What's New in BIOVIA R2021x

Provide intuitive and meaningful access to scientific experimental data.

• Record, collate and organize complex experimental details
• Index experiment metadata and organize information to allow findability of records and project knowledge for reuse and reporting
• Provide data integrity and support specific business workflows with integrated corporate and industry compliance
• Allow multiple scientist to contribute to one experiment in real-time

Optimize Drug Design and Discovery combining Artificial Intelligence, Chem Informatics and Structure-based Modeling

• Use automated virtual creation, testing and selection of novel small molecules/biologics to optimize lead molecule design in advance of physical testing.
• Enhance machine learning models by re-learning models with proprietary data.
• Use artificial intelligence (AI) techniques to optimize target, anti-target, synthesizability, safety and toxicity profiles for molecules ready for synthesis and testing.
• Design lead molecules in advance of physical testing, using automated virtual creation, testing and selection of novel small molecules and biologics.
• Improve molecular quality and shorten discovery timelines, resulting in potential savings of millions of research dollars per program.
• Create tools for project teams and domain experts, not expert data scientists.

Access scientific views and make efficient and informed decisions for product and process innovation.

• Manage scientific data structured in a Target Product Profile plan
• Consolidate In vivo/vitro/silico results as answers to the TPP
• Track and trace substances, protocols and tests in all stages of the project
• Efficiently task experiments and recover the results
• Author and trace fitness of compounds versus the TPP based on consolidated results interpretation
• Search with widgets and facetted dashboards
• Collaborate with real-time access to a single source of data
• Drive Discovery projects using the Target Product Profile

Leverage past experiments instead of repeating them. Include storage conditions and periodic interval testing for stability.

• Plan, perform and analyze experiments, draw conclusions and documents outcome
• Develop methods and processes
• Share results with colleagues and teams
• Ensure that organizational standards and operating procedures are followed
• Capture results, sign and countersign records to ensure intellectual property is protected
• Label and integrate with material inventory, registration and sample management systems

Gain deeper insights from scientific data by leveraging data science capabilities and executing best practices workflows.

• Allow teams to use previously developed and published Pipeline Pilot protocols in areas including: chemistry, machine learning, image analysis, genomics/proteomics, ETL, numerical analysis and dashboards
• Execute best practice workflows created by domain experts. Gain efficiency with automated data processing, integration, ETL, analysis and reporting methods
• Enable rapid democratic consumption of results by productizing scientific solutions on the 3DExperience Platform

Efficiently create, design, manage and report studies for materials and products. Schedule and monitor testing across multiple time intervals and experiment variants.

• Create and design new studies
• Include storage conditions and periodic interval testing for stability
• Automate sample management and logistics
• Automate scheduling and alerting of upcoming activities
• Assign activities to different scientists
• Collect data and evaluate analyses
• Project shelf life from available data
• Automate calculation of targeted timepoint dates
• Report studies and evaluate results with trending

Improve Therapeutics Discovery with Better Understanding of Disease Mechanisms and Drug Modes of Action

• Streamline the assembly of scattered and static knowledge into actionable and meaningful models
• Design in silico pre-clinical experiments to efficiently generate and investigate biology research hypothesis
• Execute qualitative simulations of complex biological systems including multiple perturbations in a timely manner
• Analyze and interpret results to rationalize the decision-making and reduce wet lab investigations
• Structure, share and perpetuate the captured biomedical expert knowledge within the R&D community for reuse