Have you ever sat back and thought to yourself - hey, what does AI think of clinical trials? Well, if you have, then we have something in common!
Unless you’ve gone off the grid as part of your New Year’s resolution, you’ve probably heard of a little something called ChatGPT. The potential applications of this nifty chatbot are endless, but we thought we’d see what it thinks about clinical trials.
We hope you enjoy this edition of a Fireside Chat (it counts if the fire is a YouTube video playing in the background, right?)
For a robot, the answers weren’t half bad, and they do shed light on a lot of the problems people running trials face. Lack of diversity is a major issue when it comes to clinical trials. The FDA’s snapshot analysis from 2020 looking at just under 300,000 trial participants found 11% and 7% of trial participants were of Asian and Black/African-American backgrounds respectively. Stats like that show we aren’t quite there when it comes to providing data that serves a global population.[i]
To hone in on the diversity issue a little more, we were curious what ChatGPTs neural network had to say about solving the problem it highlighted. The proposition of having a diverse research team was actually super interesting – is there perhaps an element of unconscious bias that plays in recruitment? Does having a more diverse recruitment team help reduce the impact of that? Interestingly, Niranjan et al conducted a qualitative study regarding perspectives on recruiting minorities to oncological trials, and there is evidence that there is some negative perception in recruitment towards minorities.[ii] This does raise the possibility that introducing AI into clinical trial recruitment might help mitigate the presence of this bias.
We’re probably most excited for the first point ChatGPT raised which is the potential applications of predictive modeling. It isn’t just predicting outcomes, but it could even be used to predict things like trial termination.
This question was totally not put in as an opportunity for us to talk about how we recently got published in … Hey by the way, we got published in Nature for demonstrating machine learning can be used to predict early trial termination and further optimise clinical trial design and execution.[iii]
Yes, machine learning (ML) has the potential to significantly reduce the time and cost of clinical trials by automating certain tasks and reducing the need for manual labor. Some examples of how ML could be leveraged in clinical trials include:
It's important to note that ML is an evolving field, and it's important to evaluate and validate the results of any ML-based applications in clinical trials. Furthermore, it's essential to ensure that any ML applications used in clinical trials are accurate, reliable, and have undergone appropriate testing and validation.
Alright ChatGPT, show us your crystal ball. In fairness to the bot, a century is a long time and technology does change exponentially – it’s hard to predict something when the machine hasn’t had a chance to learn what 2123 looks like, but we thought we’d find out anyway.
It is difficult to predict exactly what clinical trials will look like in 100 years, as advancements in technology and medicine are constantly evolving. However, it is likely that clinical trials will continue to become more personalized and efficient. Some possible trends include:
It's important to note that these predictions are based on current trends, and the field of medicine and technology are constantly evolving, so it's possible that the future of clinical trials will take a different direction.
If you ask us, you could distil the below advice from ChatGPT to the following sentence; work with an experienced team. Naturally, clinical trials are complex processes to navigate regardless of how much experience someone has. Working with a company that understands how to seamlessly combine expertise in clinical trials with cutting-edge technology is probably the best way to go about a clinical trial.
My advice for someone who is planning to run a clinical trial, whether they have extensive experience or no experience at all, would be to thoroughly plan and organize the trial in advance. A well-planned and organized trial is more likely to be successful and will minimize the risk of errors and delays.
Remember, running a clinical trial is a complex and challenging process, but with proper planning and organization, it can be done successfully
Firstly, this is incredibly exciting technology and we’re amazed at what everyone at OpenAI is doing – this technology applied in the right way is going to be transformational for the way we work. If AI can write you a PhD dissertation these days, it’s not long until we start seeing ground-breaking stuff in the clinical trial space. Secondly, you’ve all the arguments for how AI is streamlining the way clinical trials are run – it’s important to work with people who understand the importance of continuing to develop and optimise trial design. And finally, that last question to ChatGPT was an important one because it shows that even machine learning recognises the importance of working with a team with solid expertise in clinical trials (hint hint: get in touch!).
Thanks for joining us for this slightly more virtual than usual Fireside Chat – we hope you found this as enjoyable as we did! What else would you want to know from ChatGPT? Drop us an e-mail and let us know.
Our mission at Lindus Health is to accelerate clinical trials, so patients can benefit from new treatments sooner. We are a next-generation CRO helping Digital Therapeutics pioneers run radically faster, more reliable clinical trials. We do this by marrying a world class clinical team with an end to end technology platform, including EDC, database, site and feasibility products. We also have unique access to over 5m electronic health records. We can recruit participants and execute a trial efficiently, from capturing trial endpoints, managing screening and patient visits.
Our products have been used to recruit, onboard and handle data from thousands of patients and Lindus Health has helped run over 70 studies up to 3x faster than traditional CROs. Get in touch to see how we could help solve your next clinical trial!
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