In this pitch, Ashwin Gopinath presents the "Nano Doctor Octopus," a DNA‑origami based nanoparticle designed to detect and eliminate senescent cells for longevity applications. The device displays an array of 36 aptamers (covering 10‑15 protein markers) arranged in a specific multivalent pattern that serves as a unique surface‑receptor signature for target cells. A billion‑variant library is screened via next‑generation sequencing to identify high‑affinity binders. Upon strong, sustained binding, a built‑in actuator—modeled on T‑cell ligand clusters—triggers apoptosis. A kinetic‑proofreading mechanism ensures that only sufficiently long binding events activate cell death, reducing off‑target effects. The underlying hypothesis is that each cell type possesses a conserved spatial arrangement of surface receptors that can be exploited for selective targeting. Development is outlined in three phases: Phase 1 (proof‑of‑concept for senescent cells, 3 years, $15 M), Phase 2 (pre‑clinical diagnostic and therapeutic development for cancer, leveraging the same platform), and Phase 3 (clinical trials and manufacturing), with an estimated total program cost of ~$400 M. The presentation also discusses scalability using existing single‑cell sequencing and RNA‑seq data to map receptor arrangements across tissues, suggesting the platform could be extended beyond senescent cells.
Chapters
Okay.
So our idea is to make this nano doctor octopus. It's basically an approach that we looked at what should be done, and we tried to use one step away from existing technologies to build a product which essentially what it does is it looks around and it touches the cell and it looks at the surface, and it can be used for marking or killing of any cells. And we are focusing on senescent cells specifically for longevity cases. So the aspects of our approach that makes it unique is that it detects the cell based upon an array of 36 aptamers. What that means is it looks for 36 different bind— 36 arrangements of up to somewhere between 10 or 15 kinds of proteins. So it's looking for arrangement of markers rather than just a single marker. And we are going to do the selection based by creating a billion different versions of these nanoparticles, and we are going to analyze them by next-gen sequencing to identify the ones that bound the cell of interest. And not only are we going to bind it to the cell, but we are also going to have an actuator in there that uses the same mechanism that is used by T cells, our immune cells, to kill other cells. These are these receptors, these tiny little ligand clusters that will trigger an apoptosis. So it triggers— it tells the cell to kill itself. And we have something known as kinetic proofreading. What that means is unless the binding event occurs or unless it— unless the particle binds the cell for a certain length of time, it's not going to trigger the cell death. So it basically touches around and whatever that it touches for a longer time, that means it's binding it strongly, it's going to kill it. And the way in which it binds is by looking at an arrangement of proteins. It's not looking for just a single protein or a single marker, but it's looking for a variety of markers in a specific arrangement. And our hypothesis is that the arrangement of the markers is specific to the cell. So this is what the picture actually looks like. So you have a cell, and the red little dot that you see is an origami. And if you zoom in, It has aptamers, there are just 4 of them at a specific arrangement. And it's because of the arrangement of the aptamers, and it's sensing what is on the surface. And if it matches it, it sticks on and holds on there. And if it holds on there, it's going to kill the cell. Here I don't have a picture, in the picture I don't have the actuation. And like I said, the novel aspect is that it's looking for multivalency, it's not looking for a single marker. And all the origami itself and the construct itself can be selected by sequencing. It can actuate. Not only can it sense, it'll kill it. And also it has a proofreading mechanism as a potential approach to reduce crosstalk. So it doesn't— it's so that it doesn't kill a cell that it's not supposed to. So the construct itself looks like this. So this little Picture is that of the origami, and each number represents a particular aptamer that binds one of these ten markers. These these ten proteins have been identified as markers for senescent cells already, and each number tells you an aptamer, a weak binder to that, and it's arranged in this particular order. Does this order remind you of anything? Anyone?
Yeah.
No, it's actually 3.14159.
So—
Yeah.
Yes.
Yeah.
So you look carefully. So again, so we have not actually shown the arrangements on how it triggers apoptosis. But the idea is this arrangement of these binders is a signature of the cell. So it is reasonable to assume that every cell in your body has a unique signature of the surface receptors. And the surface— and the reason why we think about this is every cell interacts with its environment in subtly different ways. We know that. And the way in which it interacts with the world is through its surface, through its surface receptors. So it is reasonable to assume that the arrangement of receptors or arrangement of the surface is a unique identifier to the cell itself. And that's what we are looking for. And again, we have not shown the mechanism by which we will trigger the apoptosis. So the way in which we are structuring the milestones and budget, Martin will actually explain that. But the idea is basically to quickly verify the basic mechanisms and then to scale up from there.
So we're looking at a Phase 1, which is the proof of concept dealing with senescence, and we figured that would take about 3 years and $15 million to identify the So the assumptions are the items that you see on the slide. How do we go to the next slide? And there's an assumption that you actually need a market, which we don't have for senescence right now. So we're assuming a cancer market. And that means that you actually need to go through development and clinical trials. So this is the development phase, Phase 2. Which would take you through 2 things. One would be a cancer diagnostic and the other would be a therapeutic using the mechanism that we weren't showing before on how apoptosis occurs. And that would take you through your initial preclinical work and work for diagnostic and therapy. Then Phase 3 would be the actual clinical trials and production of the material. You can see the whole— the overall cost of the whole program would probably be about $400 million.
Yep. So questions?
We'll start if there are judges' questions or comments.
Are you going to have a portion of your Phase 1 devoted to actually studying different cells to actually identify a modification? I guess finding activators.
Did I miss something? So the core technology itself, we are focusing right now to— so in principle, if we can validate this for one particular kind of cell, it's reasonable that we can extend it out to multiple cells. And due to the fact that we have single-cell sequencing, RNA-seq already existing, it would be pretty straightforward to think that we can scale it up to study on tissue levels. If you have— if you take tissue samples from different body parts and use existing single-cell sequencing methods to identify the cell receptors on the surface, the arrangement of the cell receptors. So in some sense, we want to try to validate this for senescent cells because we have those 10 markers already done. But once that is done, once we have actually validated it, we can extend it to any cell. And because of the fact that we are using sequencing and single-cell existing technologies, we should be able to scale it up quite quickly. Does that help?
Yeah.
So it doesn't have to be personalized? Not necessarily. I mean, it could be, but it's not necessary. We are going with the hypothesis that every single cell has a signature that is conserved between people.
Okay.
But we don't know that.
Right. Yeah.
We don't. That is a hypothesis which— I mean, looking at the really preliminary data that is coming out on the surface markers, It seems reasonable. And from first principles, it seems reasonable. But we don't know the answer to that question. Are they always the same distance apart from each other? We don't know the answer to that question.
