Microdialysis as an Important Technique in Systems Pharmacology—a Historical and Methodological Review

Microdialysis enables the chemistry of the extracellular interstitial space to be monitored. Use of this technique in patients with acute brain injury has increased our understanding of the pathophysiology of several acute neurological disorders. In 2004, a consensus document on the clinical application of cerebral microdialysis was published. Since then, there have been significant advances in the clinical use of microdialysis in neurocritical care. The objective of this review is to report on the International Microdialysis Forum held in Cambridge, UK, in April 2014 and to produce a revised and updated consensus statement about its clinical use including technique, data interpretation, relationship with outcome, role in guiding therapy in neurocritical care and research applications. Electronic supplementary material The online version of this article (doi:10.1007/s00134-015-3930-y) contains supplementary material, which is available to authorized users.

Many decisions in drug development and medical practice are based on measuring blood concentrations of endogenous and exogenous molecules. Yet most biochemical and pharmacological events take place in the tissues. Also, most drugs with few notable exceptions exert their effects not within the bloodstream, but in defined target tissues into which drugs have to distribute from the central compartment. Assessing tissue drug chemistry has, thus, for long been viewed as a more rational way to provide clinically meaningful data rather than gaining information from blood samples. More specifically, it is often the extracellular (interstitial) tissue space that is most closely related to the site of action (biophase) of the drug. Currently microdialysis (microD) is the only tool available that explicitly provides data on the extracellular space. Although microD as a preclinical and clinical tool has been available for two decades, there is still uncertainty about the use of microD in drug research and development, both from a methodological and a regulatory point of view. In an attempt to reduce this uncertainty and to provide an overview of the principles and applications of microD in preclinical and clinical settings, an AAPS-FDA workshop took place in November 2005 in Nashville, TN, USA. Stakeholders from academia, industry and regulatory agencies presented their views on microD as a tool in drug research and development.

One of the major challenges in the development of central nervous system (CNS)-targeted drugs is predicting CNS exposure in human from preclinical data. In this study, we present a methodology to investigate brain disposition in rats using a physiologically based modeling approach aiming at improving the prediction of human brain exposure. We specifically focused on quantifying regional diffusion and fluid flow processes within the brain. Acetaminophen was used as a test compound as it is not subjected to active transport processes. Microdialysis probes were implanted in striatum, for sampling brain extracellular fluid (ECF) concentrations, and in lateral ventricle (LV) and cisterna magna (CM), for sampling cerebrospinal fluid (CSF) concentrations. Serial blood samples were taken in parallel. These data, in addition to physiological parameters from literature, were used to develop a physiologically based model to describe the regional brain pharmacokinetics of acetaminophen. The concentration–time profiles of brain ECF, CSFLV, and CSFCM indicate a rapid equilibrium with plasma. However, brain ECF concentrations are on average fourfold higher than CSF concentrations, with average brain-to-plasma AUC0 − 240 ratios of 121%, 28%, and 35% for brain ECF, CSFLV, and CSFCM, respectively. It is concluded that for acetaminophen, a model compound for passive transport into, within, and out of the brain, differences exist between the brain ECF and the CSF pharmacokinetics. The physiologically based pharmacokinetic modeling approach is important, as it allowed the prediction of human brain ECF exposure on the basis of human CSF concentrations.