"Drugs rushed to approval just before the deadline are two to three times more likely to eventually be pulled off shelves due to safety concerns, two to seven times more likely to receive added label warnings known as 'black box revisions', twice as likely to experience changes in manufacture, and two to seven times more likely to be voluntarily discontinued by manufacturers due to weak clinical demand," said Daniel Carpenter, the lead author of the paper to be published in the New England Journal of Medicine. The FDA first imposed a deadline on the drug approval process in 1992 as part of the Prescription Drug User Free Act, which stipulated that the FDA would face funding cuts if 90 per cent of all drug candidates were not been acted on within 12 months of submission. In 1997 the deadline was cut to just 10 months. For some time anecdotal evidence has suggested that these deadlines were having a detrimental effect on the drug approval process, because the drug regulators do not have enough time to plan the optimum design of clinical trials to obtain the most useful data about a drug's performance. To put this to the test, Carpenter created a mathematic model, based on data from drug trials dating back to 1950, which "learnt" to make drug approval decisions in the same way as the FDA. Carpenter then tested his model on new data, while changing both the timing of the deadlines and the bonus the FDA would receive if it met the deadline compared to the punishment if it missed the deadline. Factors contributing to the value of this bonus could include funding cuts, or issues such as loss of reputation or stress. "We saw a pile up of drugs waiting for approval near the deadline, and these drugs show more errors," Carpenter told LabTechnologist.com. However, the impact of this is not simply on how safe the drug is. "We must emphasise the effect this has on the efficacy of a drug, as well as the drug safety. We need high quality data on how the drug should be used." While Carpenter's research has not yet suggested a better approach to ensure a prompt drug approval process that still produces high quality data, he believes that relaxing the deadlines and providing more resources to the FDA may be the answer. "My hunch is that you would get a process in which we'd have greater confidence in drugs, and it would give the FDA leeway to ask for more data. It would reduce the pressure's on the FDA to give a more efficient regulatory process."