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Uncertainty Analysis in Pharmacokinetics and Pharmacodynamics: Application to Naratriptan
Authors:Ivelina?Gueorguieva  author-information"  >  author-information__contact u-icon-before"  >  mailto:gueorguieva_ivelina@lilly.com"   title="  gueorguieva_ivelina@lilly.com"   itemprop="  email"   data-track="  click"   data-track-action="  Email author"   data-track-label="  "  >Email author,Ivan?A.?Nestorov,Leon?Aarons,Malcolm?Rowland
Affiliation:(1) Centre for Applied Pharmacokinetic Research, School of Pharmacy and Pharmaceutical Sciences, University of Manchester, Oxford Road, Manchester, M13 9PL, UK;(2) Zymogenetics Inc., 1201 Eastlake Avenue East, Seattle, Washington 98102, USA;(3) School of Pharmacy and Pharmaceutical Sciences, University of Manchester, Oxford Road, Manchester, M13 9PL, UK;(4) Lilly Research Centre, Erl Wood Manor, Sunninghill Road, Windlesham, Surrey, GU20 6PH, UK
Abstract:Purpose The aim of the study was to predict pain relief of migraine in patients following naratriptan oral (tablet) administration by using uncertainty analysis. The analysis was based on phase I pharmacokinetic naratriptan data, sumatriptan pharmacodynamic data, and naratriptan preclinical (animal) potency information, together with general knowledge as to how migraine affects oral absorption. Methods A previously developed pharmacokinetic (PK)/pharmacodynamic (PD) model for naratriptan disposition and effect was used. The uncertain parameters in the model, which were associated with absorption and scaling between first-in-class compound sumatriptan and naratriptan, were modeled using fuzzy sets theory. Global sensitivity analysis was then used to investigate the impact of each PK/PD parameter on the responses. Results Acknowledging parametric uncertainty did not improve prediction of the probability of pain relief. Global sensitivity analysis demonstrated that predictions were heavily influenced by interindividual variability in pharmacodynamics, as the dose response relationship was relatively insensitive to the pharmacokinetics. Conclusions To predict the probability of pain relief following oral (tablet) administration of naratriptan, a simple dose response, instead of the PK/PD model, would have yielded very similar predictions. The naratriptan PK/PD model may be improved by either refining the PD model or better still by specifying the interindividual error by additional data collecting with an improved design.
Keywords:clinical trial simulation  fuzzy set theory  naratriptan  pharmacodynamics  pharmacokinetics  sensitivity analysis
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