Rare Resolved
3 Key Activities in Finding Rare Drugs
Number 1
Is our population big enough?
What can we do to collect family data into registries?
We need to get as much patient history information into a Patient Registry database as practical. Think of what types of data that will be impactful for patient inclusion in a trial. Strive to exceed 1,000 individuals in the database, however even low 100s can be minimal set that attracts big Pharma. Achieving these large patient populations often entails getting related organizations, both nearby and around the world, to collaborate and harmonize their data. Ideally, we get a large population that is pre-consented to being part of a trial or study.
Number 2
Do we have the right biomarkers?
Can we develop two types of biomarker assays?
The first biomarker focus is to find a fast and easy screen. Ultimately we strive to find a simple test (“Killer Assay”) that has a good signal, preferably one that can be seen in a plate-reader format. This assay test is what we will deploy in our drug screens.
The second biomarker focus is to try to find an endpoint that is shared across systems (cells, animals and the patient). If we can find a biological endpoint that is in both the animals and humans (eg. RNA-seq, proteomics, etc), then we will have taken a big step in finding a surrogate biomarker that will pass FDA muster. We will also help derisk clincal trails because the molecular markers dependency on patient’s genetic predisposition will allow it to be a precision medicine endpoint in clinical trials. So, we need to consider wisely what it takes to become "a validated biomarker", which may lead to a Companion Diagnostic Application and add synergy at market to drive adoption of a therapy in clinic.
Number 3
Can we find a candidate drug?
Can we get some drug repurposing screens done?
Drug repurposing is perhaps the lowest-hanging-fruit for getting a drug that can be brought into the patient the fastest. If you can get a handful of hits, you can then start screening for conserved effect across multiple test systems (eg. cell culture, worms, fly, fish, rodent, NHPs, human iPSC tissues). The more you can show the drug effect is conserved across testing models, the more attractive and validated the "asset" will be to Pharma. Once we have good results with a repurposed drugs, we can recycle the platform to be more efficient in bringing new entities (NCEs, ASOs, AAVs and HSCT-GTs) thought the same screening systems to find best-in-class performance that supersedes our first-in-class repurposing performance.
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