SOLUTION DESIGN

Transform Raw Data Into Actionable Insights

At Ario Health, we help pharmaceutical manufacturers use large language models (LLMs) to analyze Real-World Data (RWD) to improve components throughout the full lifecycle from development to post-approval. Our AI and pharmaceutical experts integrate LLMs designed explicitly for the complexities of analyzing complex structured and unstructured RWD.

With Ario Health, we transform raw data into actionable insights that enable data-driven decisions that:

  • Accelerate drug discovery

  • Reduce development costs

  • Improve patient care outcomes

  • Streamline regulatory compliance

These insights advance  innovations, like Real World Data analysis and Real World Evidence generation, reducing development costs, expanding therapies, and speeding time to market. 

Our Commitment

Empowering the Life Sciences industry with advanced capabilities to unlock the hidden value in unintegrated, siloed Real World Data.  We deliver unprecedented speed, depth, and complexity of analyses through the innovative power of AI Large Language Models. Aiding in faster time-to-market, reduced development costs, and improved patient experiences.

SOLUTIONS TO MEET THE STRICTEST LIFE SCIENCES DEMANDS

Ario Health offers use-case-specific solutions to aid your organization through the AI transition, regardless of your size, maturity, or requirements.

  • Book With Light

    AI UNIVERSITY

    Enroll in our advanced training sessions, where we guide companies on integrating AI into research, development, and clinical workflows, improving decision-making and accelerating innovation.

    Leverage hands-on learning experiences that demonstrate practical applications of AI tailored to the uses in life sciences, from drug discovery to regulatory compliance.

    Offered virtually or on-site for your team.

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    Topics Covered:

    Solution component functionality overview

    Similarities and differences of leading LLMs

    Choosing LLMs

    Natural language prompt creation

    Regulatory and compliance challenges

    Operational Best Practices

  • Book With Light

    REAL WORLD DATA UNIVERSITY

    Enroll in an intuitive and engaging course that will provide you with a comprehensive understanding of the fundamental principles of accessing, integrating, connecting, and analyzing Real World Data.

    Our curriculum will cover the essential aspects of selecting appropriate solutions, acquiring suitable data, and initiating natural language analysis.

    Offered virtually or on-site for your team.

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    Topics Covered:

    Common RWD data types, values, and uses

    New and upcoming RWD data types to consider leveraging

    Leveraging unstructured data

    Connecting and linking of RWD sources

    Evaluating and selecting data sources

    Regulatory and compliance challenges

    Operational Best Practices

  • Person using a laptop with a digital graph overlay showing increasing bar chart and line chart, indicating data analysis or growth.

    REAL WORLD DATA VALUATION

    Receive an industry-targeted assessment of the market value of your real-world data (RWD). With increasing demand for high-quality, actionable data to drive healthcare innovations and maximize your return.

    Receive a comprehensive analysis of your datasets, leveraging advanced methodologies and market insights to determine their commercial value.

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    Common Metrics:

    Data Quality and Completeness: Ensuring datasets meet industry standards for usability and reliability.

    Accuracy and Freshness: Deliver the right data with the right frequency to maximize the accuracy and timeliness of insights.

    Relevance and Uniqueness: Evaluating the alignment of your data with market needs, including its uniqueness in competitive landscapes.

    Potential Applications: Identifying the diverse use cases for your data, from drug development and clinical research to regulatory submissions and health economics.

    Improvement Metrics: Identify ways to leverage new data collection methods to increase the value and applicability of your data.

  • Patient Journey Management

    PATIENT JOURNEY MANAGEMENT

    Link complex healthcare data sources to reveal a complete, connected view of each patient’s journey.

    Connect fragmented claims, diagnostics, EHR, lab data, and more to create clear patient journey timelines. Life sciences companies gain deep insights into treatment pathways, adherence patterns, and points of intervention—empowering more informed engagement strategies with providers and patients.

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    Common Metrics:

    Data Linkage Completeness: Proportion of patients successfully connected across claims, EHR, lab, and diagnostics data.

    Journey Insight Depth: Number of measurable touchpoints or variables contributing to treatment understanding.

    Time-to-Insight: Reduction in time required to generate actionable journey analytics for targeted interventions.

  • Adverse Event Tracking

    ADVERSE EVENT TRACKING

    Identify emerging safety risks sooner through intelligent, AI-powered surveillance of real-world evidence and clinical reports.

    Continuously analyze real-world data, EHRs, and patient reports to identify and categorize adverse events with speed and precision. This enables pharmacovigilance teams to detect safety signals earlier, streamline regulatory reporting, and improve patient safety outcomes.

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    Common Metrics:

    Signal Detection Time: Reduction in time from event occurrence to identification of potential safety signals.

    Event Classification Accuracy: Precision and recall in detecting and categorizing adverse events.

    Regulatory Reporting Compliance: Percentage of events accurately reported within required timeframes.

  • Clinical Trial Optimization

    CLINICAL TRIAL OPTIMIZATION

    Optimize clinical trial operations by forecasting patient eligibility, refining site selection, and anticipating recruitment performance.

    Improve trial design and execution by predicting eligible patient populations, identifying optimal trial sites, and modeling recruitment outcomes. This reduces delays, improves diversity in enrollment, and accelerates trial timelines, ensuring therapies reach patients faster.


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    Common Metrics:

    Recruitment Efficiency: Time reduction in identifying and enrolling qualified participants.

    Trial Cost Reduction: Percentage decrease in operational or site management costs due to AI optimization.

    Diversity and Representativeness: Improvement in demographic or geographic diversity of enrolled participants.

  • New Therapy Planning

    NEW THERAPY PLANNING

    Identify promising therapeutic opportunities with AI-powered data analysis and modeling.

    Analyze clinical, genomic, diagnostic, and market data to uncover patterns that inform the development of innovative therapies. By modeling potential outcomes and unmet needs, life sciences companies can prioritize the most promising therapeutic opportunities with confidence.

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    Common Metrics:

    Opportunity Identification Rate: Number of new therapeutic areas or mechanisms of action identified per cycle.

    Predictive Accuracy: Precision of AI models in forecasting clinical or market success probabilities.

    R&D Investment ROI: Return on investment based on AI-informed portfolio prioritization.

  • Real World Evidence Generation

    REAL WORLD EVIDENCE GENERATION

    Link diverse data sources to create robust, regulatory-ready real world evidence.

    Streamline the creation of high-quality real world evidence by linking diverse data sources and standardizing outputs for regulatory and scientific use. This provides life sciences companies with robust, scalable evidence to support label expansions, payer negotiations, and post-market studies.

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    Common Metrics:

    Evidence Volume and Quality: Number of high-quality, regulatory-acceptable RWE outputs produced per year.

    Study Cycle Time: Reduction in time from data acquisition to publication or submission-ready evidence.

    Regulatory or Payer Acceptance Rate: Percentage of RWE studies adopted in reimbursement or label-expansion decisions.

  • Scientific Paper Research

    SCIENTIFIC PAPER RESEARCH

    Instantly surface insights from vast volumes of publications to guide discovery and strategy.

    Accelerate scientific discovery by scanning thousands of publications, extracting relevant findings, and linking them to your therapeutic area. Life sciences teams gain faster insights into emerging research, competitive activity, and potential biomarkers—reducing weeks of manual review to actionable knowledge in hours.

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    Common Metrics:

    Insight Extraction Speed: Time saved in identifying relevant publications, biomarkers, or clinical findings.

    Research Coverage: Percentage of literature and data sources analyzed across targeted therapeutic areas.

    Evidence Relevance Score: Proportion of extracted insights directly applicable to current R&D or clinical initiatives.

WE DELIVER SOLUTIONS THAT MAXIMIZE THE VALUE OF REAL-WORLD DATA

We transform the siloed, unconnected RWD into an integrated data library, easily analyzable using simple natural language prompts.  Our comprehensive consulting approach guides clients through the end-to-end process of LLM implementation, from assessing business objectives to handling data pre-processing and deployment. We deliver end-to-end solutions that supercharge your RWD analysis.

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TRANSFORM YOUR RWD OPERATIONS

With Ario Health, pharmaceutical manufacturers can leverage LLM technology to uncover patterns, detect novel biomarkers, generate Real-World Evidence (RWE), and improve predictive accuracy. Pharmaceutical manufacturers are now advancing innovation, reducing time-to-market, and enhancing patient outcomes.

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ACHIEVE SUSTAINABLE SUCCESS

We build a program around your LLM operations for ongoing management and improvement. We emphasize continuous refinement and tailoring so that your AI programs consistently gain value through regular monitoring, tuning, and retraining of models. Our team optimizes LLM performance and periodically updates models, keeping companies at the forefront of AI-driven data analysis.

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REALIZE YOUR VISIONS

Through a finely honed process designed specifically for the life sciences industry, we deliver ready-to-use solutions. Engaging in a thorough assessment process, we craft a detailed profile of your AI needs, business objectives, business constraints, and regulatory requirements. Once defined, we deliver an optimal solution that offers the best results.

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Ario Health: Removing the Barriers to Actionable Insights

Healthcare’s digital expansion—from wearables and diagnostics to EHRs and social media—has unleashed massive volumes of Real-World Data. Yet most life sciences firms remain constrained by siloed systems and disconnected datasets.

Ario Health breaks down these barriers. We design and implement domain-specific LLMs that unify structured and unstructured RWD, transforming scattered information into connected, context-rich insights.

Our tailored LLMs expand analytical power without expanding resources—accelerating research, optimizing trials, and deepening patient understanding. The result: faster, smarter, more efficient paths from discovery to market.