Interview with Christina Kim on advanced tech and pharma

Advanced Tech Transforming How Life Science Industry Functions

Part 2: Interview on the life science industry with Christina Kim, EVP Data Analytics, Omnicom Health Group  

Read how leaders in pharma digital and marketing discuss the new innovations that will transform the life science industry and its relationship with audeices. Despite the challenging conditions, leaders from the industry met virtually to learn and discuss the future of the industry. This meeting took place at Eye for Pharma Philadelphia 2020—the event has since become part of Reuters Events Pharma.    

In this interview, SciencePOD speaks with Christina Kim, EVP Data Analytics, Omnicom Health Group. Other interviews in the set include talks with Francesca Wuttke, Chief Digital Officer at Almirall and Haider Alleg, Global Head of Digital Excellence, Ferring.    

“Advanced technologies already transforming how pharma works and functions.”

— Christina Kim

What are the biggest challenges facing pharma in utilizing data in marketing?  

I want to start by thinking a little about how we got here. About 20 years ago every company was a software company. As a result, we’ve made some significant investments in shoring up our tech stacks to become software businesses. In the last decade, we’re now told that every company is a data company. We have businesses all over the world that are applying algorithms and formulas to figure out what data they need to bring to the table.  

Today, I would like to propose that every company is an impact company or a value company. With all of these tech investments that we’ve made, we have to start focusing on the right data and asking the right questions. The question for me is how do we decide what is impactful? One way to start is to start with the end in mind. Pharma companies have been and still are data companies. They’ve been using data to develop their products and apply a test/learn approach on what products to bring to market. 

Test and learn in the life science industry

Clinical trials are a classic example of test and learn. This phrase means the data requirements, inputs, and outputs, all of which are set up at the beginning. Similarly, we need to think about what we’re trying to achieve and test and learn from that approach for data in marketing. Once we identify this, we can be more thoughtful about layering in different kinds of datasets. Then we can think about how we actually test and learn and how we interpret the results delivered. Finally, we can optimise for greater impact. 

What are the most exciting opportunities to implement digital innovations such as AI in life science industry marketing?  

When I think about AI, it’s simply taking a test and learn mindset at scale. With AI and machine learning, we can apply algorithms to mine data at scale. We’ve seen it applied to public social conversations to better understand what our audiences are saying about their conditions and treatments so that our communications are more relevant. Another problem within healthcare marketing is data interoperability. 

With these advanced innovations, we are beginning to analyse and integrate data sets that were historically very much in silos and we can now be much more insightful about. For example, a treatment journey, from the moment a patient sees a physician to the continuation of their treatment post-diagnosis. We can also use AI to better understand what’s not always visible but influential, like culture. Ultimately, these types of advanced innovation help us to achieve precision marketing so that our communications are not just one size fits all. 

What simple business problems can be solved with advanced technology, transforming how the life science industry works/functions?  

We’ve seen some of these advanced technologies already transforming how pharma works and functions. For example, AI solutions have helped pharma companies more quickly identify the proteins in drug research. Advanced technologies and improvements in processing speed, storage abilities, and even APIs have enabled improvements in data mining and brought us even further along the curve in terms of interoperability. And these improvements in tech have accelerated precision targeting to effect more personalised content. It’s important to give all healthcare audiences access to the information they need and ultimately, to the products that are clinically appropriate for treatment.  

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