Estimation of median effective dose of anti spasmodic medicine in adaptive design by combining the models

authors:

avatar Alireza Akbarzadeh Bagheban ORCID , * , avatar Malihe Nasiri , avatar Hamid Alavi Majd , avatar Bijan Shafaghi


how to cite: Akbarzadeh Bagheban A, Nasiri M, Alavi Majd H, Shafaghi B. Estimation of median effective dose of anti spasmodic medicine in adaptive design by combining the models. koomesh. 2010;11(3):e152285. 

Abstract

Introduction: Estimation of target dose with high precision is a key goal in pharmaceutical studies that achieving this goal depends greatly on an efficient design. One of these adequate designs is adaptive design. The median effective dose is an important dose that is criterion for assessment the power of a medicine. The purpose of this study was estimation of the median effective dose of anti spasmodic medicine in adaptive design and comparison the precision of the estimation with conventional parallel design. Materials and Methods: Seventy guinea pigs were divided into seven groups (n=10) and each group was studied for one dose. One of the adaptive designs that uses frequently in pharmaceutical studies is up-and-down design. In this design, the number of samples in each dose was determined. Then for estimation of median effective dose, we used a method of the combination of dose-response logistic, dose-response log-linear, linear and Emax models and R software was used for data analysis. Result: In parallel design, number of samples in each dose was 10, but in adaptive design, number of samples in and doses was 21 and other doses were 7. MSE in parallel design was 59 and in adaptive design were 21. Estimation of median effective dose in dose-response logistic was , in dose-response log-linear , in Emax and in linear model was . Using combination of the four models in adaptive design, median effective dose was estimated . Conclusion: In addition to flexibility of adaptive design that concentrates the allocation of observations near the target dose, it seems this design is more efficient than parallel design in medicinal studies.