Clinical pharmacology in neuroscience drug discovery: quo vadis?

Clinical Pharmacology in Neuroscience Drug Discovery in recent years has concentrated on First Time in Human safety and pharmacokinetics. The more traditional pharmacological research in humans has been reduced mainly as a response to the difficulty of developing human pharmacology models in neuroscience diseases. As a consequence, opportunities are being missed to aid in target selection and in target validation. The decision of big Pharma to reduce investment from the Neurosciences has had implications for clinical pharmacologists in this area. It remains to be seen whether academia, government laboratories and contract houses will respond to the challenge of carrying out increased Clinical Pharmacology in the Neurosciences.

Experiments with cocaine and heroin addicts--are they predictive?

Treating cocaine addiction using dopamine replacement strategies, treats withdrawal but not relapse. Experiments with diverse pharmacological agents shows involvement of multiple pharmacologies and new approaches are emerging to treat the drug seeking behaviour and craving associated with relapse. Neuropathological studies are showing structural and connectivity changes in the brain of addicts which appear permanent, making control of learned behaviours associated with these changes extremely challenging. Heroin addiction is treated successfully with opiate replacement strategies but relapse and switch to other drugs of abuse remains. Combination therapies are partially successful in treating co-abused substances but do little to the heroin relapse rate. As with cocaine, attention is shifting to understanding the neuropathological changes, particularly in the pre-frontal cortex and hippocampus.

Why receptor reserve matters for neurokinin1 (NK1) receptor antagonists.

The difference in location between the receptor occupancy curve of an agonist and its functional response has been described as receptor reserve. This "reserve" for a specific receptor has been found to differ from tissue to tissue and between agonists acting on the same tissue. Recently, two structurally different neurokinin 1 (NK1) receptor antagonists were taken into human and both were tested as antidepressants and for insomnia. Vestipitant and Casopitant both have high affinity for the human NK1 receptor (pKi = 9.4 and 10.2, respectively). In human, at the chosen clinical doses, receptor occupancy was measured in the frontal cortex, at 24 hours post administration, as ∼90% for vestipitant (15 mg) and ∼100% for casopitant (30 mg). In patients with moderate to severe major depression, vestipitant given at 15 mg for 8 weeks showed no statistical significant benefit as measured by change in baseline in HAM-D total score; whereas casopitant at 80 mg achieved statistically significant improvement versus placebo at week 8 (LOCF HAMD17 = -2.7, p = 0.023). A lower dose of 30 mg showed a clear but not significant separation from placebo. However, in acute studies in insomnia, both vestipitant and casopitant at 15 mg and 30 mg, respectively, significantly reduced latency to persistent sleep, wakenings after sleep onset and increased total sleep time by similar amounts. These clinical results suggest that for major depression the receptor occupancy of an NK1 antagonist needs to be very high (almost 100%), whereas, for insomnia a lower occupation is sufficient to give clinical effect.

Results from 2 randomized, double-blind, placebo-controlled studies of the novel NK1 receptor antagonist casopitant in patients with major depressive disorder.

Clinical study results for neurokinin (NK) receptor antagonists in the treatment of depression have been mixed, with Phase III studies failing to fulfill the early promise demonstrated in Phase II studies. Casopitant, a selective NK1 antagonist that achieves nearly complete receptor occupancy was studied in 2 randomized, placebo-controlled, double-blind, Phase II trials in depressed outpatients to test the hypothesis that nearly complete NK1 receptor occupancy is required to achieve antidepressant efficacy. Study 092 used an interactive voice response system to recruit depressed patients with baseline Hamilton Depression (17-item, HAMD17) total scores higher than 24 who were randomized to fixed-dose casopitant 30 mg/d, 80 mg/d, or placebo for 8 weeks (n = 356). Study 096 required Carroll Depression Scale-Revised self-assessment scores of higher than 24 for randomization to casopitant 120 mg/d, paroxetine 30 mg/d (both reached via forced titration), or placebo for 8 weeks (n = 362). In study 092, casopitant 80 mg but not 30 mg achieved statistically significant improvement versus placebo on the primary outcome measure, week 8 last observation carried forward change from baseline HAMD17 (difference = -2.7; 95% confidence interval, -5.1 to -0.4, P = 0.023). In study 096, neither casopitant nor paroxetine achieved statistical separation from placebo at end point on HAMD17 (casopitant difference = -1.7; 95% CI, -3.8 to 0.4, P = 0.282). Casopitant and paroxetine were generally well tolerated in most patients. These studies suggest that NK1 antagonists that have nearly complete receptor occupancy may be effective in the treatment of depression.

Effect of sustained-release (SR) bupropion on craving and withdrawal in smokers deprived of cigarettes for 72 h.

RATIONALE: Sustained-release (SR) bupropion enhances quit rates of smokers, generally decreases tobacco withdrawal, and in some studies, reduces craving. OBJECTIVE: Investigate the effects of SR bupropion on craving and withdrawal during cigarette abstinence. METHODS: Twenty three smokers participated in three 17-day periods composed of 14 out-patient days followed by 3 (72 h) in-patient days. During the out-patient days, subjects received SR bupropion, placebo, or no drug. During the in-patient days, subjects were abstinent from cigarettes on two occasions while receiving either SR bupropion or placebo and smoked freely during the other occasion. SR bupropion was titrated over the first three out-patient days followed by a fixed dose (300 mg/day) for 14 days (including the three in-patient abstinence days). Cigarette craving, withdrawal, and selected physiological measures were assessed repeatedly over the 72-h periods. RESULTS: During the 72-h periods, craving intensity was significantly lower with free smoke and SR bupropion than with placebo, and significantly lower during free smoke than during SR bupropion. Overall withdrawal symptoms were significantly lower with free smoke than with either placebo or SR bupropion. Among individual withdrawal symptoms (excluding craving), appetite increase was significantly reduced during SR bupropion compared to placebo. During placebo and SR bupropion, craving intensity displayed a circadian pattern that was different from that observed during free smoke. CONCLUSIONS: SR bupropion reduced craving and appetite increase during smoking abstinence. These findings support the hypothesis that craving and withdrawal symptoms may be controlled by distinct central nervous system pathways.

EEG power spectra and auditory P300 during free smoking and enforced smoking abstinence.

We investigated resting EEG and auditory P300 during free smoking and 36 h of enforced smoking abstinence in 12 healthy volunteers. Resting EEG was recorded on 19 scalp leads and auditory P300 was obtained by an oddball paradigm task. Spectral analysis of EEG (absolute and relative power, mean frequency), latency and amplitude of auditory P300 were considered for statistical analysis. EEG changes were not significant during free smoking but were significant during smoking abstinence. Theta absolute power increased by +57% (P<.001), whereas alpha and delta absolute power increased by +26% (P<.01) and +19% (P<.01), respectively; theta absolute power change was delayed and prolonged. Alpha mean frequency reduced by -0.31 Hz (P<.001), whereas delta, theta and beta1 mean frequency increased by +0.13 Hz (P<.05), +0.09 Hz (P<.05) and +0.23 Hz (P<.01), respectively. Auditory P300 amplitude and latency were unaffected by smoking abstinence. Resting EEG, but not auditory P300, was sufficiently sensitive to detect changes during enforced smoking abstinence, and EEG bands had different temporal changes.

Smokers deprived of cigarettes for 72 h: effect of nicotine patches on craving and withdrawal.

RATIONALE: Research on the effects of nicotine abstinence and nicotine replacement has not provided consistent information about the impact of replacement therapies on tobacco withdrawal and craving. OBJECTIVE: . This study investigated craving and withdrawal symptoms over a 72-h period of abstinence from cigarettes. METHODS: . Twenty-four healthy volunteers, not intending to quit smoking, were housed in an experimental unit during three 72-h conditions, consisting of either free smoking, enforced smoking cessation with nicotine replacement therapy (NRT) patches, or enforced smoking cessation with placebo patches. The conditions were adhered to using a randomized crossover design, each separated by at least 10 days of washout. Patches, administered in a double-blind fashion, were given as nicotine (21 mg/24 h) and placebo every 24 h. Self-reported cigarette craving and withdrawal were assessed using multi-item scales at fixed intervals over each condition period. Urinary and plasma cortisol levels were also assayed at fixed intervals over each period. RESULTS: Craving intensity was significantly lower with free smoke than with placebo and with NRT patches than with placebo. No difference in craving levels was found between those who smoked or those who had NRT patches. Withdrawal symptoms were significantly lower with free smoke than with either placebo or NRT patches, but there was no difference in levels of withdrawal between those on NRT patches and those on placebo. During the placebo and NRT patch periods, craving intensity displayed a circadian rhythm, with craving levels lowest in the morning and peaking in the evening. Nicotine delivered via the patch had no impact on these circadian variations in craving. There was no evidence of systematic temporal variations in craving levels during the free smoking period. CONCLUSIONS: The data suggested that craving and withdrawal symptoms may be sustained by different physiological pathways, and that only selected components of cigarette craving are influenced by NRT.

Correlation and predictive performances of saliva and plasma nicotine concentration on tobacco withdrawal-induced craving.

AIMS: To investigate whether saliva is a useful alternative to plasma for routine monitoring of nicotine and evaluate the predictive performances of saliva and plasma concentration on craving estimated by a Tiffany Questionnaire on Smoking Urge-Brief Form. METHODS: Thirteen healthy smokers were enrolled in a randomized, two period, crossover trial. Linear and power models were evaluated to predict the plasma nicotine concentrations from the saliva measurements, whereas a population PK/PD indirect response model was used to predict craving using either saliva or plasma nicotine concentration as the independent variable. RESULTS: The results of the analysis revealed that the power model was preferred over the linear one. The bias on the predicted plasma concentrations was of 0.47 ng ml-1 with a 95% confidence interval of [-0.57, 1.52] and a precision of 5.68 ng ml-1. The placebo effect model was initially fitted to data, then the indirect response approach (with inhibition in k(in)) was used to model the craving scores using plasma and saliva nicotine concentrations as independent variables. The two indirect response PK/PD models based on saliva and plasma nicotine concentrations, adequately described the onset, extent, and duration of craving. The maximal inhibition I(max) was 0.722 and 1 for saliva and plasma concentrations while the estimated nicotine concentrations giving 50% of the maximal inhibition were 269 ng ml-1 and 24.3 ng ml-1 for saliva and plasma, respectively. CONCLUSIONS: A good correlation between plasma and saliva nicotine concentrations has been found using a power model. Comparable values of bias and precision on the model-predicted craving indicate that plasma and saliva concentration can equally well be used to predict the onset of tobacco withdrawal induced craving. Analysis of saliva definitely offers a potentially more attractive way to assess nicotine concentration values, as samples can be collected easily and noninvasively. In addition, saliva sampling avoids the pain and discomfort involved in venepuncture. In studies that assess psychological measures, such as subjective mood, blood collection could present a possible confounding factor because of the anxiety and pain that accompanies it. For these reasons saliva can reasonably be considered as the ideal sampling site for all clinical studies conducted for the evaluation of the potential activity of drugs on nicotine deprivation symptoms.

Absolute quantification of cerebral blood flow with magnetic resonance, reproducibility of the method, and comparison with H2(15)O positron emission tomography.

While H2(15)O positron emission tomography (PET) is still the gold standard in the quantitative assessment of cerebral perfusion (rCBF), its technical challenge, limited availability, and radiation exposure are disadvantages of the method. Recent work demonstrated the feasibility of magnetic resonance (MR) for quantitative cerebral perfusion imaging. There remain open questions, however, especially regarding reproducibility. The main purpose of this study was to assess the accuracy and reproducibility of MR-derived flow values to those derived from H2(15)O PET. Positron emission tomography and MR perfusion imaging was performed in 20 healthy male volunteers, who were chronic smokers, on day 1 and day 3 of a 4-day hospitalization. Subjects were randomly assigned to one of two groups, each with 10 subjects. One group was allowed to smoke as usual during the hospitalization, while the other group stopped smoking from day 2. Positron emission tomography and MR images were coregistered and rCBF was determined in two regions of interest, defined over gray matter (gm) and white matter (wm), yielding rCBF(PET)gm, rCBF(MR)gm, rCBF(PET)wm, and rCBF(MR)wm. Bland-Altman analysis was used to investigate reproducibility by assessing the difference rCBFday3 - rCBFday1 in eight continual-smoker volunteers. The analysis showed a good reproducibility for PET, but not for MR. Mean +/- SD of the difference rCBFday3 - rCBFday1 in gray matter was 6.35 +/- 21.06 and 0.49 +/- 5.27 mL x min(-1) x 100 g(-1) for MR and PET, respectively; the corresponding values in white matter were 2.60 +/- 15.64 and -1.14 +/- 4.16 mL x min(-1) x 100 g(-1). The Bland-Altman analysis was also used to assess MRI and PET agreement comparing rCBF measured on day 1. The analysis demonstrated a reasonably good agreement of MR and PET in white matter (rCBF(PET)wm - rCBF(MR)wm; -0.09 +/- 7.23 mL x min(-1) x 100 g(-1)), while in gray matter a reasonable agreement was only achieved after removing vascular artifacts in the MR perfusion maps (rCBF(PET)gm - rCBF(MR)gm; -11.73 +/- 14.52 mL x min(-1) x 100 g(-1)). In line with prior work, these results demonstrate that reproducibility was overall considerably better for PET than for MR. Until reproducibility is improved and vascular artifacts are efficiently removed, MR is not suitable for reliable quantitative perfusion measurements.

In silico prediction of optimal in vivo delivery properties using convolution-based model and clinical trial simulation.

PURPOSE: To develop a new strategy for the in silico evaluation of the optimal in vivo delivery properties of a drug, minimizing a cost function defined by the brain receptor occupancy obtained in positron-emission tomography experiments. METHODS: A convolution-based model was formulated to link in vivo delivery rate to plasma concentrations whereas a second-stage model was used to link plasma concentrations to the pharmacodynamic effect. A feedback control approach was applied to identify the optimal in vivo delivery rate given an appropriate optimality criterion. Finally, clinical trial simulation was used as a supportive tool for decision-making by evaluating different scenarios accounting for pharmacokinetic/pharmacodynamic parameter uncertainty, inter-subject variability. and drug potency. RESULTS: The results revealed that the mean in vivo delivery time significantly affects brain receptor occupancy whereas the fraction of the dose available for the systemic circulation shows the highest influence on brain receptor occupancy for a given in vivo delivery rate. Finally, variability on receptor occupancy seems to be more affected by the inter-individual variability on the disposition PK parameters. CONCLUSION: The integration of convolution-based model. feedback control approach, and clinical trial simulation offers a unique tool for in ilico improvement of the drug development process by identifying critical issues on drug properties, optimal in vivo delivery rate, and potential problems related to the inter-individual variability.

Estimate the time varying brain receptor occupancy in PET imaging experiments using non-linear fixed and mixed effect modeling approach.

Positron-Emission Tomography (PET) is an imaging technology currently used in drug development as a non-invasive measure of drug distribution and interaction with biochemical target system. The level of receptor occupancy achieved by a compound can be estimated by comparing time-activity measurements in an experiment done using tracer alone with the activity measured when the tracer is given following administration of unlabelled compound. The effective use of this surrogate marker as an enabling tool for drug development requires the definition of a model linking the brain receptor occupancy with the fluctuation of plasma concentrations. However, the predictive performance of such a model is strongly related to the precision on the estimate of receptor occupancy evaluated in PET scans collected at different times following drug treatment. Several methods have been proposed for the analysis and the quantification of the ligand-receptor interactions investigated from PET data. The aim of the present study is to evaluate alternative parameter estimation strategies based on the use of non-linear mixed effect models allowing to account for intra and inter-subject variability on the time-activity and for covariates potentially explaining this variability. A comparison of the different modeling approaches is presented using real data. The results of this comparison indicates that the mixed effect approach with a primary model partitioning the variance in term of Inter-Individual Variability (IIV) and Inter-Occasion Variability (IOV) and a second stage model relating the changes on binding potential to the dose of unlabelled drug is definitely the preferred approach.