Model-Based Approach to Predict Adherence to Protocol During Antiobesity Trials.
J Clin Pharmacol
; 58(2): 240-253, 2018 02.
Article
en En
| MEDLINE
| ID: mdl-28858397
ABSTRACT
Development of antiobesity drugs is continuously challenged by high dropout rates during clinical trials. The objective was to develop a population pharmacodynamic model that describes the temporal changes in body weight, considering disease progression, lifestyle intervention, and drug effects. Markov modeling (MM) was applied for quantification and characterization of responder and nonresponder as key drivers of dropout rates, to ultimately support the clinical trial simulations and the outcome in terms of trial adherence. Subjects (n = 4591) from 6 Contrave® trials were included in this analysis. An indirect-response model developed by van Wart et al was used as a starting point. Inclusion of drug effect was dose driven using a population dose- and time-dependent pharmacodynamic (DTPD) model. Additionally, a population-pharmacokinetic parameter- and data (PPPD)-driven model was developed using the final DTPD model structure and final parameter estimates from a previously developed population pharmacokinetic model based on available Contrave® pharmacokinetic concentrations. Last, MM was developed to predict transition rate probabilities among responder, nonresponder, and dropout states driven by the pharmacodynamic effect resulting from the DTPD or PPPD model. Covariates included in the models and parameters were diabetes mellitus and race. The linked DTPD-MM and PPPD-MM was able to predict transition rates among responder, nonresponder, and dropout states well. The analysis concluded that body-weight change is an important factor influencing dropout rates, and the MM depicted that overall a DTPD model-driven approach provides a reasonable prediction of clinical trial outcome probabilities similar to a pharmacokinetic-driven approach.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Pacientes Desistentes del Tratamiento
/
Peso Corporal
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Fármacos Antiobesidad
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Modelos Biológicos
/
Obesidad
Tipo de estudio:
Clinical_trials
/
Prognostic_studies
/
Risk_factors_studies
Límite:
Adult
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Female
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Humans
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Male
/
Middle aged
Idioma:
En
Revista:
J Clin Pharmacol
Año:
2018
Tipo del documento:
Article
País de afiliación:
Estados Unidos