Fingerprints of CNS Drug Effects: a Plasma Neuroendocrine Reflection of D-2 Receptor Activation Using Multi-Biomarker Pharmacokinetic/pharmacodynamic Modelling

BACKGROUND AND PURPOSE Because biological systems behave as networks, multi-biomarker approaches increasingly replace single biomarker approaches in drug development. To improve the mechanistic insights into CNS drug effects, a plasma neuroendocrine fingerprint was identified using multi-biomarker pharmacokinetic/pharmacodynamic (PK/PD) modelling. Short-and long-term D-2 receptor activation was evaluated using quinpirole as a paradigm compound. EXPERIMENTAL APPROACH Rats received 0, 0.17 or 0.86 mg.kg(-1) of the D-2 agonist quinpirole i.v. Quinpirole concentrations in plasma and brain extracellular fluid (brainECF), as well as plasma concentrations of 13 hormones and neuropeptides, were measured. Experiments were performed at day 1 and repeated after 7-day s.c. drug administration. PK/PD modelling was applied to identify the in vivo concentration-effect relations and neuroendocrine dynamics. KEY RESULTS The quinpirole pharmacokinetics were adequately described by a two-compartment model with an unbound brainECF-to-plasma concentration ratio of 5. The release of adenocorticotropic hormone (ACTH), growth hormone, prolactin and thyroid-stimulating hormone (TSH) from the pituitary was influenced. Except for ACTH, D-2 receptor expression levels on the pituitary hormone-releasing cells predicted the concentration-effect relationship differences. Baseline levels (ACTH, prolactin, TSH), hormone release (ACTH) and potency (TSH) changed with treatment duration. CONCLUSIONS AND IMPLICATIONS The integrated multi-biomarker PK/PD approach revealed a fingerprint reflecting D-2 receptor activation. This forms the conceptual basis for in vivo evaluation of on-and off-target CNS drug effects. The effect of treatment duration is highly relevant given the long-term use of D-2 agonists in clinical practice. Further development towards quantitative systems pharmacology models will eventually facilitate mechanistic drug development.