A third of clinical trials cancelled during Phase II

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Analysis of 13,490 clinical trials finds almost a third have been cancelled during Phase II amidst an overall decline in clinical development productivity.

Data analytics company Phesi has released the results of its mid-year global analysis of all clinical trials conducted in 2023 to date.

The analysis reveals that Covid-19 is no longer one of the top five most studied disease areas, and trial activity for depression has increased – becoming the fourth most studied disease globally.

Three of the top five most-studied diseases fall within oncology, with solid tumours the most studied disease indication, and breast cancer falling to the second-most studied, stroke third, and prostate cancer fifth.

“Awareness of the global mental health crisis has been growing in the wake of the Covid-19 pandemic. An estimated 5% of adults are affected by depression globally. New therapies to tackle this disease are desperately needed, with SSRIs – the last major class of antidepressants – launched over forty years ago,” commented Dr Gen Li, President, Phesi.

Phase II study attrition

The analysis also found that the rise in Phase II study attrition identified in Phesi’s end-of-year 2022 analysis has increased further. So far in 2023, 31% of trials at Phase II have been cancelled – this is a 55% increase on pre-Covid levels.

High levels of cancellations at Phase II increase the overall costs of clinical development considerably. More worryingly, such delays will have a knock-on effect on the rate at which new therapies reach market, and may even prevent viable new therapies from ever reaching patients.

“The clinical development industry is still feeling the effects of disruption caused by the pandemic. The fallout will be with us for some time longer, and we predict that we will see around two more years of high levels of Phase II attrition. The strain of these trial cancellations on the global drug development pipeline will be severe, and to ease the pain, productivity and trial efficiency needs to improve,” explained Dr Li.

“Unnecessary protocol amendments and trial cancellations are a symptom of inadequate protocol design. We must go back to the fundamentals and use data to improve the design of clinical trial protocols. By applying predictive analytics in protocol design, the industry can overcome enrollment difficulties, accelerate clinical trials and avoid amendments, overall improving productivity.”

The full report can be downloaded here.

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