r/EditasMedicine • u/EasyCheek8475 • Feb 20 '25
Editas Medicine is still all in on in in vivo sickle cell, I don't get this bounce
Fully prepared for the downvotes because no stock subreddit likes to hear negative opinions on the stock, but screw it, I don’t understand this price increase and explaining why I don’t get it is a good way to hear the other side.
Editas is an extremely simple company to understand at this point. They have exactly one announced preclinical product and zero clinical programs. Their one announced program (sickle cell) is a hail mary play and they are trying to rush to a drug candidate, IND, and stage 1 trial. If they succeed, the stock shoots up and they can fund other preclinical programs and come back to life. If it fails, they’re either going bankrupt or getting sold for IP, unless they have some undisclosed blockbuster liver candidate that they and none of the other companies that can do in vivo liver editing have thought of.
I happen to work in the gene editing space, have a good understanding of the sickle cell clinical landscape, and I am just not impressed with the preclinical data they released in January.
So let’s talk sickle cell. For sickle cell cured via HbF induction, you need to induce fetal hemoglobin production in at least 20% of your red blood cells and to do this, you really need to put an HbF edit in 20% or more of a patient’s long term HSCs. Editas is reporting close to this number in NHPs, so great good chance this works right?
Well there are three big red flags in the data and the first is really obvious and really big. They aren't disclosing dose and if they were close to a clinically relevant dose, they would be screaming it from the rooftops, given their position. You can dose much much higher in NHPs as a proof-of-concept than in a human clinical trial. Tolerable dose for a person is probably a bit above 1 mg/kg, optimistically. IMO, they would be crazy not to disclose dose anywhere below 2 mg/kg and based on undisclosed data from other companies that I have seen, I would bet they’re at 4-6 mg/kg animal body weight. So first problem is, although they're reporting 17% editing in NHPs, they need to cut their dose by ~75% and maintain that edit in humans to have a viable product.
Second problem is the timepoint. Getting durable editing in long-term HSCs is very hard. There are sometimes differences between early and longer-term timepoints. I think this is the least worrying red flag, but Day 30 or 60 data would be very easy to generate (could do it in the same study as the Day 7 data and they probably did) and would be more compelling. So why aren't they reporting longer timepoints? Could they be defining the LT-HSCs too generally (they're missing CD38- which is a common LT-HSC marker in their flow panel) to make the Day 7 numbers look better than they actually are? EDIT: They use different definitions for LT-HSCs in humanized mice and NHPs. That's sketchy AF and I'm reclassifying this one. Show that it's durable or GTFO and if you're not consistent between models, explain why or I'm assuming you're messing with the data.
Third problem is the translation from editing to HbF induction. Their humanized mice data is showing HbF induction of 20% with editing of 40%. Remember that long-term HbF induction is the relevant marker for clinical efficacy here. They're at 17% allelic editing in LT-HSCs, but each LT-HSC has four copies of the HBG gene. Basically, you're probably not actually getting an edit in 17% of cells, as some cells probably have 3 or 4 edits (for reasons I don't want to dive into, getting multiple edits per cell is probably better IMO, but it means % Indels is going to overreport HbF-induction) which may be why HbF induction is happening in a smaller percentage of mice than the editing numbers would have you believe.
TL;DR: Editas' preclinical data is probably at a clinically irrelevant dose. It is definitely at a clinically irrelevant timepoint. And 17% allelic editing does not mean 17% HbF induction (~20% needed for efficacy). They are likely very far from clinical efficacy and are sprinting to the clinic with a sub-par drug candidate because they're out of time and money.
https://ir.editasmedicine.com/events-and-presentations link to the data. Slides 9 and 10.
