"With AI innovation in healthcare, right trust and transparency need to be built"

08 March 2024 | Views

As the life sciences industry increases its focus on technologies such as AI, machine learning, GenAI, and ChatGPT, BioSpectrum took this opportunity to speak with Pratap Khedkar, Chief Executive Officer, ZS, to understand more about the impact of these trends in the coming times.

What do you think are the new trends along with the challenges which will take the limelight for the life sciences industry in 2024? You could break it down in verticals as per their priority, but if you have to broadly classify the trends, what would those be for 2024?

Let me start with the slightly broader global pharma angle because I think some of those are obviously felt in a similar way, but with some twists. I think there are going to be 3 key things for 2024, not just for one year, but I think these are things that will be relevant over the next three years with some immediate action fairly soon.

I think one is health system reforms everywhere, and when I say reforms, I mean pricing pressure. Another phenomenon which is new actually with policy, which pharma is grappling with now–which hasn't existed in the past but has been there in some shape or form–is the time pressure. What happened is, if you look at the legislation in the EU which says I’ll knock off 2 years, from 10 to 8, if you don't launch in the 27 major markets or the legislation in the US which says to limit small molecules to 9, large molecules to 13. Basically, what that time pressure is doing is, pharma is saying, if I agree to the cutoff, they’ll have to, I will leave about 35% of the total products value along its life cycle – off the table, like 35% is taken away. Now I can recoup it by launching much more effectively.

The second big pressure that's coming up in pharma is demographic shifts. India is a very young population and the young part of the population is still growing. But for the rest of the world, the number of people above 60 is going to double in the next few years. Because of this demographic or the sort of the bubble moving into the 60-65 plus category, there are a few implications. One is, pharma has to actively start investigating therapy areas that concern the old, which is already big with things like Alzheimer's, cardiovascular disease. These become much more attractive because they were considered smaller problems in the past. But in the demographic, dividend is going to become a very big issue. The second part is because you have 2X population, affordability has entered the conversation, which is you can find an amazing drug, it may be cost effective, it may be priced reasonably well, but if it's going to go to 100 million people, it will not be affordable. So, the shift from cost effectiveness to affordability is sort of issue no. 2.

The third big pressure, which is less in India because I think the Indian healthcare consumer is slightly less mature, but a couple of things that India I think is doing well, is this idea of patient experience and expectations. There is very big gap developing which is now being measured and it's not just about health equity, I will call it the care gap in a different sense. In the US for instance, if you ask physicians if your patients feel cared for, 80 percent will say yes. But if you ask patients themselves, there is 40%. There's a big gap between what the patients want and what the patients get. 

The perspective that you have given for the Indian market, what are the plus points, something that is going to attract more pharma business? What would that be?

This idea of applying AI and Gen AI in healthcare is an important piece. My personal view is that when it comes to innovation of AI in healthcare, you have to set up the right guard rails and not create too much regulation because the third shift that I talked about–patient experience and expectations–and then some of the hospital providers approach to this, that together will put in place enough competitive pressure that you will have to build in the right trust, you will have to build in the right transparency and you will have to build in the right sort of competence rather than over regulating all these things, which is I think the approach that Europe is moving towards and the US is not clear, but they'll probably come with something in between the free market forces and the European approach are probably midway.

I think India is taking a very interesting and positive approach to say, we have such a big gap that once we get the data, we need the AI innovation in place to actually use the data because just collecting the data isn't enough. The US discovered that, so India’s lesson is, let's innovate on the next step in parallel with the first step. In order to innovate, if you constrain it too much, innovation stops. I think they're taking the right balance of making sure the second step progress happens well enough that by the time the first step the data infrastructure is ready, we are beginning to see very quick benefits thereafter. I think that's another place where I think India is ahead.

Talking about artificial intelligence or newer technologies, do you think the startup, specially the tech startups in India will progress well in this direction in the coming year? What is the support system that is required for these startups to take up the technology?

I tend to think of three things, for any technology to actually succeed in improving the human condition in terms of real impact–one is innovation, which is where the startup scene fits much more. The second is scaling and the third is adoption. All three have their time and place.

Let's focus on the first one. I think in India, what we are discovering is there are two things that worked.  One thing is amazing talent. ZS has now been in India for 18 years now. We had initially analytics talent and then the bulk of our AI people are actually in India because we recruited a lot of talent here. So, the talent is absolutely first class. 

The second piece though is you need this mindset of what are you applying AI to. In India, what I see most clearly is the idea of frugal innovation, meaning, it is not innovation as in I will give you the most cutting-edge fancy stuff, which tends to be the innovation in the US, even from startups. But here it is fit for purpose in that for this particular problem in India, in this particular sense, is there something we can do with data and AI that will be “jugaad”, which is a popular word for it. The point is, is there a way to be very clever about solving a real healthcare problem given the Indian conditions, without getting too fancy or cutting edge just for the sake of the best algorithm or the biggest neural network? Let me give you an example. One of the things that we wanted to do is to encourage these startups. But how do you identify the winners? How do you help them? 

One of the things we started doing a few years ago was the ZS PRIZE and it's one example. It has Rs 1.5 crore prize money and we've done multiple iterations of it. The second iteration was last year.  We focus on AI in digital in healthcare, that is the theme of the competition. This time we had 25,000 registrations, thousands of ideas. We boiled it down to twenties and eight and so on. That is one effort. But my point is, for innovation to succeed, you have to focus on what we found when we looked at the cases, is you actually need to help them. It's not about picking the winner. Yes, that's part of it. But about what are some of the learnings in terms of communication and fine tuning? There's of course the prize money and the celebration and the visibility, which then leads to the second step, which is scaling.

Now we don't invest in scaling directly. We have created and are focusing more on adoption in general, not just in India. In India, we don't directly work with healthcare hospital providers, but I wanted to point out one case, and it did start with a startup. This is an Apollo Hospitals’ case which is for cardiovascular risk. Apollo had data for a hundred thousand patients actually over 10 years and they ended up figuring out how can we create an AI algorithm that will predict the cardiovascular risk, which is a very big problem. 

What expectations should the industry have from the government to enhance the growth of the life sciences sector?

There are many different pieces of the pharma industry. I don't think they would have a uniform ask. I would say the best thing to do right now would be, that don't just think in terms of direct price controls or ceilings. We need to figure out how to take price and the cost effectiveness or evidence of impact clinically and affordability, which is where I think the government's concerns come from, is how do we make it affordable as opposed to impactful. So, we need a framework for value in healthcare. 


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