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Verily

Unlock unprecedented insights into human health and the transition to disease with the Verily Project Baseline Health Study (PBHS) dataset. This landmark longitudinal study, conducted by Verily in collaboration with Duke University, Stanford Medicine, and others, deeply characterizes approximately 2,500 diverse individuals over four years. The PBHS integrates extensive clinical assessments, medical imaging, continuous sensor monitoring via the Verily Study Watch, and rich participant-reported outcomes to create a comprehensive, multi-dimensional map of health. Leverage this unique, deeply phenotyped dataset to explore the definition of healthy baselines, explore early markers of disease, understand health trajectories, and develop new predictive health models using integrated, high-resolution data collected both in-clinic and in real-world settings.

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Project baseline

Project Baseline

Explore the Project Baseline Health Study (PBHS) dataset. Access longitudinal clinical, sensor, and participant data from 2,500 individuals. Unlock insights into human health & disease

Project Baseline | Verily | Data Catalog

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Gain near real-time insights into community health trends with Verily Sightline Wastewater Data. This public health monitoring offering leverages advanced pathogen detection and  quantification to monitor the presence and concentration of various infectious disease pathogens circulating within communities. By analyzing pathogen RNA/DNA in wastewater samples collected from diverse locations , Sightline provides an early warning system, complementing clinical-based  surveillance systems and often detecting trends before clinical cases rise. Utilize this population-level data to track infectious disease spread, inform interventions, and support research efforts aimed at monitoring and mitigating disease impact.

Sightline Wastewater

Get near real-time community health insights with Verily Sightline Wastewater Data. Track infectious disease trends, inform interventions, and support research efforts

Sightline Wastewater | Verily| Data Catalog

Sightline Wastewater | Verily | Data Catalog

Accelerate your Amyotrophic Lateral Sclerosis (ALS) research with the Target ALS Data Collection – a comprehensive ecosystem of integrated, critical resources provided with minimal restrictions. Overcome common research barriers by accessing standardized, well-characterized components designed to fuel discovery:


Integrate insights across these unique resources – tissue, cells, and longitudinal fluid/clinical data – to investigate ALS mechanisms, discover and validate novel biomarkers, and drive the development of effective treatments.

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Target ALS

Accelerate ALS research with the Target ALS Data Collection. View and access longitudinal biofluids, postmortem tissue, & iPSC lines. Fuel discovery & treatment development

Target ALS | Data Catalog

This large-scale international dataset provides access to genomic data (primarily whole-genome genotyping and sequencing) from over 70,000 participants, including individuals with Parkinson's disease (PD) and related disorders, related individuals, and healthy controls, with a strong emphasis on genetic diversity. It is a critical resource for researchers investigating the genetic architecture of PD, identifying novel risk variants across diverse populations, exploring gene-environment interactions, and accelerating the development of genetically informed therapies.


GP2 (Global Parkinson’s Genetics Program) comprises a collection of independently led active and completed studies of Parkinson's disease with genetic data collection. Cohort contributors to GP2 are partners in its global mission to improve our understanding of Parkinson's disease and accelerate scientific breakthroughs.

Global Parkinson's Genetics Program | Michael J Fox Foundation

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Overview of GP2, a large-scale international Parkinson's genetics dataset with genomic and clinical data from over 70,000 participants. Accelerate your PD research

GP2 | ASAP Initiative | MJF Foundation | Data Catalog

ASAP is a global research initiative changing the way science is typically done. By emphasizing collaboration, generation of research-enabling resources, and data sharing, ASAP is accelerating the pace of discovery and informing the path to a cure for Parkinson’s disease. ASAP is managed by the Coalition for Aligning Science and implemented in partnership with The Michael J. Fox Foundation for Parkinson’s Research.


Access a unique portfolio of cutting-edge resources designed to deepen our understanding of Parkinson's disease (PD), generated by the ASAP CRN, an international, multidisciplinary, and multi-institutional network of collaborating teams working to address high-priority research questions. Explore diverse datasets focused on critical knowledge gaps in PD Functional Genomics, Neuro-Immune Interactions, and Circuitry/Brain-Body Interactions


This openly shared collection includes significant resources like:

Leverage these resources - emerging from a network committed to open science - to accelerate your research, uncover novel mechanisms, and identify potential therapeutic targets for Parkinson's disease.

ASAP Collaborative Research Network (CRN)

Aligning Science Across Parkinson’s (ASAP) | Michael J. Fox Foundation

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ASAP CRN

Explore the ASAP CRN data catalog from Verily. Access Parkinson's disease research data from the ASAP Initiative & MJF Foundation. Accelerate discovery with multi-modal datasets.

ASAP CRN | ASAP Initiative | MJF Foundation | Data Catalog

The Verily Data Catalog includes proprietary datasets collected via Verily solutions across research, care, and public health, plus a growing set of multimodal partner datasets available for analysis.

Join thousands of researchers on the Verily Platform Pre. Create a free Pre account via Verily Workbench, to browse the full data dictionary and request access.

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Explore Verily's data catalog, featuring proprietary datasets and partner datasets for research, care, and public health. Access multi-modal data for analysis.

Verily Data Catalog

The 10,000 Brains Project is a philanthropic initiative designed to accelerate the use of artificial intelligence (AI) and computational methods in the fight against neurodegenerative diseases. This project is creating a large-scale, open-access digital brain bank of up to 10,000 neuropathology cases from patients with conditions such as Alzheimer's, Parkinson's, and Frontotemporal Dementia (FTD). The core of this resource consists of ultra-high-resolution whole slide images of brain tissue, which will be shared freely with the global research community.

The 10,000 brains project

Path ND

Path-ND Digital Brain Banking Program

Path-ND

Accelerate the use of artificial intelligence (AI) and computational methods in the fight against neurodegenerative diseases with the 10,000 Brains Project.

Path-ND | 10,000 Brains Project | Data Catalog

Access the All of Us dataset - a uniquely large and multimodal longitudinal dataset from over half a million participants across the United States.  Verily partners with Vanderbilt University Medical Center (VUMC) as the All of Us DRC to support the National Institutes of Health (NIH) All of Us Research Program’s Researcher Workbench platform.

This resource integrates participant-provided information (surveys), electronic health records, physical measurements, extensive genomic data (whole genome sequences, arrays), and wearable device data. It is designed to support research across nearly all health conditions, enabling exploration of individual differences in biology, lifestyle, and environment that influence health and disease. Data is accessible via the Researcher Workbench following 

 Research Program, Curated Data Repository (CDR)

All of us research program

All of Us CDR

Access the All of Us dataset - a uniquely large and multi-modal longitudinal dataset from over half a million participants across the United States.

All of Us CDR | All of Us | Data Catalog

Go beyond the limitations of traditional real-world data. Standard real-world datasets, derived from fragmented EHRs, leave critical gaps in the patient story. They lack the high-resolution lifestyle, behavioral, and continuous monitoring data needed to truly understand cardiometabolic disease. Verily’s Cardiometabolic Cohort dataset is built differently. Sourced from our engaged 

 community, we connect directly with consented participants to fill in those gaps — capturing the rich, longitudinal data, from patient-reported GLP-1 side effects to continuous readings from devices (e.g. CGMs, consumer wearables), that EHRs or claims data alone simply cannot provide.

This unified view empowers you to evaluate real-world treatment effectiveness, predict disease progression, derive novel variables from unstructured data, and answer prospective research questions through participant re-contact — ultimately informing the development of more personalized and effective therapies.

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Use cases unlocked with the foundational Cardiometabolic Cohort dataset

Use cases unlocked with advanced offerings for patient recontact, data linkage, and/or custom variables

Advanced Offerings and Custom Research Services

While standard RWD struggles to capture the ‘why’ behind a therapy change, Verily’s platform can uncover this deep clinical context. We leverage advanced methodologies, like applying large language models (LLMs) to unstructured physician notes, to derive custom variables critical to your research. 

The following is an example of the deep insights our platform's AI-powered methodologies can unlock for custom research projects.



Examples of GLP-1 Switching Reasons, Identified and Categorized from Unstructured Data

e.g. Achieved desired effect


“The patient used to take GLP-1 (Ozempic) and switched to another drug (SGLT2 inhibitor, Empagliflozin/Jardiance). The reason for the switch was noted as improvements in weight and diabetes control, potentially indicating achievement of desired effect.”




“The patient was taking Ozempic (a GLP-1) and stopped because they "did not see any weight benefit from it and also her sugars are elevated". They switched to Tirzepatide (another GLP-1).”




“The patient stopped taking the GLP-1 medication Ozempic due to significant digestive problems (constipation).”




“The patient was taking the GLP-1 medication Wegovy for weight loss, but switched to or stopped due to the insurance denial of prior authorization, which is a non-trivial reason (insurance coverage/cost-related).”




“Switched from dulaglutide (a GLP-1 receptor agonist branded as Trulicity) to tirzepatide (Mounjaro), which is another type of GLP-1 medication. The reason for this switch was due to the pharmacy having difficulty obtaining Mounjaro, although the patient was tolerating it.”

This ability to derive data from unstructured notes offers an additional layer of deep clinical insight, showcasing the power of Verily's platform to generate custom variables critical to your research goals. Partner with us to apply this same AI-powered methodology to derive custom variables from clinical notes that are critical to your specific research goals.

Data Spotlight: Uncovering the 'Why' Behind Treatment Changes

Cardiometabolic Cohort

Explore Verily's Cardiometabolic Cohort dataset. Access longitudinal, real-world data including clinical, survey, and lab data from a diverse cohort with cardiometabolic conditions to advance research and understanding of patient journeys.

Cardiometabolic Cohort | Verily | Data Catalog

Segmed streamlines access to diverse, high-quality real-world data, including medical imaging and clinical records. Segmed’s platform allows for building fit-for-purpose datasets with access to approximately 30 million patients including 150 million de-identified standardized imaging datasets and associated clinical data through a global network of healthcare partners across five continents. This specific dataset contains digital breast tomosynthesis (DBT) exams of 558 patients with breast imaging reporting and data system (BI-RADS) scores of 0, 1, or 2. 271 patients have biopsy proven malignant lesions and 287 patients were benign. Each case contains at least one DBT examination in combination with prior and follow-up breast exams, expert annotations and free-text radiology reports that describe the radiological findings, produced in routine clinical practice. To protect patient privacy, all images and reports have been de-identified.

Segmed: Breast Cancer Imaging - Digital Breast Tomosynthesis (DBT)

Digital breast tomosynthesis (DBT) is a powerful imaging modality that allows for improved lesion visibility, characterization, and localization compared to conventional two-dimensional digital mammography. DBT has been increasingly adopted in screening and diagnostic settings globally, particularly for women with dense breast tissue where tissue overlap presents a significant diagnostic challenge. Use cases include, but are not limited to:

Note that Segmed’s data is available through Datavant for overlap assessment.

Segmed

Access Segmed's DBT dataset of 558 patients (BI-RADS 0-2). It includes 271 malignant and 287 benign cases, annotations, and de-identified radiology reports.

Digital Breast Tomosynthesis | Segmed | Data Catalog

This longitudinal dataset includes 393 newly diagnosed Acute Myeloid Leukemia (AML) patients treated with Venetoclax plus Azacitidine as a first-line therapy. The dataset tracks patients from their diagnosis date (EVENT) through treatment, follow-up, and subsequent therapies. It is derived from the RefinedScience platform, which combines high-fidelity clinical data with single-cell omics to identify novel drug targets and stratify patient risk.


Key features include access to companion analysis tooling for patients who had CITE-seq performed on bone marrow specimens at diagnosis and/or follow-up timepoints. This unique dataset supports precision medicine by linking granular clinical outcomes with deep molecular profiling.

Refined Science

Longitudinal dataset of newly diagnosed AML patients treated with Venetoclax plus Azacitidine. Includes clinical data, outcomes, and single-cell omics via companion analysis tooling.

RefinedScience AML Dataset | RefinedScience | Data Catalog

Advance your research into Parkinson's disease (PD) and related neurodegenerative disorders with the AMP® PDRD initiative. Building upon the foundational AMP® PD program, this expanded public-private partnership (managed by FNIH) integrates data to address PD and conditions with similar biology or symptoms (e.g., synucleinopathies, atypical Parkinsonisms). Access integrated, harmonized multi-omics and clinical data designed specifically to accelerate the discovery and validation of biomarkers that can differentiate these conditions, track progression, stratify patients, and ultimately improve clinical trial success and broaden treatment options across this spectrum of diseases.

Foundation for the National Institutes of Health

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AMP PD / PDRD

Advance research on Parkinson's disease and related neurodegenerative disorders with the AMP® PDRD initiative. Access multi-omics and clinical data to accelerate biomarker discovery

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