Unveiling Global Trends in Pharmaceutical Data Science: Insights from the PMSA Global Summit

The PMSA Global Summit was full of insights, informed expert leaders from Merck, Lilly, AstraZeneca, Novartis, GE Healthcare, Boringer Inglelheim, and their partners. As a data scientist participant, I took the opportunity to delve into the operations side of our work, saw early AI implementation reviews, and learned about the global pharmaceutical analytics workforce.

Several speakers acknowledged the geographic distribution of data science work, with a significant portion (50-60%) being undertaken in India, followed by Latin America (10-15%), and the rest remaining in the US. This underscores the global nature of pharmaceutical data science, and double underlines India's growing role.

Another key takeaway I noticed is the strategy of leveraging low/no code solutions for rapid insights. Taking the agile approach, transitioning dashboards from traditional programming/software development methods into off the shelf technologies, reflects a broader industry theme of providing “speed to insight.”  Another way to put this is, if you can buy it, do not build it.  

On the topic of AI, here’s what I noted:

• GenAI used to spot quality issues and insights in unstructured data
• Radiology and pathology are not losing their jobs, and instead AI is evolving the job to higher complexity
• AI should replicate what analytics pipelines already provide
• AI at Merck is about making an internal chatGPT for documents, and next having a chatbot to talk to your dashboards
• AI at AZ required the creation of Reliable AI markup language, RAIMLs.

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Many presenters noted the growing presence of engineers in senior leadership roles across the pharmaceutical sector. Predictions for the next 12 months suggest a shift towards valuing quality of insight over data availability.  This requires training for discernment in an era where information is abundant but not always meaningful.  I was struck by this as speed is our strength in HCP profiling, but it's our in-depth knowledge of Medicare claims data that brings clients to us – to help them understand complex questions related to regimen, dosage, titrations, and line-of-therapy, and switching patterns - that’s what powers CareSet’s differentiation. 

‍As a day one keynote speaker and as an IT New Delhi graduate, Jassi Chadha, CEO of Axtria, summarized decades of investment into Indian IT and data science personnel. 

“Don't come here for cost savings, as the costs are increasing 10% per year… come here for talent and premier experience."

As more companies add offices in India, he cited a trend among IT graduates.  Decades ago, top engineers mostly left, whereas now, only 5% of graduates leave India for opportunity.  This speaks volumes about the changing dynamics in global talent and opportunities distribution. He ended by foreshadowing that India can and will provide the best data science services to the world.  As an Indian-American, those words still stir.

The imperative: Global analytics teams must build trust. In context, cultural and linguistic differences exist everywhere, not just between EU, US, and India, for example, but also within India’s own dialects and cultures. How do you accomplish this?  Communicate values everywhere. The teammate fit is as important as performance, so only keep teammates who are trying to replicate skills and uphold the culture.  Wise words from a 10x leader.

In Part 2: ZS CEO keynote, career planning, global leadership and capacity, and more on AI.

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