Advancing AI through Data Engineering in Pharmaceuticals
Sep 19, 2024
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In this engaging discussion, Catherine Shen, Executive Director at Merck, shares her impressive journey from luxury retail to pharmaceuticals, sparked by personal experiences. She delves into the critical evolution of data engineering, emphasizing AI's transformative role in the industry. Catherine highlights the importance of collaboration and innovative strategies in overcoming unstructured data challenges. Additionally, she reflects on leadership moments, confidence building, and the exciting future of data-driven healthcare solutions.
Catherine Shen's career transition highlights how personal experiences can uniquely influence professional paths in the biopharma sector.
The evolving role of data engineering in pharmaceuticals now emphasizes streamlined data preparation and automation for enhanced operational efficiency.
Deep dives
Catherine Shen's Journey to Pharmaceuticals
Catherine Shen's transition to the pharmaceutical industry was initially serendipitous, spurred by a personal connection to a medication that could help her mother with severe osteoporosis. This experience ignited her passion for biopharma, leading her to pursue opportunities that combined her prior background in luxury retail with her newfound interest in healthcare. Her career in the pharmaceutical sector has spanned over 18 years, during which she has held prominent roles that emphasized the significance of data and analytics in addressing patient needs. Catherine's journey highlights the impact personal motivations can have on career direction, illustrating how individual experiences can shape professional paths in unexpected ways.
The Evolution of Data Engineering in Pharma
In recent years, the pharmaceutical industry has increasingly recognized the critical importance of data engineering in driving insights and decision-making processes. Catherine notes that previously, data analysis was often prioritized over data preparation and automation, but a paradigm shift is underway where companies now understand the need for streamlined data cleansing and feature generation. At Merck, the implementation of diverse data product teams has led to an impressive increase in operational efficiency, enabling scalable insights across various therapeutic areas and markets. This evolution underscores the growing awareness within the industry that robust data engineering is foundational to leveraging data effectively and driving business success.
Innovative Data Solutions and Their Business Impact
Catherine describes a key innovative data solution implemented at Merck that focused on optimizing patient-level data analysis for rare diseases. Prior to this solution, data analysts spent a disproportionate amount of their time—up to 80 percent—preparing data for analysis rather than conducting actual analysis. The introduction of a common data model across various sources significantly reduced preparation time by 70-80%, allowing analysts to allocate more resources toward meaningful insights. This initiative not only enhanced efficiency but also established a scalable framework that could be applied to other tumor types, thereby maximizing the overall value derived from patient-level data.
Embracing AI for Enhanced Efficiency
AI has been a transformative force in Catherine's work, with its application spanning multiple stages of the data lifecycle. From automating data matching processes to enabling faster feature generation, AI augments human capabilities and enhances productivity. Catherine envisions that as technology continues to advance, organizations will increasingly invest in AI to streamline operations, which will lead to reduced labor costs and improved decision-making efficiency. She emphasizes the need to harness unstructured data to fully realize the potential of AI in the pharmaceutical industry, suggesting that overcoming challenges related to unstructured data will unlock new opportunities for innovation and effectiveness.
(00:00) Introducing Catherine Shen’s Career (00:32) Transition from Luxury to Pharma (01:55) Role of Data in Pharma (02:52) Evolution of Data Engineering (04:06) Innovative Data Solutions Impact (07:23) AI’s Role in Pharma Industry (10:24) Future AI Investments and Strategy (13:09) Solving Unstructured Data Challenges (14:02) Partnering with Math Company (16:44) Measuring Success in Partnerships (20:05) Pivotal Leadership Moments (23:22) Believing in Innovation and Confidence (25:29) Balancing Personal and Professional Life (26:12) Building Confidence Over Time (30:55) Creating Innovative Healthcare Collaborations (33:02) Confidence Grows with Tenacity (34:38) Excitement for the Future of Data (36:39) Catherine’s Closing Remarks
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