The Orphan Drug Act provides special status to a drug or biologic to treat a rare disease or condition affecting fewer than 200,000 Americans. Orphan designation qualifies the sponsor for various development incentives, including tax credits for qualified clinical testing, waived prescription drug user fees, and eligibility for seven years of marketing exclusivity.
However, there are additional challenges sponsors face when developing these drugs, particularly patient recruitment for clinical trials and extended trial timelines.
Raremark builds research networks of rare disease patients, providing biopharmaceutical companies with access to anonymized and aggregated patient data to support clinical development. The Raremark platform is designed to engage and retain patients using machine learning in an effort to raise health literacy and informed participation in medical research. Content algorithms help to boost engagement and advanced data analytics help understand the mechanisms, symptoms and heterogeneity of rare diseases. The resulting insights aim to enable companies to develop and offer treatments more tailored to patient profiles.
Founder of Raremark, Julie Walters, discusses the challenges in the rare disease space, finding the hard-to-reach, and leveraging big data and machine learning in drug development. –KB
Contract Pharma: What are the main challenges sponsors face with rare disease research and development?
Julie Walters: The challenges in clinical trial recruitment are well known with 94% of studies increasing their study duration to reach their enrolment target. The task is even harder in rare disease, where the average time from IND filing to FDA approval is 10.7 years, compared to 7.8 years for non-orphan conditions, according to the Tufts Center for the Study of Drug Development. So, anything that can be done to shorten recruitment timelines in rare disease can make a big difference.
In addition, screen failure rates in rare disease are 81% compared to 57% in more prevalent chronic diseases. Randomization failure rates are also higher in rare. Once an appropriate trial candidate is found, keeping them engaged in a screening process that can take weeks is also crucial to success. Trial sites can easily become overwhelmed by screening inappropriate candidates, so it’s important to only refer candidates that closely match the trial’s inclusion criteria, understand what’s involved in taking part and are ready to take the next step.
CP: Please describe Raremark’s platform and the challenges it aims to address?
JW: Over the past four years, Raremark has supported clinical trial teams by going direct to patients and caregivers online and advising them about research opportunities that may be suitable for them. The fundamental philosophy is that the biggest driver of change in rare conditions is the patient or caregiver, who is searching for new options that their current clinician may not know about. Most patients find out about clinical trials through an online search.
The Raremark team combines skills in digital marketing, behavioral science, machine learning and patient education so patients can easily find a trial when they search online. We also look after the patient once they register interest and make the connection to the closest trial site that has opted in for referrals. After the referral, we check in with the patient to make sure they are not forgotten in a system that, from the outside, can seem slow to respond. When you find the needle in the haystack, it’s important that they don’t disappear again! Our approach has resulted in a 30% reduction in screen failures.
CP: How is the platform implemented?
JW: Our technology platform is compliant with all relevant legislation, including European data privacy law, HIPAA and ISO 27001. Data security is paramount.
In our experience, the biggest challenge we have had to tackle is keeping patients engaged over time. For those who do not live near a trial site or don’t want to join a placebo-controlled trial, it’s important to offer other benefits apart from trial recruitment.
That’s why we have expanded our offer to include our community members sharing their valuable real-world experience with each other. Raremark thereby becomes a growing knowledge base of patient experience, built by those most affected and who live the experience every day. They do it by answering questions and telling their stories on how they have learned to live with their condition.
CP: How are pharma/biopharma companies currently leveraging big data and machine learning in drug development?
JW: In rare disease, patient data tends to be small but perfectly formed. For commercial teams, having patient input from even a few dozen patients with an ultra-rare condition can be very helpful for launch, when it can feel like you’re making your plans in the dark.
Our clients appreciate that we use machine learning to engage patients over time and to maintain a relationship with patients and caregivers that is at arm’s length from pharma. Patients like to communicate once they find a community of other people like them and it’s difficult for industry to be able to respond to comments in a timely manner. Raremark also has Twitter, Facebook and Instagram channels to initially reach patients where they live online.
Our knowledge base is carefully modelled on questions from the latest behavioral science research and we use machine learning to personalize each member’s interactions.
Julie Walters is the Founder and driving force behind Raremark, which connects families affected by rare disease with up-to-date information, community insights and clinical trials. She believes that we are at an important point in the history of health where the power of the internet, science and AI will soon change the lives of millions of people.