a series where structural modifications do not significantly affect the pKa values. The classical work of Hansch showed that these relationships were often parabolic; hence, the relationship often leads to an optimum value for the log P for a desired activity or selective distribution. Relationships of this type include:

Parabolic: Activity = m logP — c( logP)2 — k (60)

Rectilinear: Activity = m log P — c( log P + 1) — k (61)

where m, k, and c are constants generated using regression analysis to correlate the observed biological data with measured partition coefficients. The mathematical techniques most commonly used to develop this correlation involve use of multi-variate analysis, principal component analysis, and partial least square regression. Standard textbooks of statistics should be consulted to learn more about the applications and limitations of each of these approaches to data analysis.

The use of organic solvents to model complex bilipids is very simplistic. While there have been some successes in modeling the response of compounds, large differences in the activity between molecules of different structures or the activity between enantiomers cannot be easily understood. In these cases, it is very useful to combine physical measurements with molecular modeling, molecular property, and spectroscopic data and use multivariate analysis. For both CNS penetration and gastric absorption, the relationship appears to be parabolic with an optimum log P value of around 2 + 1. Evidence for this comes from a wide variety of experiments in the literature from brain concentration of radiolabeled compounds to behavioral studies.

Other methods of analysis used include molecular properties, such as partial charged surface area (PSA) and study of the effects of hydrogen bonding on drug absorption.

Besides projecting the solubilitythe log P value has several important applications providing greater insight into how the molecule crosses various biological barriers and hence, proves effective as a prospective new lead compound. In general, where passive absorption is assumed, log P can be related to various fixed value ranges (Fig. 11).

Generally, a low log P (below 0) is desirable for injectable products, whereas a medium (0-3) range is suitable for oral administration; transdermal administration requires a higher value (3-4), but once the range of four to seven is reached, we risk the accumulation of the drug in the body fat that can be prove toxic due to accumulation of drug in multiple dosing situations. The renal clearance of drugs with log D (measured at pH 7.4) above zero will decrease renal clearance and increase metabolic clearance; the pKa of drugs also plays an important role here as highly ionized drugs are kept out of cells and thus out of systemic toxicity;

Figure 11 Optimal log P values for absorption from different parts of the gastrointestinal tract.

generally, a pKa of six to eight will be most optimal for transport across various biological membranes.

When making a choice, generally a drug with lowest log P will be desirable; however, it might be required to make a choice between a high versus a low MW molecule; it is known that high molecular weight drugs are generally more allergenic. The goal should be to achieve a minimum hydrophobicity using a combination of log P, pKa, and molecular size. The principle of minimum hydrophobicity keeps the drugs out of CNS that might produce side effects like depression, and son on, which means that most molecules should have a log P lower than 2.0; this technique was used in the design of the new generation of nonsedative antihistamines. A very high lipophilicity should also be avoided because of adverse effects on protein binding and on drug absorption, including solubility.

The ideal drug candidate, going into human studies, should have already been designed with the idea of keeping lipophilicity as low as possible, provided this can be done without loss of affinity to the target receptor.

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