Verily's Project Baseline: rebuilding health data from the ground up. Verily's Project Baseline isn't just data collection; it's a structural re-think of health evidence, challenging traditional clinical trial models. The assumption that traditional Randomized Controlled Trials (RCTs) are the sole arbiter of medical truth is becoming a liability, not an asset. Verily's Project Baseline, launched by Alphabet's life sciences arm, offers a compelling counter-narrative, particularly in the US. It's not merely accumulating data; it's architecting a new foundation for real-world evidence, moving beyond the sterile, controlled environment of an RCT to capture the messy, dynamic reality of human health. This shift allows for a granular understanding of disease trajectories and personalized wellness, fundamentally reshaping how interventions are conceived and validated. You might be tracking your sleep with a wearable, vaguely wondering if the data is actually doing anything useful beyond telling you you're tired. You might google "how does my health data help science" or "can my wearable data predict disease." Or perhaps you're a clinician, struggling to piece together a coherent picture of a patient's health trajectory from fragmented EHRs, thinking, "there has to be a better way to understand chronic illness progression." You're looking for insights beyond a single snapshot, beyond a controlled intervention. You're intuiting that the true determinants of health, and the efficacy of interventions, live in the unscripted moments of daily life, not just the clinical visit. Project Baseline's architecture is built on the premise that comprehensive, continuous, and multimodal data streams offer a superior lens into health and disease. Unlike an RCT, which typically focuses on a narrow intervention in a highly controlled group, Project Baseline integrates diverse data types: genomics, imaging, self-reported health, wearable sensor data (e.g., activity, sleep, heart rate), clinical encounters, and environmental factors. This creates a deeply textured, longitudinal health record. This approach addresses the limitations identified by Glasziou and Chalmers (2018), who argued for more relevant evidence derived from routine care rather than just efficacy in ideal settings. The program's Health Study, for example, recruited thousands of participants across the US to collect deep phenotyping data, far exceeding the scope of typical observational studies. This breadth of data allows for the identification of subtle biomarkers and early disease signatures that would be missed by isolated measurements. The mechanism here is one of structural integration and statistical power. By linking diverse datasets, Project Baseline facilitates the creation of robust digital biomarkers and predictive models. For instance, the TCM (Type 2 Diabetes Clinical Management) Study within Project Baseline leverages continuous glucose monitoring and activity data to understand glycemic control in a real-world setting, far more dynamically than intermittent lab tests. This echoes the work of Topol (2019), who champions the integration of 'omics, imaging, and sensor data for precision medicine. The sheer volume and variety of data enable machine learning algorithms to uncover patterns and correlations that are invisible to human clinicians or traditional statistical methods. Raghupathi and Raghupathi (2014) highlight how big data in healthcare transforms descriptive analytics into predictive and prescriptive insights, allowing for proactive rather than reactive care. Project Baseline embodies this transition, using rich data to anticipate disease onset and personalize interventions, shifting the focus from treating illness to sustaining wellness. For clinic founders, this means designing care pathways that can ingest and interpret multimodal data, moving beyond siloed EMRs to integrated health platforms. For clinicians, it means a future where diagnostic certainty and treatment personalization are significantly enhanced by continuous, real-world data streams, requiring new skills in data literacy and interpretation. For tech leaders, the challenge is to build interoperable, secure, and privacy-preserving platforms that can handle this data complexity at scale. Investors should seek out companies developing solutions that can leverage or contribute to such comprehensive datasets, focusing on robust data governance and analytical capabilities. Patients and wellness practitioners should demand transparent data collection practices and engage with platforms that empower them with actionable insights derived from their own real-world health information. Common questions. * Q: What is Project Baseline? * A: Project Baseline is a broad initiative by Verily, part of Alphabet, that aims to map human health using comprehensive, multimodal real-world data. It collects everything from genomics and imaging to wearable sensor data and electronic health records to understand disease progression and wellness over time. * Q: How does Project Baseline help medical research? * A: It provides a massive, longitudinal dataset that allows researchers to identify subtle disease biomarkers, track health changes dynamically, and develop more personalized and predictive models for health and disease. This moves beyond traditional clinical trial limitations by observing health in real-world contexts. * Q: Is my data safe with Project Baseline? * A: Verily emphasizes strong privacy and security protocols, including de-identification where appropriate, to protect participant data. Participants typically provide informed consent outlining how their data will be used and shared for research purposes. * Q: What kind of data does Project Baseline collect? * A: Project Baseline collects a wide array of data, including genetic information, medical imaging, self-reported health surveys, data from wearable sensors (like activity trackers), clinical visit records, and sometimes environmental data. * Q: How is Project Baseline different from a regular health study? * A: It's distinct due to its vast scale, the continuous and multimodal nature of its data collection, and its ambition to create a foundational dataset for understanding the full spectrum of human health, rather than focusing on a single disease or intervention. Tl;dr. * Verily's Project Baseline challenges traditional clinical trial limitations with real-world evidence. * It collects multimodal data: genomics, imaging, wearables, EHRs, self-reports, environment. * This longitudinal data creates robust digital biomarkers and predictive health models. * Project Baseline shifts healthcare from reactive treatment to proactive wellness management. * The initiative drives demand for integrated, data-literate care platforms and skilled clinicians. Sources. * Glasziou and Chalmers (2018): Evidence-Based Medicine. Argued for increasing the relevance of clinical research by integrating real-world data from routine care settings. * Topol (2019): Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again. Championed the integration of 'omics, imaging, and sensor data for a more personalized and predictive approach to healthcare. * Raghupathi and Raghupathi (2014): Journal of Biomedical Informatics. Discussed the transformative power of big data analytics in healthcare, moving from descriptive to predictive and prescriptive insights. * Verily Life Sciences (Ongoing): Project Baseline Official Website. Provides details on the study design, participant engagement, and types of data collected. * Project Baseline Health Study (Ongoing): ClinicalTrials.gov Identifier: NCT03154817. Publicly available information on the large-scale observational study component of Project Baseline.

PacBio and Verily Health announce multi-year strategic collaboration to scale long-read genomics for biomedical AI. Verily Pre will connect PacBio HiFi Sequencing with governed cloud analysis, multimodal health data and AI-ready research workflows. October 19, 2026 09:05 ET | Source: PacBio MENLO PARK, Calif. and DALLAS, Oct. 19, 2026 (GLOBE NEWSWIRE) - PacBio (NASDAQ: PACB), developer of the world's most advanced sequencing technologies, and Verily Health Inc., a healthcare data intelligence company, announced today a multi-year strategic collaboration to integrate PacBio HiFi sequencing with Verily Health's governed data and AI platform. The collaboration will link PacBio sequencing workflows to Verily Pre, combining long-read genomic data with real-world clinical data at population scale. The resulting AI-ready clinico-genomic datasets will support biomedical discovery efforts and AI model training and deployment. The collaboration addresses a growing bottleneck in biomedical AI: increasingly powerful models require biological data with greater depth, context and scale. Long-read sequencing can reveal complex genetic variants, structural changes, methylation information, and full-length RNA transcripts that are difficult to capture with short-read approaches, offering richer insights into disease biology. Yet, processing these large, complex datasets and integrating them with clinical data for model training remains fragmented, unscalable and largely bespoke. PacBio and Verily Health intend to connect those steps, making rich genomic data more accessible and usable to power the next generation of biomedical AI applications. Verily Pre already supports population-scale biomedical research, while Workbench serves more than 20,000 researchers and has supported more than 700 publications. And because PacBio HiFi whole-genome sequencing workflows already run end-to-end within the Verily Pre environment, it provides an existing and robust technical foundation for the multi-year collaboration. "This collaboration reflects a shared focus on making high-quality genomic data more accessible and useful across research and development, while creating a foundation for continued innovation in health," said Stephen Gillett, Chairman and CEO of Verily Health. "Working with PacBio, we hope to deliver a meaningful impact to researchers and innovators working to find new answers for neurology, oncology, rare disease, and other areas of critical unmet need." "PacBio HiFi sequencing offers our customers the most complete and highest quality data available, which is ideal for training AI models where the input determines the success of the output" said Mark Van Oene, President and CEO of PacBio. "Through this collaboration with Verily Health, we are building a path to turn richer biological data into AI-ready data at scale to ultimately help researchers get more from both their sequencing and their models." Verily Pre provides the foundation to build, deploy and scale intelligent applications across healthcare and life sciences. Under the collaboration, Verily Health will configure Pre Workbench to connect PacBio sequencing workflows, acting as the secure governed research environment for the aggregation, analysis, and curation of HiFi genomic datasets. The companies also plan to use the Verily Pre trusted agentic environment (TAE) to run model training and inference, enabling researchers to explore deeper, longitudinal genomic datasets and support their workflows. Over the course of the multi-year collaboration, PacBio and Verily Health plan to expand the integration to support increasingly large and complex long-read programs across research organizations, biopharma and population genomics. The companies envision a common infrastructure that can scale with increasingly large and complex long-read programs, supporting multimodal research and AI development across biopharma, clinical institutions, population genomics and other areas of precision health. About PacBio PacBio (NASDAQ: PACB) is a premier life science technology company that designs, develops, and manufactures advanced sequencing solutions to help scientists and clinical researchers resolve genetically complex problems. Our products and technologies, which include our HiFi long-read sequencing, address solutions across a broad set of research applications including human germline sequencing, plant and animal sciences, infectious disease and microbiology, oncology, and other emerging applications. For more information, please visit www.pacb.comand follow @PacBio. PacBio products are provided for Research Use Only. Not for use in diagnostic procedures. About Verily Health Inc. At the intersection of technology, data science, and healthcare, Verily Health transforms complex health data into trusted intelligence, enabling health solutions that are more personal, predictive, and precise. Verily's flagship Governed Health Intelligence platform, Verily Pre, enables healthcare organizations to responsibly govern, model, and securely activate their protected health data at scale, deploying intelligence with the scientific rigor, oversight, and auditability needed for healthcare. Disclaimer: The Verily Pre platform is not a medical device and has not been evaluated by the FDA. Customers developing Software as a Medical Device (SaMD) are solely responsible for regulatory compliance. Forward looking statements This press release may contain "forward-looking statements" within the meaning of Section 21E of the Securities Exchange Act of 1934, as amended, and the U.S. Private Securities Litigation Reform Act of 1995. All statements other than statements of historical fact are forward-looking statements, including statements relating to the availability, uses, accuracy, advantages, quality or performance of, or benefits of using, or expected benefits of using, PacBio products or technologies, including in connection with the collaboration between PacBio and Verily Health; plans to integrate PacBio HiFi sequencing with Verily Health's governed data and AI platform to create AI-ready clinic-genomic datasets; making genomic data more accessible and usable to power future biomedical AI application and create a foundation for continued innovation in health; impact in finding new answers for neurology, oncology, rare disease, and other areas of critical unmet need; building a path to turn richer biological data into AI-ready data; Verily Health configuring Pre Workbench as secure governed research environment; the use of TAEs to run model training and inference; developing a common infrastructure capable of supporting increasingly large and complex long-read programs; and other future events. You should not place undue reliance on forward-looking statements because they are subject to assumptions, risks, and uncertainties and could cause actual outcomes and results to differ materially from currently anticipated results, including, challenges inherent in using, and collaborating with third parties to develop, new technologies; potential product performance, interoperability and quality issues; potential regulatory issues relating to the development and use AI technologies; rapidly changing technologies and extensive competition in, and potential FDA regulatory issues relating to, genomic sequencing; unanticipated increases in costs or expenses; interruptions or delays in the supply of components or materials for, or manufacturing of, PacBio products and products under development; third-party claims alleging infringement of patents and proprietary rights or seeking to invalidate PacBio's patents or proprietary rights, among others. Additional factors that could materially affect actual results can be found in PacBio's most recent filings with the Securities and Exchange Commission, including PacBio's most recent reports on Forms 8-K, 10-K, and 10-Q, and include those listed under the caption "Risk Factors." These forward-looking statements are based on current expectations and speak only as of the date hereof; except as required by law, PacBio disclaims any obligation to revise or update these forward-looking statements to reflect events or circumstances in the future, even if new information becomes available. Media Contacts