Classification of Drugs by CNS Access: An Insight from Quantitative Blood-Brain Transport Characteristics
Poster Apr 04, 2012

Kiril Lanevskij, Pranas Japertas and Remigijus Didziapetris, Advanced Chemistry Development Inc.
INTRODUCTION
The ultimate goal of QSAR analysis focusing on blood-brain barrier penetration is the ability to discriminate between CNS active and inactive molecules. The objective of the current study was to establish the relationship between quantitative blood-brain transport parameters and qualitative data indicating whether the compound penetrates into the brain efficiently enough to exhibit action in the central nervous system (CNS).
Two quantitative characteristics were considered: brain/plasma equilibration rate (log [PS • fu,br]), and the extent of brain/plasma partitioning at equilibrium (log BB). Analysis of a diverse data set consisting of >1500 compounds from the World Drug Index (WDI) database with experimentally assigned brain penetration categories revealed that a linear combination of the above mentioned parameters allowed classification of drugs by CNS access with 94% accuracy. Furthermore, the devised classification score correlated well with the unbound brain/plasma partitioning coefficient (log Kp,uu), which is recognized as an unambiguous determinant of brain exposure. The obtained results confirm the validity of the proposed classification approach.
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OTHER POSTERS
During early drug discovery, the study of metabolism plays an essential role in determining which drug candidates move forward into development and later stages. As an alternative to traditional Data Dependent Acquisition (DDA), the use of MSE/All Ions Fragmentation (AIF) has become common in metabolite identification workflows for the analysis of metabolic hot spots. Here we present a solution for analysis of MSE/AlF in metID studies.
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