Discover how Bayer and Thoughtworks co-developed PRINCE, a GenAI-powered research assistant that transforms preclinical drug development by streamlining data retrieval, regulatory drafting, and metadata reannotation—cutting manual effort by 90% and enabling faster, more compliant decision-making.
GenAI shows promise in drug discovery, but cutting through the noise to understand where it’s truly making an impact can be difficult. This webinar will focus on how genAI is being applied in practical ways today, from designing novel molecules to predicting toxicity and extracting knowledge from complex datasets.
Asha Mahesh from Johnson & Johnson will share what it takes to make genAI useful and usable in discovery science. Join the webinar to:
AI tools for supporting scientific research have come a long way over the past couple of years. From limited beginnings, they’re now able to play a key role in accelerating pharmaceutical research. But finding and using the right AI scientific assistant is still a minefield. In this webinar, Rob Brown, Head of Scientific Office at Sapio Sciences, looks at the advancements in AI scientific assistants and agentic AI, how these tools can be integrated into the research process, and what Sapio’s own AI scientific assistant, ELaiN, is capable of.
As life-science organizations race to adopt (generative) AI, one point begins to stand out: your AI is only as good as your data. While large language models (LLMs) offer powerful capabilities, they’re not tailored to specialized scientific data—and do need a solid data foundation. Making data Findable, Accessible, Interoperable, and Reusable (FAIR) enables AI systems to deliver more accurate, reliable, and cost-effective outcomes.
Key points include:
Whether you’re a data steward, scientist, or innovation leader, this session will help you get more perspective aligning your data and AI strategies for maximum impact. Join us on May 21 to explore why durable AI strategy needs a robust data strategy including FAIR Principles. Don’t let unstructured data hold your AI back—make it FAIR.
Hosted by Giovanni Nisato, Project Manager, Pistoia Alliance
Pharma organizations are swimming in data—but turning that data into actionable insight remains a challenge. This webinar explores how knowledge graphs (KGs), ontologies, and semantic enrichment create a semantic layer that connects and contextualizes pharma data to drive better decisions and more effective innovation. He will speak to the value knowledge graphs for boosting GenAI and share real-world examples.
Thomas Woodcock, PhD., Technical Sales Manager, Scibite
Pistoia Alliance 2025 London conference presentation by Mark Hahnel, VP Open Research, Digital Science
Pistoia Alliance 2025 London conference presentation by Dr. Karen Sayal, Senior Director in AI-driven Industrialised Clinical Translation, Recursion; Honorary NHS Consultant in Clinical Oncology
Pistoia Alliance 2025 London conference presentation by Prof Conrad Bessant, Queen Mary University of London
Pistoia Alliance 2025 London conference presentation by Brian Martin, Senior Research Fellow, Abbvie
2025 Pistoia Alliance London conference presentation by Miles Davies, CEO, Amino Data
In the rapidly evolving landscape of information science, the development and maintenance of ontologies and terminologies are critical for ensuring accurate data representation and interoperability across various domains.
This webinar aims to explore the transformative potential of artificial intelligence, specifically Large Language Models (LLMs), in streamlining and augmenting the creation of these essential knowledge structures. Attendees will gain insights into how AI can assist users in building comprehensive reference terminologies and ontologies more efficiently, thereby saving valuable time and resources. We will delve into early results from recent studies, demonstrating the practical applications and benefits of LLMs in this context.
Join us to discover innovative methodologies, share experiences, and discuss future directions for integrating AI into ontology and terminology development workflows.
This session is ideal for data scientists, knowledge engineers, domain experts, and anyone interested in the intersection of AI and knowledge management.
Simon Jupp, Head of Semantic Technology, SciBite
Simon is the head of Semantic Technology at SciBite, where he leads the development of CENtree, an innovative Enterprise Ontology Management solution. Simon’s interests are focused on how semantic technologies can be utilised to address the complex challenges of large-scale data interoperability. He is an expert in developing and applying ontologies within the life sciences and is advancing these technologies at Elsevier.
Pharma R&D is increasingly costly and the industry is looking to AI for productivity and ROI improvements. A critical bottleneck in early stage R&D is insight discovery. Huge amounts of researcher time is spent interrogating the literature to find biological connections and uncover new insights, Elsevier has a history of deploying AI to transform these tasks. Guy and Ivana will take you through recent innovations in this space as well as some of the key lessons we have learned.
