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Harnessing AI To Expedite R&D

Resource Tag: Harnessing AI To Expedite R&D

Agentic AI: Perspectives in the Pharmaceutical Industry

Join us for an insightful webinar exploring the transformative potential of Agentic AI across the pharmaceutical landscape. Featuring expert speakers from across the ecosystem — including pharma, solution vendors, publishers, and data governance leaders — this session will delve into real-world use cases, as well as the technical and business challenges shaping adoption. Gain diverse perspectives on how Agentic AI is redefining drug development, accelerating regulatory document creation and data stewardship, and discover the opportunities and risks that lie ahead for the industry.
 

Agenda
  • Introduction – Rob Gill, Pistoia Alliance
  • Agentic AI Technology and Use Cases – Dr Nicole Mather & Dr Daniel Ehmann, IBM
  • Content and Semantic Technologies: Foundations for Agentic AI – Joseph Mullen, Scibite
  • Data Importance in Agentic AI – Ian Harrison, Amino Data
  • A Pharma Perspective – Chaithanya Bandi, Genentech
  • Panel Discussion
Speakers
  • Nicole Mather, Life Sciences Lead, Health Data & AI Lead, IBM Consulting, UKI & EMEA
  • Daniel Ehmann, Global Tech Lead, Agentic AI Apps, IBM
  • Ian Harrison, Senior Data Architect, Amino-Data
  • Chaithanya Bandi, Senior Principle Applied Scientist, Genentech
  • Joseph Mullen, Product Director, Software Solutions, Scibite

Accelerating Preclinical Drug Discovery with Agentic AI

Inside Bayer’s PRINCE Multi Agent System

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.

Beyond the Hype: Real-World GenAI Use Cases in Discovery Science

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:

  • Learn which genAI use cases already deliver value across early discovery workflows and which remain aspirational
  • Understand the foundational infrastructure, data strategy, and talent needed to support genAI at scale
  • Get a realistic view of genAI’s limitations and what to watch for as the technology matures

How To Accelerate Biopharma Research With AI Scientific Assistants

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.

AI-Ready Data and Why FAIR Data Matters in Life Science Companies

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:

  • Why many AI projects are still fundamentally reliant on robust data management
  • How FAIR Data complements LLMs through explicit semantics and structure
  • The critical role of data quality and governance in AI success

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.

Speakers
  • Angelika Fuchs, Roche, Chapter Lead, Data Products & Platforms
  • Martin Robbins, Ontoforce, Product Manager
  • Tom Plasterer, XponentL Data, Managing Director, Knowledge Graph & FAIR Data Capability
  • Ted Slater, EPAM, Managing Principal, Scientific Informatics Consulting

Hosted by Giovanni Nisato, Project Manager, Pistoia Alliance

Unlocking Value in Pharma with Knowledge Graphs and the Semantic Layer

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.
 

Speaker

Thomas Woodcock, PhD., Technical Sales Manager, Scibite

Next Gen Technology for Next Gen Trials

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

AI for Drug Discovery in 2025

A view from the industry-academia interface

Pistoia Alliance 2025 London conference presentation by Prof Conrad Bessant, Queen Mary University of London

Leveraging AI for Enhanced Ontology and Terminology Development

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.

Speaker

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.