As the industry begins to embrace the power of AI, the lakehouse brings patient, research, and operational data together at scale to deliver new innovations in research and care
Databricks, the Data and AI company and pioneer of the data lakehouse paradigm, today launched the industry’s first lakehouse platform for organisations across the healthcare and life sciences industries.
The Databricks Lakehouse for Healthcare and Life Sciences eliminates the need for legacy data architectures which have historically inhibited innovation in patient care and drug discovery by creating data silos and making advanced analytics difficult.
With a single platform for data management, analytics and advanced AI use cases like disease prediction, medical image classification, and biomarker discovery, healthcare organisations can deliver on the promise of precision medicine.
Early adopters in Australia include Healthdirect Australia, Arden Street Labs and Austin Health, while global customers include GE Healthcare, Regeneron, ThermoFisher and Walgreens, as well as partners like Lovelytics, John Snow Labs and ZS Associates.
“All of our solutions are built leveraging Databricks’ lakehouse platform as a core foundation, providing us the ability to rapidly move from Lab to Operations, whilst maintaining data security and computational scalability. Databricks has been key to our ability to support the COVID-19 response here in Victoria, enabling real-time insights and data pipelines as we scaled from managing thousands of patients to hundreds of thousands of patients throughout the Omicron wave.” Jeff Feldman, CTO of Arden Street Labs.
“One of the biggest challenges facing healthcare organisations today is building a comprehensive view of the patient. The Databricks Lakehouse for Healthcare and Life Sciences is helping GE Healthcare with a modern, open, and collaborative platform to build patient views across care pathways. By unifying our data in a single platform with a full suite of analytics and ML capabilities, we’ve diminished costly legacy data silos and equipped our teams with timely and accurate insights.” Joji George, Chief Technology Officer, LCS Digital, GE Healthcare
Databricks is already empowering a new breed of data and AI innovators in healthcare. For example, Cognoa, a paediatric behavioural health company, is using AI to develop diagnostic and therapeutic products with the goals of enabling earlier and more equitable access to care and improving the lives and outcomes of children and families living with behavioural conditions.
In other instances, scientists can detect the presence of cancer tumour DNA in blood long before traditional detection methods and provide early cancer screening during annual physicals from a single blood draw. And precision medicine organisations are leveraging the power of data to further the discovery and development of differentiated genomics-based solutions for transplant patients.
“We recognise the important role that data plays in getting our products into the hands of those that need them the most, and the Databricks Lakehouse for Healthcare and Life Sciences solution helps us achieve that goal. This modern platform for data and AI has enabled us to eliminate costly data silos, unlock new opportunities to innovate, and become a more data-driven organisation.” Feng Liang, Sr. IT Director, Thermo Fisher Scientific
Databricks’ Lakehouse for Healthcare and Life Sciences offers customers tailored data and AI solutions to address common industry challenges. Through analytics accelerators and open source libraries – like Glow for genomics – along with a certified ecosystem of partners, organisations can jumpstart their analytics projects and save weeks to months of development time for data engineers and data scientists. These solutions include:
- Disease Risk Prediction: use ML to assess the risk of a patient for a given condition based on a patient’s encounter history and demographics information.
- Digital Pathology Classification: rapidly analyse thousands of whole slide images with deep learning to automate the detection of metastasis.
- Real World Evidence Suite: seamlessly ingest a wide variety of data types, map to analytic data models like OMOP, and build cohorts with tools like propensity score matching.
- Natural Language Processing with John Snow Labs: analyse unstructured medical text using NLP for use cases such as oncology research, drug safety monitoring and anonymising PHI.
- Interoperability with Lovelytics: automate the ingestion of streaming FHIR bundles into the lakehouse for downstream patient analytics at scale.
- Biomedical Research with ZS Associates: improve biomarker discovery for precision medicine with a highly scalable and extensible whole-genome processing solution.
“With the Lakehouse for Healthcare and Sciences, we can help accelerate the development of novel therapeutics and fundamentally change the way care is delivered by going from measuring disease to predicting it,” said Michael Sanky, Global Industry Lead for Healthcare and Life Sciences at Databricks.
Michael Hartman, SVP of Regulated Industries at Databricks added, “The opportunity for healthcare to be transformed with data and AI cannot be overstated. As organisations fully transition to electronic medical records, new data types like genomics evolve, and IoT and wearables take off, the industry is awash in massive amounts of data. But this data is siloed, and teams don’t have the tools to properly use it. With Lakehouse for Healthcare and Life Sciences, we can drive transformation across the entire healthcare ecosystem and help empower our customers to solve specific industry challenges and, ultimately, drive better outcomes for the future of healthcare.”
