Purpose. To describe an extended point-area deconvolution approach for eval
uating drug input rates based on the application of piecewise cubic polynom
ial functions.
Methods. Both the nonimpulse response data and the impulse reference data w
ere independently represented by the piecewise cubic polynomials to obtain
interpolations, numerical integration, and reduced step size for the stairc
ase input rates. A moving average algorithm was employed to compute the inp
ut rate estimates. The method was illustrated using data from preclinical a
nd human studies. Simulations were used to examine the effects of data nois
e.
Results. In all cases examined, the piecewise cubic interpolation functions
combined with the moving average algorithm yielded estimates that were rea
sonable and acceptable. Compared to the standard point-area approach based
on the trapezoidal rule, the present method resulted in estimates that were
closer to the expected values.
Conclusions. The point-area deconvolution analysis is one of the preferred
approaches in assessing pharmacokinetic and biopharmaceutic data when it is
undesirable to assume the functional forms of the input processes. The pre
sent method provides improved performance and greater flexibility of this a
pproach.