ABSTRACT:New, more efficient methods of estimating unbound drug concentrations in the central nervous system (CNS) combine the amount of drug in whole brain tissue samples measured by conventional methods with in vitro estimates of the unbound brain volume of distribution (V u,brain ). Although the brain slice method is the most reliable in vitro method for measuring V u,brain , it has not previously been adapted for the needs of drug discovery research. The aim of this study was to increase the throughput and optimize the experimental conditions of this method. Equilibrium of drug between the buffer and the brain slice within the 4 to 5 h of incubation is a fundamental requirement. However, it is difficult to meet this requirement for many of the extensively binding, lipophilic compounds in drug discovery programs. In this study, the dimensions of the incubation vessel and mode of stirring influenced the equilibration time, as did the amount of brain tissue per unit of buffer volume. The use of casette experiments for investigating V u,brain in a linear drug concentration range increased the throughput of the method. The V u,brain for the model compounds ranged from 4 to 3000 ml ⅐ g brain ؊1 , and the sources of variability are discussed.The optimized setup of the brain slice method allows precise, robust estimation of V u,brain for drugs with diverse properties, including highly lipophilic compounds. This is a critical step forward for the implementation of relevant measurements of CNS exposure in the drug discovery setting.Current drug discovery programs strategically focus on achieving a mechanistic and quantitative understanding of the time course of pharmacological effects and how they are related to drug exposure and the drug-target interaction. This approach identifies key issues for lead optimization as well as facilitating predictions of human exposure to the drug. A critical step in the establishment of these pharmacokinetic-pharmacodynamic relationships is the estimation of exposure to the drug in experimental animals. The unbound drug concentration in plasma is the most relevant and convenient measure of systemic exposure. For centrally acting drugs, however, the bloodbrain barrier can regulate drug exposure in the CNS, and the unbound plasma concentration may no longer reflect the concentration at the target site. Our definition of CNS exposure is the unbound drug concentration in the brain interstitial fluid, C u,brainISF , which surrounds most central drug targets. If a drug target is intracellular, however, exposure would be best defined as the unbound drug concentration in the intracellular fluid. This concentration is regulated not only by events at the blood-brain barrier but also by drug transporters at the brain cell plasma membrane (Dallas et al., 2006). Calculation of C u,brainISF , a rational and increasingly common approach in drug discovery for assessing CNS exposure, is approached by measuring the amount of drug in brain tissue (A brain ) and estimating the unbound brain volume of dis...

The glucose-insulin system is a challenging process to model due to the feedback mechanisms present, hence the implementation of a model-based approach to the system is an on-going and challenging research area. A new approach is proposed here which provides an effective way of characterising glycaemic regulation. The resulting model is built on the premise that there are three phases of insulin secretion, similar to those seen in a proportional-integral-derivative (PID) type controller used in engineering control problems. The model relates these three phases to a biological understanding of the system, as well as the logical premise that the homeostatic mechanisms will maintain very tight control of the system. It includes states for insulin, glucose, insulin action and a state to simulate an integral function of glucose.Structural identifiability analysis was performed on the model to determine whether a unique set of parameter values could be identidied from the available observations, which should permit meaningful conclusions to be drawn from parameter estimation. Although two parameters -glucose production rate and the proportional control coefficient -were found to be unidentifiable, the former is not a concern as this is known to be impossible to measure without a tracer ex- * Principle corresponding author * * Corresponding author

The glucose-insulin system is a challenging process to model due to the feedback mechanisms present, hence the implementation of a model-based approach to the system is an on-going and challenging research area. A new approach is proposed here which provides an effective way of characterising glycaemic regulation. The resulting model is built on the premise that there are three phases of insulin secretion, similar to those seen in a proportional-integral-derivative (PID) type controller used in engineering control problems. The model relates these three phases to a biological understanding of the system, as well as the logical premise that the homeostatic mechanisms will maintain very tight control of the system. It includes states for insulin, glucose, insulin action and a state to simulate an integral function of glucose.Structural identifiability analysis was performed on the model to determine whether a unique set of parameter values could be identidied from the available observations, which should permit meaningful conclusions to be drawn from parameter estimation. Although two parameters -glucose production rate and the proportional control coefficient -were found to be unidentifiable, the former is not a concern as this is known to be impossible to measure without a tracer ex- * Principle corresponding author * * Corresponding author