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At RxDataScience we leverage a wide range of open-source and commercial solutions to build comprehensive AI, ML, and Data Analytics tools custom developed for large enterprise organizations. The RxDS AppBuilder framework, a core in-house technology, enables us to develop rapid, iterative front-end solutions. Our tools are backed by numerous NoSQL and traditional data mining platforms that together with AppBuilder allow us to deliver complex solutions quickly in an agile environment.
With over 160 years of combined pharma experience, the team at RxDataScience has delivered numerous business-facing solutions that span a wide spectrum of core healthcare disciplinary areas. Solutions that address challenges in Real-World Evidence Data Analysis, Commercial Market Research, Scientific Computing for R&D, and Data Lake for the Pharma Data ecosystem are but some of the areas our team has worked on extensively with some of the biggest names in the healthcare industry.
We utilize a variety of cloud-based and on-premises SQL and NoSQL based database solutions to power our platform.
We utilize both standard ML software such as R and Python as well as more advanced CUDA-based deep learning solutions to solve unique and challenging predictive analytics use cases in pharma.
Our proprietary AppBuilder Framework allows us to create completely customized UI dashboards in a matter of hours.
Our advanced solutions go beyond data mining and machine learning into the realm of high-performance computing with low-level tools developed in C/C++ and quantitative models developed in Matlab and Mathematica. Automated scripting framework support execution of complex quantitative models for simulation, optimization, and other mathematical operations across hundreds of cloud-based servers and tens of thousands of cores.
At RxDataScience, we have developed one of the most advanced Medical Device data analysis platforms — able to capture and analyze large-scale streaming Sensor and IoT Data at scale. Capable of ingesting up to 50 TB of data, the platform can provide real-time analysis on critical scientific measurements. Vidyut is available as an on-demand SaaS application so that organizations can scale up without high up-front investments. Built-in advanced compression and a low-latency NoSQL columnar database combined with a sophisticated cloud architecture enables querying vast amounts of both real-time and historic data on a single unified interface.