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ConvergeHEALTH™ CognitiveSpark™ for Clinical

Using AI and machine learning in clinical trial data management

Automate data management across the clinical trial life cycle to help improve efficiency and deliver breakthrough therapies to patients at the speed of need.

Why ConvergeHEALTH CognitiveSpark for Clinical?

Speed clinical trials using AI and machine learning

For a patient awaiting a life-saving treatment, the current drug development timeline can feel like an eternity. As life sciences CIOs and R&D leaders know, that’s because the traditional flow of data across the clinical trial life cycle can be a complicated maze marked by manual effort, rework, and inefficiency.
These pain points add up, contributing to both increased trial time and cost. To help alleviate the pain and open new opportunities, life sciences companies need an advanced solution that harnesses the power of AI and machine learning to streamline the clinical trials life cycle: ConvergeHEALTH CognitiveSpark for Clinical.

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The benefits

Accelerate trial cycle times

CognitiveSpark for Clinical enables the downstream use of data elements, automates data quality checks, and features user-driven Study Data Tabulation Model (SDTM) conversions to drive faster, more efficient clinical trials.

Improve clinical trial efficiency and data quality

With a collaborative authoring platform, metadata traceability to standards, and machine learning features, CognitiveSpark for Clinical delivers data quickly—while preserving data quality.

Lower trial costs

By standardizing workflows and documentation and adding studies automatically, you can limit resource needs, manual errors, and costs.

Scale—and customize—to your needs

Easily extend CognitiveSpark for Clinical across therapeutic areas and trial types to promote an end-to-end digital workflow.

Our solutions

Clinical Data Repository (CDR)

A scalable data foundation for raw, enriched, and analytical data sets

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Metadata repository

Provides access to metadata for consumption by downstream systems

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AI/ML algorithm store

A set of standard application programming interfaces focused on insight generation

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Study designer

Creates comprehensive digital study specifications—including objectives, endpoints, biomedical concepts, and eligibility criteria

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Data harmonization

Integrated mapping from source systems to SDTM and Analysis Dataset Model, aided by automation and machine learning

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Tables, listings, and figures (TLF) creation

Automates the creation of TLF shells using standards and templates

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ConvergeHEALTH CognitiveSpark for Clinical in action

Insights to guide your journey

Bringing new therapies to patients

Article

Five potentially transformative strategies for accelerating drug development

Using AI to accelerate clinical trials

Retail clinics may be the next frontier for clinical trials

Intelligent clinical trials

Article

Achieving clinical trial diversity requires trust, awareness, access

Interested in joining our team?

Explore our job openings

Ready to get started?

Connect with us to learn how ConvergeHEALTH CognitiveSpark for Clinical can help you cut cycle times and reduce trial costs.

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Amy Cheung

Amy Cheung

Principal