The Blood-Brain Barrier (BBB) is a physical and biochemical barrier that restricts the entry
of certain drugs to the Central Nervous System (CNS), while allowing the passage of others. The ability
to predict the permeability of a given molecule through the BBB is a key aspect in CNS drug discovery
and development, since neurotherapeutic agents with molecular targets in the CNS should be able to
cross the BBB, whereas peripherally acting agents should not, to minimize the risk of CNS adverse
effects. In this review we examine and discuss QSAR approaches and current availability of
experimental data for the construction of BBB permeability predictive models, focusing on the
modeling of the biorelevant parameter unbound partitioning coefficient (Kp,uu). Emphasis is made on
two possible strategies to overcome the current limitations of in silico models: considering the
prediction of brain penetration as a multifactorial problem, and increasing experimental datasets through
accurate and standardized experimental techniques.
Keywords: Blood-Brain Barrier, Brain Penetration, Central Nervous System, In Silico Models, Microdialysis, Passive
Difussion, Pharmacokinetic, Protein Binding, QSAR Models, Unbound Drug Fraction.
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