Investigating Rates of Food and Drug Administration Approvals and Guidances in Drug Development: A Structural Breakpoint
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ORIGINAL RESEARCH
Investigating Rates of Food and Drug Administration Approvals and Guidances in Drug Development: A Structural Breakpoint/ Cointegration Timeseries Analysis Iraj Daizadeh, PhD1 Received: 10 January 2020 / Accepted: 15 January 2020 © The Drug Information Association, Inc 2020
Abstract Background The number of original and supplemental ANDAs, BLAs, NDAs, and Biosimilars FDA drug/biologic approvals (Approvals) has risen dramatically in the recent years, incidentally, so has the number of issued FDA guidances (Guidances). It is hypothesized that if the structures of the two timeseries are similar and/or concomitantly co-evolving, then there is a relationship between the two variables that may be worthy of further investigation. Methods Structural breakpoint (SBP) and cointegration (CI) analyses are used to provide insights into the relatedness of the two timeseries (Approvals, Guidances). Various descriptive statistics (e.g., nonparametric correlation testing, decomposition, unit testing, stationarity, and maximum order of integration) were also performed to better understand the nature of the timeseries understudy. Results Structural breaks were identified with the following dates: Approvals (1983, 1989, 1996, 2004, and 2012) and Guidances (1995 and 2012). Approvals and Guidances were (medium) correlative, nonstationary, and cointegrated with a maximum order of integration of one (I(1)). Descriptive statistical markers suggest additional similarities (e.g., seasonal variation) between the two timeseries. Conclusions To the author’s knowledge, this is the first work to empirically investigate Guidances and their relationship with Approvals. The similarity in the structure of the timeseries (e.g., seasonal variation, SBPs and CI) suggests a deeper relationship between Guidances and Approvals, including the existence of a “long-run” equilibrium (wherein one or more exogenous factors restrain the divergence) between the two variables. This work offers an exciting opportunity for further research into the processes influencing the rates of Approvals and Guidances. A discussion on the limitations of the approach is also presented. Keywords FDA · Guidances · Approvals · Cointegration · Structural breakpoints · Timeseries
Introduction There has been much interest in understanding a key metric associated with drug development: the number of Food and Drug Administration (FDA) approvals per time. Considering original and supplemental ANDAs, BLAs, NDAs, and Biosimilars approvals, the trend rises in an exponential-like pattern over recent years culminating to the highest annual rate on record. While some researchers have criticized this * Iraj Daizadeh [email protected] 1
Global Regulatory Affairs, Pfizer, Inc., 610 Main Street, Cambridge, MA 02139, USA
record achievement as potential easing in approval standards (see, e.g., [1] and reference therein), others have lauded this trend, attributing the success to technologies’ progress yielding treatments for those with (very) rare to (very) commo
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