Meetu Arora — Updated On December 6th, 2022
Artificial Intelligence Data Science Healthcare Researchers & Scientists


In a continually disruptive space of data science, life sciences, and analytics, staying abreast with the newest trends and happenings in the industry is vital. In an endeavour to keep the audiences engaged and updated, Fractal hosts a series of podcasts frequently with the mavericks of the data science industry. Sagar Shah, the Client Partner at Fractal, invited Suman Giri, the Global Head of Data Science & Analytics at Merck, for an enlightening conversation over a podcast to discuss the newest trends penetrating the space, the effect of the covid-19 pandemic on the pharma industry, and more such blazing topics.

Here are a few excerpts from this conversation in the leader’s own words for you all to listen to the Fractal podcast and take notes.

Excerpts from Fractal Podcast

Sagar Shah: How is the pharmaceutical industry affected by today’s volatile economy?

Suman Giri: Well, not to the extent that the other industries are! Firstly, barring a few exceptions, drugs are fairly inelastic. People will continue to get sick, so the demand isn’t as much a function of spending power as it might be in the other sectors.  If anything, because of covid, some pharmaceutical companies did fairly well, as we all know. I believe there were some numbers I heard over the past week that the SAP Index is down by 20% over the past year or so, but the pharma index is up by 3%. This gives you a sense of how we perform concerning the general economy. Most of the positive investor outlook on our company has been driven by our strong products and pipeline.


Sagar Shah: How is AI Analytics helping drive competitive advantage at work?

Suman Giri: We use data science in every product lifecycle stage, from research to manufacturing and commercialization. So, data science is crucial in understanding the diseases we treat and their prevalence, creating personalized medicine strategies, and accelerating how we design and develop new drugs. For in-line products in the commercial space, which is where we operate, there is a lot of sophisticated data science that takes place today, especially when it pertains to forecasting, calculating the effect of commercial marketing, reviewing promotional content for compliance, competitive threat analysis, and in creating personalized engagement strategies for healthcare professionals to make them aware of the drugs and their benefits. There are also some use cases like automated data matching, rare disease patient finding, and more where machine learning and analytics have been heavily leveraged.


Sagar Shah: How are you developing careers for your teams in AI & Analytics?

Suman Giri: We are thinking hard about talent retention! Our competitive advantage in the general marketplace is our relentless focus on impact. We know that analytics and data science folks today have options; they could work anywhere because every industry and every company needs data science talent. But would you rather use the skills you have to make a bottle more colourful or to save lives? So that is the valid proposition with which we focus on the ‘why’ of what we do. But we are also mindful that the impact is just one aspect, and we are making sure that our talent pool is mostly mobile so that they can move across different verticals and have good exposure to the business. We have a partnership with Analytics Vidhya right now. We are also providing growth opportunities at both management and technical tracks. We also encourage participation in various things, like building accelerators and partnerships with other universities and capstones. We want to make it a fun and fulfilling place to work at.


Sagar Shah: What challenges are you currently facing in building successful analytics teams?

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 are after, and people want to feel that they are a part of the community, they have a growth map, and they have a say in what they work on and how they want to do it. So, we are mindful of that. Most of our time as a leadership team is spent on how we create a structure that enables all of these different facets at scale, and that is, I believe, the hard part.


Sagar Shah: What new data sources will help pharma, especially Merck, in the upcoming few years?

 Suman Giri: We are so focused on the impact that the one data source we could leverage a lot more is Social Determinants of Health (SDOH), which helps advance health equity and truly ensures that our products have the impact that they are intended to. So, there’s much work around that! There is a new construct of tokenization within commercial and syndicated datasets that allow you to match your consumer activity with your claims data with LCP engagement data. Companies like Liebrand and Datavant are playing in this space and enabling you to do many more interesting things with the existing data that you wouldn’t normally do otherwise. We have also seen a lot of imaging and lab data, even on the commercial side; there are probably use cases that can be tackled through them. Finally, I am very bullish about the prospect and the potential of synthetic data as it enables scale in areas that don’t have the data and also has privacy-preserving implications. In addition to the data you can buy, purchase and generate, synthetic data is something I am excited about.

Podcast | Suman Giri | Sagar Shah


Sagar Shah: How will analytics & AI transform the pharma industry in the next few years?

Suman Giri: We have heard about the ‘alpha fold’ work front deep mine. So, they took on this protein folding problem, a part of the drug discovery, and solved it at scale. Now the next frontier is protein binding, like what are the candidate proteins that a drug can bind with. I believe that will be the next holy grail as far as the potential of AI in the pharma industry, especially drug discovery, is concerned. On the commercial side again, which is what we represent, there’s a lot of potentials for us to look at the work we have done over the past so many years in a specific way and use all of the new technological advances in AI. All of these advancements can potentially revolutionize how we have been doing things slightly less efficiently or less accurately and take them to the next level so we can truly have the impact we know we can.


Sagar Shah: How has your AI journey been since the last decade?

Suman Giri:  I studied data science and machine learning as a part of my graduate education and majored in maths. During the thesis, my research focus was on energy disaggregation. I focussed on taking a single-source, multi-channel signal and disaggregating it into individual sources. I was looking for an industry where I could use my skills and create an impact. I am big on working on meaningful problems, and healthcare sounded like a decent space to explore. I landed on the insurance side and worked at Atena; then, I moved into Highmark, a peer provider that gave me a good vantage point regarding the healthcare ecosystem. I am moving to Consulting for a bit, again in the data science role, so I can understand how the industry functions. For the past 2 years, I have been at Merck because it was one industry that I didn’t have enough exposure to, and life sciences are the current domain I am operating in. By and large, I have created a career out of navigating the US healthcare ecosystem and using data science to make things better and have a greater impact.


Sagar Shah: What excites you every day?

Suman Giri: Apart from the potential of the things I do, ensuring that somebody is getting the treatment they need and getting years added to their lives is a big motivator for me. Even when I am feeling a bit down, the impact of the situations helps me stay motivated. If I were to pin down the exact thing that excites me, it would be the potential to build and design systems that scale. Pharma, by nature, because of the different therapeutic areas we operate in, is a system built to scale the same question that gets asked across different therapeutic areas and different markets. Working with the smartest people I know to build systems that can truly scale is what keeps me excited.


Sagar Shah: What future trends may be realized in the next 5-10 years?

Suman Giri: It has to be Web 3.0 as it is first-party data, primarily from a privacy-preserving data perspective. I am a big believer in the Web 3.0 landscape. Commercial organizations, specifically those that rely on syndicated data, will have to adapt to how they create a first-party data strategy. Metaverse is again big, and I don’t know if anyone realizes but in the next 5-10 years, we will see the first few tangible use cases come through. In the next 5-10 years, Quantum Computing will start seeing problems that aren’t possible today with our computing power. One trend I am hoping big on and rooting for is responsible and sustainable AI being a part of our conversations increasingly and a part of the process we follow as we build and extend our use cases.

Thank you, Suman, for your time and sharing insights on the pharma industry. We are enthralled by your enthusiasm and can’t wait to see how Metaverse and AI will extend their role in the pharma industry.


We hope you all got an overall view of the pharma industry and how AI plays a major role in the industry’s transformation. Watch the detailed Fractal post here. Suman Giri highlights the importance of data science and how it helps to understand various diseases and create personalized strategies to create medicines to treat ailments. We would love your thoughts on the collaboration of AI, analytics and the pharma industry. So, please comment below and share!

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