Congress Themes

Following extensive research with the Lab of the Future Community, the USA multi-track congress program includes case studies and use cases from exciting start-up biotechs, insightful sessions on collaborative research partnerships and discussions on how to address the challenges of onboarding novel technologies in research, development, and manufacturing.


Keynote sessions will discuss the major challenges being faced by the biopharma sector in driving scientific innovation. Key themes to be discussed include digital transformation, change management, lab automation, cross-stakeholder collaboration as well as the latest breakthroughs in scientific research.

Alongside this, we’ll discuss the new and emerging technologies with potential for impact in the drug discovery and development space and how we can effectively integrate these tools within the enterprise. Featured technologies will include generative AI and large language models, intelligent laboratories and robotics, AR/VR, cloud, LIMS as well as digital therapeutics and novel large molecule modalities.

Data Strategy:

Data strategy comprises generating and optimizing methods to store, access, standardize, analyze and share data generated within the drug discovery pipeline. This track will cover centralization of data within a cloud environment and improving data accessibility and sharing using the cloud. Discussions will also examine how to manage the growing volumes of data generated through knowledge graphs and data lakes, ensuring data is FAIR and data security in an increasingly digital environment.

  • Data management platforms, LIMS
  • RWD and RWE
  • Data sharing
  • Cybersecurity


  • Kam Chana, Director, Computational Platforms, Merck 
  • Mimika Koletsou, Director of Informatics, Kinnate Biopharma
  • Jennifer Heymont, Associate Director, Scientific Informatics, Eisai US 
  • Cindy Novak, Associate Director, R&D Systems, Avidity Biosciences 
  • Christopher Perkins, Director Labs IT, Flagship Pioneering
  • Cailin Kelly, Director, Global consent and Data privacy Strategy, Bristol Myers Squibb


Artificial intelligence and machine learning are rapidly being integrated into the drug discovery pipeline to improve efficiency and reduce workload for scientists. The track discusses how large language models, natural language processing and text-mining are being harnessed by scientists, and highlights AI-driven platforms that are aiding target identification and optimization, patient stratification and beyond.

  • LLMs
  • Generative AI
  • NLP
  • Distinguishing realistic applications from the AI hype


  • Bino John, Global Team Leader, Director, Data Science and AI, AstraZeneca
  • Yves Fomekong Nanfack, Head of End to End AI Foundations, Large Molecules Research Platform, Sanofi
  • Brian Martin, Head of AI in R&D Information Research, Research Fellow, AbbVie
  • Alison Jones, Senior Director, Chemistry, Charles River Laboratories 
  • Patrick Schwab, Senior Director, AI and ML & Head, Biomedical AI Group, GSK
  • Pat Walters, Chief Data Officer, Relay Therapeutics
  • Clement Chatelain, Head of Human Genetics and Genomics, Sanofi
  • Thras Karydis, CTO, DeepCure

Lab Operations:

Creation of a physical and virtual infrastructure that allows scientists to innovate across the value chain. The track will feature discussions on new developments in lab build and design, lab asset management, application of sustainable working practices in the lab, cross stakeholder research partnerships and use of digital technologies within the lab environment.

  • Asset Management
  • Workspace design
  • Sample tracking
  • Sustainability


  • Nivetha Paterson, Head of Scientific Services, Sanofi
  • Joseph Pease, Senior Director, Genentech
  • Richard Caron, Sr. Director, Digital QMS and Laboratory Systems, Moderna
  • Sally Madden, Bioinformatics Software Engineer, Genentech
  • Emrah Sueruen, Senior Market Solutions Manager, R&D Solutions, Roche
  • Stefan Datz, Head of R&D Services, Roche Diagnostics

Digital Transformation:

Digital transformation is transforming the way research is carried out in the lab. This track will feature new and emerging platforms and technologies that will facilitate digital transformation of the lab. Other areas of discussion include digital health solutions, applications of real world data, wearables and remote patient monitoring, the use of AR/VR, as well as the skills, people and culture required to achieve successful transformation.

  • AR/VR
  • Wearables
  • Virtual trials
  • Digital transformation journeys


  • Pamela Sepulveda, Director, Digital Strategy, Pfizer 
  • Jennifer Perkins, Data Sciences Project Manager, Pfizer
  • Greg Moody, VP Research and Development IT, Biogen
  • Alex Zhavronokov, CEO, Insilico Medicine 
  • Mohit Agnihotri, Senior Director, Development Sciences Data & Digital Strategy, AbbVie
  • Jordan Stobaugh, CMC Scientific Architecture Lead, AbbVie
  • Steve Prewitt, SVP Global Head of Digital Innovation, Sumitovant Biopharma

Automation and Robotics:

Automation of instruments and workflows to improve efficiency and accuracy, is becoming widespread throughout the industry. This track will discuss automating laboratory workflows through discovery and development, the application of robots, cobots and mobile technologies and the impact of automation on QA and QC processes. As well as the power of digital twins and AR/VR in both R&D and manufacturing for process optimization.

  • Digital Twins
  • Self-driving labs
  • Automated labs, CMC and manufacturing
  • Intelligent robotics


  • Joseph Pease, Senior Director, Genentech 
  • Mary Belfast, Automation Manager, Teva Pharmaceuticals 
  • Mike Berke, Director, Research & Automation Technologies, CRADI, Amgen 
  • Amandeep Nijjar, Associate Director, Sample Management, Cytokinetics
  • Daisy Flemming, Data Engineer, GSK

Interoperability and Connectivity:

In an increasingly collaborative scientific environment, interoperability of systems and connectivity within and between organizations is more important than ever. This track discusses the data platforms and technologies which can allow data sharing, methods to ensure safe and secure data transfer and storage, standardization of data to allow sharing and reuse, and case studies of successful collaborations.

  • Data Standards
  • Cloud
  • Collaborative science
  • Data sharing platforms


  • Patrick Leblanc, Director Business Relationship Management, Regeneron Pharmaceuticals 
  • John Boles, IT Director, Molecular Data Integration, Janssen

Scientific Innovation:

Scientific innovation is the driver of novel therapeutics, and covers everything from new modalities and personalized therapies, to new screening techniques and testing methods. Also covered are the new and emerging technologies facilitating these innovations, by allowing the exploration of greater chemical and molecular space, or increasing efficiency and accuracy of early research processes.

  •  Cell and gene therapy
  • Personalized Medicine
  • Digital Therapeutics
  • Organoid and Organ-on-a-Chip models


  • John Baldoni, ATOM Consortium
  • Alexander Finlayson, CEO, Nye Health 
  • Roxanne Kunz, Process development Principal Data Scientist, Amgen 
  • TJ Cradick, CSO, Excision BioTherapeutics 
  • Emanuele de Rinaldis, VP, Global Head of Precision Medicine and Computational Biology, Sanofi