c ID: 4.8 yrs, Anal. 4.8, Resp. 6.2, CV: 6.5, Endo. 7.8, Oncol. 7.9, CNS: 8.9, GI 9.7 yrs
Fig. 1.22. R&D Productivity: Speed to Market Times
Source: Getz KA, deBruin A. Pharm Exec July 2000; Center Watch. State of the Clinical Trials Industry 5th Ed. Thomson Pub. 2005 (data
manufacturing and sales by the drug's originator company is often short after product approval. Most drug patents have only about 5 years left after approval, although a patent exists for 17 years (20 years with North American Trade Agreement; NAFTA). This situation relates to patenting of a drug during the early research stage and the long time frame for R&D, which uses up the patent life before approval.
Figure 1.22 presents statistics for clinical development times for all product approvals during the 1980s, 1990s, and 2000s. The overall average time was about 6 years to perform all the clinical research studies but ranged widely from 4 to 10 years. The therapeutic category for a potential product dramatically influences the time for clinical research, with the shortest being infectious disease at 4.8 years, related to the simpler studies and the longest for gastrointestinal (GI) and central nervous system (CNS) categories at 8-9 years. Oncology products are being studied over shorter times, as the fast-track status for many of the newer products in the 2000s has become the norm. Individual companies benchmark each other with this statistic, addressing their relative efficiency. Schering-Plough ranked at the top with a 4.6 years average for their products with all the top companies at or under about 6 years, based on 1996 and 2001 data. In an earlier publication, AstraZeneca ranked first with a 3.7 years average and GlaxoSmithKline was second at 4.1 years for 1981 to 1999 data. It should be noted that the companies identify global portfolio planning management (PPM) as one of the best practices to achieve the better (shorter) time frames. PPM also directly and favorably impacts a couple of other best practices, project team operations and use of technology for planning and communications by the teams. Realistic protocols are important in speed because they espe cially will be easier to conduct for the sites and investigators, easier to interpret in statistical analysis, and likely require less review time for regulatory authorities [22, 34].
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