Distinguishing between the Permeability Relationships with Absorption and Metabolism To Improve BCS and BDDCS Predictions in Early Drug Discovery

The biopharmaceutics classification
system (BCS) and biopharmaceutics
drug distribution classification system (BDDCS) are complementary
classification systems that can improve, simplify, and accelerate
drug discovery, development, and regulatory processes. Drug permeability
has been widely accepted as a screening tool for determining intestinal
absorption via the BCS during the drug development and regulatory
approval processes. Currently, predicting clinically significant drug
interactions during drug development is a known challenge for industry
and regulatory agencies. The BDDCS, a modification of BCS that utilizes
drug metabolism instead of intestinal permeability, predicts drug
disposition and potential drug–drug interactions in the intestine,
the liver, and most recently the brain. Although correlations between
BCS and BDDCS have been observed with drug permeability rates, discrepancies
have been noted in drug classifications between the two systems utilizing
different permeability models, which are accepted as surrogate models
for demonstrating human intestinal permeability by the FDA. Here,
we recommend the most applicable permeability models for improving
the prediction of BCS and BDDCS classifications. We demonstrate that
the passive transcellular permeability rate, characterized by means
of permeability models that are deficient in transporter expression
and paracellular junctions (e.g., PAMPA and Caco-2), will most accurately
predict BDDCS metabolism. These systems will inaccurately predict
BCS classifications for drugs that particularly are substrates of
highly expressed intestinal transporters. Moreover, in this latter
case, a system more representative of complete human intestinal permeability
is needed to accurately predict BCS absorption.