Credit Photo by Marc Zimmer on Unsplash
Throughout my career in the pharmaceutical industry managing clinical trials and study programs, I have been confronted with the same recurring problems. Trials struggle to recruit and retain enough patients, they fail to meet target timelines and the vast majority don’t conclude on time.
There are some staggering statistics in the industry, for example, 86% of clinical trials don’t reach recruitment targets in the specified time and 90% of clinical drug development fails.
One obvious reason for these shocking figures is that the pharmaceutical industry overestimates its ability to recruit. But, more troublingly, study design and protocol development seemingly fail to truly reflect patients’ lives or account for the reality in the clinic.
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These issues were one of the main reasons why I decided to step away from the pharma and CRO world and instead look more at enabling technologies and how we can start to really capture the patient experience to better inform what those clinical development programmes should look like.
With novel approaches, we can now detect people who are not yet diagnosed as patients but are likely to have a disease. In some cases, we find that 75% of people are remaining undiagnosed. So, we prefer talking about ‘people living with disease,’ instead of calling them patients. Many are not yet known as patients, but we can now know more about their condition than ever before.
First, though, we need to understand the barriers. Unfortunately, there has been a failure to sufficiently include those people that are unknowingly living with the disease in the design of clinical development plans and study protocols. This is then combined with an inherent bias in terms of how the process is handled. Most pharma companies believe that “we know what these patients look like.” Our experience has shown that this just isn’t the case. And although Companies assess together with clinicians, those clinicians are not necessarily a representative group.
Most companies have their own medical experts, many of whom have gone straight from medical school into the pharma industry. These pharmaceutical doctors very often haven’t seen a patient in years. To be fair, they do seek further insights, mostly from key opinion leaders (KOLs). But these KOLs are often quite advanced in their medical and academic careers, and typically are not seeing patients when they first present with problems. Instead, they are the specialist doctors that mostly see the more difficult patients; the “special cases” that are “escalated up the referral ladder". These can be non-representative of the disease you are working on as a whole. Or, in the rare or difficult-to-diagnose disease space, these are quite likely the patients that are far along the disease diagnosis trajectory, what we commonly call the diagnostic odyssey, and have finally arrived at the specialists who at last can work out what the patient has, from knowing everything there is to know about that person living with their disease.
If we want to have protocols that are more relevant to people living with a disease, the industry needs to include more treating physicians in the design, not just KOLs.
Scientific advisory boards should include both types of physicians: key opinion leaders, who carry authority and are respected because of their specialist knowledge, and whose voices are listened to. But also, clinicians who actually see the majority of patients out there. Your KOLs should comprise a quarter or at most a third of the board and the rest should be treating clinicians, those who see the most patients.
In addition, when you’re designing and recruiting for your clinical trial, don’t just focus on the obvious medical disciplines for your rare disease. Reach out to clinicians in other therapeutic areas, because we know that rare diseases are heterogeneous and can affect different parts of the body and almost any organ. As a result, many of the people living with disease may not be where everybody expects them to be.
Crucially, ensure you conduct thorough natural history studies, which can help to uncover sentinel events or detectable physiologic changes that are key predictors of disease progression or that are clinically important in their own right. These can help you understand which subgroups of people living with disease might benefit from your drug in development, and you therefore want to target for inclusion in your clinical trial.
Yes, by all means include patient advocacy groups to ensure patient-centricity, but these are typically vocal, passionate groups of people known to be living with disease, or their caregivers, who can stand up for themselves and their loved ones. So, importantly, we need to ensure those who don’t have a voice, who are struggling with illness but don’t have a diagnosis are included. For that, we need to dig much deeper!
We know from experience that artificial intelligence can better inform clinical development strategy, design, and patient stratification. It can help you to identify those who have not yet been diagnosed with a rare disease, ensuring their inclusion in the clinical research effort, way earlier in the progression of their disease. This democratisation of the data by virtue of guaranteeing all data – meaning anyone who potentially might be living with a disease – is considered and analysed.
We know that the way clinical trials are designed needs to be improved, and we know how difficult it is to recruit people for rare disease studies, simply because it is hard to find those people. As an industry, we need to rethink how we have gone about designing protocols and how we are recruiting people living with disease, if we are going to bring life-saving and life-changing treatments to those who need them – the people living with a rare or difficult-to-diagnose disease, wherever they may be.
Léon van Wouwe is Clinical Innovation Director at Volv, focussing on building bridges for wellbeing between biotech, health tech, clinical researchers, clinicians, patients, and people living with disease. Léon has spent many years in clinical development, at pharma companies of different sizes, at CROs, and as a life-science industry consultant.
Volv’s inClude, helps sponsors identify the target patient population among both diagnosed and undiagnosed rare disease patients, establish clinical outcome assessments that characterise earlier disease states and can be considered as novel endpoints in clinical trials, and expand the range of biomarkers to advance biological understanding of the disease