Screening for phospholipidosis induced by central nervous drugs: Comparing the predictivity of an in vitro assay to high throughput in silico assays

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 log P and pKb 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.