The State of Respiratory in Clinical Research - 2020&Beyond - a podcast by ERT

What trends have you seen in respiratory in 2019?

In previous years, there were a number of blockbuster drugs developed for conditions like asthma and COPD. However, these drugs are beginning to move off-patent, so the industry is beginning to see studies for generics taking place. Because these blockbuster drugs are still on the market, sponsors are instead looking for new indications to apply these treatments to, where they might achieve small benefits. In order to find these incremental effects, the size of the study must increase. However, respiratory trials are not immune from the industry-wide patient recruitment issue. Additionally, these new products are fairly niche and respond to a small subset of patients; as drug companies are testing a lot of the same mechanisms, this leads to more competition for an already small patient population. The shift in clinical research towards personalized medicine continues to exacerbate the problem. Finally, this new search for small treatment effects requires very accurate data.

What do you anticipate respiratory drug development looks like in 2020 and beyond?

The key change is going to be a stronger focus on data quality and the importance of understanding exactly how the drug works in every individual patient. In order to do this, the challenge of data variability needs to be addressed by a shift towards research-grade quality lung function testing. This will allow the data to reflect small treatment effects. The updated ATS/ERS guidance published in October 2019 recognizes the importance of reducing data variability.

How does this new guidance and focus on reducing data variability affect the industry in general?

High quality data often comes with a higher cost but the potential rewards are huge, because data variability has an impact on every phase of development and can compromise decision-making and revenue potential. We’ve learned that the results of a trial can be undermined even if only 10% of the data is corrupt.

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