Feedback modeling of non-esterified fatty acids in rats after nicotinic acid infusions

A feedback model was developed to describe the tolerance and oscillatory rebound seen in non-esterified fatty acid (NEFA) plasma concentrations following intravenous infusions of nicotinic acid (NiAc) to male Sprague-Dawley rats. NiAc was administered as an intravenous infusion over 30 min (0, 1, 5 or 20 μmol kg−1 of body weight) or over 300 min (0, 5, 10 or 51 μmol kg−1 of body weight), to healthy rats (n = 63), and serial arterial blood samples were taken for measurement of NiAc and NEFA plasma concentrations. Data were analyzed using nonlinear mixed effects modeling (NONMEM). The disposition of NiAc was described by a two-compartment model with endogenous turnover rate and two parallel capacity-limited elimination processes. The plasma concentration of NiAc was driving NEFA (R) turnover via an inhibitory drug-mechanism function acting on the formation of NEFA. The NEFA turnover was described by a feedback model with a moderator distributed over a series of transit compartments, where the first compartment (M1) inhibited the formation of R and the last compartment (MN) stimulated the loss of R. All processes regulating plasma NEFA concentrations were assumed to be captured by the moderator function. The potency, IC50, of NiAc was 45 nmol L−1, the fractional turnover rate kout was 0.41 L mmol−1 min−1 and the turnover rate of moderator ktol was 0.027 min−1. A lower physiological limit of NEFA was modeled as a NiAc-independent release (kcap) of NEFA into plasma and was estimated to 0.032 mmol L−1 min−1. This model can be used to provide information about factors that determine the time-course of NEFA response following different modes, rates and routes of administration of NiAc. The proposed model may also serve as a preclinical tool for analyzing and simulating drug-induced changes in plasma NEFA concentrations after treatment with NiAc or NiAc analogues

A Flexible Nonlinear Feedback System That Captures Diverse Patterns of Adaptation and Rebound

An important approach to modeling tolerance and adaptation employs feedback mechanisms in which the response to the drug generates a counter-regulating action which affects the response. In this paper we analyze a family of nonlinear feedback models which has recently proved effective in modeling tolerance phenomena such as have been observed with SSRI’s. We use dynamical systems methods to exhibit typical properties of the response-time course of these nonlinear models, such as overshoot and rebound, establish quantitive bounds and explore how these properties depend on the system and drug parameters. Our analysis is anchored in three specific in vivo data sets which involve different levels of pharmacokinetic complexity. Initial estimates for system (kin, kout, ktol ) and drug (EC50/IC50, Emax/Imax, n ) parameters are obtained on the basis of specific properties of the response-time course, identified in the context of exploratory (graphical) data analysis. Our analysis and the application of its results to the three concrete examples demonstrates the flexibility and potential of this family of feedback models

Smart Sensors and Virtual Physiology Human Approach as a Basis of Personalized Therapies in Diabetes Mellitus

Diabetes mellitus (DM) has a growing incidence and prevalence in modern societies, pushed by the aging and change of life styles. Despite the huge resources dedicated to improve their quality of life, mortality and morbidity rates, these are still very poor. In this work, DM pathology is revised from clinical and metabolic points of view, as well as mathematical models related to DM, with the aim of justifying an evolution of DM therapies towards the correction of the physiological metabolic loops involved. We analyze the reliability of mathematical models, under the perspective of virtual physiological human (VPH) initiatives, for generating and integrating customized knowledge about patients, which is needed for that evolution. Wearable smart sensors play a key role in this frame, as they provide patient’s information to the models

The Hepatocellular Transport of Sulfobromophthalein-Glutathione by Clofibrate Treated, Perfused Rat-Liver

The hypolipidemic drug clofibrate is known to affect the hepatic transport of various organic anions including bilirubin, fatty acids and sulfobromophthalein. Changes in the rate of metabolism and/or intracellular transport have been claimed responsible for the effect. To evaluate these possibilities, the transport of sulfobromophthalein-glutathione, a model compound that does not require metabolism for biliary excretion, was studied in perfused livers isolated from clofibrate-treated and control rats. Cytosolic fatty acid binding protein and glutathione S-transferase activity were also measured. Clofibrate treatment significantly increased liver weight; as a result glutathione S-transferase activity (toward 1-chloro-2,4-dinitrobenzene) fell if expressed per gram of liver (4560\ub1420 (SE) vs 7010\ub1260 nmoles/min for clofibrate treated and controls respectively, p0.5). Irrespective of how it was expressed fatty acid binding protein was significantly increased by the drug treatment. Steady state sulfobromophthalein-glutathione removal velocity was saturble with increasing concentrations of sulfobromophthalein-glutathione in both control and clofibrate-treated livers. Steady state extraction ratio, as well as Vmax and Km for removal, did not differ between the two groups. In keeping with other observations, these data collectively indicate that the hepatic steady state removal of nonmetabolized compounds is not affected by clofibrate. Because the concomitant decrease in glutathione S-transferase activity only reflects an opposite change in liver weight, it remains to be determined whether clofibrate alters the hepatic transport of sulfobromophthalein and other compounds that are conjugated with glutathione solely by changing their rate of metabolis