A Robust, Viable, and Resource Sparing HPLC-Based LogP Method Applied to Common Lipophilic Drugs to Help in Expanding in Silico Training Datasets

Abstract

Reliable, experimentally determined partition coefficient P (logP) for most drugs is often unavailable in the literature. Many values are from in silico predictions and may not accurately reflect drug lipophilicity. In this study, a robust, viable, and resource-sparing method to measure logP was developed using reverse-phase high-performance liquid chromatography (RP-HPLC). The logP of twelve common drugs was measured using calibration curves at pH 6 and 9 that were created using reference standards with well- established logP. The HPLC method reported here can be used for high throughput estimation of logP of commonly used drugs. LogP values here showed general agreement with the other few HPLC-based literature logP values available. Additionally, the HPLC-based logP values found here agreed partially with literature logP values found using other methodologies (± 10%). However, there was no strong agreement since there are few experimentally determined literature logP values. This paper shows a facile method to estimate logP without using octanol or computational approaches. This method has excellent promise to provide reliable logP values of commonly used drugs available in the literature. A larger pool of reliable logP values of commonly drugs has the promise to improve the quality of medicinal chemistry, pharmacodynamic, and pharmacokinetic training sets, and models.