• 1. Save time & resources

    AI-powered Literature Screening:‍

    ⇀ Reduces manual searching through vast medical databases, saving researchers significant time.

    ⇀ Identifies relevant COAs (Clinical Outcome Assessment) efficiently, focusing efforts on promising options.

    Reduced Risk of Errors

    ⇀ Automated literature screening minimizes the chance of overlooking relevant endpoints

    ⇀ Helps ensure researchers select the most appropriate endpoints for
    their study, reducing the risk of wasted time and resources due to
    unsuitable COAs.

  • 2. Make Data-Driven Decisions for optimal trial outcomes

    Holistic view of endpoints:

    ⇀ Provides a comprehensive overview of available endpoints, eliminating the need to research each one individually.

    ⇀ Allows researchers to quickly assess strengths, weaknesses, and suitability for their specific needs.

    Streamlined research workflow:

    ⇀ Eliminates time-consuming manual tasks, allowing researchers to focus on designing and conducting research.

    ⇀ Simplifies the endpoint selection process, improving overall research efficiency.

Our recently published article using our Clinical Endpoint Report

This study delves into the critical role of patient-reported outcome measures (PROMs) in assessing health-related quality of life from the patient’s perspective. Our findings highlight a significant shift in clinical research practices and underscore the necessity of integrating tailored PROMs.

Alhelou C, Dufour J, Clement R. In the era of patient-centricity, is the
use of PROMs optimized?—a narrative review based on AI models. J Med Artif Intell 2024.

Link to article

Discover below what you can achieve by leveraging our cutting-edge research findings to enhance patient care and drive innovation in healthcare.

Patient-Centric Approach:

Gain insights into competitor COAs (Clinical Outcome Assessments) to identify patient's unmet needs that may not have been considered. This allows you to develop a more patient-focused trial design, potentially leading to higher recruitment rates and better participant retention.

Identify Opportunities:

Analyze competitor trials to identify areas where they may be lacking, allowing you to develop a more comprehensive and effective trial design.

Discover an example here

Get a glimps of it!

Example here

Explore our Clinical Endpoints Reports

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Is it possible to have this product set-up locally?

ArcaScience offers on-site technology setup, ensuring that all sensitive
data remains securely in-house. This allows seamless integration with
existing systems while maintaining data privacy and security.

What kind of data are accessible?

ArcaScience integrates all major public scientific databases, including PubMed, Medline, and ClinicalTrials.gov, and can seamlessly integrate any client's databases
via on-site instances or private cloud solutions. Additionally, through
strategic partnerships, ArcaScience can access and integrate databases behind paywalls

How reliable are our outputs?

Our AI models leverage state-of-the-art transformer architectures and the most advanced semantic models recognized as the best in the world in their fields (StartusInsight, 2023) ensuring
exceptional accuracy and reliability. With robust training on vast,
diverse datasets, they deliver precise, actionable insights, maintaining
high standards of performance and integrity.

What quality control is used to ensure reliability?

We implement stringent quality control measures, including robust validation using gold-standard datasets, continuous performance monitoring, and iterative model refinement. Our AI models are meticulously evaluated to ensure exceptional precision, recall, and reliability, consistently meeting the highest industry standards for accuracy and dependability.