Nicotine AddictionNCT02643914
Control Systems Approach to Predicting Individualized Dynamics of Nicotine Cravings
A study testing Nicotine and MR Compatible Nicotine Delivery Device in people with Nicotine Addiction and Cigarette Smoking, run by Stony Brook University at 1 site in United States.
Trial summary
Nicotine is the most common drug of abuse in the United States, and has addiction strength comparable to cocaine, heroin, and alcohol. It is the primary addictive component of tobacco, and its use markedly increases risk for cancer, heart disease, asthma, miscarriage, and infant mortality. Read more about this study
- Who is it for?
- Ages 21 to 65 yearsHealthy volunteers can take part
- Conditions the study is for
- Nicotine Addiction, Cigarette Smoking
- What is being tested?
- Nicotine and MR Compatible Nicotine Delivery Device
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 23 participants
- Where
- 1 siteUnited States
- Study dates
- Sep 2015to Dec 2017
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 21 to 65 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- 21-65years of age
- Moderate to severe addiction to smoking/nicotine
- Willingness to withdraw from nicotine for 12 hours prior to testing
- Eyesight correctable to 20/20 with contact lenses.
Who cannot join
- Electrical implants such as cardiac pacemakers or perfusion pumps
- Ferromagnetic implants such as aneurysm clips, surgical clips, prostheses, artificial hearts, valves with steel parts, metal fragments, shrapnel, facial tattoos, or steel implants
- Claustrophobia
- Pregnancy or breastfeeding (for females, pregnancy status will be confirmed with urine test)
- Chronic nasal congestion, sinusitis, or common cold Use of nicotine cessation therapy (patch, gum, inhaler, nasal spray)
- History of asthma, cardiovascular or peripheral vascular disease (anginas, arrhythmias, myocardial infarction, Raynaud's disease, insulin dependent diabetes)
- History of neurological disease (brain tumor, stroke, traumatic brain injury, epilepsy)
- Current use of psychotropic medication
Trial locations and contacts
1 site in 1 country.
United States1 site
Bioengineering Building , Stony Brook University
Stony Brook, New York, 11794
About this study
Official title: Using Control Systems to Predict Individualized Dynamics of Nicotine Cravings
Nicotine is the most common drug of abuse in the United States, and has addiction strength comparable to cocaine, heroin, and alcohol. It is the primary addictive component of tobacco, and its use markedly increases risk for cancer, heart disease, asthma, miscarriage, and infant mortality. Addiction is thought to be caused primarily by the intersection of two components: 1) the impact of drug pharmacokinetics on the dynamics of dopamine response, and 2) dysregulation of the brain's reward circuit. While the term 'dysregulated' tends to be used qualitatively within the neuroscience literature, regulation has a precise and testable meaning in control systems engineering, which has yet to be addressed in a quantitative manner by current neuroimaging methods or models of addiction. Current approaches to neuroimaging have primarily focused on identifying nodes and causal connections within the meso-circuit of interest, but have yet to take the next step in treating these nodes and connection as a self-interacting dynamical system evolving over time. Such an approach is critical for improving our understanding, and therefore prediction, of trajectories for addiction as well as recovery.
Read the detailed description
Nicotine is the most common drug of abuse in the United States, and has addiction strength comparable to cocaine, heroin, and alcohol. It is the primary addictive component of tobacco, and its use markedly increases risk for cancer, heart disease, asthma, miscarriage, and infant mortality. Addiction is thought to be caused primarily by the intersection of two components: 1) the impact of drug pharmacokinetics on the dynamics of dopamine response, and 2) dysregulation of the brain's reward circuit. While the term 'dysregulated' tends to be used qualitatively within the neuroscience literature, regulation has a precise and testable meaning in control systems engineering, which has yet to be addressed in a quantitative manner by current neuroimaging methods or models of addiction. Current approaches to neuroimaging have primarily focused on identifying nodes and causal connections within the meso-circuit of interest, but have yet to take the next step in treating these nodes and connection as a self-interacting dynamical system evolving over time. Such an approach is critical for improving the understanding, and therefore prediction, of trajectories for addiction as well as recovery. These trajectories are likely to be nonlinear (e.g., involving thresholds, saturation, and self-reinforcement), as well as highly specific to each individual. This study is designed to provide the first step towards addressing this gap: integrating ultra-high-field (7T) and ultra-fast (<1s) fMRI with computational modeling, to provide a bridge between the dynamics of meso-circuit regulation and the dynamics of human addictive behavior. The investigators propose to test the hypothesis that control systems regulation, measured by dynamic analyses of fMRI data, can predict-on an individual basis-exactly when an addicted smoker will want to take his next puff. This will be achieved by first validating a MR-compatible nicotine delivery system, by comparing its neurobiological and autonomic effects against those of a cigarette and e-cigarette. Once this is achieved, the investigators will then acquire fMRI data from addicted smokers while they 'smoke.' Using individual subjects' neuroimaging data, the investigators will derive coupled differential equations for a control system that predicts craving and behavioral response for that individual. Using independent data sets to estimate the parameters and to test them, the investigators will assess the model's accuracy in predicting each individual subject's cravings, as measured behaviorally by the frequency at which each smoker self-administers nicotine. If successful, this approach could then be exploited to develop individualized prevention and treatment of addiction by identifying individual-specific amplitude, duration, and frequency of dosing in nicotine replacement therapy that is least likely to trigger cravings. More generally, the methods proposed have the potential to rigorously examine system-wide dysregulation in addiction for the first time, opening the door to exploration of other dysregulatory brain-based diseases in humans.
- Conditions
- Nicotine Addiction, Cigarette Smoking
- Being tested
- Nicotine, MR Compatible Nicotine Delivery Device
- Medical subject headings
- Tobacco Use Disorder, Cigarette Smoking
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
NicotineDrug
Also called Nicotrol NS
MR Compatible Nicotine Delivery DeviceDevice
| Study group | Role | What they receive |
|---|---|---|
| Nicotine Cravings | Experimental | Not described Receives: Drug: Nicotine; Device: MR Compatible Nicotine Delivery Device |
What is being measured
The primary outcome is the main question the study is designed to answer.
Autonomic nervous system activity will be measured by analysis of heart rate variability and electric dermal activity alongside a 0-10 craving scale.
Measured: through study completion, an average of 1 year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted31 Dec 2015 (estimated)
- Study startSep 2015
- Primary completionJun 2017
- Study completionDec 2017 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (6)Papers the sponsor has linked to this study.
- Other trials for Nicotine AddictionStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 23 participants (actual)
Sponsor and investigators
- Lead sponsor
- Stony Brook University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Lilianne Strey, Stony Brook University
- Investigators
- Lilianne Mujica-Parodi, PhD, Principal investigator, Stony Brook University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT02643914
- Sponsor's protocol ID
- 1R21DA038467-01
- Status last verified
- Jun 2017
- First submitted
- 24 Nov 2015
- Last updated
- 2 Jul 2017
- Results posted
- No
- Data monitoring committee
- No
Publications
Koob GF, Volkow ND. Neurocircuitry of addiction. Neuropsychopharmacology. 2010 Jan;35(1):217-38. doi: 10.1038/npp.2009.110.
PubMed 19710631Koob GF. Addiction is a Reward Deficit and Stress Surfeit Disorder. Front Psychiatry. 2013 Aug 1;4:72. doi: 10.3389/fpsyt.2013.00072. eCollection 2013.
PubMed 23914176Volkow ND, Fowler JS, Wang GJ. The addicted human brain viewed in the light of imaging studies: brain circuits and treatment strategies. Neuropharmacology. 2004;47 Suppl 1:3-13. doi: 10.1016/j.neuropharm.2004.07.019.
PubMed 15464121Fagerstrom KO. Measuring degree of physical dependence to tobacco smoking with reference to individualization of treatment. Addict Behav. 1978;3(3-4):235-41. doi: 10.1016/0306-4603(78)90024-2. No abstract available.
PubMed 735910Heatherton TF, Kozlowski LT, Frecker RC, Fagerstrom KO. The Fagerstrom Test for Nicotine Dependence: a revision of the Fagerstrom Tolerance Questionnaire. Br J Addict. 1991 Sep;86(9):1119-27. doi: 10.1111/j.1360-0443.1991.tb01879.x.
PubMed 1932883Mujica-Parodi LR, Strey HH, Frederick B, Savoy R, Cox D, Botanov Y, Tolkunov D, Rubin D, Weber J. Chemosensory cues to conspecific emotional stress activate amygdala in humans. PLoS One. 2009 Jul 29;4(7):e6415. doi: 10.1371/journal.pone.0006415.
PubMed 19641623
Study at a glance
From the registry record, last updated by the sponsor on 2 Jul 2017. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Using Control Systems to Predict Individualized Dynamics of Nicotine Cravings
- ClinicalTrials.gov ID
- NCT02643914
- Acronym / sponsor ID
- 1R21DA038467-01
- Conditions
- Nicotine Addiction, Cigarette Smoking
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 23 participants (actual)
- Lead sponsor
- Stony Brook UniversityUniversity, hospital or other
- Study start
- Sep 2015
- Primary completion
- Jun 2017 (actual)
- Study completion
- Dec 2017 (estimated)
- First posted
- 31 Dec 2015 (estimated)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Nicotine is the most common drug of abuse in the United States, and has addiction strength comparable to cocaine, heroin, and alcohol. It is the primary addictive component of tobacco, and its use markedly increases risk for cancer, heart disease, asthma, miscarriage, and infant mortality. Addiction is thought to be caused primarily by the intersection of two components: 1) the impact of drug pharmacokinetics on the dynamics of dopamine response, and 2) dysregulation of the brain's reward circuit. While the term 'dysregulated' tends to be used qualitatively within the neuroscience literature, regulation has a precise and testable meaning in control systems engineering, which has yet to be addressed in a quantitative manner by current neuroimaging methods or models of addiction. Current approaches to neuroimaging have primarily focused on identifying nodes and causal connections within the meso-circuit of interest, but have yet to take the next step in treating these nodes and connection as a self-interacting dynamical system evolving over time. Such an approach is critical for improving our understanding, and therefore prediction, of trajectories for addiction as well as recovery.
Detailed description
Nicotine is the most common drug of abuse in the United States, and has addiction strength comparable to cocaine, heroin, and alcohol. It is the primary addictive component of tobacco, and its use markedly increases risk for cancer, heart disease, asthma, miscarriage, and infant mortality. Addiction is thought to be caused primarily by the intersection of two components: 1) the impact of drug pharmacokinetics on the dynamics of dopamine response, and 2) dysregulation of the brain's reward circuit. While the term 'dysregulated' tends to be used qualitatively within the neuroscience literature, regulation has a precise and testable meaning in control systems engineering, which has yet to be addressed in a quantitative manner by current neuroimaging methods or models of addiction. Current approaches to neuroimaging have primarily focused on identifying nodes and causal connections within the meso-circuit of interest, but have yet to take the next step in treating these nodes and connection as a self-interacting dynamical system evolving over time. Such an approach is critical for improving the understanding, and therefore prediction, of trajectories for addiction as well as recovery. These trajectories are likely to be nonlinear (e.g., involving thresholds, saturation, and self-reinforcement), as well as highly specific to each individual. This study is designed to provide the first step towards addressing this gap: integrating ultra-high-field (7T) and ultra-fast (<1s) fMRI with computational modeling, to provide a bridge between the dynamics of meso-circuit regulation and the dynamics of human addictive behavior. The investigators propose to test the hypothesis that control systems regulation, measured by dynamic analyses of fMRI data, can predict-on an individual basis-exactly when an addicted smoker will want to take his next puff. This will be achieved by first validating a MR-compatible nicotine delivery system, by comparing its neurobiological and autonomic effects against those of a cigarette and e-cigarette. Once this is achieved, the investigators will then acquire fMRI data from addicted smokers while they 'smoke.' Using individual subjects' neuroimaging data, the investigators will derive coupled differential equations for a control system that predicts craving and behavioral response for that individual. Using independent data sets to estimate the parameters and to test them, the investigators will assess the model's accuracy in predicting each individual subject's cravings, as measured behaviorally by the frequency at which each smoker self-administers nicotine. If successful, this approach could then be exploited to develop individualized prevention and treatment of addiction by identifying individual-specific amplitude, duration, and frequency of dosing in nicotine replacement therapy that is least likely to trigger cravings. More generally, the methods proposed have the potential to rigorously examine system-wide dysregulation in addiction for the first time, opening the door to exploration of other dysregulatory brain-based diseases in humans.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Nicotine Cravings | Experimental | Drug: Nicotine, Device: MR Compatible Nicotine Delivery Device |
Who may qualify
- Ages
- 21 to 65 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (4 listed)
- 21-65years of age
- Moderate to severe addiction to smoking/nicotine
- Willingness to withdraw from nicotine for 12 hours prior to testing
- Eyesight correctable to 20/20 with contact lenses.
Key exclusion criteria (8 listed)
- Electrical implants such as cardiac pacemakers or perfusion pumps
- Ferromagnetic implants such as aneurysm clips, surgical clips, prostheses, artificial hearts, valves with steel parts, metal fragments, shrapnel, facial tattoos, or steel implants
- Claustrophobia
- Pregnancy or breastfeeding (for females, pregnancy status will be confirmed with urine test)
- Chronic nasal congestion, sinusitis, or common cold Use of nicotine cessation therapy (patch, gum, inhaler, nasal spray)
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| NicotineAlso: Nicotrol NS | Drug | Nicotine Cravings |
| MR Compatible Nicotine Delivery Device | Device | Nicotine Cravings |
Primary outcome
Autonomic nervous system activity will be measured by analysis of heart rate variability and electric dermal activity alongside a 0-10 craving scale.
Time frame: through study completion, an average of 1 year
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 2 Jul 2017.
- Background: PubMed 19710631Koob GF, Volkow ND. Neurocircuitry of addiction. Neuropsychopharmacology. 2010 Jan;35(1):217-38. doi: 10.1038/npp.2009.110.
- Background: PubMed 23914176Koob GF. Addiction is a Reward Deficit and Stress Surfeit Disorder. Front Psychiatry. 2013 Aug 1;4:72. doi: 10.3389/fpsyt.2013.00072. eCollection 2013.
- Background: PubMed 15464121Volkow ND, Fowler JS, Wang GJ. The addicted human brain viewed in the light of imaging studies: brain circuits and treatment strategies. Neuropharmacology. 2004;47 Suppl 1:3-13. doi: 10.1016/j.neuropharm.2004.07.019.
- Background: PubMed 735910Fagerstrom KO. Measuring degree of physical dependence to tobacco smoking with reference to individualization of treatment. Addict Behav. 1978;3(3-4):235-41. doi: 10.1016/0306-4603(78)90024-2. No abstract available.
- Background: PubMed 1932883Heatherton TF, Kozlowski LT, Frecker RC, Fagerstrom KO. The Fagerstrom Test for Nicotine Dependence: a revision of the Fagerstrom Tolerance Questionnaire. Br J Addict. 1991 Sep;86(9):1119-27. doi: 10.1111/j.1360-0443.1991.tb01879.x.
- Background: PubMed 19641623Mujica-Parodi LR, Strey HH, Frederick B, Savoy R, Cox D, Botanov Y, Tolkunov D, Rubin D, Weber J. Chemosensory cues to conspecific emotional stress activate amygdala in humans. PLoS One. 2009 Jul 29;4(7):e6415. doi: 10.1371/journal.pone.0006415.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Lilianne Mujica-Parodi, PhD principal investigator
Stony Brook University
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Nicotine and MR Compatible Nicotine Delivery Device in people with Nicotine Addiction and Cigarette Smoking, run by Stony Brook University at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 8 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 2 Jul 2017. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Autonomic nervous system activity will be measured by analysis of heart rate variability and electric dermal activity alongside a 0-10 craving scale. (time frame: through study completion, an average of 1 year). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT02643914, which also lists 6 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 2 Jul 2017.