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Now, more than ever, the healthcare industry is searching for ways to live by the ‘work smarter, not harder’ motto. The first few months of the global pandemic certainly pushed pharmaceutical companies to reevaluate how to conduct clinical trials. Then and now, all aspects of clinical development are being reviewed to improve trial efficiencies. However, the truth is that addressing inefficiencies throughout the trial process to enhance clinical outcomes has been a focus for sponsors long before COVID-19. In an increasingly complex clinical development landscape, sponsors need to improve productivity and drive higher quality outcomes over accelerated trial timelines, while reducing costs, which is no easy feat. At the same time, it is essential to reduce the burden on patients and site teams.
Especially with unprecedented obstacles, like the pandemic, sponsors realise it is necessary to examine individual trial processes within the end-to-end model to address inefficiencies that inhibit productivity. Most organisations are turning to digital solutions, including artificial intelligence/machine learning (AI/ML), to digitise and modernise the clinical development process. This evolution allows sponsors and study teams to increase productivity by automating repetitive routine work they traditionally spend time and effort to complete. COVID-19 provided a catalyst for sponsors to investigate and adopt these solutions at scale.
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