Find out how we can help you tackle your healthcare challenges.


Driving Medical Innovation With Real-World Evidence

Medical Innovation-Blog

The failure rate for new life sciences developments is shockingly high. Just under 10% of compounds ever make it to Phase I trials. Of those, about 14% eventually win approval from the FDA. Along the way, roughly 80% of clinical trials are derailed for failing to meet enrollment timelines and requirements. Then, after all of that work to get a treatment across the finish line, only half of the patients who are prescribed medications for chronic conditions end up taking those drugs regularly in the real world.

While miracle breakthroughs – like creating a COVID-19 vaccine in under a year – justify the cost of all the misses, there is no other industry on the planet operating with such a high failure rate.

However, thanks to a dramatic increase in electronic health information and patient-centered data, the industry now has access to real-world evidence (RWE) to help overcome these barriers and accelerate drug development. 

Effective use of real-world data promises to improve early discovery decisions, enhance clinical trial design, feasibility, and execution, and improve life cycle management by reducing the resources required for post-market surveillance and studies. 

Enhancing Early Discovery 

RWE can facilitate early discovery by identifying diseases or indications that represent a significant disease burden in different patient populations. By tapping into RWE, teams can support critical decisions and frame questions about disease identification and progression that need to be answered through clinical studies. Electronic health records, claims data, and other health data sources can provide a truer understanding of patient and provider behaviors, the burden of disease on the community, and disease pathways. 

The result? More targeted drug development. 

Hurdles and Barriers 

Once targets for research and development are established, the design and execution of clinical trials represent the bulk of the costs associated with drug development. Of the $2 billion it costs to develop a new prescription medicine, $1.5 billion goes toward clinical trials.

Recruiting and retaining patients remains one of the biggest hurdles to the development of innovative new medications. 

This is in part because only a small number of individuals actively seek clinical trial opportunities, leaving much of the burden of identifying and recruiting patients on Life Sciences companies. This challenge becomes even more daunting for rare diseases. Take paroxysmal nocturnal hemoglobinuria, for example, which affects only 1 to 1.5 persons per million and presents with a wide spectrum of symptoms. Finding patients at the relevant moment in their complex disease journey is akin to finding a needle in a haystack.

In addition, Black and Hispanic patients are consistently underrepresented in trials, resulting from a number of factors: accessibility of trial site locations, lack of transportation, high costs associated, significant time burden that may interfere with work or family responsibilities, and more. As long as minority communities continue to be underrepresented in clinical studies, many prescription medicines will be developed based on skewed research and result in clinical knowledge that isn’t generalizable to the population subsets that may be most in need of treatment. 

These problems add to the hefty development costs and result in medications that do not necessarily reflect our diverse society. 

Enhancing Clinical Study Design and Execution 

Through patient-centered data, study teams can enhance both recruitment and retention for their clinical trials. 

When determining the target population for a clinical study or setting eligibility criteria for study participation, protocol authors traditionally rely on literature, experience, and expert opinion. As a result, decisions may be made on outdated insights or information that doesn’t reflect actual clinical practice. 

At the same time, the industry tends to work with providers and institutions that are already well-known, leading to a depletion of potential trial participants at those study sites and limiting the diversity of that pool. That makes it harder for Life Sciences companies to fulfill recruiting requirements.

By turning to RWE, Life Sciences companies can address both of these challenges. Pulling insights from a complete, timely dataset, study teams can design more realistic trial protocols and eligibility criteria based on how patients operate in a real-world clinical setting. 

Patient-level data also enables clinical study teams to identify real-time recruitment opportunities. Through our proprietary Healthcare Map™, Komodo streams 15 million encounters each day. Because of this, we can examine specific patient cohorts who can be reached precisely at the right point during their patient journey when they're potentially eligible for participating in a study. 

So, by leveraging RWE, study organizers can identify institutions or providers – beyond the “go-to” research centers – that treat a significant number of patients, creating a larger and more diversified pool for recruitment. 

Companies like Janssen exemplify this next-generation approach to clinical development. 

The Future of Clinical Development 

The COVID-19 pandemic has highlighted the impact that rapid, targeted development projects can have on improving human health. While development timelines for the COVID-19 vaccines reflect an unprecedented, collective sense of urgency among Life Sciences companies and regulatory bodies, such shortened development timelines do not need to be a one-off. 

Thanks to RWE, we can evolve the way we discover and develop new therapeutics to not only save the industry time and resources but to accelerate the delivery of new, life-saving medications.

Learn more about how Komodo can support clinical development here.

By providing your email address, you agree to receive marketing communications from Komodo Health. For more information on how we process personal information, please refer to our published Privacy Notice.
Recent Stories