This report describes the application of a well-established time series model to ClinicalTrials.gov registry data to quantitatively estimate the effect of the COVID-19 pandemic on the number of clinical trials in 2020. The approach described here is unique, given that 13 years of pre-COVID-19 clinical trial registry data were included in the model (previous analyses have relied on more recent data, with the earliest data being from 2015 (26)). This facilitated the observation of both seasonal and long-term trends, and it further allowed robust forecasts of what the dynamics might have been in the absence of COVID-19.
The COVID-19 pandemic is an unprecedented event that continues to leave its mark on all areas of socioeconomic functioning. This analysis has confirmed that the pandemic led to the widespread suspension of ongoing trials and postponement of planned studies. Based on the ETS model, the number of ongoing trials in 2020 Q2 would have been higher by approximately 2,300 trials if the pandemic had not occurred. This gap decreased later during the year, partly because of an increase in new studies related to COVID-19, but the number of ongoing trials in 2020 Q4 remained lower than expected by approximately 1,300 trials. If studies related to COVID-19 are excluded, this gap increases to a peak of almost 5,000 in 2020 Q2.
Besides the pronounced drop in clinical trial numbers in 2020, there was also a slight but noticeable decrease in 2019 when considering the long-term trend observed over the period of 2007–2018. The reasons for this are unclear, but this decrease might have been related to 2019 being the year of the lowest world economic growth since the financial crisis of 2008–2009 (27). This makes 2019 a poor reference for year-to-year comparisons, as it would lead to underestimation of the impact of COVID-19 on the dynamics of clinical trials during 2020. To overcome the limitations of such an approach, we based our analysis on a comparison of the actual number of trials in 2020 Q1–Q4 in the CTDB with those forecasted by an ETS model fitted to data from the entire available historical pre-COVID-19 timespan (2007–2019) (23).
The field of clinical research has shown great flexibility and the ability to accommodate completely new conditions. This was illustrated by the upsurge in new experimental trials related to COVID-19 that were registered in Q2—relatively soon after the outbreak began. One consequence of which, was that the number of ongoing trials in the area of infectious diseases noticeably exceeded predictions based on data from previous years. This implies that less than a quarter was required to design, prepare, and initiate these new clinical trials. Secondly, a re-emergence of non-COVID-19 trials was observed in the second half of 2020, such that the number of trials registered in 2020 Q4 exceeded the predictions for all 20 of the health domains. Lastly, the observed shift from traditional drugs to biologics in COVID-19 studies may reflect the recent advancements in bioinformatics and molecular biology that have accelerated the development pathway for new therapies (including vaccines) compared with the traditional research approaches applied to small molecules (28).
Despite the increase in new trials in 2020 Q4, the overall number of ongoing studies at the end of 2020 remained lower than expected based on trends over the pre-COVID-19 era. However, looking at the recent upward trend in new trials, there is a chance that the expected level of active trials will soon be attained. This is of paramount importance to the pharmaceutical industry, clinicians, and patients, since drugs undergoing clinical trials have the potential to increase the spectrum of available therapies for a variety of diseases, and any delays in clinical trials may translate into a loss of clinical benefit (29). The higher-than-forecasted proportions of trials ended in 2020 Q4 might have also been associated with the financial closure of projects at the end of the year, due to the postponement of difficult financial decisions regarding trial closure to the end of the annual financial cycle (for many companies, this coincides with the end of the calendar year).
Several risk mitigation measures have been implemented to reduce the likelihood of SARS-CoV-2 transmission and lessen the impact of the pandemic on clinical trial programs (3, 4, 10, 11, 14, 30, 31). These measures have included staggering staff shifts, prioritizing specific trials and canceling or postponing others, pausing patient recruitment for ongoing trials, substituting in-person site monitoring visits and patient visits with technology-based solutions wherever feasible (e.g., using e-consent methods, telemedicine consults, remote electronic medical record access, and virtual monitoring of data), extending patient study visit windows, and shipping oral drugs directly to patients. Regulatory agencies such as the U.S. Food and Drug Administration (32) and the European Medicines Agency (33), as well as various research, philanthropic, and advocacy organizations, have issued guidance to help address the challenges inherent in conducting clinical trials in the pandemic era (11).
Although the pandemic has been disruptive to clinical programs worldwide, experts believe that many of the adaptations made to mitigate this impact and rapidly generate high-quality evidence in COVID-19-related trials are beneficial outside of this context, offering long-term opportunities to transform the clinical trial landscape (4, 9, 11, 34–37). Several of these improvements are considered long overdue even in the absence of COVID-19, such as more streamlined trial designs and the widespread adoption of digital and remote technologies.
The approach used in this study has several limitations. First, not all clinical trials are registered in the CTDB. Second, since all studies with keywords related to COVID-19 were classified as COVID-19-related, it is possible that the proportion of COVID-19 trials was overestimated by including studies amended, suspended, terminated, or withdrawn for any reason related to the COVID-19 outbreak. To estimate the extent of this overestimation, we re-ran the analysis with COVID-19-related studies redefined as only those with COVID-19-related keywords in the study title. We found that 84% of studies with a keyword related to COVID-19 in any field also had such a keyword in the title; these studies were, therefore, highly likely to actually comprise COVID-19-related trials. Thus, we concluded that the approach used to classify studies in this analysis provided a good trade-off between sensitivity and specificity and did not lead to substantial overestimation of the proportion of studies related to COVID-19 therapies. Third, this analysis was based on a “snapshot” of the data published by the CTDB on January 1, 2021, and this dataset might not have contained updates of the CTDB records from 2020 that were delayed. Fourth, although study records submitted to the CTDB are subject to quality control and the Posting Procedures guidelines (38), users have substantial freedom to enter customized records. Thus, inconsistencies, inaccuracies, and deficiencies in the entered information (including dates) are unavoidable.