Mathematical modeling of the glucose–insulin feedback system is necessary to the
understanding of the homeostatic control, to analyze experimental data, to identify and …

This paper is a survey of existing estimation methods for pharmacokinetic/pharmacodynamic
(PK/PD) models based on stochastic differential equations (SDEs). Most parametric …

Optimal Design for Nonlinear Response Models discusses the theory and applications of
model-based experimental design with a strong emphasis on biopharmaceutical studies …

Diabetes mellitus is a major health risk in many countries, and the incidence rates are
increasing. Diverse therapeutic agents are applied to treat this condition. Since 1960 …

Stochastic differential equations have been shown useful in describing random continuous
time processes. Biomedical experiments often imply repeated measurements on a series of …

Blood glucose (BG) regulation in type 1 diabetic patients has been investigated by
researchers for a long time. Many mathematical models mimicking the physiological …

Growth curve data consist of repeated measurements of a continuous growth process over
time in a population of individuals. These data are classically analyzed by nonlinear mixed …

The metabolic, hormonal and psychological determinants of the feeding behavior in humans
are numerous and complex. A plausible model of the initiation, continuation and cessation of …

Several models of Gastric Emptying (GE) have been employed in the past to represent the
rate of delivery of stomach contents to the duodenum and jejunum. These models have all …

We consider a bidimensional Ornstein–Uhlenbeck process to describe the tissue
microvascularization in anti‐cancer therapy. Data are discrete, partial and noisy …