Tackling Rare Diseases With RNA Therapeutics

RNA therapeutics has taken off in the last five years or so, not only because of the mRNA approach to the COVID-19 vaccine, but also because of blockbuster, life-changing drugs like Spinraza®. There has been a rapid increase in consumer genetic testing that has enabled the identification of causal mutations for numerous rare diseases; I see this only increasing over the next few years.

RNA-targeting therapeutics are the only modality that has proven itself repeatedly in the clinic.

I should clarify that there are two sides to RNA therapeutics: mRNA and RNA-targeting. mRNA therapy has only been clinically proven as a vaccine. Companies are working on protein replacement therapy using mRNA, but delivery challenges and the toxicity of lipid nanoparticles are likely to keep chronic dosing of mRNA for protein replacement away for a long time. 

RNA-targeting therapies are here to stay and look to be on the verge of a rapid increase. These therapies include modalities like antisense oligonucleotides – where a small, 18–20 base pair DNA or RNA-like molecule binds to a complementary sequence on a target RNA transcript to invoke a biological process for therapeutic benefit. This can be to either knock down, modulate splicing or even increase the target RNA.

The most obvious and scientifically elegant story is Spinraza. This is a situation where kids are born with a mutation in one gene, SMN1. But humans have another gene called SMN2 – though this is a pseudogene, since it doesn’t create a stable protein. Adrian Krainer at Cold Spring Harbor Laboratory developed an antisense oligonucleotide therapeutic that modulated splicing in a way that created a functional protein and therefore compensated for the broken SMN1 gene. This has saved the lives of countless children.

The great thing about RNA-targeting therapeutics is that any target is accessible, and in my opinion, it’s the closest to a “rational” drug design process in which scientists don’t have to screen large libraries of compounds and perform medicinal chemistry to optimize leads.  Antisense oligonucleotide therapies are much more strategic and cost-effective.  As such, it stands to be the platform of choice for all rare diseases, including n-of-one.

La Jolla Labs is an RNA technology company. We have built the only commercially available software tool for designing RNA-targeting screening campaigns for splicing, upregulation and knockdown; we include in this multiple machine learning models based on proprietary data and public resources.

We also have a wet lab where we perform partner screens and validate our machine learning models. We are a discovery engine and have a pretty good track record for multiple indications including numerous neurological compounds in preclinical studies and even a couple in the clinic for ultra-rare disease.  We do not take intellectual property on the compounds we do with partners. In that way, it seems like we are a contract research organization; however, we do get to use the data and experience in aggregate to feed back into our AI models. This way, we evolve as a platform for drug discovery.

We then provide these models to our software users – big pharma – who are going after larger, more financially viable therapeutics.

AI and automation are essential for us to travel down what we call the “long tail of rare disease”. There are over 7,000 rare diseases catalogued and growing. Many might say that every disease is a rare disease, as our personal genetic background is constantly working in ways that vary disease expression and penetrance. For example, some were impacted more than others by COVID.

The use of AI is growing rapidly, but for therapeutics, it’s particularly difficult to find relevant data, i.e., we need to find a way to connect clinical outcomes to drug discovery without having to rely on animal models. This is virtually impossible due to the rigid control of information that flows through clinical programs; companies are simply not going to share this information. However, this is not necessarily the case in the ultra-rare disease space.

The FDA published a draft guidance for antisense oligonucleotide therapy for ultra-rare and severe diseases that allows for skipping large animal models and relying only on a rodent toxicology study. Soon, groups like n-Lorem and the N1C will have enough clinical data on antisense oligonucleotides that, I believe, will enable transformative leaps in the ability to translate drug designs into safe and efficacious therapies.

90% of drugs that enter clinical trials fail. This is not a model that works for the rare disease community. A deep integration of automation and AI in the drug discovery and development process is essential. Also, it’s important that as we become more personalized with therapies, we need to recognize that we are dealing with human needs, not wants. There must be a shift in corporate sentiment to address a solution for patients more than just ROI for investors. I believe we will see the birth of “lifestyle” companies that are financially sustainable, but less focused on profit and growth and more focused on patient outcomes.

Too many companies have been a problem for the rare disease community as they over-promise, engage patients in data collection efforts and then drop them when it’s no longer convenient. There is no Hippocratic oath in business; we aim to change that.