Data Science Tool for Scientists
Science and Engineering Data Management
BIOVIA focuses on integrating research, development, QA/QC, and various scientific, experimental, and information requirements arising from manufacturing processes.It provides capabilities across scientific data management, including biological, chemical, material modeling and simulation, scientific pipelines, research management, quality control, environmental health and safety, and operational information.
- Manage scientific analysis and information and easily connect with other systems
- Develop research process compliance products and processes with QA/QC
- Implementing enterprise-wide intelligence that shortens the cycle for product commercialization
- Streamline enterprise-wide data access and reporting and find information best suited to improving stakeholder decision-making
- Creating a collaborative environment that facilitates access
- organization，interpretation and sharing of information over internal and external research networks
Increase data resource utilization for efficient research and development by collecting, processing, analyzing, and reusing diverse data. It makes AI and machine learning easier, especially in engineering and science. Pipeline Pilot allows Data Scientist to create models, compare the performance of model types, and store them for future use with just a few clicks.
A secure cloud infrastructure that supports solutions for research collaboration, laboratory information, quality and compliance throughout the product development lifecycle. Cloud environments provide a collaborative space that organizations in the enterprise can easily access anytime, anywhere.
Integrate people, resources, processes, data and interfaces for greater efficiency and collaboration. Reduce duplication and build knowledge of processes and data. Build and coordinate models for future experiments and tests to accumulate available knowledge.
BIOVIA Discovery Studio can jointly develop world-class In-silico technologies such as research for life sciences and molecular dynamics, free energy computation, and the potential for biotherapy development. This can dramatically reduce the time and cost of finding new drug candidates by enabling researchers to verify drug efficacy, stability, pharmacological properties, and ecological toxicity through virtual molecular modeling and simulation.