The pipeline to new drugs isn’t straightforward. Whilst some estimates of only 5-10% of drug programs making it to approval may be lowballing the true rate, success is still far from guaranteed. What is guaranteed is the gargantuan time and cost of taking a compound from discovery to therapy. In response, pharmas are wising up and seeking to make use of what is perhaps their greatest resource – data.
Leveraging molecular data before trials begin means better selection of target compounds and a quicker development process. But data isn’t just a tool, it’s a commodity, and a hugely valuable one. How can we encourage companies to share data assets freely?
One potential solution is offered by Machine Learning Ledger Orchestration for Drug Discovery (MELLODDY). This Innovative Medicines Initiative (IMI)-funded consortium hopes to leverage blockchain architecture to guarantee shareability and security for pharmaceutical data. What’s more, it already has the backing of 10 major pharmas. We talked to Hugo Ceulemans, MELLODDY Project Leader and Scientific Director, Discovery Data Sciences at Janssen Pharmaceutical NV and Mathieu Galtier, Project Coordinator at data science company Owkin to find out more.
MELLODDY is a new Innovative Medicines Initiative (IMI)-funded consortium of pharmaceutical, technology and academic partners across Europe. MELLODDY is aiming, for the first time, to use machine learning methods on the annotated chemical collections of 10 pharma companies to develop a platform capable of creating more accurate prediction models of which compounds could be promising in the later stages of drug discovery and development.
MELLODDY was launched to accelerate drug discovery using machine learning to unlock the maximum potential of pharma data – the world’s largest collection of small molecules with known biochemical or cellular activity – to enable more accurate predictive models and increase efficiencies in drug discovery.
Maximizing the chances of discovering a drug successfully with machine learning is a great leap forward in the ever exciting world of medicinal pharmaceuticals. This is indeed a great news for pharma manufacturers in India and other formulation companies in India. The technology can be a boost in many imaginable and also unimaginable ways.
Read more here: https://www.technologynetworks.com/drug-discovery/blog/maximizing-drug-discovery-success-with-machine-learning-322056