A new approach to discovering treatments for rare diseases
Because of the cost, time and risk involved in conventional drug discovery and development, many rare diseases are left out of the treatment pipeline.
Our Perlara Drug Discovery Platform is based on creating disease models using simple animals that share genetic similarity with humans, allowing us to screen massive numbers of disease models and drug candidates quickly and at low cost.
How the Perlara Platform works
1. Build an Ark
We use gene editing technology to model specific human diseases in simple animals like yeasts, worms, flies and fish. Think Noah’s Ark of Drug Discovery.
2. Try out a boat load of compounds
We screen compounds on our disease models, and gather massive amounts of chemical and physiological response data.
3. Predict the best candidates
Data will fuel our predictive engine to identify high-potential drug candidates for specific patient mutations.
4. Precision treatments
We collaborate with BioPharma and partner with patients to turn Perlara drug candidates into precision treatments for rare and common diseases.
Treatments for genetically similar rare and common diseases
So far we have identified at least 250 single-gene diseases that fit the Perlara Platform. Each of these diseases is caused by an ancient gene that also contributes to common disease risk. Our first PerlQuest™, Niemann-Pick C (NPC) disease, could lead to therapies for common neurodegenerative diseases. Learn more about PerlQuests on our FAQs page.
Does it really work?
Science updates from our Blog
I, along with Nina, performed our first high-throughput screen – well really medium-throughput but high-throughput for us – on Niemann-Pick Type C (NPC) patient-derived fibroblasts a couple of months back. We wanted to do a pilot screen with the Microsource bioactives...read more
Well it has been a little while since I wrote a post, and a lot has happened since then, which I am sure you read about in our blogs and tweets. We changed our company name, partnered with Novartis and started partnering with patient groups to engineer our organisms...read more
Two weeks ago we posted Perlara's first preprint to bioRxiv, along with all the raw data on GitHub: https://twitter.com/biorxivpreprint/status/796019478999998465 This effort was led entirely by a very talented undergrad named Maria Teresa Chavez, who reached out to...read more