Pharmacokinetics of a Transdermal Nicotine Patch Compared to Nicotine Gum

Lane, James D.; Westman, Eric; Ripka, Gail V.; Wu, Jhili; Chiang, Chin-Chih; Rose, Jed E.

doi:10.3109/03639049309069337

Cited by 3 publications

(2 citation statements)

References 14 publications

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“…14-18 A set of well-defined and experimentally determined drug-dependent parameters (clearances, unbound plasma fractions, bioavailability, log P, pKa, solubility, etc) incorporate relevant information about the drug's physicochemical and PK properties to enable prediction of their absorption, distribution, metabolism, and excretion (ADME) mechanisms. [19][20][21][22][23][24][25][26][27][28][29][30][31] Another set of important drug-dependent parameters are tissue-toplasma partition coefficients (Kp) for the organs included in the mechanistic model. Kp values characterize the pattern of drug distribution throughout the body and degree of accumulation at specific anatomical locations.…”

Section: Overview Of Bioisim Platformmentioning

confidence: 99%

<p>Scalable in silico Simulation of Transdermal Drug Permeability: Application of BIOiSIM Platform</p>

Maharao¹,

Antontsev²,

Hou³

et al. 2020

DDDT

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Introduction: Transdermal drug delivery is gaining popularity as an alternative to traditional routes of administration. It can increase patient compliance because of its painless and noninvasive nature, aid compounds in bypassing presystemic metabolic effects, and reduce the likelihood of adverse effects through decreased systemic exposure. In silico physiological modeling is critical to predicting dermal exposure for a therapeutic and assessing the impact of different formulations on transdermal disposition. Methods: The present study aimed at developing a physiologically based transdermal platform, "BIOiSIM", that could be globally applied to a wide variety of compounds to predict their transdermal disposition. The platform integrates a 16-compartment model of compound pharmacokinetics and was used to simulate and predict drug exposure of three chemically and biologically distinct drug-like compounds. Machine learning optimization was composed of two components: exhaustive search algorithm (coarse-tuning) and descent (fine-tuning) integrated with the platform used to quantitatively determine parameters influencing pharmacokinetics (eg permeability, k perm) of test compounds. Results: The model successfully predicted drug exposure (AUC, C max and T max) following transdermal application of morphine, buprenorphine and nicotine in human subjects, mostly with less than twofold absolute average fold error (AAFE). The model was further able to successfully characterize the relationship between observed systemic exposure and intended pharmacological effect. The predicted systemic concentration of morphine and plasma levels of endogenous pain biomarkers were used to estimate the effectiveness of a given therapeutic regimen. Conclusion: BIOiSIM marks a novel approach to in silico prediction that will enable leveraging of machine learning technology in the pharmaceutical space. The approach to model development outlined results in scalable, accurate models and enables the generation of large parameter/coefficient datasets from in vivo clinical data that can be used in future work to train quantitative structure activity relationship (QSAR) models for predicting likelihood of compound utility as a transdermally administered therapeutic.

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Section: Overview Of Bioisim Platformmentioning

confidence: 99%

<p>Scalable in silico Simulation of Transdermal Drug Permeability: Application of BIOiSIM Platform</p>

Maharao¹,

Antontsev²,

Hou³

et al. 2020

DDDT

View full text Add to dashboard Cite

show abstract

“…Additionally, irrespective of dose, peak plasma levels using nicotine patch may occur 6 to 8 hours after initial application (Lane et al, 1993;Russell, 1988). There may also be an initial higher level of nicotine on the first day of patch wearing due to remnant nicotine from the previous day's smoking and nicotine derived from nicotine patches only reach a steady state dose after three days of continuous wear, with no accumulation (Hurt et al, 1993).…”

mentioning

confidence: 99%

A Combination Nicotine Replacement Therapy (NRT) Algorithm for Hard-to-Treat Smokers

Bittoun¹

2006

J Smok Cessat

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Many smokers have not succeeded in quitting using a single nicotine replacement mode. An algorithm was developed for clinicians to enhance success rates when recommending nicotine replacement therapy (NRT) to smoking patients. The algorithm is based on clinical experience with chronic smokers with respiratory illnesses attending one-on-one smokers clinics in the Central Sydney Area Health Service. Based on transdermal nicotine therapy (patch) other forms of NRT are added if required for ‘breakout’ smoking for 2 weeks. Outcomes have shown 60% confirmed continuous abstinence at 3 months. Smokers can be safely and successfully treated symptomatically for nicotine withdrawal relief using combination NRT aggressively. This enhances treatment efficacy by minimising relapse in the first few weeks and months of quitting.

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Recent Advances in Noninvasive Systemic Delivery of Pharmaceuticals and Biopharmaceuticals

Chien

1994

Drug Development and Industrial Pharmacy

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Many systemically-active pharmaceuticals and biopharmaceuticals are reportedly subjected to extensive pre-systemic elimination when taken orally. To circumvent this dilemma in systemic delivery, extensive research efforts have recently been devoted to explore various nonparenteral (noninvasive) routes of administration for enhancing systemic bioavailability of pharmaceuticals and biopharmaceuticals, which have been reportedly subjected to extensive pre-systemic elimination, via the bypassing of hepatogastrointestinal "first-pass" metabolism. Using nicotine, a pharmaceutical, and enkephalin, a biopharmaceutical, the systemic delivery of pharmaceuticals and biopharmaceuticals through the skin and the various absorptive mucosae has been illustrated. The mechanisms and kinetic processes involved for their systemic delivery are explored and various technical issues encountered are discussed in this article.

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Pharmacokinetics of a Transdermal Nicotine Patch Compared to Nicotine Gum

Cited by 3 publications

References 14 publications

<p>Scalable in silico Simulation of Transdermal Drug Permeability: Application of BIOiSIM Platform</p>

<p>Scalable in silico Simulation of Transdermal Drug Permeability: Application of BIOiSIM Platform</p>

A Combination Nicotine Replacement Therapy (NRT) Algorithm for Hard-to-Treat Smokers

Recent Advances in Noninvasive Systemic Delivery of Pharmaceuticals and Biopharmaceuticals

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