Solutions > Clinical Sciences and RWE Analytics

Clinical Sciences and RWE Analytics

Producing an ideal trial design is complex, involving a variety of factors that make optimizing protocols difficult. Enrollment planning and site selection is largely a manual process that doesn’t produce robust enrollment estimates. In addition, processing and analyzing real-world data is complicated, involving a variety of security, compliance, and data formatting concerns. bPrescient can help, using predictive data science and AI-driven patient stratification strategies to optimize inclusion/exclusion criteria, accelerate enrollment, and minimize drop-out rates.

Solution Overview

Our solution for Clinical Sciences and RWE Analytics includes:

Tools to mine public trial data to provide accurate enrollment and reporting during trial to monitor enrollment against plans.

Predictive models of trial enrollment rate based upon trial inclusion/exclusion criteria.

Machine learning and AI-based analytics to process patient and biomarker data to identify stratification strategies that balance trial performance with enrollment targets.

Systems for ingestion and QC of patient data that leverage automation and data standards.

Vendor selection and review of clinical systems for data capture, management, and reporting.

Solution Benefits

Partnering with bPrescient benefits your clinical pipeline in a variety of ways:

Realistic enrollment rate estimates drive trial planning that can be used to produce accurate budgets and timelines.

Reduced trial cycle time to accelerate clinical timelines, reducing overall costs.

Stratification strategies and inclusion/exclusion criteria grounded in data produce trial designs with the best chance of success.

Well-organized patient data sets allow posing of a broad range of questions related to trial design.

Robust and validated clinical systems provide trusted repositories for valuable clinical data, limiting regulatory exposure and audit costs.

Relevant Expertise

This service draws on our expertise in the following areas:

Strategy & Roadmap Development

Scientific Informatics: Software Design and Implementation

AI & Machine Learning: Generating Novel Insights

Data Science for Clinical Trials & Healthcare

Data Engineering, MLOps, and CloudOps

Let’s talk

Tell us about your toughest R&D challenge and let’s discuss how bPrescient can solve it.

Clinical Sciences and RWE Analytics

Solution Overview

Solution Benefits

Relevant Expertise

Example Tools and Data Sources

Related Case Studies

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Drug Development Simulation

Clinical Data Governance and MDM

AI-Based Drug Repurposing Research

Let’s talk