Clinical trial NCT01590277
Conditions: Active Ethanol and Active Iomazenil Active Ethanol and Placebo Iomazenil Placebo Ethanol and Active Iomazenil Placebo Ethanol and Placebo Iomazenil Alcohol Effect Driving Under the Influence Alcohol Impairment
Sponsor: VA Office of Research and Development
Start date: 2012-12-14; Completion date: 2018-11-02
Enrollment: 33 participants; Allocation: RANDOMIZED; Intervention model: CROSSOVER

Brief summary:
Alcohol is abused commonly, but there is no remedy for alcohol intoxication. This project is looking at the substance iomazenil and its effect on alcohol intoxication and alcohol's effects on driving using a driving simulator.

Detailed description:
Alcohol is abused commonly, but there is no antidote for alcohol intoxication the way naltrexone or naloxone is an antidote for opioids. A medication that has the potential to block alcohol actions in the Central Nervous System could act as a unique medication in the treatment of alcohol intoxication and alcoholism. This project is evaluating the benzodiazepine partial inverse agonist, iomazenil, as an agent that could reverse alcohol's effects on subjective intoxication, alcohol's effects on driving using a driving simulator and on measures of electrophysiology in the laboratory in healthy subjects.

Arms: arm 1: Participants will receive in a randomized, double-blind, cross-over design, ethanol or placebo and iomazenil or placebo.

Potential Randomizations: a) active ethanol and placebo iomazenil, b) active ethanol and active iomazenil, c) placebo ethanol and active iomazenil, and d) placebo ethanol and placebo iomazenil arm 2: Participants will receive in a randomized, double-blind, cross-over design, ethanol or placebo and iomazenil or placebo.

Potential Randomizations: a) active ethanol and placebo iomazenil, b) active ethanol and active iomazenil, c) placebo ethanol and active iomazenil, and d) placebo ethanol and placebo iomazenil arm 3: Participants will receive in a randomized, double-blind, cross-over design, ethanol or placebo and iomazenil or placebo.

Potential Randomizations: a) active ethanol and placebo iomazenil, b) active ethanol and active iomazenil, c) placebo ethanol and active iomazenil, and d) placebo ethanol and placebo iomazenil arm 4: Participants will receive in a randomized, double-blind, cross-over design, ethanol or placebo and iomazenil or placebo.

Potential Randomizations: a) active ethanol and placebo iomazenil, b) active ethanol and active iomazenil, c) placebo ethanol and active iomazenil, and d) placebo ethanol and placebo iomazenil
Interventions: intervention 1: Active Ethanol intervention 2: Active Iomazenil intervention 3: Placebo intervention 4: Placebo
Intervention descriptions: intervention 1: Target BrAC of 0.1% reached over 30 minutes and then clamped to maintain this dose for an additional 60 minutes. This dose is equivalent to consuming approximately 5 drinks. Administered over a total of 90 minutes. intervention 2: Active iomazenil, administered intravenously at a dose of 3.7 ug/kg. Administered over 10 minutes, beginning 10 minutes after the start of the ethanol/placebo clamp. intervention 3: Control: no alcohol, administered for a total of 90 minutes. intervention 4: Control: no iomazenil, administered for a total of 10 minutes

Protocol documents:
Prot_000.pdf: 
Ability of Partial Inverse Agonist, Iomazenil, 
to Block Ethanol Effects in Humans
NCT01590277
June 10, 2022


ver. 6/10/2022 
ABILITY OF PARTIAL INVERSE AGONIST, IOMAZENIL, TO BLOCK ETHANOL EFFECTS IN 
HUMANS 
 
Principal Investigator: Deepak Cyril D’Souza, MD  
 
Objective: The main objective of this study is to evaluate whether iomazenil can attenuate the 
affective and cognitive effects of alcohol.  
 
Background: The pathological use of alcohol is a major public health challenge facing VHA. 
Among soldiers returning from Iraq and Afghanistan, alcoholism is one of the most common initial 
psychiatric disorders. There is a need to develop effective treatments for alcohol intoxication and 
alcoholism. The stimulation of extrasynaptic GABAA receptors by ethanol contributes 
substantially to its effects at doses associated with human   intoxication. Therefore, drugs that 
could block ethanol actions at GABAA receptors might play a unique role in the treatment of 
alcohol intoxication and alcoholism. Preclinical studies suggest that benzodiazepine inverse 
agonists, but not benzodiazepine antagonists, attenuate the effects of ethanol on many levels. 
They attenuate ethanol-stimulated Cl- influx thereby affecting the rewarding, sedating, ataxic, and 
amnestic effects of ethanol, the discriminative stimulus effects of ethanol, operant behavior 
motivated by ethanol and ethanol self- administration. However, this has not yet been shown in 
humans. This project is evaluating the benzodiazepine partial inverse agonist, iomazenil, as an 
agent that could reverse alcohol's effects on subjective intoxication, alcohol’s effects on driving 
using a driving simulator and on measures of electrophysiology in the laboratory in healthy 
subjects. 
 
 Research Methodology:  We hypothesize that: the GABAA benzodiazepine partial inverse agonist, 
iomazenil, will attenuate several measures of ethanol intoxication in healthy human subjects. In a 
double-blind, placebo-controlled fashion, counterbalanced, within-subjects design, participants will 
receive an intravenous (IV) infusion of placebo or active ethanol (target BrAc=100mg%) followed 
by placebo or active iomazenil (3.7 µg/kg) administered intravenously via a separate IV.  Subjects 
will undergo four test days. Subjects will receive the following drug combinations: (1) active ethanol 
and active iomazenil; (2) active ethanol and placebo iomazenil; (3) placebo ethanol and active 
iomazenil; and (4) placebo ethanol and placebo iomazenil. Measures of intoxication will be 
collected before, and several times during and after drug administration. Automobile driving will be 
assessed using a driving simulator. Cognitive function will be assessed using the visual novelty 
oddball paradigm. EEG will be recorded during the driving simulator and novelty oddball tasks, 
allowing for the analysis of ERP components related to making errors (error-related negativity, ERN; 
driving simulator) and target (P3b) 
   
Innovation and Impact: Although inverse agonists have been shown to attenuate several aspects 
of ethanol in animals, this has not yet been demonstrated in humans. The innovative elements 
of the study are:1) the use of the only BZ inverse agonist probe available for use in humans – 
one that was developed at this center and to our knowledge is not available elsewhere for use at 
pharmacological doses, 2) the use of event- related potential and event-related oscillations, 3) 
the use of simulated driving, a functional measure of ethanol effects, and driving error-related 
potentials, 4) the use of eyeblink conditioning as a biomarker of alcohol’s effects on cerebellar 
function. This study may provide insights into the neurobiology through which iomazenil 
attenuates features of ethanol intoxication in humans. In so doing, this project may help to 
advance the exploration of benzodiazepine inverse agonists as ethanol “antidotes” and possible 
treatments for pathological alcohol use. Characterizing the interplay of iomazenil-ethanol 
interactions on several overlapping measures will contribute to the rational development of 
agents similar to iomazenil as antidotes or pharmacotherapies for alcoholism. 
 

SAP_001.pdf: 
Ability of Partial Inverse Agonist, Iomazenil, 
to Block Ethanol Effects in Humans
NCT01590277
June 10, 2022


ABILITY OF PARTIAL INVERSE AGONIST, IOMAZENIL, TO BLOCK ETHANOL EFFECTS 
IN HUMANS 
 
Principal Investigator: Deepak Cyril D’Souza, MD  
 
Statistical Analysis Plan: All data will be transcribed onto respective teleforms, checked for 
completeness and clarity. Continuous variables will be checked for normality using normal 
probability plots and Kolmogorov- Smirnov statistics. Transformations will be applied if 
necessary. A criterion of P < 0.05 will be used throughout to determine statistical significance. In 
the mixed models described below, the correlation between repeated measures on an individual 
will be modeled using random effects and/or structured variance-covariance matrices. The best-
fitting variance-covariance structure will be determined by information criterion. The mixed- 
effects approach is advantageous in that it is unaffected by randomly missing data and allows 
greater flexibility in modeling the correlation structure of repeated-measures data. We will test 
for order effects, although any such effects should be greatly minimized with the inclusion of the 
baseline session. All tests will be two-sided and considered statistically significant at alpha=.05. 
Significance levels for secondary comparisons will be adjusted for multiple tests using the 
Bonferroni correction, basing the adjustment on the number of conceptually related statistical 
tests within each hypothesis. 
 
To determine whether iomazenil, attenuates the “buzzed” feeling state of ethanol intoxication 
in healthy human subjects. We expect that the behavioral data will not conform to normality as 
in our previous studies. Therefore, a nonparametric analysis for repeated measures data will 
be conducted with ethanol (active or placebo), iomazenil (active or placebo) and time as 
within-subject factors. The analysis will be performed by rank transforming the data, then 
fitting a mixed-effects model with an unstructured variance-covariance matrix using 
PROCMIXED in SAS (SAS Institute Inc, Cary, NC), and finally adjusting the P values for the 
analysis of variance–type statistics (ATS). One of the advantages of this approach is that it 
uses all available data on each subject including dropouts. If the 3-way interaction among 
ethanol, iomazenil, and time are significant, contrasts for testing interactions between 
iomazenil and ethanol will be performed at each time point. For the points where significant 
interactions are observed, the simple effects of ethanol, and iomazenil will be tested to 
determine the nature of the interaction. Bonferroni corrections will be applied for multiple 
analyses within, but not across, domains.