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Printable version

PAGE. Abstracts of the Annual Meeting of the Population Approach Group in Europe.
ISSN 1871-6032

PAGE 27 (2018) Abstr 8649 []

PDF poster/presentation:
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Poster: Methodology - New Modelling Approaches

II-26 Eva Germovsek An exposure-response model relating nicotine plasma concentration to momentary craving across different nicotine replacement therapy formulations

Eva Germovsek (1), Anna Hansson (2), Maria C Kjellsson (1), Juan Jose Perez Ruixo (3), Åke Westin (2), Paul A Soons (3), An Vermeulen (3), Mats O Karlsson (1)

(1) Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden; (2) McNeil AB, Helsingborg, Sweden; (3) Janssen R&D, a division of Janssen Pharmaceutica NV, Beerse, Belgium

Objectives: Tobacco use is estimated to cause over 7 million avoidable deaths yearly [1] by increasing the risk of developing cancer, causing chronic obstructive pulmonary disease, accelerating cardiovascular diseases, increasing the risk of infectious diseases and insulin resistance, etc. Tobacco use is therefore a major individual and also a global public health problem, thus it is vital to reduce its use. Nicotine replacement therapy (NRT) medications reduce craving for nicotine, and hence facilitate smoking reduction and cessation [2]. Our aim was to improve the understanding and to quantify the relationship between nicotine plasma concentrations and momentary craving across different NRT formulations. By developing a pharmacokinetic-pharmacodynamic (PKPD) model we were also aiming to quantify the between-subject variability and to identify possible formulation-dependent differences. Additionally, since the momentary craving was assessed using two different scales (specifically, a 4-category scale, and a 100 mm visual analogue scale (VAS), i.e. a 101-category scale), we also aimed to link the results from both scales.

Methods: Data available for analysis originated from 17 different studies, including four NRT formulations: mouth spray, lozenge, gum and patch. Subjects in the studies received NRT medications only and were instructed not to smoke. Existing formulation-specific population pharmacokinetic (PK) models and individual PK parameter estimates were utilised to obtain dynamic nicotine PK profiles for each individual. If individual PK parameter estimates were unavailable, the population estimates were used. A linear direct-effect model was used to relate nicotine plasma concentration to craving (reduction), and formulation-specific slopes were investigated. To link the observations from the two different scales, a joint model was developed for the VAS scale based on a bounded-integer model concept [3], where a probit-based model provides the probability of each observation. For the scores from the 4-category scale, we estimated the probabilities, in order to be able to link them with the VAS scores. NONMEM 7.3 (ICON Development Solutions, Ellicott City, Maryland) with the Laplace approximation was used to obtain the likelihood.

Results: The data included 1,077 adult subjects with median (range) age 28 (18-55) years and weight 72 (49.4-112.8) kg, smoking 20 (5-50) cigarettes per day for 12 (1-45) years. The subjects provided 41,424 momentary craving observations, 15,424 of which were measured with the 4-category scale, and 25,922 with the VAS. In this analysis, the slopes for all oral NRT formulations were estimated to be similar (i.e. -0.24 mL/ng, -0.20 mL/ng, -0.14 mL/ng for mouth spray, lozenge and gum, respectively), but the slope for patch was estimated to be lower (-0.04 mL/ng). The score of 1 on the 4-category scale was estimated to represent scores 0-27 on the VAS, score of 2 as 28-65, score of 3 as 66-91, and score of 4 as 92-100 on the VAS.

Conclusions: A linear direct-effect PKPD model was developed and related nicotine plasma concentrations to momentary craving from four different NRT formulations. A new methodology, bounded integer model was for the first time applied to link observations from two separate pharmacodynamic endpoint scales. Future work will include, for example, testing non-linear models to describe the concentration-effect relationship, evaluating a possible delay in the onset of the effect, assessing the influence of other covariates (such as markers of nicotine dependence), and perhaps including a tolerance development or other time dependency in the PKPD relationship.

Disclosures: EG, MCK and MOK declare no conflicts of interest; AH, JJPR, ÅW, PS and AV are (former) employees of subsidiary companies of Johnson & Johnson.

[1] World Health Organisation, WHO report on the global tobacco epidemic. Monitoring tobacco use and prevention policies, 2017.
[2] Benowitz, N.L., Clinical pharmacology of nicotine: implications for understanding, preventing, and treating tobacco addiction. Clin Pharmacol Ther, 2008. 83(4): 531-41.
[3] Karlsson, MO et al, A bounded integer model for rating and composite scale data, 2018, PAGANZ meeting