AI in Clinical Research is On the Rise (and More from DIA 2021)
Each year, thousands of professionals from across the pharmaceutical industry come together to share data and ideas at the Drug Information Association (DIA) conference. This year, AiCure wanted to leverage the collective experience of those attending DIA to gain insights into how the industry views its evolving use of advanced machine learning and artificial intelligence (AI) technologies. We surveyed a large group of professionals at the conference, asking a range of questions focused primarily on industry innovation.
Following is a look at what we learned.
Investments in AI and machine learning are increasing
The vast majority of those surveyed reported that their companies are dedicating significant resources to AI and machine learning technologies and platforms. 42.2% noted that their organizations increased their investments in these technologies by 50%.
An increasing number of professionals are getting hands-on experience with AI and machine learning technologies
While about half of the survey respondents (51.1%) said that the amount of time they personally spend working with AI or machine learning stayed the same over the past year, nearly one-third (28.9%) told us that their time with the tech increased by 50%. And about 7% told us that their time working with AI and machine learning increased by double or more.
DIA attendees are bullish on the potential for Digital Biomarkers
When asked what facet of DBM technology has the greatest potential for impacting patient health over the next year, those surveyed saw a range of possible technologies with most impact.
- 29.5% – Speech content/language processing
- 21.3% – Patient video
- 19.7% – Actigraphy
- 14.8% – EEG
- 14.8% – Voice analysis
This relatively even spread reflects the broad utility of DBM. Additionally, we asked respondents to name the most impressive data they have seen in regard to digital biomarkers and received some compelling answers, including:
- Continuous DBM endpoints that could replace invasive biopsy
- COVID-19 biomarkers
- The use of smartphone biosensors to analyze sweat and obtain metabolic data
The industry is excited about the potential for these advanced technologies to help in oncology studies
There is no doubt that AI and machine learning are useful in multiple therapeutic areas, but DIA attendees were particularly enthusiastic about the potential benefits for oncology studies, with 42.2% noting cancer as the therapeutic area with the highest potential for improvement via these technologies.
When discussing digital biomarkers (DBM), attendees were consistent, with 42.6% identifying oncology as the area where DBM could have the most impact.
It is always valuable to reach out to those working in our industry to get a level-set regarding the strategies for growth and innovation that are important to us. As leaders in the use of AI and machine learning in clinical research, we are excited to have the opportunity at DIA to interact with our industry peers and we are so grateful for their informed feedback and insights into the areas where we are focused.
It is great to see that our colleagues on the front lines are experiencing and seeing the advantages of implementing AI, DBM and other technologies into research. We believe strongly in the ability of these technologies to transform how we conduct clinical trials and are confident that the growing comfort the industry is showing in these solutions will lead to more and more effective therapies, brought to market more quickly.
For more on how AI and predictive analytics can augment the trial process, click here to watch AiCure’s recent webinar, “Administering a Digital Solution — Leveraging Predictive Analytics to Enhance Trial Efficiency,” on-demand.