Data scientists must harness big data to understand disease mechanisms, stratify patients, discover new targets, and select the best-performing therapeutic candidates. However, before they can extract such insights, computational scientists must overcome tedious and time-consuming data mining tasks. What they need is a purpose-built data science ecosystem that allows rapid data processing and analysis, analytical tool development, and knowledge dissemination.
This is where Genedata comes in.
Our Customers
We are excited to implement the Genedata Biopharma Platform as a central integrated data backbone to streamline the capture, integration, democratization, and analysis of increasingly complex and diverse data types.
We especially appreciated the high level of expertise and support provided by Genedata, which enabled us to optimize every stage of our analytical processes—while incorporating industry best practices—and quickly generate high-quality results.
During our initial deployment, we recorded quantifiable increases in productivity. The number of results posted to our data warehouse more than doubled, indicating that we could capture results from many more experiments, while the cost of running day-to-day operations decreased.
The Biologics Data Platform supports our scientists in a complex, multi-site environment by providing all the necessary information and tools to streamline the biologics lead generation and optimization process.
The Genedata platform is an important cornerstone in enhancing the analytical capabilities of our teams with cutting-edge digital technology.
One of the reasons we chose Genedata was the platform’s process coverage. We required that the full diversity of Pfizer’s large-molecule processes and technologies be supported by one integrated system.
Genedata enables us to integrate a wide variety of complex data generated by novel experimental workflows so we can gain a holistic molecular understanding of production cells with the goal of developing high performing bioproduction processes.
We need to enhance our capacity to analyze large amounts of high-dimensional ‘omic data emerging from our rapidly growing number of translational and clinical research projects. We chose Genedata because it is the end-to-end enterprise software able to harmonize our dispersed data analysis pipelines.
We aimed to extend automation and further enhance the efficiency of our cell line, upstream and bioanalytical development operations, and quickly realized that Genedata addresses many of our requirements off-the-shelf, eliminating the need for expensive customization.
Genedata gives all our R&D groups a central place to record and access TCR-related information in real time, along the end-to-end workflow.
To optimally handle the complex data, we need a centralized genome knowledge management and analysis solution that addresses the interdisciplinary challenges in next-generation biotechnology innovations. Genedata was our obvious choice.
Thanks to its flexible architecture, Genedata Biologics can truly support our entire discovery process – right through from the immunization of transgenic mice, to lead selection, molecular modification and final candidate assessments.
Genedata tracks all biologics molecules from early discovery to development, and gives the UCB R&D organization central access to all relevant information on these molecules.
Extract Valuable Insights. Efficiently.
- Advance all projects with open architecture — regardless of whether using R, Python, Nextflow, command line, or any other current tool — eliminating the need to adapt code or transfer data between different environments.
- Seamlessly connect to diverse sources to import or federate data, ensuring self-service data is always available for downstream activities.
- Automate data ingestion, curation, quality control (QC), and analyses with out-of-the-box workflows to standardize routine data mining tasks.
- Simplify the finding and retrieval of datasets for curation and analysis by leveraging excellent annotation and clear project organization, enforcing data FAIRness.
Unlimited Scalability. High Performance.
- Efficiently manage high volumes of multi-omics data, optimizing performance and reducing costs as datasets expand.
- Adopt a highly robust underlying platform technology designed for elasticity and resilience and centralize data management to streamline data retrieval and reduce redundancy.
- Utilize advanced computing resources such as GPUs and an AI-enabling framework for faster insights and reduced computational costs.
- Facilitate the adoption of new machine-learning-based approaches across teams and uncover hidden trends in data faster.
Collaboration. Naturally.
- Deliver harmonized, annotated, and FAIR datasets for downstream integration and analysis, ensuring accessibility for authorized colleagues.
- Build and deploy user-friendly analytical tools in an advanced development environment, empowering non-coding colleagues to easily visualize, explore, and compare results, test existing hypotheses, and develop and explore new ones.
- Benefit from built-in code version control to maintain traceability and reproducibility, facilitating compliance and unified collaboration.
Informed Decision-Making Along the R&D Process
“Our teams constantly bring in new science and innovative technologies that require custom workflows, additional metadata, or integration with robotics and automation equipment. By having the Genedata enterprise platform as our central data backbone, we can build our own in-house solutions around it and keep all the information secure, stable, and accessible in one central place.”
Implementation of Enterprise Software Solutions
We especially appreciated the high level of expertise and support provided by Genedata, which enabled us to optimize every stage of our analytical processes—while incorporating industry best practices—and quickly generate high-quality results.” Juliet Padden, Bayer.