Dose-response-time data analysis involving nonlinear dynamics, feedback and delay.

This paper offers dose-response-time data analysis of four different case studies where the pharmacological response (neuronal ACh-release, tail-flick response, locomotor activity, NEFA) was modelled by a biophase-driven turnover model. The analysis uses a mathematical/analytical perspective in which analytic properties of the models involved are exploited in order to address the dual challenge of extracting information from these time-series about (i) the biophase kinetics following different routes of administration and (ii) pharmacodynamic issues such as transduction, saturation, and adaptation, and more specifically, parameter identifiability, such as correct estimation of potency (SD50 or ID50). It is shown how many of these estimates can be obtained by analytical means, giving considerable insight in the dynamics involved.