Clinical Data Analytics
ICH E6/E8 and a drive for patient-centricity ushered in a new era for conducting clinical trials. Real-time access to aggregated data is imperative when taking a Risk-based Quality Management (RBQM) approach and monitoring risks centrally. The technology advancements harnessed by ThoughtSphere provide a continuous 360º view of clinical and operational data and alert users when risk triggers are detected.
The ThoughtSphere platform delivers a streamlined and simplified solution for executing clinical trials by breaking down operational and system silos and integrating processes from data aggregation to the generation of submission ready datasets.
Built using Data Lake architecture, ClinHUB is a patented data aggregation and harmonization solution that is source system agnostic, highly configurable and able to ingest structured and unstructured data in virtually any format.
ClinHUB’s Smart Map engine leverages Natural Language Processing (NLP) and AI/ML algorithms to automate the mapping process with little to no manual intervention required, drastically reducing study implementation time from weeks to days.
ThoughtSphere’s integrated Modeling and Analysis Programming (MAP) solution provides an integrated statistical computing interface for data scientists and biostatisticians to seamlessly develop data models using SAS, R, and Python, with no data transfers or exports required. Apply MAP’s out-of-the-box AI/ML quality checks to uncover atypical patterns, data signals, and outliers or create new prediction and classification models to find patterns and irregularities in raw or structured data. Leveraging SDTM compliant data generated in ClinHUB, programmers can also use MAP to create ADaM datasets for data interpretation and study deliverables.
Business Intelligence Tool
Our embedded BI Tool leverages the standardized data from ClinHUB and data models from MAP to provide a robust suite of data visualizations, analytics, and dashboards to support the identification of data trends and anomalies. This includes interactive multi-variate and statistical monitoring analytics that allow a user to compare lab analytes over time or look at the data distribution of key endpoints across subject cohorts with the click of a mouse. Additionally, custom analytics, reports, and listings can be easily configured, approved, and published at the study, program, or enterprise level using BI Designer.
Our robust RBQM solution facilitates the complete risk lifecycle from risk identification through issue resolution with automated triggers and configurable user workflows to provide end-to-end traceability. Starting with the risk assessment, users can upload an external Risk Assessment (e.g., RACT) or create it from scratch in our platform by leveraging our risk library and Smart Risks AI feature. Apply our out-of-the-box KRIs, KPIs, and QTLs to monitor risks for the study or create your own custom visualizations and indicators. Streamline and automate risk & safety reviews through data-driven or cadence-based triggers and customizable user workflows. Oversee the status of risk reviews and provide real-time operational oversight metrics with strategic oversight dashboards.
Put the power of aggregated and harmonized data in the hands of the data managers with DMSphere. Our data review workbench allows users to automate complex relationship checks, cross-source checks, and SAE reconciliation reviews historically performed through inefficient manual listing reviews. Using our Smart Check technology, data check rules are automatically configured, irrespective of the study’s metadata definition, using NLP and statistical-based text comparison algorithms. Manage data review activities and track data cleanliness parameters (e.g., forms submitted, SDV status, Queries outstanding) at the subject/site/trial level in near real-time to support interim data deliveries and database lock.
Our Site Payment and Contracting Environment (SPACE) provides end-to-end automation with integration of site contract and payment modules to accelerate payment cycles and reduce manual errors.