To systematically study the pharmacodynamics of a CNS drug early in the development process, we developed and validated a battery of drug-sensitive CNS tests, which we call NeuroCart. Using this test battery, data-intensive phase 1 studies in healthy subjects can be performed to demonstrate the specific, time- and dose-dependent, neurophysiological and/or neuropsychological effects of a compound, thereby confirming whether the test compound reaches its intended target in the CNS - or does not reach its intended target. We use this test battery to demonstrate that a compound passes the blood-brain barrier.

This study assessed the acute physiologic effects over time of (co)administration of Delta9-tetrahydrocannabinol (Delta9-THC) (the main psychoactive compound of cannabis) and 3,4-methylenedioxymethamphetamine (MDMA or "ecstasy") in 16 healthy volunteers. Pharmacokinetics and cardiovascular, temperature, and catecholamine responses were assessed over time. Both single-drug conditions robustly increased heart rate, and coadministration showed additive effects. MDMA increased epinephrine and norepinephrine concentrations, whereas THC did not affect the catecholamine response. Coadministration of MDMA and THC attenuated the increase of norepinephrine concentrations relative to administration of MDMA alone. These results show that THC mediates heart rate increase independent of sympathetic (catecholaminergic) activity, probably through direct cannabinoid receptor type 1 (CB(1)) agonism in cardiac tissue. Furthermore, THC coadministration did not prevent MDMA-induced temperature increase, but it delayed the onset and prolonged the duration of temperature elevation. These effects may be of particular relevance for the cardiovascular safety of ecstasy users who participate in energetic dancing in nightclubs with high ambient temperature.

Resting state fMRI (RSfMRI) and arterial spin labeling (ASL) provide the field of pharmacological Neuroimaging tool for investigating states of brain activity in terms of functional connectivity or cerebral blood flow (CBF). Functional connectivity reflects the degree of synchrony or correlation of spontaneous fluctuations--mostly in the blood oxygen level dependent (BOLD) signal--across brain networks; but CBF reflects mean delivery of arterial blood to the brain tissue over time. The BOLD and CBF signals are linked to common neurovascular and hemodynamic mechanisms that necessitate increased oxygen transportation to the site of neuronal activation; however, the scale and the sources of variation in static CBF and spatiotemporal BOLD correlations are likely different. We tested this hypothesis by examining the relation between CBF and resting-state-network consistency (RSNC)--representing average intranetwork connectivity, determined from dual regression analysis with eight standard networks of interest (NOIs)--in a crossover placebo-controlled study of morphine and alcohol. Overall, we observed spatially heterogeneous relations between RSNC and CBF, and between the experimental factors (drug-by-time, time, drug and physiological rates) and each of these metrics. The drug-by-time effects on CBF were significant in all networks, but significant RSNC changes were limited to the sensorimotor, the executive/salience and the working memory networks. The post-hoc voxel-wise statistics revealed similar dissociations, perhaps suggesting differential sensitivity of RSNC and CBF to neuronal and vascular endpoints of drug actions. The spatial heterogeneity of RSNC/CBF relations encourages further investigation into the role of neuroreceptor distribution and cerebrovascular anatomy in predicting spontaneous fluctuations under drugs.

Background and methods This opinion paper expanded on the WHO “six-step approach to optimal pharmacotherapy,” by detailed exploration of the underlying pharmacological and pathophysiological principles. This exercise led to the identification of a large number of domains of research that should be addressed to make clinical pharmacology progress toward “precision clinical pharmacology,” as a prerequisite for precision medicine. Result In order to improve clinical efficacy and safety in patient groups (to guide drug development) as well as in individuals (to guide therapeutic options and optimize clinical outcome), developments in clinical pharmacology should at least tackle the following: (1) molecular diagnostic assays to guide drug design and development and allow physicians to identify the optimal targets for therapy in the individual patient in a quick and precise manner (to guide selection of the right drug for the right patient); (2) the setting up and validation of biomarkers of target engagement and modification as predictors of clinical efficacy and safety; (3) integration of physiological PK/PD models and intermediate markers of pharmacological effects with the natural evolution of the disease to predict the drug dose that most effectively improves clinical outcome in patient groups and individuals, making use of advanced modeling technologies (building on deterministic models, machine-learning, and deep learning algorithms); (4) methodology to validate human or humanized in vitro, ex vivo, and in vivo models for their ability to predict clinical outcome with investigational therapies, including nucleic acids or recombinant genes together with vectors (including viruses or nanoparticles), cell therapy, or therapeutic vaccines; (5) methodological complements to the gold-standard, large Phase 3 randomized clinical trial to provide clinically relevant and reliable data on the efficacy and safety of all treatment options at the population level (pragmatic clinical trials), as well as in small groups of patients (as low as n = 1); (6) regulatory science, so as to optimize the ethical review process, documentation, and monitoring of clinical trials, improve efficiency, and reduce costs of clinical drug development; (7) interventions to effectively improve patient compliance and to rationalize polypharmacy for the reduction of adverse effects and the enhancement of therapeutic interactions; and (8) appraisal of the ecological and societal impact of drug use to safeguard against environmental hazards (following the “One Health” concept) and to reduce drug resistance. Discussion and conclusion As can be seen, precision clinical pharmacology aims at being highly translational, which will require very large panels of complementary skills. Interdisciplinary collaborations, including non-clinical pharmacologists, will be key to achieve such an ambitious program.