So what we're trying to do is one project of ours is regrow the cartilage so that in 3 to 5 years from now you don't need a knee replacement. That's a painful surgery. It has great outcomes and great results. But imagine if we found you at 45 because you're a runner or at 55 when your cartilage started wearing out. You had already stored your stem cells with us. We reprocess those cells or we got the autologous cells from the lab and then put those back into your knee joint.
Biology is fascinating because there is all the time real-time analytics going on in the human body. Your brain is constantly receiving signals from sensors within every organ, every tissue. And there's constant real-time analytics going on in your brain. Your billions of neurons are processing huge amounts of information and real-time coming up with predictive algorithms that basically translate into inference.
So our next two speakers are really working at the frontiers of medical health and of the possibilities that will be unleashed for us in a positive way for longevity, for living without disease and of using technology in a way that is optimistic and productive and without all of the philosophical anxieties and existential anxieties that we were discussing over the last two sessions. So to discuss the frontiers of medicine and where technology can be used, ladies and gentlemen, please welcome on stage Kiran Mazumdar-Shaw and Sangita Reddy.
Both of them you already know but I'll just do that one line which is of course Kiran is the chairman of Biocon and been an absolute frontier pioneer in biotechnologies and life sciences and Sangita with Apollo is again pushing the boundaries of how technology can be used for bringing health to the masses with AI and with many others with genome mapping and that is the landscape of what we're going to discuss here. So Kiran I wanted to start with you, you know that we were hearing about all the really anxious situations around AI and super intelligence but you are very hopeful about the way it can be deployed for human health. You know you have an idea of how AI can actually learn from the human body. So do share with the audience what this idea is.
Yeah. So, I personally believe that of course AI proving...
From this side that they can't hear. So, there seems to be some reverb. Could you just fix that? Can you hear me?
I'll give her the mic. I will switch my...
No. Can you hear me now?
Okay. So, I have always believed that AI-enabled biology is the way forward. AI provides you with very deep insights into biology and I think AI needs to learn from biology in terms of how intelligence is built because this has to be a symbiotic relationship between AI and biology because biological intelligence to me is what we really need to build in the future for many, many reasons. If you look at the way you've just heard how large language models is akin to rote learning and I think when you look at biological intelligence it's about how do you think of new things, how do you create new ideas, new knowledge and I think that's what is very important for us to basically understand. What fascinates me is that when you think of biology, biology is fascinating because there is all the time real-time analytics going on in the human body. Your brain is constantly receiving signals from sensors within every organ, every tissue and there's constant real-time analytics going on in your brain. Your billions of neurons are processing huge amounts of information and real-time coming up with predictive algorithms that basically translate into inference that is trying to look at deviations from homeostasis and correct it. So this is going on all the time in your body. But what is fascinating about how biology builds intelligence and operates in terms of inferences is about having distributed data centers. This is about distributed data centers, control mechanisms and edge computing which is what makes all this possible. So we have to learn the way biology does it so efficiently. But without getting AI to understand what happens in biology, it cannot really benefit from biology. So I think it's a two-way street. It's symbiotic.
So I'm going to come back to probe that idea Kiran but it's in a way bringing us humans back into the apex species for you to remind all the technologists working with AI that you know AI really needs to learn now not just from human mind but from the human body system itself.
Yeah. So the super intelligent or you know AI that you're trying to create will only come if you understand how biology learns.
Yeah. Which is unlocking a whole new thing but I'm going to come to that. Sangita I want to bring you into this that you know just moving away now from a more conceptual idea you've really been very, very optimistic and gung-ho about using AI at scale in India for bringing therapy and predictive medicine to the masses you know so give us an idea of what you want to do and where are we at.
So I assume you can hear me. Good afternoon. I think I'm extremely excited.
Will you speak into the mic?
I'm extremely excited about the potential of what we can do because just for a minute we need to understand that the problem on hand is quite large. Non-communicable disease have overtaken infectious disease. The rate while longevity is progressing. The fact is that people are living longer but not healthier. And therefore we need to find ways to change the current paradigm of healthcare. And that paradigm is moving from sick care to rushing to a hospital when you have a heart attack to finding out what happened when you were 30 years old and your first artery started clogging. Which aspect of your genetics and your lifestyle is causing your neurological deterioration and why do some populations live healthier longer? I just had a fascinating conversation with a scientist who's analyzing the blue zones of the Sardinian health system. So to do this we need AI, we need technology. I'll just share very quickly two or three things. In the year 2000 we started doing telemedicine, 2000, so 26 years ago we did the first telemedicine connecting an Indian village where my father was born to our high-tech hospitals so we could give second opinion services in that village. Now this has scaled tremendously the government, the private sector, India to the world and vice versa but then comes the fact that if you can use the AI data how do you map appropriate doctor to appropriate patient. How do you enhance this to build agents so that 80% of the questions being asked are answered by agents immediately automatically. And then I want to go one level further in one of the things that I think is the most important especially in a country like India or large populations significant is risk scoring. How do we isolate populations which are at deeper risk? So in this AI-CVD risk score that we did with Microsoft almost 6 years ago, we've now done 3.4 million people across India and other geographies and we've been able to identify risk. I'm going to, you know, there's a whole realm of things that we can do but I just want to conclude this piece by saying one thing and that is the combination of knowledge of biology which is the body, the cells, how they work, what is gene expression, the use of bytes or the processing capacity whether it's imaging capacity of x-rays or CT or computational capacity and bytes is now getting replaced by tokens because of AI and then bandwidth because it's no fun having advanced healthcare in our big cities and knowing that villages in Africa and India or even in the United States that they are neglected. So the combination or the convergence of knowledge through biology, bytes and bandwidth is going to be the transformational bioeconomy and I think we are at a point, an inflection point in the history of the world where we can dream of every individual being healthy. That's what I'm looking forward to.
So Sangita I'm going to come back to examine that but Kiran coming back to you. You know when you were talking about the body as being this vast network of data and processing you came up with this, you know, that phrase of pharmacology network, you know, you're saying that medicine itself needs to behave in this kind of distributed complex way in which the human body works. Could you help us understand and is that, I won't say a contradiction but does that run differently from the idea of precision medicine now where you know you can come down to literally the genome, the mutation, you know, that's what we've been hearing but you're now talking about something which is a pharmacology network itself. What does that mean in terms of medicine, you know, give us an example.
So as we get insights into biology we are clearly seeing that this targeted approach one target at a time is not really working that effectively in terms of having enduring effect. So let's just look at the latest craze of GLP-1s, you know, the Ozempics, the Mounjaros. How does it work? It's this one tiny peptide, this enteroendocrine that has multiple targeted approaches. Whether it's your pancreas, whether it is your vagus nerve, whether it is your hypothalamus, whether it's your gastric cells, will you speak into that?
Whether it's your gastric cells, it is basically sending signals to suppress appetite, to tell your brain that you're full, to delay gastric emptying. So, you can see how it works in a network effect. And we need to discover more and more drugs that have this network effect of getting the final impact.
So I think the way we are looking at medicine going forward is really to understand how the network pharmacology works in your body that gives you sustained performance of any drug. In fact, the ultimate goal is to have reprogrammed cells. Can we get cancer cells to be reprogrammed into non-malignant cells? Because everything that happens in our body is about health equilibrium. And when those guardrails fail, we get disease. Okay? So the body is constantly trying to keep you in a state of good health. That's the guardrails that nature has provided. Now when those guardrails break, of course you have all these problems in your body. And the question today is can you get into regenerative, reprogrammable cells which can bring you back to health, back to equilibrium. That is really the big exciting frontier research that's happening in biology which of course is going to be hugely aided by AI.
Well, you know, immediately after lunch, we have a really cutting edge scientist, a speaker who's working on, you know, re-engineering organs, regenerating organs and reprogramming cells. So, it's very much in keeping with what you're saying, Kiran, but I do want to ask you that, you know, we've been discussing the state of AI. So when both of you are saying that AI should do this, AI can do that, is there any models that you're already using to do this, are any of the existing models in which trillions of dollars are being invested, are they able to do any of what you all are talking about?
