A new cloud-based data platform has been launched to help life sciences businesses overcome the challenges of modern R&D by enriching and harmonizing proprietary and external data and delivering it in an AI-ready environment.
With nearly a fifth of pharmaceutical spending going to R&D and the average cost of bringing a new drug to market estimated at $4 billion, life sciences companies urgently need more efficient ways to analyse data.
Drawing on its longstanding experience in the life sciences, information analytics business Elsevier has created Entellect.
This new platform can save time and costs by de-siloing, contextualising and connecting drug, target, and disease data to deliver normalized, discoverable and model-ready information.
“The life sciences are perhaps the most demanding field in which to undertake data science,” said Cameron Ross, Managing Director of Life Science Solutions at Elsevier.
“The complexity involved is the reason so many companies are looking to AI, and machine and deep learning, to solve their biggest challenges. Too often their efforts are frustrated because of multiple data management barriers, and they’re not yet seeing the insights from AI they expected.
“Entellect provides a sophisticated platform enabling them to get far more value out of their data. We designed Entellect to handle the sorts of data challenges that life sciences companies encounter – from handling huge volumes of existing data stored in individual Electronic Lab Notebooks, to finding the desired piece of information in scientific literature.”
Entellect allows researchers to produce far more accurate predictive models across a range of pre- and post-market activities, including drug efficacy studies, risk-benefit analyses and pharmacovigilance activities.