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Discovery & Development Clinical Trials, Digital Technologies, Trends & Forecasts

The Art of Prescreening

Credit: Interviewee supplied

Clinical trials have historically been plagued with bottlenecks in the recruitment process. The COVID-19 pandemic piqued public interest in the clinical trial arena and also encouraged more companies to focus on the patient experience. However, not all patients interested in a trial can take part.

Cara Brant is the CEO and owner of patient enrollment company Clinical Trial Media, having purchased it in 2018. For her, automation and data analysis are key to improving prescreening and recruitment, but it’s also important not to forget the human element. We spoke with her to learn more. 

Why prescreen?

Many people every year show interest in participating in a trial, but not all of them will qualify. Protocol criteria are purposefully stringent and narrow for both safety and efficacy reasons. It’s challenging to find the right patient that matches with the right study. Prescreening is an early step to try and find the right participants. 

But prescreening is an art form. Our job is to take those people who are interested in trials and then to match them with the right protocol so that, when people are sent to the research site, they are likely to qualify. If we just sent over everyone who put their hand up, researchers would quickly be overwhelmed and would spend time screening unqualified people. Whatever we can do to better qualify patients before they get to the site has immense value in terms of speeding up the process and resulting in a better patient experience. 

How does the process work?

In simple terms, the prescreening process involves a questionnaire. But we’re always busy considering how we can adjust the question format, the question type, the way it’s laid out, and how we can use our data to better match and qualify patients. Some protocols are highly complex, and include a lot of details, so it’s important to ensure that patients understand. We can now lean on decades of data and use machine learning to help us understand how patients are behaving and whether they are getting stuck on any of the questions.

We’ve also started implementing secondary screening, wherein we ask questions on our website through the software, but nurses will dive deeper with the patients on medication history and disease history for more complex protocols. One lesson learned is that some patients weren’t fully understanding some of the questions on a web screener, so they needed a nurse to talk to. I expect we’ll continue to see other such opportunities for improvement. 

Another challenge is in diversity, equity, and inclusion. The pharma industry is striving to be more inclusive, ensuring researching and testing medications to benefit everyone. Given that people may respond to questions and prompts differently, it’s important to be mindful of how best to connect with different audiences. We want to continue to learn, evolve, and build on the lessons of the past using the data of the present. New software has revealed a great deal of excitement around increasing those conversion rates, getting more qualified patients, improved user experience data, and an improved screening process. We’re also testing our ability to better match with patients representative of every community, and that is another exciting development. Early diversity testing is showcasing a potential increase in about 300 percent of diverse qualified referrals based on this new software, which we’ve designed to be accessible to everyone – from font sizes to screens and colors – to make it easier to navigate.

Do patients seem to prefer a relationship with a healthcare professional rather than automated access to clinical trials?

With the world increasingly focused on automation and technology, there are concerns about the removal of the human element. When it comes to healthcare, and especially clinical trials, people are nervous and do not know what to expect. Giving them the option to speak to a real person can go a long way. In any given study, we still see a significant percentage of people picking up the phone and calling one of our nurses. They just want that reassurance of somebody explaining what comes next.

What other trends are you seeing in clinical trials?

The COVID-19 pandemic has really brought clinical research to the masses and there has been an increase in the number of people who want to take part. However, the volume of clinical trials going on at any given time is higher than it has ever been. There can be hundreds, if not thousands, of trials in one particular disease. Each trial may be looking for the same set of patients. The companies meeting patients where they are and understanding the data are the companies that are going to succeed here. It’s important that we make sure we're always connecting back with the human element; remembering what patients are sacrificing, what they're contributing to, and finding ways to stay connected with them. 

How do you think awareness and education could change public perception of the pharmaceutical industry?

Raising awareness about the value and importance of clinical trials is critical. There are no advances in medicines or treatments without clinical research. I’ve devoted my career and my life to this pursuit of educating people so they have the option to consider a clinical trial. Unfortunately, in our healthcare systems, there is a separation between what a doctor might talk about versus clinical trials. I’m not saying a clinical trial is right for everyone, but I believe that everyone should be aware of the option. For many participants, a clinical trial is a standard of care and a way to access the advice of expert physicians and diagnostics. 

What further impact could AI and machine learning have on clinical trials? 

Across the industry, everyone is looking for ways to apply AI and machine learning. At Clinical Trial Media, we’re heavily focused on automation and AI through data analytics. I’m a big believer in data-driven decision making – and I see a huge opportunity to scale and further automate in clinical trial recruitment.

Prescreening is just the beginning for a patient; there are many steps before they randomize into a trial – and there will be many data points. The opportunities in the industry to improve the use of data are endless, but it’s going to be a delicate balance between understanding compliance, privacy, data security, and new tools.

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