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The Evidence



Real-world data

Building the future of behavioral health with Real-World Data and analytics
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the urgent need

Behavioral health disorders are a defining problem of our generation.

Behavioral health is a fundamental and persistently overlooked aspect of overall health. Mental and substance use disorders impact a staggering 970 million people worldwide, with over US$1 trillion in global economic burden each year. Despite the skyrocketing crisis, progress has lagged behind other disease areas. Less than half of those living with major depression, the most widespread mental illness, reach remission on currently available treatments. Recent rising awareness has driven demand onto a system not equipped to support the depth and breadth of need.

There is a debilitating evidence gap that inhibits research and innovation, stemming from inherent limitations in behavioral health: complex disease etiologies, lack of quantifiable biomarkers, and institutional silos. Despite decades of research, we still do not know how to alleviate most behavioral health disorders.

We need new solutions, and we need them now.

Code Templates

Analytics Tools

Research-Grade EHR

Collage of different NeuroBlu panels that shows the following graphs: cohort count, distribution of age, proportion of gender, patient count by race and number of visit per patient.

Reimagining Behavioral Health

NeuroBlu is a data and analytics platform that enables uniquely powerful evidence generation. With the most robust behavioral health database of its kind and seamless AI-powered analytic tools, NeuroBlu gives researchers, pharma, clinicians, and other industry partners the ability to create insights like never before.

More than just an analytics tool, NeuroBlu enables discovery to improve lives.

Behavioral health transformation starts here.


Scientifically Validated,
Clinically Meaningful Insights

NeuroBlu gives users unprecedented ability to generate novel insights, with longitudinal structured data on disease severity, symptoms, side effects, and external stressors.

Abstract representation of a non-linear research approach


Delve into a rich, unique database in an easy-to-use interface designed for fast and scalable queries


Investigate research questions with an integrated R interface, advanced analytics packages, and our built-in Holmusk-developed code library


Generate insights with longitudinal severity scores and NLP-derived signs and symptoms, external stressors, and side effects


Powerful Behavioral Health Data

NeuroBlu is fueled by a uniquely powerful behavioral health database, the only one of its kind.

Leading Source for Behavioral Health Real-World Evidence




Rows of data


Years of longitudinal data


diverse psychiatry clinics

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Over 20 years of longitudinal data and patient records spanning both inpatient and outpatient sites including hospitals, emergency departments, and community psychiatry clinics

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Meaningful clinical information not typically captured in a structured way is transformed into analyzable keywords representing a large family of symptoms, side effects, and external stressors

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Quantitative outcome measure allows users to track patient function and outcomes over time and understand efficacy of different interventions


Uncovering Real-World
Insights with NLP

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Over 300 psychiatry-specific labels

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NLP model trained on notes from over 11,000 clinicians and 6 million data points

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Disease severity score for most encounters

Our novel Natural Language Processing (NLP) algorithm transforms rich clinician notes into structured data that predicts disease severity.

Clinician notes are valuable troves of information on patient experience, treatment response, and outcomes that are not captured in other EHR or claims data sources. Analyzing unstructured notes is typically arduous and time-consuming.

Our proprietary NLP model unlocks insights from clinician notes, allowing for large-scale analysis and disease modeling. We have over 300 psychiatry-specific structured labels on granular symptoms, side effects, external stressors, and more. These labels can also be used to predict disease severity based on CGI-S scores, opening up a new frontier for scalable analysis of patient experiences through clinician notes.

Going beyond standard context-aware keyword search NLP approaches, our proprietary NLP models are designed specifically to handle the complexity of psychiatric care, which lacks standardized terminology and relies heavily on subjective assessments and verbose descriptions. Our NLP approach leverages the latest innovation in machine learning and language modeling to interpret full sentences using an attention based deep learning, producing granular structured data labels.

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Over 300 psychiatry-specific labels

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NLP model trained on notes from over 11,000 clinicians and 6 million data points

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Disease severity score for every encounter


Accelerate Evidence Generation with Fast, Scalable Studies

Designed by a team of scientists, clinicians, and industry experts, NeuroBlu's robust tools drive Real-World Evidence generation with unparalleled ease.

NeuroBlu's custom-built architecture brings the power of high-performance computing and innovation to real-world studies. User-friendly tools streamline typically laborious and error-prone analysis steps, enabling users to get to insights without having to spend hours cleaning data and troubleshooting code. Built-in custom libraries let you use the data with ease - no need to spend hours navigating a complex data model, because our data scientists did it for you.

Data Explorer showcasing multiple number of data tables available,

View data and get high-level summaries of the dataset, including a set of visualizations describing the population characteristics

Cohort Builder interface with updated statistics based on the user's cohort selection.

Intuitive graphical interface allowing you to build your study cohort using a few clicks, and view cohort characteristics with charts updated in real-time

Category Mapper that shows antidepressant drugs selected.

Simple and streamlined tool to build groupings of values (e.g., diagnosis codes or drug type) to create custom categories for use across multiple projects in a simple and less error-prone way

R Code interface that showcases the code panel with different types of files such as 'R', CSV, Image.

Perform custom analytics in R with your own code or from our built-in library of code templates for popular studies

New Releases



Perform powerful analyses using Holmusk's proprietary advanced analytics packages, created by our data scientists to provide easy access to frequently used analytics methods such as survival analysis and comparative effectiveness studies

Project Notes

Seamlessly annotate, replicate, and compare results across your research studies with our integrated Project Notes feature, allowing users to write and store research notes


Bring Treatments to Market Faster with Real-World Evidence

Address key research questions to drive clinical
and commercial success in life sciences.

Research and Development

Improve probability of technical success and reduce cycle times

R&D Strategy

  • Identify opioid use disorder patient subsegments with unmet needs, such as poor outcomes despite being on a treatment regimen

Clinical Development

  • Identify characteristics of patients with Major Depressive Disorder with anhedonia to enrich screening for clinical trials and significantly accelerate recruitment
  • Understand propensity of acute phases in patients with Major Depressive Disorder with varying degrees of severity and subsegment to inform design of trials for a drug candidate targeted towards treatment-resistant depression

Medical Affairs

Investigate clinical context driving prescription behaviors and improve clinical guidelines

  • Compare key endpoints - such as Clinical Global Impression-Severity (CGI-S), Global Assessment of Function (GAF), and side effect burden - for patients on competitor drugs to provide evidence of differentiated benefit
  • Design and characterize more patient-centric endpoints such as mood, function, and engagement in real world settings that can significantly affect patient adherence, clinician prescription decisions and overall outcomes
  • Evaluate patterns in product off-label usage of Major Depressive Disorder drugs in other behavioral health indications and identify opportunities for further clinical evaluation
  • Create publications highlighting therapeutic benefit in real-world settings to increase impact factor with Key Opinion Leaders and other HCPs

Market Access and HEOR

Evaluate real-world comparative outcomes and enable value-based care

  • Determine comparative effectiveness beyond standard clinical endpoints, e.g., hospitalization among patients on different drug formulations (e.g., oral versus long acting injectable atypical antipyschotics) to establish cost-benefit
  • Track drug performance in real-world settings and identify opportunities for value-based arrangements

We're Here to Help

We know data is only as useful as its impact. Our team has spent years building expertise in the intricacies of behavioral health data, and we will work collaboratively with you to help generate evidence that matters.

Training and Reference Tools

Rapid onboarding and training with dedicated customer support plus in-depth tutorials and FAQs

Customer Success

Dedicated support to help you extract the most value from your NeuroBlu license

Advanced Analytics Services

Tap into our data science and machine learning expertise for custom analytics

Contact us

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