Orphan drugs (ODs) for rare diseases (RDs) present pharma companies with the opportunity to address a substantial unmet medical need. There are approximately 7,000 RDs, and only about five percent have effective treatments. In the US, around 25-30 million people are affected by a RD; many are often chronic and deteriorating conditions, with the majority starting in childhood and frequently resulting in early death. This creates significant economic and social burdens for patients, caregivers and healthcare systems.

The global problem of how to encourage drug development in the area of RDs was addressed with the Orphan Drugs Act of 1983 in the US, and similar legislation in the European Union (Regulation 141/2000 on Orphan Medicinal Products, 2000). There’s little doubt that the Orphan Drugs Act worked to stimulate R&D in the orphan field – there were only two orphan therapies approved by the FDA in 1983, but the average number approved each year in the following 10 years was nine, and the average for the ten years preceding 2018 was 36.

But commercializing Orphan drugs presents unique challenges, requiring different solutions. Here, we explore those differences and suggest ways in which pharma companies can navigate the commercialization landscape.

Finding patients and dealing with diagnosis

The successful commercialization of ODs requires a range of strategic and tactical elements to be implemented by pharma companies. Starting from the clinical trial stage of the product/project lifecycle, the first major challenge is patient recruitment. While finding appropriate patients is always a challenge for conducting clinical trials, this is especially acute for RDs, given the small populations involved. Pharma companies must develop strong relationships with all key Rare Disease Patient Organizations (RDPO) and research hospitals (e.g., children’s hospitals, key academic research hospitals, etc.), which puts pressure on external medical affairs teams to foster relationships with key opinion leaders (KOLs) and RD experts.

Another key element is the diagnosis and treatment of RD. Unfortunately, many RDs go undiagnosed. Again, collaboration is key. Pharma companies must work closely with major research centers focusing on RDs, governmental agencies, RDPOs, and other companies, and data sharing is crucial. There also needs to be an international network for data and information sharing for undiagnosed patients.Due to the length of time it can take for patients to get a correct diagnosis, it is common for patients to cycle between physicians for months or years. This means that pharma companies must make it easier for patients to access information, make it more affordable for patients to conduct necessary tests to determine their RD, and work with payers on the cost-effectiveness of providing healthcare subsidies to support faster detection of RDs. In addition, artificial intelligence (AI) and machine learning (ML) techniques can be beneficial to determine the attributes associated with an accurate RD diagnosis to shorten this pathway and help define metrics that physicians and patients can use to diagnose RDs accurately and quickly.

These points illustrate the need for pharma companies to develop a more patient-centric (rather than the current physician-centric) approach to RDs. Patients diagnosed with RDs are highly motivated, engaged, and informed so a strong digital and social media presence is recommended. There may also be a role for patient support infrastructure, such as patient hubs, to help pull-through patients by providing patient support for gaining access to therapy, and continued engagement with patients and physicians to help drive adherence to the prescribed therapy.

Pharma companies should also develop an extensive database of physicians by RD and share such information with patients. One reason for patients having longer diagnosis times for their RD is not being able to find a physician expert who can accurately diagnose and treat their RD. Expertise in RD diagnosis and treatment tends to be concentrated among a small subset of specialists, often in academic hospitals.

Market access and patient affordability

When it comes to affordability, pharma companies need to develop strong health-economic models for RDs to demonstrate the value (private health insurance and government) of subsidizing patient healthcare costs (5). Health economic and outcomes research (HEOR) and real-world evidence (RWE) analyses must be closely connected with commercial modeling. The often chronic and debilitating nature of RDs results in significant healthcare costs. Given the small patient populations, drug costs can also be an issue. Drug price elasticity analysis combined with HEOR/RWE is necessary to determine the economic burden to patients, as well as to payer plans and healthcare systems if these RDs go untreated. This means that performance-based contracts for ODs are much more likely than for non-ODs. Thus, the ability to link and track HEOR/RWE analysis with these payer contracts will be critical, as will the use of AI/ML technology to produce ongoing updates on projected health and economic outcomes.

In addition, the healthcare coverage of RDs significantly varies by plan and region; and patients often absorb a significant amount of the cost of the treatment (drug and overall healthcare costs). A payer registry for health plan coverage of RDs must, therefore, be shared with patients so they can plan accordingly on the cost-outlays required to obtain treatment of their RD. A payer registry can also be of benefit to a pharma company in planning their payer strategy and tactics necessary to support RD patients (e.g., the distribution and amount of copay support and discounts/rebates to payers/pharmacy benefit managers (PBMs)).Strong database management is also important. The small number of patients with RDs will mean that the ability to link databases without losing data is paramount. This database capability will affect a wide range of clinical, on-going HEOR/RWE analyses for payer contracts, and sales and marketing activities.

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