Productivity tools helped trial sector recover from COVID says IQVIA

Clinical trial activity has recovered from COVID-19 according to new analysis, which suggests “productivity enabling” technologies and increased biopharma R&D spending are the key dynamics.

The research, by the IQVIA Institute for Human Data Science, revealed that the total volume of clinical trial starts stabilized in 2024 after the year-on-year declines seen in 2022 and 2023, reaching 5,318.

According to the authors, short-term volatility caused by the pandemic has been offset by an increase in trials from China-headquartered companies and, more recently, an uptick in Phase I activity at emerging biopharma and larger firms.

In addition, clinical productivity increased from 2023 to 2024, as evidenced by an increase in Phase III success rates.

The IQVIA team also noted that enrollment duration – the time taken to identify and recruit participants for drug studies – stabilized in 2024, after having increased between 2021 and 2023.

Furthermore, average inter-trial intervals – the periods between the end of a study and the start of the next – are currently 17 months, which is much less than the 32-month interval seen in 2022.

Productivity

The research also indicated an increase in biopharma funding – from $71 billion in 2023 to $102 billion last year – which Murray Aitken, IQVIA Institute executive director and research author, said was a positive sign.

“Increases in funding, normalization of clinical trial starts, stabilization or acceleration of key cycle time drivers, and improvements in late-stage success and clinical productivity — all of which were observed in 2024 — demonstrate meaningful year-on-year progress in biopharmaceutical R&D.

“Although geopolitical, economic and other external ecosystem factors are increasing pressure on innovators, effective application of a range of productivity enablers has had a positive impact on the efficiency of clinical development,” Aitken said.

Examples of “productivity enablers” include clinical technologies, better patient representation and increased use of real-world evidence and artificial intelligence solutions.

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Header image: Depositphotos@EdZbarzhyvetsky