Bikalpa Neupane, Head of AI and NLP at Takeda, discusses the challenges of siloed data and trust in data science processes in life sciences. Topics include enabling data science in healthcare, centralizing and integrating healthcare data, the importance of trust in drug discovery, and exploring generative AI models in research.
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Quick takeaways
The challenges faced by life sciences leaders in data science include the need for robust data foundations, data governance, and quality control.
The complexity and diversity of healthcare data create challenges in enabling data for downstream data science and analytics activities, requiring the bringing together of diverse data from various sources in a unified manner.
Deep dives
Challenges in Data Science in Life Sciences
In the podcast, Bacalpa New Payne discusses the challenges faced by life sciences leaders in terms of data science. He highlights the need for robust data foundations, data governance, and quality control. He also emphasizes the challenges of reproducibility and scalability. Bacalpa specifically focuses on the technical and operational challenges within the industry.
Complexity and Diversity of Healthcare Data
Bacalpa highlights the complexity and diversity of healthcare data as a major challenge. He explains that the diversity of data sources, including clinical data, experimental data, patient data, and more, creates complexities in enabling the data for downstream data science and analytics activities. The challenge lies in bringing together diverse data from various sources in a unified manner.
The Importance of Trust in Data Science
Trust plays a crucial role in data science practices within the life sciences. Bacalpa emphasizes the need to establish trust within the life sciences community and among external stakeholders. He discusses the challenges of aligning the perspectives of scientists and technologists in terms of data and AI. Bacalpa also highlights the significance of trust in ensuring ethical practices, mitigating biases and discriminations, and building trustable insights and results.
Today’s guest is Bikalpa Neupane, Head of Artificial Intelligence and Natural Language Processing at Takeda. He joins us on today’s program to discuss how siloed data and trust in data science processes are among the biggest challenges facing life sciences leaders and the promise of new use cases and generative AI tools in confronting those challenges. If you’ve enjoyed or benefited from some of the insights of this episode, consider leaving us a five-star review on Apple Podcasts, and let us know what you learned, found helpful, or liked most about this show!
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