RESUMEN
Drug-induced phospholipidosis is a side effect for which drug candidates can be screened in the drug discovery phase. The numerous in silico models that have been developed as a first line of screening are based on the characteristic physicochemical properties of phospholipidosis-inducing drugs, e.g. high logP and pK(b) values. However, applying these models on a predominantly high lipophilic, basic CNS chemistry results in a high false positive rate and consequently in a wrong classification of a large number of valuable drug candidates. Here, we tested 33 CNS-compounds (24 in vivo negative and 9 in vivo positive phospholipidosis-inducers) in our in house developed in vitro phospholipidosis screening assay (Mesens et al., 2009) and compared its predictivity with the outcome of three different, well established in silico prediction models. Our in vitro assay demonstrates an increased specificity of 79% over the in silico models (29%). Moreover, by considering the proposed plasma concentration at the efficacious dose we can show a clear correlation between the in vitro and in vivo occurrence of phospholipidosis, improving the specificity of prediction to 96%. Through its high predictive value, the in vitro low throughput assay is thus preferred above high throughput in silico assays, characterized by a high false positive rate.