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| About Dennis Pelletier (Pfizer) |
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Modeling In Silico Prediction of Phospholipidosis Induction Potential
Dennis Pelletier, Pfizer Global Research & Development
Compound-induced phospholipidosis is a generalized condition in humans and animals that is characterized by an intracellular accumulation of phospholipids and the concurrent development of concentric lamellar bodies. It can occur in multiple tissue types but is often observed in lymphocytes, lung, and liver, and is usually only seen at compound doses that are many multiples of the expected efficacious dose. In addition, the condition is generally considered to be reversible, with disappearance of the phospholipidotic inclusions within days or weeks following cessation of compound administration.
While the risk associated with compound-induced phospholipidosis is considered manageable, due to the effect being seen only at doses that are many multiples of the intended therapeutic dose (i.e. a wide therapeutic index), its observation can lead to delays in compound development while additional studies are carried out to demonstrate reversibility. Factors relating to the intended indication of the compound such as duration of therapy and target population (e.g. pediatric) can also alter the comfort level a development team has for this finding. Additionally, induction of phospholipidosis in certain tissue types (e.g. CNS) may require larger therapeutic indices.
It has long been recognized that cationic amphiphilic drugs (CADs) are associated with induction of phospholipidosis. Compounds of this type generally contain a hydrophobic region (typically an aromatic ring or ring system) and a hydrophilic side chain that is positively charged at physiological pH. The publication of an in silico model based on calculation of the physicochemical properties pKa and ClogP has raised the possibility of a high-throughput, low-cost screening tool for predicting phospholipidosis-inducing potential. To be presented are the results of work aimed at defining the predictive capacity of the published model as well as efforts to improve upon the model, including modifications to the existing model rules and a Bayesian model build using a common validation list of compounds.
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