Optimal clinical trial design based on a dichotomous Markov-chain mixed-effect sleep model

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Ernest II, CharlesUppsala universitet,Institutionen för farmaceutisk biovetenskap (författare)

Optimal clinical trial design based on a dichotomous Markov-chain mixed-effect sleep model

Artikel/kapitelEngelska2014

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2014-10-12
Springer Science and Business Media LLC,2014
electronicrdacarrier

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LIBRIS-ID:oai:DiVA.org:uu-208583
https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-208583URI
https://doi.org/10.1007/s10928-014-9391-zDOI

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Språk:engelska
Sammanfattning på:engelska

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Ämneskategori:art swepub-publicationtype

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D-optimal designs for discrete-type responses have been derived using generalized linear mixed models, simulation based methods and analytical approximations for computing the fisher information matrix (FIM) of non-linear mixed effect models with homogeneous probabilities over time. In this work, D-optimal designs using an analytical approximation of the FIM for a dichotomous, non-homogeneous, Markov-chain phase advanced sleep non-linear mixed effect model was investigated. The non-linear mixed effect model consisted of transition probabilities of dichotomous sleep data estimated as logistic functions using piecewise linear functions. Theoretical linear and nonlinear dose effects were added to the transition probabilities to modify the probability of being in either sleep stage. D-optimal designs were computed by determining an analytical approximation the FIM for each Markov component (one where the previous state was awake and another where the previous state was asleep). Each Markov component FIM was weighted either equally or by the average probability of response being awake or asleep over the night and summed to derive the total FIM (FIMtotal). The reference designs were placebo, 0.1, 1-, 6-, 10- and 20-mg dosing for a 2- to 6-way crossover study in six dosing groups. Optimized design variables were dose and number of subjects in each dose group. The designs were validated using stochastic simulation/re-estimation (SSE). Contrary to expectations, the predicted parameter uncertainty obtained via FIMtotal was larger than the uncertainty in parameter estimates computed by SSE. Nevertheless, the D-optimal designs decreased the uncertainty of parameter estimates relative to the reference designs. Additionally, the improvement for the D-optimal designs were more pronounced using SSE than predicted via FIMtotal. Through the use of an approximate analytic solution and weighting schemes, the FIMtotal for a non-homogeneous, dichotomous Markov-chain phase advanced sleep model was computed and provided more efficient trial designs and increased nonlinear mixed-effects modeling parameter precision.

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Nyberg, JoakimUppsala universitet,Institutionen för farmaceutisk biovetenskap(Swepub:uu)jonyb109 (författare)
Karlsson, Mats O.Uppsala universitet,Institutionen för farmaceutisk biovetenskap(Swepub:uu)matskarl (författare)
Hooker, Andrew C.Uppsala universitet,Institutionen för farmaceutisk biovetenskap(Swepub:uu)ancho179 (författare)
Uppsala universitetInstitutionen för farmaceutisk biovetenskap (creator_code:org_t)

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Ingår i:Journal of Pharmacokinetics and Pharmacodynamics: Springer Science and Business Media LLC41:6, s. 639-6541567-567X1573-8744

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Av författaren/redakt...: Ernest II, Charl ...; Nyberg, Joakim; Karlsson, Mats O ...; Hooker, Andrew C ...

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MEDICIN OCH HÄLSOVETENSKAP: MEDICIN OCH HÄLS ...; och Medicinska och f ...; och Farmaceutiska ve ...

Artiklar i publikationen: Journal of Pharm ...

Av lärosätet: Uppsala universitet

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