Ratnadeep Bhattacharjee: This understandably is a very debatable topic. There will be  many different connotations and permutations combinations which will kick in when we  discuss these things. Similar to this topic, one of the most debatable or regressed upon  topic is the value of outsourcing in the healthcare industry. Outsourcing a certain portion of the technology to a third party vendor. You cannot ignore outsourcing, you can  probably avoid it, but cannot ignore it.  

So I wanted to understand from you a bit on what your thoughts are and how can  people or how can healthcare companies primarily decide on what to outsource and  how to outsource, most importantly? Can you shed light on what your thoughts are on  that one?  

Mahek Chhatrapati: Whether it’s healthcare or not healthcare, I think outsourcing has a ton of value across the industry. I think it just depends on what you believe as a  company or what some of your core competencies are and what are not. If there’s areas  that are core competencies that you excel in, there’s something proprietary, that’s  something you believe you can build in, else I wouldn’t outsource.  

If there’s other areas where you believe you need expertise, you really feel like some of  these tasks are going to be fairly expensive for your team and you could benefit from outsourcing, I think that’s where companies, whether you’re healthcare or not, or even in engineering, can you can really see value in it? I think that’s one of the things that companies should try to consider when they make this decision.  

Ratnadeep Bhattacharjee: Let’s let’s talk about DocNexus a bit. So DocNexus is harnessing the power of AI to draw insights from a massive corpus of scientific texts,  clinical trials, and more of these, all in seconds. Can you tell us about a real life situation where DocNexus made a tangible difference in healthcare delivery or patient outcomes? And how do you think this rapid excess of information will shape healthcare in the days to come?  

Mahek Chhatrapati: We recently worked with a client across the Alzheimer’s landscape. One of the instances that we saw was Alzheimer’s drugs hadn’t changed in the past 20-25 years. So this is where new drugs are coming to market. It’s harder to measure impact directly across patients. It’s more across “How to get patients access to the right drugs that they need?” and so we’re very upstream of the patient journey.  

We’re at the stages of where companies are coming about. They are actively working  on a product that’s either going through clinical trials, that’s about to go through clinical  trials, that’s about to get FDA clearance, and they’re trying to talk to healthcare  providers across the ecosystem. Whether it’s healthcare providers in India, Asia, Europe  or US, they’re trying to figure out who’s the right healthcare provider that’s going to really support my product all the way through to launch? Or even once the products launch, how are they going to get this in the hands of patients better? 

So one instance that we saw was a large pharmaceutical organization that came to us.  They wanted to figure out who the top experts were across the Alzheimer’s landscape.  We helped determine who these experts were, how they go about engaging with them.  And then we would track every single piece of information about these healthcare  

providers, what are they publishing about, what trials are they actively working on,  which other pharmaceutical organizations have they received payment from, are they any competing interests, and what are they doing across the social media landscape as well.  

Then we even look through claims. We’d look through information on what type of patients are these physicians treating in aggregate? Are they usually treating folks with  Alzheimer’s or dementia or a mix of things from that perspective? Then we would  provide, “Okay, these are some of the experts you should be talking with as you bring  this new product to market because they would have a lot of valuable insights.” And so I think this is where the use cases knowledge graphs are going to become immensely more valuable. Because it’s that physician or even in this case, let’s say it’s a medical concept that’s the center. Alzheimers.  

You now figure out in that inner circle who are the top experts that are globally or nationally known. You can even go regionally and then you can break down locally.  Every market is very different. If someone’s treating me in Iowa versus someone’s treating me in Seattle, I’m gonna go see a very different position. I want to get the best treatment options, who should I be seeing?  

You look at that physician in Iowa or even in Seattle, now you want to figure out what other types of patients are they treating. What are they actively working on? Are they active within academic research? Are they big within industry? Are they getting payments from large pharmaceutical organizations? And how does that tie you? So that’s the picture that we gather at DocNexus.  

Ratnadeep Bhattacharjee: It’s a great product I must say, Mahek. You’re doing great things for healthcare. As we delve into the future I’m sure our listeners are curious about what a world with even tighter integration between AI and Healthcare might look like from where you stand? Mahek, can you share a surprising or counter-intuitive prediction  you may have about the future of AI in Healthcare?  

Mahek Chhatrapati: Across the healthcare landscape, things take time. It’s not going to be where everyone’s talking about ChatGPT, talking about large language models.  We’re talking about implementation. We have to keep in mind that a lot of healthcare 

institutions still use fax machines. We’re still operating in a world that is compliant heavy. It’s going to take years and years before we see a lot of adoption of these models.  

Physicians, surgeons, and a lot of these people aren’t going away. I don’t think healthcare is going to like be a place where jobs are going to be eliminated. I think people are just going to be a lot more efficient. A lot of these tools are going to hopefully help physicians. I think a lot of people think that, “Oh I can use ChatGPT to diagnose my medical conditions. I don’t need to go see a surgeon or a physician.” That’s not the world we’re gonna be in any time soon.  

I think we’re going to be in a world where people even physicians may use these large language models on a regular basis to potentially add to their spectrum of, “Oh these are some additional diagnoses that the patient may have right.” and so that’s the world we’re probably going to be in in the next three to five years, and that’s going to continue developing. And these tools are going to help both patients and physicians long term.  

Ratnadeep Bhattacharjee: I think this is an interesting point that you’ve put across. On similar lines I would say partnerships will play a vital role in this AI Empowered  Healthcare landscape. From your viewpoint, what’s the blueprint for an ideal symbiosis between AI innovators like DocNexus and healthcare providers? How can we create a  supportive and productive ecosystem in this dynamic field?  

Mahek Chhatrapati: I guess between us and more so healthcare providers, the best way to bridge this relationship or the world between healthcare providers and life science firms, is where some healthcare providers are really excited about engaging with pharma but they’ve never engaged with pharma in the past. So they may have developed a ton of expertise across diabetes or Alzheimer’s or specific type of cancer within oncology. So we’re trying to really bridge that Gap.  

We’re trying to get physicians to actually highlight what their field of expertise is based off public data. Also looking through claims data, figure out, “Okay this is the level of expertise for that physician” and then figure out what healthcare provider like or what life science firm is kind of in that cycle. A lot of life science firms are in very different cycles  in terms of drug development. Some products get through clinical trials and phase one,  some get through phase two, some of them like don’t. So trying to figure out what that  right match is between the product that’s getting developed and what type of physicians  are actually treating patients, that’s the bridge that we’re trying to really fill. 

Ratnadeep Bhattacharjee: As we close this enlightening conversation, could you point our listeners to a source that has profoundly influenced your views on AI in Healthcare?  And one parting piece of advice for our listeners to help them navigate this landscape better, the AI centric future of healthcare. So what would be your take on that?  

Mahek Chhatrapati: I can’t point to one specific source. I think there’s a ton of podcasts. There’s a lot of information I personally even use, like ChatGPT regularly, just ask it questions. Whether it’s personal or professional questions, you can use it on a  regular basis and get a lot of insights from there. And then I think as listeners, think about the future of healthcare as we’ve seen in the last year and a half to two years,  we’ve seen it rapidly develop. It’s going to continue to do so. There’s a lot of concerns,  there’s a lot of information that probably still hasn’t been figured out. Compliance, a lot of these things are going to come into play in the near term. We’re going to start seeing this over the next couple years as well.  

I think the one piece of advice I have for the listeners is just be curious. Read as much  as you can about ChatGPT or large language models. Start practicing, try getting into  the tools, whether it’s getting into GPT-4 developer platform, whether it’s downloading the app on your iPhone, try asking any questions. That’s where the models are going to continue getting refined over time. And I think one of the things that we are going to see and I didn’t highlight this before, is we’re going to see a world where hopefully the power of users feedback may improve.  

I think that’s one of the things as these models develop, people are going to say, “Okay,  this is great, ChatGPT this is not great, and that.” Feedback is going to continue refining these models for millions of people and so hopefully everyone out there gets involved,  gets practical, learns. If you have new recommendations feel free to share them with your friends, your peers, and your family, because that’s going to not only make them but yourselves more educated.  

Ratnadeep Bhattacharjee: Well there we have it folks, a truly enriching conversation with none other than Mahek. We have journeyed through the transformative power of AI band advanced data analytics in healthcare, exploring the challenges, ethical considerations, and the vision for a future where technology and healthcare are even more closely interwoven.  

From today’s discussion it’s clear that the marriage of healthcare and AI is not only  inevitable but also crucial in driving patient outcomes and transforming healthcare 

delivery. It’s not every day that we get insights from someone who is at the forefront of such an exciting and important transition. A big thank you Mahek. I think sharing your  insights, and predictions, your work at DocNexus continues to inspire us and give us a  glimpse of the exciting possibilities ahead.  

Remember in this fast evolving digital landscape, it’s conversation like these that keep us informed, challenges our perspectives and ignite our imaginations. Thank you for all for joining us in today’s episode. We look forward to bringing you more thought  provoking discussions in the future. Until next time I am your host Ratnadeep signing off, thank you.