Generative AI in Life Science: Building Production Ready Solutions
This talk presents a comprehensive framework for implementing enterprise‑scale generative AI applications in the healthcare sector. The presentation explores the evolution from traditional AI to modern generative models, highlighting how GenAI is projected to generate $60‑110 billion in annual value across the pharmaceutical industry. The talk covers critical aspects of production deployment, including multiple GenAI approaches (fine‑tuning, RAG, custom models), architectural considerations, and practical implementation strategies. It addresses key challenges such as data privacy, model hallucinations, and cost optimization while providing concrete solutions through LLMOps frameworks and robust governance structures. Special emphasis is placed on healthcare‑applications, including , while navigating regulatory compliance and ethical considerations. The presentation concludes with a practical roadmap for scaling GenAI solutions from proof‑of‑concept to production, ensuring responsible AI deployment within healthcare’s stringent requirements.
About the speaker
Shravan Koninti
Associate Director – DSAI at Novartis
A distinguished Data Science leader with nearly two decades of experience, this professional has established himself as a pioneering force in pharmaceutical artificial intelligence and data science.
His career is marked by an impressive 11‑year tenure at Novartis, where he had held pivotal global roles that have shaped the company’s AI and data science initiatives. As a hands‑on technical expert, he possess deep expertise in various domains including predictive modelling, time series forecasting, Natural Language Processing, anomaly detection, and computer vision. Their recent focus on Generative AI and Large Language Models (LLMs) has led to innovative applications within Novartis’s Legal and Global Security teams, showcasing their ability to translate cutting-edge technology into practical business solutions. Beyond his corporate achievements, he had distinguished himself as a thought leader in the AI community, regularly speaking at industry events and publishing insightful blogs that bridge theoretical research with practical applications. His competitive spirit and technical prowess are demonstrated by his success as a Kaggle Champion, having secured top 10 rankings in various data science competitions and world championship events across different platforms. This leader’s unique combination of technical expertise, strategic vision, and practical implementation experience has established him as a respected authority in the field of Data Science and AI, particularly within the pharmaceutical and healthcare sectors.
His career is marked by an impressive 11‑year tenure at Novartis, where he had held pivotal global roles that have shaped the company’s AI and data science initiatives. As a hands‑on technical expert, he possess deep expertise in various domains including predictive modelling, time series forecasting, Natural Language Processing, anomaly detection, and computer vision. Their recent focus on Generative AI and Large Language Models (LLMs) has led to innovative applications within Novartis’s Legal and Global Security teams, showcasing their ability to translate cutting-edge technology into practical business solutions. Beyond his corporate achievements, he had distinguished himself as a thought leader in the AI community, regularly speaking at industry events and publishing insightful blogs that bridge theoretical research with practical applications. His competitive spirit and technical prowess are demonstrated by his success as a Kaggle Champion, having secured top 10 rankings in various data science competitions and world championship events across different platforms. This leader’s unique combination of technical expertise, strategic vision, and practical implementation experience has established him as a respected authority in the field of Data Science and AI, particularly within the pharmaceutical and healthcare sectors.
