12 - 14 November, 2019 | Germany

Main Conference Day 1

9:00 am - 9:15 am Chairman's Welcome & Icebreaker

9:15 am - 9:55 am Towards Models of Prospective Curation in the Drug Research Industry

  • Discuss drug industry data management - knowledge persistence and knowledge vigilance
  • Apply ontologies and machine learning-based approaches to deliver a much needed change
  • Improve your software design approaches in order to make the process of data and knowledge acquisition more attractive and empower scientists to do more

9:55 am - 10:40 am CASE STUDY: Parasite Counter: A Machine Learning Case from Vet Pharma

  • Learn how to integrate machine learning into your data strategy
  • Empower your research with machine learning technologies
  • Take action from insight

10:40 am - 11:10 am Networking Coffee Break

11:10 am - 11:50 am Data Intelligence in Pharma R&D: Semantics meets Analytics

  • Discover why, in complex scenarios, information is much more a “knowledge graph” than just a bunch of tables
  • Learn how data intelligence is coming together of “Semantics” (Ontologies) and analytics
  • Understand how with semantic underpinning, the investigative analytic UI can automatically suggest connections in dashboards and graph/link analysis 

11:50 am - 12:30 pm Data Quality-Defined Analytics Processes for Drug Development

  • Define your unique process and analytical variability quality challenges
  • Advance your predictive modelling with lessons learned from the Centre for Process Analytics & Control Technology
  • Discuss strategies to improve your data visualisation

12:30 pm - 1:30 pm Networking Lunch Break

1:30 pm - 2:10 pm Blockchain Use Cases in Pharma

  • Ensure authenticity of health records and protocols on record sharing
  • Eradicate fraudulent altering or modification of patient data and clinical trial data
  • Empower research and accelerating collaboration across the board in order to ensure adoption

2:10 pm - 2:50 pm CASE STUDY: Applied A.I. in Clinical Development

  • Analyse why AI should be implemented in clinical development
  • Discover the key obstacles to deploy a production-level AI in drug discovery
  • Examine examples of successful AI applications in drug discovery and patient stratification

2:50 pm - 3:20 pm Networking Coffee Break

3:20 pm - 4:00 pm Toward a Company Wide Data Infrastructure

  • Foster a productive culture of collaboration across departments
  • Develop your own non-competitive way to stay ahead of the curve
  • Implement a data strategy that factors in contractor obligations and market access

4:00 pm - 5:00 pm Panel Discussion: Integrating Innovation into your R&D Strategy

  • What is the best strategy to begin integrating M.L., A.I. & Blockhain into you company
  • Is it only R&D – opening and learning from collaboration externally and internally
  • Where is the proof - ROI or buzz words? 

5:00 pm - 5:30 pm Chairman's Closing Remarks