An extended point-area deconvolution approach for assessing drug input rates

To describe an extended point-area deconvolution approach for evaluating drug input rates based on the application of piecewise cubic polynomial functions.

Both the nonimpulse response data and the impulse reference data were independently represented by the piecewise cubic polynomials to obtain interpolations, numerical integration, and reduced step size for the staircase input rates. A moving average algorithm was employed to compute the input rate estimates. The method was illustrated using data from preclinical and human studies. Simulations were used to examine the effects of data noise.

In all cases examined, the piecewise cubic interpolation functions combined with the moving average algorithm yielded estimates that were reasonable 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.

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 present method provides improved performance and greater flexibility of this approach.