Dataset Information

Larval zebrafish model for FDA-approved drug repositioning for tobacco dependence treatment.

ABSTRACT: Cigarette smoking remains the most preventable cause of death and excess health care costs in the United States, and is a leading cause of death among alcoholics. Long-term tobacco abstinence rates are low, and pharmacotherapeutic options are limited. Repositioning medications approved by the U.S. Food and Drug Administration (FDA) may efficiently provide clinicians with new treatment options. We developed a drug-repositioning paradigm using larval zebrafish locomotion and established predictive clinical validity using FDA-approved smoking cessation therapeutics. We evaluated 39 physician-vetted medications for nicotine-induced locomotor activation blockade. We further evaluated candidate medications for altered ethanol response, as well as in combination with varenicline for nicotine-response attenuation. Six medications specifically inhibited the nicotine response. Among this set, apomorphine and topiramate blocked both nicotine and ethanol responses. Both positively interact with varenicline in the Bliss Independence test, indicating potential synergistic interactions suggesting these are candidates for translation into Phase II clinical trials for smoking cessation.

SUBMITTER: Cousin MA

PROVIDER: S-EPMC3962344 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Larval zebrafish model for FDA-approved drug repositioning for tobacco dependence treatment.

Cousin Margot A MA Ebbert Jon O JO Wiinamaki Amanda R AR Urban Mark D MD Argue David P DP Ekker Stephen C SC Klee Eric W EW

PloS one 20140321 3

Cigarette smoking remains the most preventable cause of death and excess health care costs in the United States, and is a leading cause of death among alcoholics. Long-term tobacco abstinence rates are low, and pharmacotherapeutic options are limited. Repositioning medications approved by the U.S. Food and Drug Administration (FDA) may efficiently provide clinicians with new treatment options. We developed a drug-repositioning paradigm using larval zebrafish locomotion and established predictive ...[more]

PMID: 24658307

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Project description:BackgroundAdverse Drug Reactions (ADRs) are of great public health concern. FDA-approved drug labeling summarizes ADRs of a drug product mainly in three sections, i.e., Boxed Warning (BW), Warnings and Precautions (WP), and Adverse Reactions (AR), where the severity of ADRs are intended to decrease in the order of BW > WP > AR. Several reported studies have extracted ADRs from labeling documents, but most, if not all, did not discriminate the severity of the ADRs by the different labeling sections. Such a practice could overstate or underestimate the impact of certain ADRs to the public health. In this study, we applied the Medical Dictionary for Regulatory Activities (MedDRA) to drug labeling and systematically analyzed and compared the ADRs from the three labeling sections with a specific emphasis on analyzing serious ADRs presented in BW, which is of most drug safety concern.ResultsThis study investigated New Drug Application (NDA) labeling documents for 1164 single-ingredient drugs using Oracle Text search to extract MedDRA terms. We found that only a small portion of MedDRA Preferred Terms (PTs), 3819 out of 21,920 or 17.42%, were observed in a whole set of documents. In detail, 466/3819 (12.0%) PTs were in BW, 2023/3819 (53.0%) were in WP, and 2961/3819 (77.5%) were in AR sections. We also found a higher overlap of top 20 occurring BW PTs with WP sections compared to AR sections. Within the MedDRA System Organ Class levels, serious ADRs (sADRs) from BW were prevalent in Nervous System disorders and Vascular disorders. A Hierarchical Cluster Analysis (HCA) revealed that drugs within the same therapeutic category shared the same ADR patterns in BW (e.g., nervous system drug class is highly associated with drug abuse terms such as dependence, substance abuse, and respiratory depression).ConclusionsThis study demonstrated that combining MedDRA standard terminologies with data mining techniques facilitated computer-aided ADR analysis of drug labeling. We also highlighted the importance of labeling sections that differ in seriousness and application in drug safety. Using sADRs primarily related to BW sections, we illustrated a prototype approach for computer-aided ADR monitoring and studies which can be applied to other public health documents.

Dataset Information

Larval zebrafish model for FDA-approved drug repositioning for tobacco dependence treatment.

Publications

Larval zebrafish model for FDA-approved drug repositioning for tobacco dependence treatment.

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