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  • MALE SPEAKER: My huge problem for today is surgery.

  • So we all know surgery.

  • Most of us will undergo surgery at least once.

  • They save a lot of lives.

  • They improve the quality of many other lives.

  • But the way we do surgeries today is very far from ideal.

  • Just to think of it, they're very, very expensive.

  • Training the staff, building the operation theater,

  • maintaining both, is a huge financial burden.

  • And that leads to the fact that most people on the planet who

  • need surgery don't have access to those facilities

  • and that personnel.

  • Just to give you some numbers, here in the US alone,

  • more than 50 million inpatient surgeries will be performed.

  • The surgeries will cost between $25 and $150 per minute

  • in the OR, not counting procedure-specific costs.

  • And between 1 and 3% of the patients

  • will die within 30 days of the procedure from complications.

  • What I'd like to do here is to propose to you

  • an alternative approach which could revolutionize

  • the entire field as it looks today.

  • So imagine that we could take all the facilities, all

  • the equipment, all the knowledge required

  • to perform a successful surgery, and encode it

  • in a single drop of saline.

  • So that drop can be put inside a syringe.

  • You can take it anywhere on earth.

  • You can give it to anyone in need

  • without even having to anesthetize them first.

  • Inside the patient, the drop inside the syringe

  • will find its target, will remove the cells,

  • kill them, locate them from A to B,

  • recruit new cells to fix that tissue,

  • and have the computation capacity of a real computer.

  • So how can this be done?

  • It sounds a bit far-fetched, but let

  • me explain to you how we can already do that.

  • And I hope it will be enabled in the very near future.

  • So if you could look inside that drop of saline magnified

  • by about 70,000, you will see billions and billions

  • of tiny objects.

  • Each of these objects that you see here

  • is a robot, with chassis and moving parts.

  • A robot that can be programmed to do amazing things.

  • These robots are built from DNA.

  • We use a technique known as DNA origami, to take a piece of DNA

  • and fold it into the 3D structure

  • that comprises the robot, the machine.

  • These robots were born about four years ago in the work

  • I did with Shawn Douglas at the lab of George Church at Harvard

  • Medical School.

  • So each robot has a very specific task

  • it knows how to do.

  • It picks up a cargo at point A, and drops the cargo at point B.

  • Now, in fact, it doesn't actually drop the cargo.

  • It rather switches the cargo from a concealed state

  • to an exposed state.

  • So basically, it switches the cargo from off to on.

  • And it can go back to off, and it can do this repeatedly.

  • In the past two years we learned to design

  • robots that are invisible to the host immune system,

  • to the mammalian immune system.

  • We learned how to tune their stability in the blood,

  • and now it ranges between several minutes

  • and many, many hours.

  • So it might seem very simple.

  • It might seem very limited in its capabilities.

  • But building on this very basic routine of pick cargo

  • at A, drop cargo at B, we can build

  • an astonishing array of tasks.

  • And what I'd like to do now is to walk together with you

  • through the tasks required to perform successful surgery.

  • And let's see how each of these can

  • be translated into the language that robots understand.

  • So the first thing is that a surgery takes place

  • at a specific interface.

  • That is the interface between the target

  • issue and a background tissue.

  • Now, a trained surgeon can manually define this interface

  • with a precision of about maybe a submillimeter.

  • But these robots can do tens of thousands of times better.

  • You can think of them as scalpels

  • as sharp as a molecule, basically.

  • So by programming robots to identify both target

  • and background tissues, we can have them organizing themselves

  • around that interface.

  • And now they can expose and activate

  • a cargo, which in this case is not a drug.

  • It's an enzyme that can cut tissue components or matrix

  • components, cut the links between cells,

  • disintegrating the tissue cell by cell.

  • The second thing that you have to know

  • how to do to make a surgery is to move cells

  • from A to B. You can either, in the most basic sense,

  • remove your target tissue to the trash, in which case

  • the trash is point B. Or you can recruit cells

  • from another place to come and fill in the gap,

  • and regrow and regenerate the tissue.

  • So that's also moving cells from A to B.

  • The robots know how to do this just like ants

  • do when they carry prey much larger than themselves.

  • They recognize the specific cells, as you can see here.

  • They detach them from their surroundings.

  • Then they can carry specifically those cells, not

  • the other cells.

  • They can carry them from point A to point B based

  • on a combination of molecules defining points A and B,

  • which is how the robots know to differentiate between points A

  • and B.

  • The second thing is, once you have the cell,

  • you need to know how to reprogram its biology.

  • You need to tell the cell to either die,

  • or you can again recruit cells and tell them to regrow,

  • and fix the tissue and regenerate that tissue.

  • So we've already shown in numerous examples,

  • including the one we published two years ago, that when

  • we load the robots with cancer drugs,

  • with proteins, with growth factors,

  • we can tell the cells to either suppress their signaling

  • or die eventually.

  • Like you see in the upper figure.

  • Or we can also tell cells to grow,

  • as you can see in the example of robots loaded with insulin.

  • So by the way, when the robots grab their cells,

  • and now they can engage those cells with selective signalling

  • molecules, you can have the robot

  • scan your entire system looking for metastatic cells.

  • And finding each of these single metastatic cells,

  • holding them, making sure they don't attach anywhere,

  • but also now acting on them, killing them,

  • making sure no cell remains.

  • So the last thing, in addition to acting on that interface

  • and on those cells, you need to be able to provide support.

  • For example, you want to regulate bleeding,

  • to prevent excessive bleeding from that surgery.

  • You want to reduce pain.

  • You want to negate inflammation.

  • There are many things you need to do that are not directly

  • related to that incision you're doing right now.

  • So we already know that these robots

  • can be programmed to carry out all those tasks.

  • I want to show you a specific example of robots

  • that can selectively target and suppress nerve cells,

  • nerve cells that transduce pain signals.

  • So the way they do that is they look

  • for cells that release above a certain threshold

  • of neurotransmitter.

  • And only that threshold activates the robots.

  • And they expose a calcium channel blocker,

  • which blocks specifically those nerve fibers.

  • So they can suppress pain deriving

  • from peripheral procedures.

  • And eventually, you want to take all those components

  • and to integrate them such that they are performed

  • automatically, just as if a computer would control them.

  • Right?

  • And that can be specific to something happening

  • inside a patient right now, and not

  • something that's constantly-- you

  • should be able, for example, to stop that procedure whenever

  • an excessive damage is caused.

  • So to do that, we designed robots

  • that can mimic the interactions between components

  • in a computer processor.

  • These robots, as you see here, can actually

  • interact with each other.

  • It means from point B to these robots

  • is actually another robot.

  • It's not a tissue.

  • So they can communicate and transfer

  • bits of information, which are also

  • DNA molecules, from robot to robot.

  • And these can emulate successfully

  • logical operators of the basic components of computation