Keitaro Nakajima1,2, Ramzi Dagher3, Laurie Strawn4, Jun Urushidani1, Tatsuo Kurokawa1, Koji Chiba1,5. 1. 1 Department of Drug Development & Regulatory Science, Keio University of Pharmacy, Tokyo, Japan. 2. 2 Regulatory Affairs Division, Development Japan, Pfizer Japan Inc, Tokyo, Japan. 3. 3 Worldwide Safety and Regulatory, Pfizer Inc, Groton, CT, USA. 4. 4 Worldwide Safety and Regulatory, Pfizer Inc, San Diego, CA, USA. 5. 5 Laboratory of Clinical Pharmacology, Yokohama University of Pharmacy, Yokohama, Japan.
Abstract
BACKGROUND: The delay of initiation of clinical development is considered a causes of delay of approval of drugs (drug lag) in Japan. METHODS: For oncology drugs newly approved between 2000 and 2012 in Japan, a possible impact of delay of initiation of clinical development (development start lag [DSL]) on delay of approval (approval lag [AL]) was investigated, focusing on the delay from the US timelines. The equation defining the relationship between the DSL and AL of 33 oncology drugs was calculated by using simulation models, then the Pearson coefficient of correlation between parameters was calculated. RESULTS: From the analysis of all drugs investigated, a positive relationship between the DSL and AL was suggested. However, the relationship seemed to have 2 phases, including a flat phase, followed by a linearly increased phase with a breakpoint at 2340 DSL days (approximately 6.4 DSL years). CONCLUSIONS: Shortening the DSL is important for reducing large AL, but it is not necessary to eliminate the DSL completely for the purpose of minimizing the AL.
BACKGROUND: The delay of initiation of clinical development is considered a causes of delay of approval of drugs (drug lag) in Japan. METHODS: For oncology drugs newly approved between 2000 and 2012 in Japan, a possible impact of delay of initiation of clinical development (development start lag [DSL]) on delay of approval (approval lag [AL]) was investigated, focusing on the delay from the US timelines. The equation defining the relationship between the DSL and AL of 33 oncology drugs was calculated by using simulation models, then the Pearson coefficient of correlation between parameters was calculated. RESULTS: From the analysis of all drugs investigated, a positive relationship between the DSL and AL was suggested. However, the relationship seemed to have 2 phases, including a flat phase, followed by a linearly increased phase with a breakpoint at 2340 DSL days (approximately 6.4 DSL years). CONCLUSIONS: Shortening the DSL is important for reducing large AL, but it is not necessary to eliminate the DSL completely for the purpose of minimizing the AL.