Data analysis platforms — Breaking down barriers to advance biomedical research

With advances in DNA sequencing, multiomics, wearables, imaging, and clinical data capture, there are more data modalities to draw from for biomedical research than ever before. These diverse datasets are the foundational building blocks of research. Alone, they are only a glimpse into our understanding of human biology and disease. Data harmonization and analysis are needed to help identify more novel drug targets and evidence that reveal the next breakthroughs.

Multimodal data also fuels AI/ML methods for faster development of new therapies. According to the Nature journal article, AI in small-molecule drug discovery: a coming wave?, biotech companies using AI-driven approaches to drug discovery have more than 150 small-molecule drugs in the pipeline, and more than 15 in clinical trials.¹ This AI-powered pipeline is expanding at an annual rate of almost 40%.¹

To fully realize data potential, it has to be FAIR — findable, accessible, interoperable, and reusable. But multimodal health data is often highly disorganized and siloed, and has disparate sources, formats, terminologies and usage rights. Also, the speed data is generated far outpaces researchers’ ability to utilize it. Existing technologies are unfit to help organizations unlock the promise of data, broaden its reach, and foster necessary, cross-industry partnerships to push scientific progress for breakthroughs. 

With expanding data pools, genomics research is plagued with similar data access and use challenges as other biomedical data types, such as technical challenges in scaling analysis, lack of standardization, privacy and security concerns, data silos, format incompatibility, and need for data aggregation and harmonization. These barriers limit genomic data use and surface inequities, creating more urgency for answers to genomic and other health data processing and sharing in order to support research and development of critical precision medicines and therapies. 

Without scientific and medical communities working together with the right tools and infrastructure to store, manage, harmonize, analyze, and share all health data in scalable, federated ways, its use in advancing biomedical research and development is limited, which ultimately costs time and money, and negatively impacts patient care and health outcomes. 

Read on to learn how data analysis platforms can offer a solution by helping researchers overcome barriers to health data access and analysis by providing collaborative research tools with the data governance and policy oversight to help safely support research speed and scale.

Through enterprise-wide infrastructure, biomedical data and analytics platforms enable more seamless and secure research workflows with tools and features to ingest, process, validate, curate, store, govern, and share data. 

Data analysis platforms can provide a “space” to build stronger communities for more effective, cross-functional collaboration regardless of company or location, fostering industry and academic partnerships for pushing progress, utilizing reproducible research, and ensuring research integrity through data governance platforms. In addition, they can enable a greater meeting of more minds by helping researchers across all disciplines and experience levels — from computational biologists, bioinformaticians, and principal investigators to data scientists, data stewards, and more — speak the same “language” with fit-for-purpose tools, such as pre-configured biomedical data analysis and data visualization tools. 

The platforms also enable large-scale medical research initiatives through multimodal data integration, modeling, and linking of fragmented sources, as well as helping manage the data lifecycle through comprehensive research management plans. For example, the National Institutes of Health (NIH) All Of Us Research Program is building a unique dataset, supported by the Researcher Workbench, an application developed in collaboration with Verily. Built as a trusted research environment, the Researcher Workbench is a secure, cloud-based platform where registered researchers across the globe can access and analyze a wide range of datasets for progressing precision medicine through greater understanding of the human genome and biological basis of disease. 

Cloud technology is also revolutionizing international biomedical data analysis platforms, offering security, scalability, and partnership opportunities. For example, UK Biobank’s cloud-based, Research Analysis Platform democratizes access to health information, contributing to today’s rich and expanding data landscape by developing a large-scale biomedical database and research resource containing de-identified genetic, lifestyle and health information, and biological samples from a vast number of United Kingdom participants for worldwide researcher access and use. 

Built on the foundation of Alphabet’s leading technology and data capabilities, Workbench is Verily’s secure data analysis platform for governing and sharing global, multimodal health data. Workbench helps solve problems in advancing biomedical research by de-siloing scientifically-valuable data, making it more discoverable, accessible, and analyzable. 

Workbench supports easier, more efficient, and more secure research for biomedical data analysis by enabling collaborative analysis of data from many sources, organizations, and geographies, while more easily adhering to regulatory and ethical policies with an integrated data governance platform. To accomplish all this, the platform is built with intuitive tools and safeguards for controlling the end-to-end data lifecycle, conducting reproducible research, and working together securely within, and across, research organizations with the full power of cloud computing in biomedical research.

Along with the All of Us Research Program and the UK Biobank, other healthcare leaders are looking to help transform research via a data analysis platform. For example, Workbench is supporting research for Parkinson’s disease, and amyotrophic lateral sclerosis (ALS)  — The Michael J. Fox Foundation (MJFF), Target ALS, and Helix, respectively. 

Helix, a population genomics and viral surveillance company, utilizes Workbench as a collaborative, genomic data processing and analysis environment for their health systems partners and commercial customers. 

Workbench supports MJFF, a global Parkinson’s research organization, collaborators such as the Aligning Science Across Parkinson’s (ASAP) initiative and its resource program the Global Parkinson’s Genetics Program (GP2) and data-sharing tool, the CRN Cloud, with more planned. And Workbench powers the Accelerating Medicines Partnership® Parkinson’s Disease (AMP PD) program. Managed by the Foundation for the National Institutes of Health (FNIH), AMP PD is a partnership with the NIH, along with multiple biopharma and life sciences companies and non-profit organizations, focused on biomarker discovery to advance therapy development for Parkinson’s disease.

Workbench also enables the Target ALS to aggregate their data and make it available to ALS researchers for advancing disease understanding, and accelerating treatments to market.

In addition to these partners strengthening biomedical research in numbers, Workbench use has grown exponentially in recent years, supporting both data provider and data consumer clients — from a top 40 pharma company and venture-backed biotech companies, to health systems and more.

It’s clear biomedical researchers are challenged by needing better data that’s harmonized and complete, better data analytics and compliance capabilities, and better ways to partner in order to advance medicine. Data analysis platforms can tend to these needs. This includes Verily Workbench data analysis platform, which helps catalyze research and development for pharma and biotech by providing the collaborative research tools and infrastructure to modernize and simplify data analytics with an integrated data governance platform. Workbench also connects data generators and providers to data consumers, such as pharma and biotech customers, to help expand their biomedical data reach and purpose, while helping answer the need in biomedical and genomics data processing, access, and sharing. 

Through greater industry partnerships, Workbench users can also help strengthen the overall health data ecosystem and connect scientific communities for uncovering medical breakthroughs, realizing the promise of precision medicine, and ultimately, bringing vital therapies to individuals who need them.

1. Jayatunga MKP, Xie W, Ruder L, Schulze U, Meier C. AI in small-molecule drug discovery: a coming wave? Nat Rev Drug Discov. 2022 Mar;21(3):175-176. doi: 10.1038/d41573-022-00025-1. PMID: 35132242.
2. Data silos threaten efficiency levels for nearly half of pharma businesses.  European Pharmaceutical Manufacturer website. https://pharmaceuticalmanufacturer.media/pharma-manufacturing-news/latest-pharmaceutical-manufacturing-news/data-silos-threaten-efficiency-levels-for-nearly-half-of-pha/. Updated February 13, 2023. Accessed July 26, 2024.