Las instituciones científico-medicas en la Murcia del XVIII : un intento fracasado de renovación de la formación médica

Presentamos un estudio sobre dos intentos que, en la Murcia del siglo XVIII, pretendieron mejorar y actualizar la formación que recibían los profesionales sanitarios. Ambos fracasaron, aparentemente por falta de acuerdo entre sus promotores, si bien pensamos que las causas fueron más profundas y habría que buscarlas en la escasa actividad científica que se desarrolló en la ciudad, lo que hacía innecesaria la existencia de instituciones docentes o de otras como las Academias de Medicina

Mechanism-based pharmacokinetic-pharmacodynamic modeling of the dopamine D-2 receptor occupancy of olanzapine in rats

A mechanism-based PK-PD model was developed to predict the time course of dopamine D-2 receptor occupancy (D2RO) in rat striatum following administration of olanzapine, an atypical antipsychotic drug. A population approach was utilized to quantify both the pharmacokinetics and pharmacodynamics of olanzapine in rats using the exposure (plasma and brain concentration) and D2RO profile obtained experimentally at various doses (0.01-40 mg/kg) administered by different routes. A two-compartment pharmacokinetic model was used to describe the plasma pharmacokinetic profile. A hybrid physiology- and mechanism-based model was developed to characterize the D-2 receptor binding in the striatum and was fitted sequentially to the data. The parameters were estimated using nonlinear mixed-effects modeling . Plasma, brain concentration profiles and time course of D2RO were well described by the model; validity of the proposed model is supported by good agreement between estimated association and dissociation rate constants and in vitro values from literature. This model includes both receptor binding kinetics and pharmacokinetics as the basis for the prediction of the D2RO in rats. Moreover, this modeling framework can be applied to scale the in vitro and preclinical information to clinical receptor occupancy

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

A Dynamic Model of Hand-and-Foot Syndrome in Patients Receiving Capecitabine

For the purpose of developing a longitudinal model to predict hand-and-foot syndrome (HFS) dynamics in patients receiving capecitabine, data from two large phase III studies were used. Of 595 patients in the capecitabine arms, 400 patients were randomly selected to build the model, and the other 195 were assigned for model validation. A score for risk of developing HFS was modeled using the proportional odds model, a sigmoidal maximum effect model driven by capecitabine accumulation as estimated through a kinetic-pharmacodynamic model and a Markov process. The lower the calculated creatinine clearance value at inclusion, the higher was the risk of HFS. Model validation was performed by visual and statistical predictive checks. The predictive dynamic model of HFS in patients receiving capecitabine allows the prediction of toxicity risk based on cumulative capecitabine dose and previous HFS grade. This dose-toxicity model will be useful in developing Bayesian individual treatment adaptations and may be of use in the clinic.Institut National de la Sante et de la Recherche Medicale,Paris, Franc