Theoretical predictions of drug absorption in drug discovery and development

The clinical development of new drugs is often terminated because of unfavourable pharmacokinetic properties such as poor intestinal absorption after oral administration. Intestinal permeability and solubility are two of the most important factors that determine the absorption properties of a compound. Efficient and reliable computational models that predict these properties as early as possible in drug discovery and development are therefore desirable. In this review, we first discuss the implementation of predictive models of intestinal drug permeability and solubility in drug discovery and development. Secondly, we discuss the mechanisms of intestinal drug permeability and computational methods that can be used to predict it. We then discuss factors influencing drug solubility and models for predicting it. We finally speculate that once these and other predictive computational models are implemented in drug discovery and development, these processes will become much more effective. Further, an increased fraction of drug candidates that are less likely to fail during clinical development will be selected.

Prediction of the volume of distribution of a drug: which tissue-plasma partition coefficients are needed?

The aim of this study was to identify the tissue-plasma partition coefficients (Kp) needed for an initial prediction of the volume of distribution at steady state (Vd(ss)) of a drug in humans. Values of Kp were collected from the literature. Only Kp values plausibly representing true steady state distribution were accepted, and data had to be available for muscle, fat, skin and at least five other organs. The apparent volume of distribution of a drug in an organ/tissue (Vapp) was calculated as Kp multiplied by the volume of the organ/tissue, and the Vd(ss) as the sum of all available Vapp values. The percentage contribution of each Vapp to the Vd(ss) was estimated. In addition, linear regressions were calculated between Kp values of all drugs in a specific organ/tissue and Kp in muscle or fat. Finally, the Vd(ss) was re-calculated using (for basic drugs) the Kp in fat to calculate Vapp in fat and lungs and the Kp in muscle for the Vapp of all other organs/tissues. The two sets of estimates of Vd(ss) were compared by linear regression. The same calculations were performed for acidic drugs, except that muscle Kp was used also forthe lungs. Distribution to fat and muscle accounted for 84% (61-91%) (median and range) of the total estimated Vd(ss) of the basic drugs (n = 17). The regressions between Kp in organs/tissues and muscle Kp were statistically significant except in the case of liver. For acidic drugs (n = 18), distribution to fat and muscle accounted for 65% (42-92%) of Vd(ss), and the regressions of Kp were significant for all organs/tissues except kidney and bone. For both types of drugs, correlations between organ/tissue Kp values and Kp in fat were generally worse. There were excellent linear correlations between Vd(ss) calculated by means of only two Kp values and the originally calculated Vd(ss) (r2> or = 0.99 for both basic and acidic drugs; slopes were notsignificantly different from unity). Thus, initial estimation of the Vd(ss) of a new drug can normally be based on only two Kp values, those of muscle and fat. The muscle Kp can be used to represent all lean tissues, including the residual "carcass", with the exception that fat Kp can be used for distribution of basic drugs to lungs.