METHODS: All new pharmaceutical products approved between January 2015 and March 2021 were examined (n = 136) using publicly available information. Factors associated with drug approval lag were determined using multiple linear regression.
RESULTS: The median drug approval lag was 855 days. Drug approval lag was associated with drug characteristics and regulatory factors. Median submission lag and median review time for products which fulfilled the requirement for the new regulations (Conditional Registration/ Facilitated Registration Pathway) were shorter compared to products which did not fulfil the requirement.
CONCLUSION: Drug approval lag may delay the access of innovative medicine to patients, and this may lead to an increase in morbidity, mortality and healthcare costs. Good Regulatory Practices ensure efficient and transparent regulatory system which support the public health policy objectives in the most efficient way. The new regulations in Malaysia reduced the median submission lag and review time. The findings may be useful for regulators to consider for future policy development for medication access.
METHODS: The OpERA tool was used to collect specific milestone data that identify time periods, review stages, and data points for new active substances and biosimilars approved by NPRA in 2017.
RESULTS: In 2017, 25 new active substances and 1 biosimilar were approved by NPRA in a median of 515 days, representing both agency and applicant time. The median time between dossier receipt and the initiation of NPRA scientific assessment was 135 days, but there was a wide variation in queuing time. The median total assessment time was 279 days (agency and applicant timing). NPRA took a median of 166 days; applicants took a median of 131 days to respond to deficiency questions, with up to 6 cycles of review required for approval and 65% of applications requiring 4-5 cycles to provide satisfactory responses.
CONCLUSIONS: As a result of these data, NPRA proposes three improvements: target start for scientific assessment 100 days after file acceptance, a maximum of 5 review cycles, and applicant response time limited to 6 months. These results will serve as a baseline for further assessment.
STUDY QUESTION: Whether FDA death data in the PLATO trial matched the local site records.
STUDY DESIGN: The NDA spreadsheet contains 938 precisely detailed PLATO deaths. We obtained and validated local evidence for 52 deaths among 861 PLATO patients from 14 enrolling sites in 8 countries and matched those with the official NDA dataset submitted to the FDA.
MEASURES AND OUTCOMES: Existence, precise time, and primary cause of deaths in PLATO.
RESULTS: Discrepant to the NDA document, sites confirmed 2 extra unreported deaths (Poland and Korea) and failed to confirm 4 deaths (Malaysia). Of the remaining 46 deaths, dates were reported correctly for 42 patients, earlier (2 clopidogrel), or later (2 ticagrelor) than the actual occurrence of death. In 12 clopidogrel patients, cause of death was changed to "vascular," whereas 6 NDA ticagrelor "nonvascular" or "unknown" deaths were site-reported as of "vascular" origin. Sudden death was incorrectly reported in 4 clopidogrel patients, but omitted in 4 ticagrelor patients directly affecting the primary efficacy PLATO endpoint.
CONCLUSIONS: Many deaths were inaccurately reported in PLATO favoring ticagrelor. The full extent of mortality misreporting is currently unclear, while especially worrisome is a mismatch in identifying primary death cause. Because all PLATO events are kept in the cloud electronic Medidata Rave capture system, securing the database content, examining the dataset changes or/and repeated entries, identifying potential interference origin, and assessing full magnitude of the problem are warranted.