Breast cancer retained its position as the most-studied disease area in clinical trials in 2022, despite a drop in activity, according to analysis from analytics company Phesi.
The company’s global analysis of all clinical trials conducted in 2022 showed that Covid-19 came second.
Three of the top five most-studied disease areas fell within oncology, with prostate cancer the third most-studied disease, solid tumours fourth, and stroke fifth.
“Oncology remains an area of high investment in clinical development, however, 2022 has seen a widespread scale back of overall activity. The reduction of recruiting trials in the top most-studied disease indications is due to several global factors including the pandemic and the war in Ukraine,” commented Dr Gen Li, President, Phesi.
“With an increase in available vaccines and therapies, it is not surprising that the number of recruiting trials for Covid-19 therapies has fallen. However, the reduction in breast cancer trials is unexpected, with 113 fewer recruiting trials in 2022 compared with 2021. This demonstrates the pressures facing the clinical development industry as the consequences from several years of disruption become visible.”
The analysis has also revealed an increase in Phase II terminations. In 2022, the attrition rate for Phase II clinical trials was 28% – 42% higher than the previous five-year average.
This is the highest proportion of terminations at Phase II in recent years and is even higher than in 2020, where the Covid-19 pandemic caused unprecedented disruption.
These high levels of attrition at Phase II are likely to have an ongoing effect on the clinical development industry and may slow the rate at which new therapies reach market, or even prevent viable new therapies from ever reaching patients.
“As we enter the fourth year of pandemic, the industry has more tools to mitigate its impact, but signs of damage continue to emerge. Clinical trial design must follow a more data-led, patient-centric approach to minimise protocol amendments and terminations, and ensure successful study outcomes,” said Dr Li.
Phesi suggests companies should use predictive analytics in protocol design, simulate trials, and use digital patient profiles, as well as indication-specific predictive modelling to streamline trial design and improve identification of patient populations and site selection.