Validation of Early Human Dose Prediction: A Key Metric for Compound Progression in Drug Discovery

Human
dose prediction is increasingly recognized as an important
parameter in Drug Discovery. Validation of a method using only in vitro and predicted parameters incorporated into a PK
model was undertaken by predicting human dose and free Cmax for a number of marketed drugs and AZ Development
compounds. Doses were compared to those most relevant to marketed
drugs or to clinically administered doses of AZ compounds normalized
either to predicted Cmin or Cmax values. Average (AFE) and absolute average (AAFE)
fold-error analysis showed that best predictions were obtained using
a QSAR model as the source of Vss, with Fabs set to 1 for
acids and 0.5 for all other ion classes; for clearance prediction
no binding correction to the well stirred model (WSM) was used for
bases, while it was set to Fup/Fup0.5 for all other ion classes. Using this combination of methods, predicted
doses for 45 to 68% of the Cmin- and Cmax-normalized and marketed drug data sets were
within 3-fold of the observed values, while 82 to 92% of these data
sets were within 10-fold. This method for early human dose prediction
is able to rank, identify, and flag risks or optimization opportunities
for future development compounds within 10 days of first synthesis.