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.
Key Takeaways
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.
