Development of an MRI-Compatible Nasal Drug Delivery Method for Probing Nicotine Addiction Dynamics.

brain circuit nasal drug delivery device nicotine addition

Journal

Pharmaceutics
ISSN: 1999-4923
Titre abrégé: Pharmaceutics
Pays: Switzerland
ID NLM: 101534003

Informations de publication

Date de publication:
03 Dec 2021
Historique:
received: 10 11 2021
revised: 29 11 2021
accepted: 30 11 2021
entrez: 28 12 2021
pubmed: 29 12 2021
medline: 29 12 2021
Statut: epublish

Résumé

Substance abuse is a fundamentally dynamic disease, characterized by repeated oscillation between craving, drug self-administration, reward, and satiety. To model nicotine addiction as a control system, a magnetic resonance imaging (MRI)-compatible nicotine delivery system is needed to elicit cyclical cravings. Using a concentric nebulizer, inserted into one nostril, we delivered each dose equivalent to a single cigarette puff by a syringe pump. A control mechanism permits dual modes: one delivers puffs on a fixed interval programmed by researchers; with the other, subjects press a button to self-administer each nicotine dose. We tested the viability of this delivery method for studying the brain's response to nicotine addiction in three steps. First, we established the pharmacokinetics of nicotine delivery, using a dosing scheme designed to gradually achieve saturation. Second, we lengthened the time between microdoses to elicit craving cycles, using both fixed-interval and subject-driven behavior. Finally, we demonstrate a potential application of our device by showing that a fixed-interval protocol can reliably identify neuromodulatory targets for pharmacotherapy or brain stimulation. Our MRI-compatible nasal delivery method enables the measurement of neural circuit responses to drug doses on a single-subject level, allowing the development of data-driven predictive models to quantify individual dysregulations of the reward control circuit causing addiction.

Identifiants

pubmed: 34959350
pii: pharmaceutics13122069
doi: 10.3390/pharmaceutics13122069
pmc: PMC8708378
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : NIH HHS
ID : 3R2DA3846702S1
Pays : United States

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Auteurs

Rajat Kumar (R)

Department of Biomedical Engineering, Stony Brook University School of Medicine, Stony Brook, NY 11794, USA.

Lilianne R Mujica-Parodi (LR)

Department of Biomedical Engineering, Stony Brook University School of Medicine, Stony Brook, NY 11794, USA.
Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA.

Michael Wenke (M)

Department of Biomedical Engineering, Stony Brook University School of Medicine, Stony Brook, NY 11794, USA.

Anar Amgalan (A)

Department of Biomedical Engineering, Stony Brook University School of Medicine, Stony Brook, NY 11794, USA.

Andrew Lithen (A)

Department of Biomedical Engineering, Stony Brook University School of Medicine, Stony Brook, NY 11794, USA.

Sindhuja T Govindarajan (ST)

Department of Biomedical Engineering, Stony Brook University School of Medicine, Stony Brook, NY 11794, USA.

Rany Makaryus (R)

Department of Anesthesiology, Stony Brook University School of Medicine, Stony Brook, NY 11794, USA.

Helene Benveniste (H)

Department of Anesthesiology, Stony Brook University School of Medicine, Stony Brook, NY 11794, USA.

Helmut H Strey (HH)

Department of Biomedical Engineering, Stony Brook University School of Medicine, Stony Brook, NY 11794, USA.

Classifications MeSH