Pharmacological approaches to studying platelet function: an overview.

Abstract

AbstractAlthough pharmacology may be strictly viewed as the study of drugs (see, for example, the British Pharmacological Society Web site at http://www.bps.ac.uk/BPS.html), for many of us it also involves the use of drugs to study receptors. Indeed, the fundamental principle behind a pharmacological approach to the study of any biological system is that quantitative analysis of the effects of drugs on the responses of cells, tissues,or whole animals can provide useful information on the receptors involved. The approach is well-suited to situations where it is relatively easy to measure a response that is closely related to receptor activation, and although originally developed using isolated smooth-muscle preparations, platelets are also a very suitable system. Indeed, platelets have some advantages over smooth-muscle preparations in this respect, as the problem of diffusion of drugs through solid tissues is largely avoided in a suspension of cells. In addition, because in general each measurement is made on a separate sample of cells, there is no risk of desensitization due to repetitive addition of drugs to a single tissue, although obviously there may be time-dependent changes in the responses, which have to be taken into account. An important consideration is which response to measure: for platelets, one has the choice of overall functional responses such as shape change, aggregation, and the release of granule contents, which are more complex but may be of pathophysiological relevance, or of simpler biochemical responses such as changes in the levels of intracellular cyclic AMP or calcium. In theory any quantifiable response can be analyzed, although in some cases the results may differ depending on the response measured.KeywordsP2Y1 ReceptorReceptor OccupancyAgonist ConcentrationQuantifiable ResponseAgonist PotencyThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.