Data Science & Biometrics
Focusing on data science instead of data management – by standardizing data from the beginning and using advanced big data-style analytics – gives deep, actionable insights into the performance of your trial… and your entire program.
How do you make trial data an integral part of guiding trial progress?
Data that empowers sponsors with the insights they need to assure success in every trial.
Transforming Trial Data Into A Powerful Asset
Our approach begins by building out a standard data structure before the trial even starts. Instead of waiting until the end of the study to standardize data for submission, we take advantage of – and build our workflow around – the CDISC SDTM and ADaM standards right from the very beginning. Not only does this approach save time in filing later, but it makes the data immediately useful across a range of functions. We are passionately committed to the CDISC standards, which are poised to become the global accepted standards for data in the same way that ICH-GCP standards govern the clinical realm. In this increasingly data-driven world, treating data as an asset rather than a liability and leveraging its power will put our Sponsors at an immediate advantage when compared to their competitors.
Our Data Science and Biometrics Service includes:
Find Deep Insights With Big Data Analytics
Deep data insight allows us to detect risks – like fraud, poor performance, safety issues, and logistical problems – well before they become problems.
Biorasi standardizes your data from beginning, and runs it through the same analytics suite used by the FDA during the approval process.
A data-driven world requires a data-driven mentality for clinical trials.
Data Science is not just data management, but an entirely new approach that transforms data from a necessary burden to a driver of clinical trial success.
Going Beyond risk-based Monitoring
The combination of transparency, a big data approach, and intelligent guidance allows for practical, actionable solutions like Smart Monitoring – Reduce your monitoring costs by as much as 50%.
Anomalies detected in multiple concurrent ways:
Data anomalies can be identified by non-traditional methods, and escalated for traditional review.