metaphactory with Amazon Neptune for Pharma & Life Sciences

Product Overview

Low-code, FAIR Data Platform to * Fast-track drug discovery * Speed up drug safety reviews * Reuse existing data and knowledge & generate continuous knowledge * Streamline processes from R&D to manufacturing * Align strategic efforts*metaphactory on top of Amazon Neptune supports customers in Pharma & Life Sciences in their digital transformation journey by allowing them to quickly build a cross-data source and cross-departmental data fabric for business users. By tapping the full potential of existing internal and external data sources and making knowledge available and accessible company-wide, you can drive research and innovation and the delivery of new products, boost productivity and support mission-critical business decisions. metaphactory commoditizes Knowledge Graphs, making the technology and its benefits accessible not only to knowledge graph experts but also to business users and domain experts. It supports the process of making data FAIR and enables a cross-departmental Knowledge Graph creation process where all relevant stakeholders can be equally involved in the process of modeling a domain ontology and mapping and describing data sources. Through its low-code approach built on a model-driven template mechanism and a rich set of ready-made Web components, metaphactory allows customers to quickly build an intuitive user experience on top of their Knowledge Graph to support search, discovery, visualization, collaboration and editing of data.
Version: 5.2.0

By: metaphacts GmbH
Categories: Healthcare & Life Sciences
Data Analytics
Application Development

Operating System
Linux/Unix, Amazon Linux 2
Delivery Methods
Amazon Machine Image

Highlights: Fast-track drug discovery & Speed up drug safety review processes: Company-wide access to research data and knowledge as well as a data-driven application building platform accelerate time-to-market for new drugs and therapies. Existing reasearch findings can be leveraged as supporting metadata in review processes mandated by regulatory agencies, thus speeding up the approval processes. Reuse existing data and knowledge & Generate continuous knowledge: Reusability of data and knowledge and the automation of data collection and integration help eliminate error-prone manual processes and allows users to focus on value-adding tasks. Data is transformed into company-wide available knowledge and can drive forecasts, prediction, and support research initiatives and business decisions. Streamline processes from R&D to clinical trials to manufacturing: Research and lab data become available to manufacturing plants, helping streamline knowledge transfer and the planning of clinical trials, manufacturing and distribution processes.

Category: Infrastructure Software

Delivery Method: Amazon Machine Image