  It is challenging to elucidate the effects of changes in external influences
(such as economic or policy) on the rate of US drug approvals. Here, a novel
approach, termed the Chronological Hurst Exponent (CHE), is proposed, which
hypothesizes that changes in the long-range memory latent within the dynamics
of time series data may be temporally associated with changes in such
influences. Using the monthly number the FDA Center for Drug Evaluation and
Research (CDER) approvals from 1939 to 2019 as the data source, it is
demonstrated that the CHE has a distinct S-shaped structure demarcated by an
8-year (1939-1947) Stagnation Period, a 27-year (1947-1974) Emergent
(time-varying Period, and a 45-year (1974-2019) Saturation Period. Further,
dominant periodicities (resolved via wavelet analyses) are identified during
the most recent 45-year CHE Saturation Period at 17, 8 and 4 years; thus, US
drug approvals have been following a Juglar-Kuznet mid-term cycle with
Kitchin-like bursts. As discussed, this work suggests that (1) changes in
extrinsic factors (e.g., of economic and/or policy origin ) during the Emergent
Period may have led to persistent growth in US drug approvals enjoyed since
1974, (2) the CHE may be a valued method to explore influences on time series
data, and (3) innovation-related economic cycles exist (as viewed via the proxy
metric of US drug approvals).
