Analysis of regulatory review times of new drugs in Japan: association with characteristics of new drug applications, regulatory agency, and pharmaceutical companies.
OBJECTIVE
Various factors have been reported to be associated with the duration of regulatory review of new drug applications (NDAs). We investigated potential links between the review times in Japan and the attributes of NDAs, the regulatory agency and pharmaceutical companies.


METHODS
We analysed new drugs approved in 2000-2009 in Japan using a proprietary database collected through annual surveys to pharmaceutical companies. Regression models in which individual firms were treated as either a fixed effect or a random effect were applied to examine factors associated with the overall review time and the duration of each step of the review.


CONCLUSIONS
The fixed effect model analysis using variations within each firm indicated that new molecular entities that were submitted to the Pharmaceuticals and Medical Devices Agency (PMDA), priority reviews and pre-NDA consultations were associated with a shorter overall review time, whereas additional studies during the review resulted in a longer review. In the random effect model analysis using both within- and between-firm variations, use of end-of-phase 2 consultations and foreign clinical data also had negative coefficients, suggesting the effect of these two vary among firms. Analysis of each step of the review process revealed NDAs reviewed by the Committee on Drugs under the Ministry of Health, Labour and Welfare, and the number of NDAs assigned to a review team were significantly linked with their duration, whereas consultation services and the number of reviewers had no relation.


CONCLUSIONS
Factors associated with each step of the review process as well as the differences in attributes and strategies among pharmaceutical companies should be considered to further improve the speed, quality and efficiency of the regulatory review.
Graduate School of Pharmaceutical Sciences, The University of Tokyo, Tokyo, Japan.
T
T
Ishibashi
M
M
Kusama
Y
Y
Sugiyama
S
S
Ono
D016208:Databases, Factual; D017277:Drug Approval / Q000458:organization & administration / Q000706:statistics & numerical data*; D004345:Drug Industry / Q000706:statistics & numerical data*; D006801:Humans; D017387:Investigational New Drug Application / Q000706:statistics & numerical data*; D007564:Japan; D012044:Regression Analysis; D013997:Time Factors