Medra Raises $52 Million to Speed Drug Discovery With AI Robots

Watch Medra Raises $52 Million to Speed Drug Discovery With AI Robots - Bloomberg on Dailymotion

Transcript

00:00When you and I first met a few years ago, you had an idea and a concept. Now you have a company

00:06moving forward with it. I think actually as a start, let's explain why having that degree of

00:13interaction with what is a robotic arm in that lab environment through natural language is

00:19necessary. What does it solve for? Yeah, so we want to give scientists directly, not just engineers,

00:26with scientists directly the ability to actually run experiments at scale. And that is why we are

00:33building the physical AI scientists, physical AI that allows them to automate their scientific

00:40experiments at scale and also the AI scientists so they can talk to it. They can co-pilot design

00:47experiments with this AI scientist. What is it that you bring that others haven't in terms of

00:53the physical AI? Is it your data that's paramount to none? Is it the fact that your scientists are

00:57paramount to none? Is it the technical technology? What is it? It is all of those things and more.

01:05Industrial automation has been the key way that life sciences has automated their labs. But we are

01:12seeing a huge paradigm shift across every industry that is using robotics, where industries are shifting

01:19away from industrial automation to physical AI. And that is also what Medra is bringing to life

01:25science, the ability to flexibly automate their lab experiments instead of using brittle lab automation

01:31technologies from before. I want to think about this. I review the photos and images. I hope we have

01:37some images to share with our audience. I think a little bit about Tony Stark and Jarvis. It's the idea that

01:44there is an artificial intelligence that one interacts with through the robotic mechanism.

01:50When we first spoke, and this is a long time ago now, this was about efficiency. Labs are difficult

01:55environments. It's hard to move around them. It takes physical strength and time. But $52 million is a lot

02:03of money. You just click your fingers and you can suddenly do it. You've solved it?

02:07No. I mean, we have so much more to be building. Because again, it's not just about automating the

02:15work, but about this idea, can we automate science itself? Can we have a scientific AI that can reason

02:22about the science, generate hypotheses, design experiments? And when we actually run the experiments

02:27with our physical AI, once that data is generated, can we take that data? And then can we think about what

02:34are the new optimizations and changes necessary to make that science better?

02:38We started the conversation by introducing this in the context of drug development of the life

02:44science fields. What is the industry there and therefore your customer?

02:49Yeah. So we are working with some of the leading biopharma companies, including Genentech, to help them

02:55use our technology to really create this lab in the loop idea. And we are working with some of the

03:03best machine learning teams at our customers, where their machine learning teams can then propose new

03:09experiments they want to run, new ideas they want to test. And then again, our physical AI scientists

03:15can take those ideas, those predictions, and turn that into data that then feeds back into their

03:21machine learning models.

03:22This $52 million, where is it going to be spent most predominantly? Talent? Marketing? What?

03:28All of those. Again, all of those above. We are growing our team and expanding our team across

03:36engineering, robotics, AI, hardware, software, and also on operations and go-to-market. We're expanding

03:43partnerships with other biopharma companies. And also, we will be building our own lab. We'll be

03:49opening up an autonomous lab with 100 robots next year to be able to run experiments and generate data

03:56data at scale. Do you think the U.S. is leading here, Michelle?

04:00We want to be leading. And Medra is going to be that force to help the U.S. lead in this area.