Life science and data technology innovator, Aigenpulse,is introducing a new state of-the-art data intelligence platform which is designed to expedite the drug discovery and development process. The Aigenpulse platform harnesses the latest artificial intelligence and machine learning tools to deliver advanced analytics to underpin scientific decision making.
Aigenpulse has built the data-agnostic platform for importing, integrating, processing, linking, visualizing, exploring and analysing biological data across multiple sources and types into a common frame of reference. It enables users to safely leverage all their data assets to create new insights, build predictive foresight and share findings with stakeholders.
Built specifically for the R&D enterprise, the Aigenpulse Platform unifies silos promoting data re-use, provides automated processing, analysis and report templating, offers in-built statistics, visualization and machine learning tools, enabling high-quality outputs to be generated at multiple stages of the R&D life cycle and democratised throughout the organisation.
Scientists can process hundreds of datasets simultaneously and at scale, freeing themup for higher value tasks. The platform can easily integrate with ELNs and LIMSs, in-house data lakes, for a single-point-of-truth for sample/experiment meta-data, and public data sources, such as TRON,TCGA, andGTeX.
Recognising the significant regulatory requirements of life science organisations, Aigenpulse developed an automated system to collect, template and store the evidence required for any configuration of its Platform.It offers automatic QA/QC on datasets, an end-to-end breadcrumb trail to ensure reproducibility of analytics and GxP alignment for use in regulated development, clinic and manufacturing.
The Aigenpulse Platform is configurable and modular and can be tailored to cater for various data types and business needs. Experiment Suites, which solve specific challenges and are focused on one type of scientific data,are mapped to organisation-wide sets of samples, vocabularies and ontologies, enabling a centralised,accessible, auditable repository of data (raw, processed andanalysed), analysis, ML models and reports.
Later this year, Aigenpulse will be fully launching its CytoML Experiment Suite – an automated, end-to-end, machine-learning solution specifically aimed at enabling streamlining and automation of cytometry analysis at scale.With it, users will benefit from a single point-of-truth about all cytometry data across an enterprise organisation.
Steve Yemm, Chief Commercial Officer commented: “The need to deliver innovative therapeutics more cost-effectively and generate profitable growth means that drug developers need to embrace disruptive technologies.Being able to fail faster, design streamlined, targeted and efficient clinical trials, and accelerate the discovery and approval of new therapeutics, whilst reducing cost,is all achievable with the Aigenpulse Platform.”
“We have designed the Platform to help digitalise the entire research process, by logically storing and securing biological data from diverse sources and applying advanced analytics to aid data integration. We thereby provide a framework by which governance, regulatory and security policies can be applied and powerful insights can be generated in real-time. Ultimately, we combine machine learning and human expertise to facilitate the efficient creation of better drugs.”
The Aigenpulse Platform is cloud-agnostic and can be deployed as a single-tenant Platform on AWS, GCP, Azure or Private Cloud. There is an annual subscription for named users and Experiment Suites. Aigenpulse provides an ITIL-compliant support level agreement, complete GXP validation when required, a 24/7 help desk and full online documentation.
About Aigenpulse
Aigenpulse Limited was founded in May 2016 to develop the unique Aigenpulse IT platform that takes into account the dynamic and evolving nature of research. With offices in Oxford shire and London in the UK and Boston in the United States, Aigenpulse consists of experts with PhD level qualifications in Life Sciences combined with highly skilled software developers, bioinformatics data scientists, cloud computing engineers and user experience/user interaction designers.