Rare diseases are not that rare when you add up all the conditions. The latest figure inches close to 10,000. To be classified as a rare disease, you have to have less than 200,000 patients in the United States. The truth is, the majority of rare diseases are actually ultra-rare, where you have less than 2000 patients in the United States. Cumulatively, that adds up to a big chunk of the problem. Let’s delve deeper to understand how technology can solve challenges in identifying, treating and collection of data of rare diseases.

Current Challenges 

The way that capital markets are structured and the cost of drug development doesn’t align with finding therapies for these extremely small conditions. Rare diseases are a public health crisis. When you add up all these small diseases, it’s a big number. Every Life Foundation put a report out that said they looked at about 400 rare diseases, the cost to the US economy was $1 trillion.     

This accounts to direct medical costs, it’s loss of productivity, unpaid bills, etc. The mental, physical, emotional burden on families compound this phenomenon into a public health crisis. That’s one important reason that brings focus on these ultra-rare conditions.  

The second is that rare diseases are a window into curing larger complex mainstream conditions, such as Alzheimer’s. Healthcare professionals have struggled with finding therapies for Alzheimer’s. It is a complicated condition where multiple genes are impacted. However, with rare conditions, the majority of them are monogenic.  

Developing Drug Trials

Considering that rare diseases involve small patient populations, drug trials can actually be a strong solution. FOXG1, for example, improves memory and cognition improve. It’s one of the genes implemented and could be a target for Alzheimer’s therapy. Drug trials can aid healthcare professionals to understand larger conditions.  

The Orphan Drug Act 

The Orphan Drug Act passed in the 80s was a great first step that provided tax incentives, priorities, and patient exclusivities to pharma companies to focus on rare diseases. However, pharma companies end up focusing on large rare diseases, like Huntington’s, which is closer to the 200,000 mark. They are not focusing on the ultra-rare conditions, which are the majority of the rare diseases witnessed in present times. Efforts need to be increased, including setting up current capital markets to find scaled solutions for rare diseases.   

The Placebo Arm 

The placebo arm is another big part of the accelerated approval trial, which is using a patient’s own natural history study as their own placebo. Through the application of innovative technologies, patient data can be collected at a much deeper level. Using a patient’s own information for a natural history study is becoming a reality. Enough bioinformatics tools can even take a small size, a small population of data and extrapolate that for a larger natural history study. The good news is a lot of companies innovating in this space, a lot of organizations looking for better endpoints, better biomarkers, and the FDA is open to listen.  

Epilepsy trials, for example, look at endpoints based on a seizure diary survey, which can be difficult to comply with. New technologies now allow for EEG tracing and analyzing spike burden, and analyze them against seizure diaries. Technologies to monitor patient data at home by families are an exciting turning point. This allows for more accurate data, as the patient is recorded within their comfort zone, which allows for collection of the exact phenotype, the exact symptom.  

Surrogate Endpoints 

In theory, the policies around rare diseases are effective, but the hurdle is that they are not being implemented at the desired level. For example, the Accelerated Approvals Act is effective, because it is designed to accelerate drug trials. For an ultra-rare condition, it allows for accelerated movement through a fast-lane process that is not confined to the standard phases of a drug trial.  

Gene therapy, as an ultra-rare condition example, costs about 75 to 100 million dollars. Pharma companies don’t want to take that expense on board, due to the limited number of patients involved. The solution to this challenge involves using a surrogate endpoint, instead of a clinical endpoint. Coming back to the FOXU1 case, an increase in protein expression is a surrogate endpoint that has not be witnessed as a clinical manifestation for a long time. The accelerated approval process then, provides approvals based on the fact that it can increase protein. Thereafter, patients are followed in post-marketing for 10 to 15 years to document their clinical trial successes. This allows the mitigation of the large pivotal study, the phase three study, which significantly brings costs down and gets drugs to patients faster. The risk may be higher, but for patients with fatal conditions and high unmet needs, it may well be worth it.   

A Digital Mind-set 

Pharma companies need to adopt an innovative and welcoming approach toward technology adoption. Data collection and analysis is entirely dependent on the openness of healthcare organizations. A willingness to invest and power through FDA approvals is a critical component. The FDA truly does want to be educated. Using advanced techniques to gather patient information, analyze it, medical record keeping, record gathering for medical records is the first step. This is followed by leveraging advanced techniques, such as machine learning, to take advantage of data. The ability to use a patient’s own HIPAA right of access and collect the entirety of their medical records is a big boon. This includes the clinic notes, EEG tracings, MRIs, etc. This data can then be applied for human extraction.  


The rare disease space relies on a collaborative care environment, where foundations do work together. Any rare disease project that is not treating the genetic core, might be taking a downstream target of basket trials. The healthcare space needs to set aside a risk-aversion mindset and adopt an openness toward innovative solutions that aid in finding much-needed cures for rare diseases.    

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