How Knowledge Graphs Accelerate Drug Discovery in Biotechs

Life Sciences, Drug Discovery & Development,
  • Tuesday, September 27, 2022

The emergence of knowledge graphs, artificial intelligence (AI), machine learning and FAIR (Findable, Accessible, Interoperable and Reusable) data principles has created a unique opportunity within the biopharmaceutical industry to capitalize on the explosion of growth in data in the last 10 years. However, there remain significant barriers to adoption of these approaches, specifically in the biotech sector where there is a need to maximize cost effectiveness in choosing tools that get results fast and allow them to scale. There is a strong desire to investigate and leverage data science, AI and machine learning approaches in drug discovery and democratize insights across the organization. However, additional challenges need to be addressed, such as lack of FAIR data, access to necessary resources and skills and internal change management.

Attendees will gain insights into a unique knowledge management platform that harmonizes siloed, disparate data using a powerful data ingestion engine and underlying knowledge graph. The platform’s flexible user interface is customized to shield end-users from complexity which enables Aelin Therapeutics and e-therapeutics to democratize insights across their wider organization to support rapid, crucial research & development decision making to accelerate their drug discovery process.

In this webinar, attendees will hear from the CIO of Aelin Therapeutics, a biotech company that leverages targeted protein aggregation to develop a completely new class of therapeutics, aiming at hard-to-treat targets in cancer and infectious diseases, and the Head of Discovery Biology at e-therapeutics, a biotech company that integrates computational power and biology to discover life-transforming RNAi medicines. The featured speakers will discuss how they collaborate with ONTOFORCE, a Life Sciences technology company which transforms data into knowledge by unlocking hidden insights from data.

Register to learn how the adoption and usage of knowledge graphs, AI and machine learning approaches accelerates drug discovery.


James Longden, e-therapeutics

James Longden, Head of Discovery Biology, e-therapeutics

James Longden is head of Discovery Biology at e-therapeutics, a drug discovery company that combines GalNAc-siRNA therapeutics with computational modelling to better understand how protein interaction networks drive disease. His team is responsible for applying computational models to identify novel therapeutic targets and then validate them experimentally.

Prior to joining e-therapeutics, James worked in early drug discovery in both academia and industry. He spent over seven years at AstraZeneca performing small molecule and natural product hit identification and over four years at Cenix BioScience, a pioneer in the field of RNAi, performing target identification and mechanism of action screens. He then moved to academia, firstly as Associate Professor at the University of Copenhagen where his research was focussed on ‘big data’ biology and the use of machine learning to predict network changes driving cancer cell metastasis and drug resistance. From thereon, he moved to the University of Edinburgh applying the same network methodologies to motor neuron disease and multiple sclerosis research. He has a PhD in biomedical science from the University of Nottingham.

Message Presenter
Paul Vauterin, ONTOFORCE

Paul Vauterin, CIO, Aelin Therapeutics

Paul Vauterin holds a master’s degree and PhD in physics from the University of Ghent. In 1997, he co-founded Applied Maths, a company that became a global leader in advanced biological data analytics for bacteria. For 15 years he headed the company’s product development team. After this, he worked at the University of Oxford, developing advanced computational tools for the interpretation of large-scale full genome data for malaria research.

In 2014, he joined Multiplicom, where as VP Informatics he started a software unit and created CE-IVD approved SAAS software for the analysis and interpretation of the company’s human diagnostics assays based on next-gen sequencing. Subsequently, he moved to ONTOFORCE, a company developing an innovative data science software platform supporting drug discovery & development, and as SVP R&D he headed the company’s product development team. Paul Vauterin is currently CIO of Aelin Therapeutics, and is responsible for bioinformatics and data science activities, being crucial elements of the company’s drug discovery and development platform.

Message Presenter

Who Should Attend?

  • Drug Discovery Professionals
  • VP and Head of Data Science
  • VP/Director of Biology
  • VP/Director of Research
  • Scientists
  • Biologists
  • Bioinformaticians
  • Medicinal Chemists
  • Pharmacologists
  • Data Scientists
  • Drug Discovery Professionals
  • Research & Development Professionals
  • Artificial Intelligence/Machine Learning Professionals
  • CIO
  • CTO 

What You Will Learn

How a data science and computational strategy can deliver value in drug discovery and development and pioneer an end user approach

How barriers to data science adoption can be addressed and best practices for demonstrating the value to the end user — approaches to change management and measuring the impact of solutions

How ONTOFORCE’s knowledge management solution brings insights fast to accelerate R&D decision making — harmonising siloed, disparate data in a flexible, easy to use user interface

How harmonized data can unlock opportunities in artificial intelligence (AI) and machine learning for drug discovery & development — a deep dive into the e-therapeutics approach:
a. How knowledge graphs accelerate drug discovery by harmonizing disparate, siloed data across biopharma companies
b. How the knowledge management platform helps to visualize the knowledge graph for non-technical users
c. Enabling data for AI, machine learning (ML) and Graph Neural Networks — exploring approaches in this area for target identification

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For more than a decade, life sciences companies turn to ONTOFORCE to face the struggles with bringing together structured and unstructured data to create new insights. These insights lead to accelerated drug discovery, more in-depth insights into research, real-world evidence, optimized clinical trial research, and a faster go-to-market.

Lighthouse customers such as Amgen, UCB, BMS, Roche, Medidata, and numerous other life sciences colleagues rely on ONTOFORCE. Thanks to the intense collaboration with renowned research institutes such as IMEC, VIB, UGent, KULeuven, and international research and industrial consortia such as ELIXIR, FAIRplus, and Pistoia Alliance, you trust to engage with a global partner that has made transforming data into insights its primary objective.

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