An algorithm for predicting tissue: blood partition coefficients of organic chemicals from n-octanol: water partition coefficient data.

The objectives of the present study were (1) to develop an algorithm to predict tissue:blood partition coefficients (PCs) of organic chemicals from n-octanol: water (Ko/w) PC data, and (2) to apply this algorithm to predict the rat tissue:blood PCs of some relatively hydrophilic organics, particularly ketones, alcohols, and acetate esters. The algorithm, developed by modifying a previously published one, involved predicting tissue:blood PCs of chemicals by dividing their partitioning into tissues by the sum of their partitioning into erythrocytes and plasma. The partitioning of a chemical into tissues, erythrocytes, and plasma was expressed as an additive function of its partitioning into neutral lipids, phospholipids, and water contained in them. The muscle, liver, and adipose tissue:blood PCs predicted with the present method were compared with the experimental values obtained from the literature for five ketones, eight alcohols, and eight acetate esters. The predicted muscle:blood and liver:blood PCs for the set of 21 hydrophilic organics were within a factor of 1.01 and 0.99 (on an average), respectively, of the experimental values. However, the predicted adipose tissue:blood PCs of the hydrophilic organics were greater than the experimental values by a factor of 4.13, which improved when vegetable oil:saline (Ko/s) PCs were used instead of Ko/w PCs (factor of 1.51). Overall, the use of the present algorithm should enable the prediction of tissue:blood PCs for organic chemicals for which Ko/w or Ko/s data are available.