Research to Protect

As the world focuses its efforts on continued research for diagnostics, treatments and vaccines against emerging virus that might affect heavily the populations, many governments are looking for ways to strengthen their scientific research capabilities and create a stronger foundation to deliver these cutting-edge therapeutics, as well as establish a foundation of collaborative research in preparation for the next crisis.

Governments, health ministries, healthcare and medical agencies, research institutions and partner companies around the world are understanding that in order to meet these challenges they must excel in scientific leadership and transform the processes throughout their highly-networked ecosystem.

Research to Protect, powered by the 3DEXPERIENCE platform of Dassault Systèmes, provides sophisticated scientific solutions to allow government agencies and public research Institutions to manage their innovation life cycle. We provide these institutions & their researchers with a scientific and business platform to imagine sustainable innovations, capable of improving patient & physician experiences in the age of precision medicine.

Research to Protect by superseding traditional approaches with Artificial Intelligence (AI) driven therapeutics design based on disease understanding, predictive tools that leverage existing experimental results to rapidly optimize the quality and safety of novel therapeutics, all delivered in an open collaborative platform enabling scientists to work in partnership and share scientific knowledge, are key to overcoming these challenges.

• Modeling and simulation for molecular therapeutic design: building virtual experience twin molecular and device therapies that can be used to simulate and predict critical material characteristics, behaviors and system interactions.
• Scientific collaboration across organizational boundaries: researchers are quickly moving from simply sharing data with external partners to sharing methods, tools and models in the cloud to eliminate time-consuming orchestration and translational efforts.
• 25% improvement in candidate identification & quality by leveraging in-silico approaches and acceleration of high potential candidate identification.
• Increased speed of innovation by leveraging contextualized data and taking more informed decisions delivering a time savings of 33%.
• Improved success rate of identified candidates through leveraging of data science.
• Improved collaboration across research sites and partners by connecting cross-disciplinar experts in a shared collaborative platform results in an 85% reduction in time and resources needed to exchange data.