uu.seUppsala University Publications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Semiparametric Distributions with Estimated Shape Parameters
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. (Farmakometri)
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. (Farmakometri)
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. (Farmakometri)
2009 (English)In: Pharmaceutical research, ISSN 0724-8741, E-ISSN 1573-904X, Vol. 26, no 9, 2174-2185 p.Article in journal (Refereed) Published
Abstract [en]

PURPOSE: To investigate the use of adaptive transformations to assess the parameter distributions in population modeling. METHODS: The logit, box-cox, and heavy tailed transformations were investigated. Each one was used in conjunction with the standard (exponential) transformation for PK and PD parameters. The shape parameters of these transformations were estimated to allow the parameter distributions to more accurately resemble a wider range of parameter distributions. The transformations were tested both in simulated settings where the true distributions were known and in 30 models developed from real data. RESULTS: In the simulated setting the transformations were better than the standard lognormal distribution at characterizing the true distributions. Improvement could also be seen in objective function value (OFV) and in simulation based diagnostics. In the real datasets, significant model improvement based on OFV could be seen in 22, 18, and 22 out of the 30 models for the three transformations respectively. CONCLUSION: Transformations with estimated shape parameters are a promising approach to relax the often erroneous assumption of a known shape of the parameter distribution. They offer a simple and straightforward way of handling and characterizing parameter distributions.

Place, publisher, year, edition, pages
2009. Vol. 26, no 9, 2174-2185 p.
Keyword [en]
estimation, normality assumption, parameter distributions, population modeling, transformations
National Category
Pharmaceutical Sciences
Identifiers
URN: urn:nbn:se:uu:diva-97515DOI: 10.1007/s11095-009-9931-1ISI: 000268584700013OAI: oai:DiVA.org:uu-97515DiVA: diva2:172494
Available from: 2008-09-12 Created: 2008-09-12 Last updated: 2017-12-14Bibliographically approved
In thesis
1. Improved pharmacometric model building techniques
Open this publication in new window or tab >>Improved pharmacometric model building techniques
2008 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Pharmacometric modelling is an increasingly used method for analysing the outcome from clinical trials in drug development. The model building process is complex and involves testing, evaluating and diagnosing a range of plausible models aiming to make an adequate inference from the observed data and predictions for future studies and therapy.

The aim of this thesis was to advance the approaches used in pharmacometrics by introducing improved models and methods for application in essential parts of model building procedure: (i) structural model development, (ii) stochastic model development and (iii) model diagnostics.

As a contribution to the structural model development, a novel flexible structural model for drug absorption, a transit compartment model, was introduced and evaluated. This model is capable of describing various drug absorption profiles and yet simple enough to be estimable from data available from a typical trial. As a contribution to the stochastic model development, three novel methods for parameter distribution estimation were developed and evaluated; a default NONMEM nonparametric method, an extended grid method and a semiparametric method with estimated shape parameters. All these methods are useful in circumstances when standard assumptions of parameter distributions in the population do not hold. The new methods provide less biased parameter estimates, better description of variability and better simulation properties of the model. As a contribution to model diagnostics, the most commonly used diagnostics were evaluated for their usefulness. In particular, diagnostics based on individual parameter estimates were systematically investigated and circumstances which are likely to misguide modelers towards making erroneous decisions in model development, relating to choice of structural, covariate and stochastic model components were identified.

In conclusion, novel approaches, insights and models have been provided to the pharmacometrics community.

Implementation of these advances to make model building more efficient and robust has been facilitated by development of diagnostic tools and automated routines.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2008. 98 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 80Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 80
Keyword
Model building, Absorption model, Transit compartment model, Nonparametric method, Extended grid method, Semiparametric, Distribution transformation, Shrinkage, Model diagnostics
Identifiers
urn:nbn:se:uu:diva-9272 (URN)978-91-554-7275-7 (ISBN)
Public defence
2008-10-03, Room B41, BMC, Uppsala, 09:15
Opponent
Supervisors
Available from: 2008-09-12 Created: 2008-09-12Bibliographically approved
2. Population Pharmacodynamic Modeling and Methods for D2-receptor Antagonists
Open this publication in new window or tab >>Population Pharmacodynamic Modeling and Methods for D2-receptor Antagonists
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Early predictions of a potential drug candidate’s time-course of effect and side-effects, based on models describing drug concentrations, drug effects and disease progression, would be valuable to make drug development more efficient. Pharmacodynamic modeling can incorporate and propagate prior knowledge and be used for simulations of different scenarios.

In this thesis three population pharmacodynamic models were developed to describe the antipsychotic effects and the side-effects prolactin elevation and Extra Pyramidal Symptoms (EPS) following administration of D2-receptor antagonists, commonly used in the treatment of schizophrenia.

Model parameter estimates of prolactin elevating potencies of six compounds correlated with in vitro values of receptor affinities, and parameters related to diurnal prolactin variation and tolerance were similar for the different compounds. The developed prolactin model can thereby be used to predict the time-course of prolactin elevation in patients for a drug candidate using information on in vitro affinity to the D2-receptor. Furthermore, the clinical antipsychotic effect and the prolactin elevation was found to correlate on the individual level for the three antipsychotic compounds investigated and a quantitative relation between D2-receptor occupancy in the brain and prolactin elevation was established. These results support the use of prolactin concentrations as a biomarker in drug development or for individual dose adjustments in clinical care.

The developed model for spontaneously reported EPS adverse events, following treatment with one of five antipsychotics drugs, characterized both the duration and severity of EPS. The model successfully described both the proportions and number of transitions between severity grades and was shown to adequately simulate longitudinal categorical EPS data.

Complex pharmacodynamic models are often associated with long estimation times and non-normal distributions of individual parameters. A method for shortening computation times by substituting differential equations for difference equations was evaluated and shown to be valuable for some models. In addition, transformation of distributions allowed for non-normal distributions of between-subject variability to be better characterized and thereby simulation properties were improved.

In conclusion, population pharmacodynamic models for a range of D2-receptor antagonists were developed and together with the investigated methods the models can facilitate prediction of effects and side-effects in drug development.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2012. 69 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 161
Keyword
population modeling, schizophrenia, D2-antagonists, pharmacodynamics, drug development
National Category
Pharmaceutical Sciences
Identifiers
urn:nbn:se:uu:diva-172540 (URN)978-91-554-8346-3 (ISBN)
Public defence
2012-05-25, B41, Biomedicinskt Centrum, Husargatan 3, Uppsala, 13:15 (English)
Opponent
Supervisors
Available from: 2012-05-03 Created: 2012-04-11 Last updated: 2012-08-01Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text

Authority records BETA

Karlsson, Mats

Search in DiVA

By author/editor
Karlsson, Mats
By organisation
Department of Pharmaceutical Biosciences
In the same journal
Pharmaceutical research
Pharmaceutical Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 606 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf