People ask why a small company would take on something this hard. Because we think it matters more than anything else we could be working on, and because almost nobody else is trying it.
The pyramid is inverting
For most of human history, a population looked like a pyramid: many young people at the bottom, a few old people at the top. That shape is inverting almost everywhere. The United Nations now projects that by the late 2070s, people aged 65 and older will outnumber children under 18 worldwide. In many countries the pyramid is already inverted, with fewer younger people supporting a larger, older population.
Older people need more care, and a lot of that care means looking directly inside the body to see if anything abnormal can be identified. Demand is going up while the number of people who are able to access this care, per patient who need it, goes down..
There aren’t enough health workers
The World Health Organization projects a global shortfall of 11.1 million health workers by 2030, concentrated in low- and lower-middle-income countries. Specialists are among the hardest parts of that gap to close. Training for a specialist takes a decade or more, the training varies from program to program and country to country, and the people who can perform a given procedure tend to cluster in particular cities and particular nations.
You can’t fix that math by asking clinicians to work harder. They’re already working harder. The supply of expertise itself has to change.
Why robots, and why inside the body
Expertise is scarce because it lives in people, and people take years to train, one at a time, in programs that rarely teach the same way twice. A robot is different. You can build it many times over, and what one of them learns can be copied into all of them instead of taught one apprenticeship at a time. This still has to be validated with evidence and under regulatory review, like everything else in medicine. But it creates the potential to scale expertise in a way that tradition training simply can’t.
That is why we are pioneering robots designed to work inside the body where so much scarce, expensive, expertise-needed work happens. It is where the bottleneck is. Whoever learns to put good machines there, and to make each generation better than the last, will shape a lot of medicine this century.
The flywheel
Every procedure one of our systems participates in, whether in our development work today or, we hope, one day in practice, could leave a record of what the robot saw, where it was when it saw it, what it did, and how a physician reviewed it. With patient consent and privacy protections, that record could become teaching material. We intend to use it to train the next generation of the system, which we hope will be more capable, produce richer data, and teach the generation after that. That loop is the engine we are building our platform around, and it only works if procedures are comparable to one another. Standard paths, spatial context and complete coverage are what make the data from one procedure useful for teaching the next.
People stay at the center
It is easy to hear “robot” and “shortage” together and draw the wrong conclusion. There will always be a strong and growing place for human clinicians. Nothing we are building is meant to replace them.
Our goal is to give them reach. The repeatable, mechanical parts of a procedure are the parts a machine could eventually take on. Judgment, communication and care are the parts that make a clinician a clinician, and those become more valuable, not less, as the mechanical work moves to machines. What we are building toward is a world where a clinician’s skill can reach far more people than it can today, and where a look inside the body is within the means of far more of the world. We have a lot to prove before we get there.
Being early
Being early isn’t glamorous up close. Mostly it means finding out what doesn’t work before anything depends on it. Our technologies are investigational, meaning they are not approved or cleared by any regulatory body. We are starting with the stomach, with seeing before steering, with steering before robot navigation autonomy, because each step is needed before the next can be undertaken.
Why we get up in the morning
What we do is hard, but it is fun. We are a bunch of unique individuals with various backgrounds all coming together to try and solve unique challenges. We know that we can do it. We are seeing real progress on a daily basis. We know there is a big problem that we can help to address by making robots small enough to swallow .
That is a big task for a small company but we are confident we will succeed.
Arman Nadershahi
CEO
Endiatx