In the ever-disruptive space of Data Science, Life Science and Analytics, it is important to keep up with the latest trends and developments in the industry. In an effort to keep the audience engaged and updated, Fractal frequently hosts a series of podcasts with veterans of the data science industry. Sagar Shah, client partner at Fractal, invites Suman Giri, Global Head of Data Science & Analytics at Merck, for an enlightening conversation on the podcast to discuss the latest trends entering the space, the impact of the COVID-19 pandemic. Pharma industry, and more such burning topics.
Here are excerpts from the talk in the leader’s own words for all of you listening to the Fractal Podcast and taking notes.
Excerpts from the Fractal Podcast
Sagar Shah: How is the pharmaceutical industry affected by today’s volatile economy?
Suman Giri: Well, not to the extent that other industries are! First of all, with few exceptions, drugs are fairly ineligible. People will keep getting sick, so demand isn’t as much spending power as it might be in other sectors. If anything, because of Covid, some pharmaceutical companies did pretty well, as we all know. I believe last week I heard that the SAP index is down 20% over the past year, but the Pharma index is up 3%. While Merck stock is up 30%, it gives you an idea of how we perform in relation to the general economy. Much of the positive investor outlook on our company has been driven by our strong products and pipeline.
Sagar Shah: How is AI Analytics helping to increase competitive advantage at work?
Suman Giri: We use data science in every product lifecycle phase, from research to manufacturing and commercialization. Therefore, data science is critical in understanding the diseases we treat and their prevalence, creating personalized medicine strategies, and increasingly how we design and develop new drugs. For in-line products in the commercial space where we operate, there is a lot of sophisticated data science that happens today, especially as it relates to forecasting, calculating the impact of commercial marketing, reviewing promotional materials for compliance, Analyzing competing threats, and creating personalized engagement strategies for healthcare professionals to create awareness about drugs and their benefits. There are also some use cases such as automated data matching, rare disease patient search, and more where machine learning and analytics have been highly leveraged.
Sagar Shah: How are you developing careers for your teams in AI and Analytics?
Suman Giri: We are thinking about talent retention! Our competitive advantage in the general market is our continued focus on impact. We know that analytics and data science people today have options; They could work anywhere as every industry and every company needs data science talent. But will you use your skills to make bottles more colorful or save lives? So it is valid proposition with which to focus on the ‘why’ of what we do. But we are also mindful that impact is just one aspect, and we are ensuring that our talent pool is mostly mobile so that they can move across different verticals and perform well for the business. We currently have a partnership with Analytics Vidya. We are providing opportunities for growth in both management and technical areas. We also encourage participation in a variety of things, such as creating accelerators and partnerships with other universities and capstones. We want to make this a fun and satisfying place to work.
Sagar Shah: What challenges are you currently facing in building a successful analytics team?
Suman Giri: It’s mostly talent! Commercial fund analytics needs both technical and domain expertise; It’s a rare unicorn pool of talent that we’re looking for, and people want to feel like they’re a part of the community, that they have a growth map, and that they can do the work they do and the way they want to do it. He has a say in that. So, we are conscious of it. Most of our time as a leadership team is spent on how do we build a structure that enables all these different aspects at scale, and I believe that’s the hard part.
Sagar Shah: What new data sources will help pharma, especially Merck, in the coming few years?
Suman Giri: We’re so focused on this impact that one data source that we can leverage a lot is the Social Determinants of Health (SDOH), which helps advance health equity and really This ensures that our products have the effect they are intended for. So, there’s a lot of work around that! Tokenization is a new construct within commercial and syndicated datasets that allows you to match your consumer activity with your claims data with LCP engagement data. Companies like LeeBrand and DataVant are working in this area and enable you to do many more interesting things with existing data that you would not normally do otherwise. We’ve also seen a lot of imaging and lab data on the business side; There are probably use cases that can be dealt with through them. Finally, I am very excited about the potential and potential of synthetic data as it enables scale in areas that do not have data and also has privacy-preserving implications. In addition to the data you can buy, buy, and generate, synthetic data is something I’m excited about.
Sagar Shah: How will analytics and AI change the pharma industry in the next few years?
Suman Giri: We have heard about the ‘Alpha Fold’ work front deep mine. So, they took this protein folding problem, which was a part of drug discovery, and solved it in a big way. Now the next frontier is protein binding, like what are the candidate proteins that the drug can bind to. I believe this will be the next holy grail as far as the potential of AI is concerned in the pharma industry, especially drug discovery. Again on the commercial side that we represent, there is a lot of potential for us to look at the work that has been done over the last several years in a very specific way and use all the new technological advances in AI. All of these advances could potentially revolutionize how we’re doing things a little less efficiently or with less precision and take them to the next level so we can actually get the effect we know we have. We can do it.
Sagar Shah: How has your AI journey been for the past decade?
Suman Giri: I studied Data Science and Machine Learning as a part of my undergraduate education and majored in Mathematics. During thesis, my research focus was on energy disaggregation. I focused on taking a single-source, multi-channel signal and separating it into separate sources. I was looking for an industry where I could use my skills and make an impact. I’m big on working on meaningful problems, and healthcare seemed like a good place to explore. I landed in the insurance sector and worked at Aetna; Then, I moved to Highmark, a coworking provider that gave me a good vantage point about the healthcare ecosystem. I’ve been going to consulting for a while, again in a data science role, so I can understand how the industry functions. For the past 2 years, I am in Merck as it was an industry I didn’t have enough experience for, and Life Sciences is the current domain I am working in. Overall, I have made a career out of navigating. US healthcare ecosystem and using data science to make things better and make a greater impact.
Sagar Shah: What excites you every day?
Suman Giri: Apart from the potential of the things I do, making sure someone is getting the treatment they need and adding years to their life is a huge motivator for me. Even when I’m feeling a little down, the power of circumstance helps me stay motivated. If I were to pinpoint the exact thing that excites me, it would be the ability to build and design systems of that scale. Pharma, naturally, because of the different therapeutic areas we work in, a system has been created to measure the same questions that are asked in different therapeutic areas and in different markets. Working with some of the smartest people I know to build systems that can truly scale is what keeps me excited.
Sagar Shah: What future trends can be felt in the next 5-10 years?
Suman Giri: It has to be Web 3.0 because it’s first-party data, mainly from a privacy-preserving data perspective. I’m a big believer in the Web 3.0 scenario. Commercial organizations, especially those that rely on syndicated data, will need to be adaptable in how they build a first-party data strategy. The metaverse is big again, and I don’t know if anyone is aware of it, but in the next 5-10 years, we’ll see the first few tangible use cases. In the next 5-10 years, quantum computing will start to see problems that are not possible with our computing power today. One trend I’m looking forward to and rooting for is responsible and sustainable AI being a part of our conversation and a part of the process we follow as we build and expand our use cases. Huh.
Thank you Suman, for sharing your time and insight on the Pharma industry. We are thrilled with your enthusiasm and can’t wait to see how the Metaverse and AI will expand their role in the pharma industry.
We hope you all got a holistic view about the Pharma industry and how AI plays a major role in the transformation of the industry. See detailed fractal post here. Suman Giri highlighted the importance of data science and how it helps in understanding various diseases and create personalized strategies to create medicines to treat diseases. We would love to have your thoughts on AI, Analytics and Pharma industry collaborations. So, please comment below and share!