Noah Nasser is the CEO of datma (formerly Omics Data Automation), a leading provider of federated real-world data platforms and tools related to analytics and visualization. datma’s mission is to help healthcare organizations optimize their data assets, drive innovation and improve patient outcomes through advanced data storage, AI-powered data orchestration, and federated query and workflow technologies. Headquartered in Oregon, the company is leading the way in transforming how healthcare data is shared, monetized and applied, enabling secure collaboration between data custodians and data consumers.
Can you explain how datma.FED is using artificial intelligence to revolutionize healthcare data sharing and analysis?
datma.FED integrates AI-driven analytics tools to securely execute queries across our federated network. Its advanced algorithms help extract, aggregate and deliver de-identified, shareable data sets, enabling data consumers such as pharmaceutical companies and research organizations to extract insights while ensuring full compliance and privacy standards.
By automating complex data queries, datma.FED accelerates access to high-quality, ready-to-use real-world data. This enables data custodians such as health systems and molecular laboratories to participate in collaborative research efforts while maintaining full control of their data assets.
What are the main challenges datma solves for molecular laboratories and health systems?
datma.FED addresses several key challenges for molecular laboratories and health systems, including:
- Data Monetization: Ability to continuously generate revenue from underutilized healthcare data while allowing data custodians to retain full ownership and control.
- Data privacy and security: Keep sensitive data secure with a privacy-first federated model that ensures it never leaves the data custodian’s environment.
- Data compliance risks: Minimize regulatory risk with audit-ready data access controls and comprehensive compliance tracking.
- Data preparation and business development: datma is responsible for data preparation to ensure data readiness while connecting data custodians with research and pharmaceutical partners.
How does datma ensure data privacy and compliance while enabling secure collaboration between data custodians and data consumers?
datma.FED uses a federated network model to securely store data within each custodian’s environment while enabling privacy-first collaboration with data consumers. Data goes through a multi-step process: it is anonymized, filtered for accessibility, and designated as shareable based on permissions defined by the custodian. datma then processes external queries without transferring raw data and only aggregates approved, de-identified data fields. Cell size limits prevent re-identification. Every data interaction is auditable and compliant with regulatory standards such as HIPAA.
How does datma.FED differ from other data platforms in terms of scalability and usability?
datma.FED is designed to scale seamlessly through its federated architecture and automated data preparation capabilities. Its design allows for seamless integration of multimodal healthcare data from multiple sources. The platform’s automated data preparation capabilities, including data labeling and normalization, simplify data preparation and reduce manual work. By ensuring data is queryable and compliant from the start, datma.FED enables large-scale, privacy-first data sharing, making it highly scalable and intuitive for research and real-world data applications.
How does the datma.FED platform facilitate multimodal healthcare data integration across silos?
datma.FED facilitates the integration of multimodal healthcare data across silos through one of its components, datma.BASE. datma.BASE is a comprehensive framework built on proprietary data stores, containers, and APIs. At scale, its advanced capabilities enable the ingestion, aggregation, and coordination of disparate healthcare data types (EHR, omics, imaging, and pathology). By breaking down data silos, datma.BASE transforms fragmented data sets into unified, actionable insights.
How can datma’s technology help bridge the data gap in pharmaceutical research and drug development?
datma.FED helps fill critical data gaps for drug research and market access strategies. datma.FED enables pharmaceutical companies to make more data-driven decisions by providing high-quality, ready-to-use real-world data (RWD) with granularity and longitudinal depth. Its secure infrastructure ensures data remains accessible without compromising privacy or security, supporting the comprehensive insights needed to discover.
How does datma enable healthcare organizations to monetize their data while maintaining ethical and regulatory standards?
datma enables healthcare organizations to monetize their data by creating a secure data sharing ecosystem where healthcare organizations retain full ownership and control. Through its federated network, data custodians can determine which data can be accessed and shared while keeping sensitive information securely within their own infrastructure. Comprehensive audit trails, role-based permissions, and compliance capabilities ensure that all data sharing activities adhere to ethical standards and privacy regulations. This approach enables healthcare organizations to generate new revenue streams while protecting patient privacy and maintaining trust.
Which trends in artificial intelligence and healthcare data do you expect to have the greatest impact over the next five years?
Artificial intelligence in healthcare is influenced by concerns about privacy, security, and is limited only by data quality. Artificial intelligence is already enabling us to deliver truly personalized care in oncology, but has only scratched the surface of what is possible. By analyzing large amounts of multimodal patient data, including genomics, imaging and biomarker data as well as medical history, demographics and lifestyle factors, we will tailor treatment plans and therapies based on individual needs. This can improve patient outcomes and ultimately reduce healthcare costs. Combining these tools with remote patient monitoring and patient-reported outcomes will enable early disease detection and improve compliance with treatment plans. The key key to all of this, however, is a sufficiently diverse source of deep contextual data.
Additionally, artificial intelligence will be key to delivering advanced personalized care. I think AI models can play a role in streamlining payer and billing logistics, simplifying tedious paperwork, and ensuring access and equity for all. Currently, LLMs have shown some limitations in this application; recent publications have pointed out their shortcomings in medical coding. Clearly, these obstacles can be overcome with better, deeper, and more complete training data.
Finally, artificial intelligence will continue to accelerate the pace of medical research. Artificial intelligence can identify new drug targets, optimize clinical trial design and accelerate drug discovery by analyzing massive data sets, spanning imaging, multi-omics and other methods. Federated learning is a privacy-preserving artificial intelligence technology that allows institutions to collaborate on research without sharing sensitive patient data, unlocking the potential of collaborative research. In particular, recent advances in causal inference and generative artificial intelligence herald significant advances in discoveries ranging from basic biology to applied therapeutics.
What is your long-term vision for datma’s impact on the healthcare system and the wider industry?
At datma, we are committed to building a better future of data-driven healthcare that is personalized, accessible and efficient. By integrating complex data sets through federated learning, we enable clinicians and researchers to address complex healthcare challenges and enable new medical breakthroughs. Our federated real-world data marketplace, datma.FED, is the first step in realizing this vision.
Imagine a future in healthcare where researchers leverage and analyze vast amounts of patient data, from genomics, imaging, medical history to lifestyle factors, to tailor next-generation treatments with precise patient focus. Clinicians, meanwhile, can leverage AI to deliver the right care at the right time while minimizing administrative burden. datma’s federated approach accelerates this vision by unlocking the power of complex, secure healthcare data. By continually expanding our datasets and launching innovative tools like datma.WHY and datma.360, we are driving earlier disease detection, improved treatments and better patient outcomes.
Our vision goes beyond the individual patient. datma’s commitment to federated learning unlocks the power of collaborative research, enabling institutions to analyze massive data sets without compromising patient privacy. This has triggered a wave of discovery, from identifying new drug targets to optimizing clinical trials. By harnessing the analytical power and causal reasoning capabilities of AI, we can accelerate medical research and get life-saving treatments to patients faster. We are committed to making this future a reality.
Thanks for the great interview, readers who want to learn more should visit datma.
