This Is How Data Gets in the Way of Clinical Research

For most of you involved with clinical trials, it’s not a secret that clinical research is not about patients, it’s not about a new treatment, it’s all about DATA. Yet, data is what we miss the most and I don’t only mean this in the sense of having access to essential information. What we miss are even earlier steps like saving data, storing data, and making the most out of it. First things first: 

Why am I even scratching the surface of such a huge topic with this article?

This article was inspired by one of my latest conversations with a CMO from one of the biggest CROs, an amazing professional, who reminded me of how important it is to have all the cards on the table before prioritizing which problem to solve first and how. 

I was sharing with him that what motivates me and my team at FindMeCure to work for better solutions in the clinical research space is something we realized in our first year:

The Clinical Research Challenges are like an iceberg. We tackle the obvious ones, the pains we feel immediately without understanding that these are just quick fixes. Unless we tackle the challenge at its origin, we won’t be able to find an actual, scalable solution.

A good example is the Patient Recruitment industry. There are hundreds of solutions out there and none of them has really moved the needle with patient recruitment. Patient Recruitment is still the biggest issue, the obvious challenge is “not enough patients”. 

The quick fix: Let’s find more: more advertising, more sites, more site visits, etc. “Not enough patients” in most cases though is not the real cause of patient recruitment challenges. It’s usually to do with protocol schedule, eligibility criteria being too strict, not the right sites selected, sites are too overwhelmed or in a country where the standard of care is high and patients are not motivated to participate. 

If you ask me, if all things are planned right from the start, yes, then digital patient recruitment is a great way to accelerate the process. But it’s the wrong decision to use as a fixing instrument. 

Back to our Iceberg. I think we all know what’s on the surface and these are the buzzwords we hear all the time (like patient recruitment). The question is what’s underwater? 

I can not tell you the full answer. My feeling brings me back to two main challenges: Alignment of stakeholders’ interests and DATA. We can speak about both topics for hours, yet, I will focus now on the challenges I have witnessed related to our access to information:

1. We produce a lot of information – the question is how we store it and what we do with it. One simple example is the clinical trial registers that have tons of data that is difficult to be used either by clinical research professionals or by patients. 

Organizations know they are obliged to send updates on their clinical trial progress to regulators and regulators to make part of it public. When these updates are not regular or systematic, this makes the information that they generate misleading. 

You will ask why this is a problem. Well, put yourself in the shoes of a patient who is desperately trying to identify a clinical trial. She calls the number provided in the register only to find out that the trial is no longer recruiting, the number is not correct (and let’s not even start the topic of what happens with call centers).

For clinical research professionals, it is a similar though less dramatic journey. The main purpose of doing feasibility is to plan your trial on budget and on time. This means you need to identify the right sites with experience and no competition, to be able to predict some sort of speed (average patient recruitment per site per month) etc. This might come from your own experience of course, but the more information you have the more accurate your estimations are. IF the information you have access to is accurate.

NB! I will post in a comment an interesting article about Clinical Trial Registers if you want to read more.

NB! 2 I have to mention one really great example led by TransCelerate and developed by DrugDev. They have created a database of sites and investigators which is co-owned by the top pharma companies and represent their overall experience and performance metrics. It is a great example of how collaboration can produce better data and thus better results. 

2. Which brings me to a topic I am intensely interested in: How do CROs store and use their know-how? CROs are the go-to for conducting clinical trials which means they’ve seen and done a lot more than the majority of sponsors out there. 

Their experience is their credibility and their future business too. Yet, some of you might be surprised to learn that what CROs fail at the most (of course I’m generalizing here for the purposes of brevity) is to collect insights from their previous clinical trials and apply them to future ones. 

They are great at having the staff on board, at following the processes and conducting clinical trials as a whole. Only a few, however, have managed to see the potential in all the insights they are generating every single day, and to store them in a way that can boost internal know-how but also power up external partners. 

Cases like creating a new proposal for a new client show us that they rely on what a single person knows when coordinating multiple people to get information, rather than invest in centralizing this knowledge and making this DATA accessible to them firsthand, and then, why not to others for all sorts of purposes in healthcare?

3. “One for all, all for one” is the famous saying, yet in life, as we see in clinical research we barely have the visionary skills to see further than our nose. Similarly to CROs, sponsors are also not open to sharing their data and know-how with their colleagues from the industry

I refer to all the completed clinical trials and the insights gathered from them which can be helpful to anyone who wants to conduct research in the same space. And I’m not saying let’s share everything we know, I am saying there is almost no access to data on previous research done by others, which can be used for purposes like removing placebo arms, optimizing protocol schedules, optimizing arms and endpoints, improving interaction with patients/investigators. 

I don’t know how we can achieve that. One thing I know though is the technology that provides the ability to analyze data and get statistics without even seeing the data exists and it’s up to us to prioritize it. 

4. Data around patients and the interaction with them is supercritical, yet missing too. It’s true that clinical research as an industry has existed for many years. Yet, the focus has always been on gathering information about the trial endpoints and neglecting the information that is being collected outside of these endpoints. 

Neglect is not the right word, as it also comes down to the extent companies are allowed to gather patient insights outside of the endpoints. Luckily, this has been changed by FDA regulations and smart technology providers have found a way to gather these patient insights even during the trial. Of course, this is still a luxury asset to the big guys and also not being shared openly.

Another type of data around patients is what happens to them after the trial is over. It is super critical to collect real-world data on how they feel and perform with the new treatment even after the trial has been completed. This information is hard to collect and maintain and so this prevents knowing how to improve the next clinical trial.

5. And the always-relevant question: Where are the patients? EHRs- the holy grail. They are supercritical for everything: identifying the untapped patient need which is being translated into R&D potential target a.k.a clinical trial. 

Later eligibility criteria, patient recruitment, placebo replacement. It all sounds amazing and like a panacea for the clinical research industry. With a minor setback – EHRs don’t exist (not in the way we need them to, at least). 

The USA and some other countries are better equipped with EHRs because of their private healthcare set up. Which means they have some medical records in an electronic format. People that have been working on technologies around that can tell you though that these records are not built for the purposes of what we need (similarly to the clinical trial registers). 

They are for billing purposes and so the information might not be complete enough to fulfill all the expectations we have. At least there is something if you ask me, and thankfully there are providers who can take on the opportunity and unite these records in order to make them more accessible. 

In the last few years, governments have been raising this topic multiple times with no real outcome yet. With privacy laws rising but also COVID-19, there is a huge pro or against debate. This means that soon it will be hard to even speak about accessing EHR data in a scalable manner unless we agree on how and in what format to share our health status. 

Maybe it is not lack of DATA that really stops clinical research, but lack of trust and lack of collaboration for the greater GOOD. Writing this article, I am thinking that on the very bottom of the iceberg there is not enough effort to work on the big challenges in clinical research. This is also to do with the fact that most companies and their leaders are driven by annual or 3-5 years KPIs more aligned with revenue, focus on public shares price rather than actual results and improvements. But I guess this is a topic for another discussion 🙂

Scroll to Top