Posted 9th September 2019 by Joshua Sewell
As Chief Data Officer for the OSTHUS Group, Eric Little co-founded LeapAnalysis, a new approach to AI, data integration and analytics.
LeapAnalysis is the first fully federated and virtualised search and analytics engine that runs on semantic metadata. It allows users to combine semantic models (ontologies) with machine learning algorithms to provide customers with unparalleled flexibility in utilizing their data.
Posted 29th May 2019 by Joshua Sewell
Manuela Maria Schöner, part of the Corporate Strategy & Consulting division at Boehringer Ingelheim, spoke to us recently about her work with blockchain. She described her perspective on the use of data in the industry, and how Blockchain could become a key tool in meeting the needs of the primary stakeholders: patients.
Posted 22nd May 2019 by Joshua Sewell
In my previous post, I discussed the likely applications of Blockchain technology in the short, medium, and long-term future. These applications follow on from the key strategic priorities necessitated by the healthcare industry’s trend towards digital decentralized care delivery models.
Lab Data Automation, Optimizing R&D Workflows and Lead Discovery from Biologically Complex Bioassays
Posted 23rd January 2019 by Jane Williams
With an increasing amount of data being generated today, pharma and biotech companies need to develop new technologies and strategies in order to structure, analyse and integrate this big data. If you weren’t able to attend our Global Pharma R&D Informatics & AI Congress, we have made these slides from Ralph Haffner, Dana Caulder and Pierre Farmer available.
Posted 12th November 2018 by Jane Williams
Since its discovery in 2012, the use of the CRISPR/Cas9 system to edit genomes has raised the expectations for the cure of untreatable disorders. Very often, as biomedical geneticists we found ourselves talking about the potentials and drawbacks of CRIPSR/Cas9 both at scientific and layman level.
Human Genomic Evidence: Revolutionising the identification and prioritisation of targets for better medicines
Posted 17th October 2018 by Jane Williams
Nine out of 10 potential drugs that enter clinical trials never make it to the market. Failure often occurs because the biological target chosen is not well understood. However, it is hard to objectively select targets with a high chance of clinical success because the data required to predict efficacy and safety are complex, dispersed and incomplete. To address this challenge, Open Targets was founded in 2014 as a public-private partnership by GSK, EMBL-EBI and the Wellcome Sanger Institute. The consortium has grown since its launch, welcoming new partners Biogen in 2016, Takeda in 2017, and Celgene in 2018.
Posted 28th September 2018 by Jane Williams
When we last spoke, Brandon Allgood told us about The Future of AI. This week, we caught up with Brandon and spoke about drug discovery and machine learning algorithms.
Posted 17th September 2018 by Jane Williams
Drug discovery and development is a complex process that requires integration of multiple data points, experiments and calculated risk/benefit assumptions. It is therefore only natural that virtualization and big data analytics are a natural fit for implementations, expected to demonstrate significant cost-effective gains for the betterment of society, providing access to effective and safe medications.