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Transient Lower Esophageal Sphincter Relaxations PKPD Modeling: Count Model and Repeated Time-To-Event Model
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
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2011 (English)In: Journal of Pharmacology and Experimental Therapeutics, ISSN 0022-3565, E-ISSN 1521-0103Article in journal (Refereed) Published
Abstract [en]

Transient lower esophageal sphincter relaxation (TLESR) is the major mechanism for gastro-esophageal reflux. Characterization of candidate compounds for reduction of TLESRs are traditionally done through summary exposure and response measures and would benefit from model-based analyses of exposure-TLESR events relationships. PKPD modeling approaches treating TLESR either as count data or as repeated time-to-event (RTTE) data were developed and compared in terms of ability to characterize system and drug characteristics. Vehicle data comprising 294 TLESR events were collected from 9 dogs. Compound (WIN55251-2) data containing 66 TLESR events, as well as plasma concentrations, were obtained from 4 dogs. Each experiment lasted for 45min and was initiated with a meal. Counts in equispaced 5-min intervals and 1-min intervals were modeled based on a Poisson probability distribution model. TLESR events were analyzed with the RTTE model. PK was connected to PD models with a 1-compartment model. Vehicle data were described by a baseline and a surge function; the surge peak was determined around 9.69min by all approaches and its width of 5min (1-min count and RTTE) or 10min (5-min count). TLESRs inhibition by WIN55251-2 was described by an Imax model, with an IC50 of on average 2.39nmol.L-1. Modeling approaches utilizing count or RTTE data linked to a dynamic PKPD representation of exposure is superior to using summary PK and PD measures. Differences in terms of predictions and power to detect a significant drug effect are illustrated with a simulation-based investigation, and a range of diagnostics for such modeling approaches is presented.


Place, publisher, year, edition, pages
Keyword [en]
PKPD, pharmacokinetic-pharmacodynamic, TLESR, Transient lower esophageal sphincter relaxation, RTTE, repeated time-to-event
National Category
Medical and Health Sciences
URN: urn:nbn:se:uu:diva-150928DOI: 10.1124/jpet.111.181636ISI: 000297267800016PubMedID: 21890509OAI: oai:DiVA.org:uu-150928DiVA: diva2:409332
E.L.P. and G.M. are two equally-contributing first authorsAvailable from: 2011-04-07 Created: 2011-04-07 Last updated: 2011-12-21Bibliographically approved
In thesis
1. Pharmacometric Methods and Novel Models for Discrete Data
Open this publication in new window or tab >>Pharmacometric Methods and Novel Models for Discrete Data
2011 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Pharmacodynamic processes and disease progression are increasingly characterized with pharmacometric models. However, modelling options for discrete-type responses remain limited, although these response variables are commonly encountered clinical endpoints. Types of data defined as discrete data are generally ordinal, e.g. symptom severity, count, i.e. event frequency, and time-to-event, i.e. event occurrence. Underlying assumptions accompanying discrete data models need investigation and possibly adaptations in order to expand their use. Moreover, because these models are highly non-linear, estimation with linearization-based maximum likelihood methods may be biased.

The aim of this thesis was to explore pharmacometric methods and novel models for discrete data through (i) the investigation of benefits of treating discrete data with different modelling approaches, (ii) evaluations of the performance of several estimation methods for discrete models, and (iii) the development of novel models for the handling of complex discrete data recorded during (pre-)clinical studies.

A simulation study indicated that approaches such as a truncated Poisson model and a logit-transformed continuous model were adequate for treating ordinal data ranked on a 0-10 scale. Features that handled serial correlation and underdispersion were developed for the models to subsequently fit real pain scores. The performance of nine estimation methods was studied for dose-response continuous models. Other types of serially correlated count models were studied for the analysis of overdispersed data represented by the number of epilepsy seizures per day. For these types of models, the commonly used Laplace estimation method presented a bias, whereas the adaptive Gaussian quadrature method did not. Count models were also compared to repeated time-to-event models when the exact time of gastroesophageal symptom occurrence was known. Two new model structures handling repeated time-to-categorical events, i.e. events with an ordinal severity aspect, were introduced. Laplace and two expectation-maximisation estimation methods were found to be performing well for frequent repeated time-to-event models.

In conclusion, this thesis presents approaches, estimation methods, and diagnostics adapted for treating discrete data. Novel models and diagnostics were developed when lacking and applied to biological observations.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2011. 80 p.
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 145
Pharmacometrics, pharmacodynamics, disease progression, modelling, discrete data, count, ordered categorical, repeated time-to-event, RTTCE, RCEpT, NONMEM, FOCE, LAPLACE, SAEM, AGQ, pain scores, epilepsy seizures, gastroesophageal symptoms, statistical power, simulations, diagnostics
National Category
Pharmaceutical Sciences
Research subject
Pharmacokinetics and Drug Therapy
urn:nbn:se:uu:diva-150929 (URN)978-91-554-8064-6 (ISBN)
Public defence
2011-05-20, B41, BMC, Husargatan 3, Uppsala, 13:15 (English)
Available from: 2011-04-28 Created: 2011-04-07 Last updated: 2011-05-05Bibliographically approved

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