Preclinical dose number and its application in understanding drug absorption risk and formulation design for preclinical species.

In the drug discovery setting, the ability to rapidly identify drug absorption risk in preclinical species at high doses from easily measured physical properties is desired. This is due to the large number of molecules being evaluated and their high attrition rate, which make resource-intensive in vitro and in silico evaluation unattractive. High-dose in vivo data from rat, dog, and monkey are analyzed here, using a preclinical dose number (PDo) concept based on the dose number described by Amidon and other authors (Pharm. Res., 1993, 10, 264-270). PDo, as described in this article, is simply calculated as dose (mg/kg) divided by compound solubility in FaSSIF (mg/mL) and approximates the volume of biorelevant media per kilogram of animal that would be needed to fully dissolve the dose. High PDo values were found to be predictive of difficulty in achieving drug exposure (AUC)-dose proportionality in in vivo studies, as could be expected; however, this work analyzes a large data set (>900 data points) and provides quantitative guidance to identify drug absorption risk in preclinical species based on a single solubility measurement commonly carried out in drug discovery. Above the PDo values defined, >50% of all in vivo studies exhibited poor AUC-dose proportionality in rat, dog, and monkey, and these values can be utilized as general guidelines in discovery and early development to rapidly assess risk of solubility-limited absorption for a given compound. A preclinical dose number generated by biorelevant dilutions of formulated compounds (formulated PDo) was also evaluated and defines solubility targets predictive of suitable AUC-dose proportionality in formulation development efforts. Application of these guidelines can serve to efficiently identify compounds in discovery that are likely to present extreme challenges with respect to solubility-limited absorption in preclinical species as well as reduce the testing of poor formulations in vivo, which is a key ethical and resource matter.