The past year has been a whirlwind of technological breakthroughs that have transformed industries and improved people’s lives in tangible ways. From groundbreaking advancements in artificial intelligence to innovative healthcare solutions, the pace of innovation has been staggering.
To get an insider’s perspective on some of the most exciting developments, we sat down with Cara Brant, CEO of Clinical Trial Media, who shared how data and machine learning have revolutionised the clinical trial process, and can help get life-saving treatments to patients faster than ever before.
She also discussed the importance of striking the right balance between automation and human expertise, as well as her vision for making drug development more equitable and accessible for all.
What’s been one of your favorite tech innovations in the last year?
Over the last year, we saw a lot of hypothetical tech use cases turn into tangible solutions. We saw companies finally figure out how to apply machine learning and artificial intelligence to putting decades of data to work in concrete ways. This is not only helping speed up historically manual or slower processes so companies can do tasks faster and at scale–it’s creating more precision so they can achieve exponentially better outcomes.
In the healthcare space, moving faster and being more methodical directly influences people’s lives. This is especially true when it comes to bringing life-changing and saving drugs to the people who need them the most. When pharmaceutical companies develop new treatments, often one of the largest holdups to getting them to market is their ability to test the treatments on real people in clinical studies. Finding people to participate in trials and keeping them on for the duration is difficult, time consuming and expensive–making it the largest source of delays and costs in drug development.
I have spent my career in this space. In the last year, our company built a technology that leverages data from over 10 million potential and actual trial participants to speed up participant screenings and qualify candidates for trial sponsors.
This innovation leverages machine learning to pre-screen over 60,000 potential participants per month and is enabling us to send more than 15% more qualified candidates to clinical trials, speeding up the recruitment process considerably.
The impact that this type of technology can have on getting treatments to market quicker is considerable.
What is one trend you foresee will change the tech world next year?
There’s no question AI has immense potential to facilitate, and even reimagine, many aspects of pretty much every industry. But over the last few years, we’ve seen the healthcare industry perhaps over-correct in its lean towards automated technology, particularly in places where human attention and intervention are requisite to an optimal outcome. Over the next year, I believe we’ll start seeing why both elements need to work in concert.
Companies across the board will take a step back and review their early AI initiatives and fine-tune their distribution of labor between AI and humans. In healthcare for instance, it’s clear that AI excels in data analysis, scale and efficiency (among other things), but falls short in areas where human care plays a crucial role in the patient experience.
Health is personal and intimate. But while AI can personalize healthcare plans and treatments, patients will continue to crave care and information from somebody they trust. Delicately toeing the line between where humans are necessary to advance care, and where automation can optimize, will lead to the optimal outcomes.
If you could change one thing in the industry, what would it be?
I’d want technology developers and other companies involved in adopting those technologies to think of problems holistically. There are too many instances where industries look at issues as individual symptoms to be treated, rather than interwoven systems that need approaches as nuanced as they are to solve them. Take clinical trials, the core of my work, for instance. Everyone in the space knows that the lack of diversity in trials is an issue, but oftentimes attempted solutions equate only to quick fixes. It can’t just be developing more effective outreach methods, or creating platforms that are easier for more communities to use. It involves taking all of the data available about clinical trial recruitment, analyzing it carefully to see the pain points from different demographics, and putting into place different action plans that can actually move the needle. Having this paradigm shift in approaches to complex issues will actually help to make a difference in the lives of the people we’re trying to serve.
And finally, if you could invent any piece of technology, what would it be?
I would like to continue working towards building technology that ensures drug development is equitable for all. This means developing new tools that empower trial sponsors to identify diverse and qualified participants for their studies, and retain them throughout the duration more effectively. While the industry has been trending in the right direction, there’s more to be done to make sure the way we develop our drugs is taking into account the diversity of our society, and that medicines are designed to be effective in everybody that needs them.
The convergence of tech and brands 