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    Democratizing data science helps teams do more with less and unlock the innovations that today’s businesses need to survive and thrive.

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    TEL: +086-010-50951355 / FAX:+86-010-50951352

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    ※Product Overview※

    Powered by the 3DEXPERIENCE® platform, BIOVIA™ provides global, collaborative product lifecycle experiences to transform scientific innovation

    BIOVIA solutions create an unmatched scientific management environment that can help science-driven companies create and connect biological, chemical, and material innovations to improve the way we live.

    The industry-leading BIOVIA portfolio is focused on integrating the diversity of science, experimental processes, and information requirements across research, development, QA/QC, and manufacturing. Capabilities cover scientific data management; biological, chemical, and materials modeling and simulation; open collaborative discovery; scientific pipelining; enterprise laboratory management; enterprise quality management; environmental health & safety; and operations intelligence.

    BIOVIA is committed to enhancing and speeding innovation, improving productivity and compliance, reducing costs, and accelerating product development from research and product ideation through commercialization and manufacturing for science-driven enterprises of all industries.




    Businesses today are swamped with data. Valuable insights are hidden among different data silos, leading to inefficiencies across the entire organization. While data scientists can help tame the flood of data, qualified individuals are in short supply. As a result, the few on staff are left to deal with piles of ad hoc analyses and manual, labor-intensive projects that yield little value to the organization.

    Organizations therefore need a scalable framework to create, validate, and consume data science workflows. From accessing and aggregating data to sophisticated analytics, modeling and reporting, automating these processes allows novice users to get the most of their data while freeing up expert users to focus on more value-added tasks. Utilizing a common framework also ensures best practices are captured and shared enterprise-wide. Democratizing data science helps teams do more with less and unlock the innovations that today’s businesses need to survive and thrive.


     • Automate the blending and preparation of data for analysis
     • Easily implement sophisticated analytics and machine learning models into end-to-end workflows
     • Develop powerful applications in a graphically-based, code-free environment
     • Deploy workflows for easy sharing and reuse
     • Create interactive dashboards for rapid consumption of data



    Science-based organizations need to optimize operations by improving efficiency while maximizing quality and adhering to regulations, while driving innovation. These challenges also apply to the lab environment, which needs to remove inefficiencies and compliance risks from lab processes and to provide a collaborative environment for innovation.

    The solution is to remove disconnected and paper-based processes that are error-prone and hamper access of relevant data throughout the research, development and manufacturing lifecycle.  It is imperative to make decisions as early as possible in the lifecycle, in order to drive innovation and to optimize processes and products. Digital Laboratory Informatics capabilities allow for streamlined and more efficient lab workflows, harmonization and standardization and a fully integrated and automated easy-to-deploy process.


     • Speed up the design and development process
     • Leverage accurate and indelible experimental results for more efficient decision-making
     • Track lab activities and processes for greater insight and resource allocation
     • Reduce compliance risks by capturing data directly in the lab and storing it as a single source of truth for all future work
     • Greatly reduce the amount of time spent searching for and collecting data across locations and domains
     • Accelerate approval cycles and reduce rework
     • Drive drug discovery projects based on live scientific data



    Quality helps ensuring patient safety, treatment efficacy, sustainability and protection of brand reputation. Dassault Systèmes helps achieving Quality and Business Excellence with a new a comprehensive data-centric approach to Quality, ensuring digital continuity, data integrity and a “Single Source of Truth” of information. The integrated capabilities include Quality Document and Content Management with automated tasks, electronic signatures, standardized controlled processes and audit trails, Quality Process Management (like CAPA investigations or root-cause analysis) with immediate access to data and documents with hyperlinks and Quality Intelligence using machine learning and federated search. Developed for the highly regulated Life Sciences industry this cloud-based solution provides full regulatory compliance, has a modern and intuitive user interface and is easily scalable from only a few to 100.000 users.


     • Automate and streamline quality processes
     • Automate reporting with data-based structured documents
     • Manage quality processes and documents in one single system
     • Improve quality and integrity of data and documents
     • Minimize compliance risks
     • Reduce inspection time and downtime
     • Easily access all data and documents
     • Minimize Cost-of-Ownership
     • Gain meaningful insights for impactful decision making
     • Adopt a comprehensive, data-centric proactive approach to Quality



    Organizations need to maximize efficiency, reduce costs and control product quality, variability and yield. BIOVIA provides process development, quality, and manufacturing users with self-service, on-demand access to process and quality data from disparate databases and paper records. It automatically aggregates and contextualizes the data and enables ad-hoc statistical investigations. Teams across different departments, organizations and geographies can collaborate and gain actionable insights. The discipline supports three major areas that empower production operations, shorten time to market, and maximize profitability. It helps improve process design by understanding the critical process parameters, increase process performance by monitoring variability enabling preemptive action and drive process improvement by understanding and control process and product variability.


     • Access and automatically aggregate and contextualize all process and quality data
     • Obtain visibility into process performance at all departments and levels in the organization
     • Gain better process understanding by ad-hoc analysis of data
     • Perform upstream and downstream correlations across pooling and splitting points in the process stream
     • Make GMP decisions for deviation investigations and batch dispositioning
     • Meet requirements for Continued Process Verification (CPV)
     • Make golden batch comparisons
     • Collaborate and share process data and knowledge
     • Leverage the value of investments in existing data infrastructure



    Declining R&D productivity is forcing organizations to think outside the box to keep up with increasing consumer demands. Relying on physical experimentation alone is not economically sustainable in such a climate. Researchers need to facilitate a deeper understanding of both how and why their products work to better tie them to project and business goals.

    Modeling & Simulation provides a snapshot of the fundamental atomic interactions supporting product performance. In silico testing allows researchers to test concepts with minimum risk and lower costs, unlocking new avenues of ideas to explore. By tying the virtual and real worlds together, researchers can better guide their projects with virtual tests guiding physical ones and vice-versa. As a result, teams are able to create better performing, safer and cost-effective products, leading to improved patient outcomes.


     • Utilize a wide range of trusted modeling and simulation engines to virtually test and optimize products
     • Investigate and test hypotheses in silico prior to costly experimental implementation
     • Leverage an open and scalable framework to automate processes and create and deploy custom workflows
     • Simulate experiments to gain a better understanding of what is happening in your lab



    Scientific discovery arises from the collaboration of diverse teams. The types of content they utilize can be equally as diverse, across disciplines such as cheminformatics, bioinformatics, proteomics, genomics and more. Organizations must ensure that researchers have the tools they need to effectively analyze and share this content to maximize its impact.

    Leveraging a common framework for managing scientific content helps facilitate an environment of collaboration across internal and external R&D networks. Researchers can easily aggregate, process and analyze data while rapidly sharing and discussing results. Scientifically-aware tools also help guarantee that researchers have the capabilities they need to explore their data more deeply. Together, such an environment facilitates innovation and helps researchers guide their work via data-driven decisions.


     • Register, track and manage individual projects and product candidates throughout the development pipeline
     • Leverage sophisticated, discipline-specific tools for chemistry and biology to more effectively analyze their data
     • Create and manage a common workspace for collaboration between internal and external teams
     • Remove paper-based workflows to drive efficiency
     • Automate processes to aggregate, blend, analyze and report data and experimental findings

     • Accelerate compliant product and process development from research through QA/QC
     • Create enterprise-wide intelligence that helps reduce cycle times for product commercialization
     • Manage and connect scientific innovation processes and information with other product lifecycle systems
     • Electronically capture, and access consistent data to improve insight into process and product quality from early design through full • commercialization
     • Streamline data access and reporting across the enterprise and reveal information in the most appropriate way for stakeholders to help improve decision making
     • Facilitate collaboration, internally and across external research networks to access, organize, analyze, and share information
     • In-silico design and selection of molecules, biologics and materials, using modeling, simulation and predictive analytics

    Customers in Life Sciences and Materials Sciences world-wide are moving from a product-centric business to a patient and consumer-centric business. Our goal is to help organizations in this journey, supporting them with our technology and scientific expertise for true, impactful digital transformation.

    Welcome to consult us!

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