Delfi Diagnostics Raises $100 Million Series A Financing

1/12/21

Delfi Diagnostics, Inc., a pioneering developer of a new class of high performance, affordable liquid biopsy tests for early cancer detection, has raised $100 million in Series A funding. The round was led by OrbiMed, with participation from existing investors including Menlo Ventures, Samsara Biocapital, Illumina Ventures, AV8 Ventures, and Windham Venture Partners, and new investors including Foresite Capital, Northpond Ventures, Cowen Healthcare Investments, Rock Springs Capital, and funds and accounts advised by T. Rowe Price Associates, Inc. Delfi plans to use this round of funds to expand its team of cancer researchers and machine learning experts and to validate its novel next-generation liquid biopsy technology through multiple prospective clinical studies.

Delfi's technology leverages advances in machine learning and recent discoveries in the genome-wide fragmentation profiles of cell free DNA to create a novel approach to detecting evidence of a tumor from a blood sample, while also pinpointing the tumor's location in the body. Delfi is applying this platform technology to develop a range of products designed to detect specific cancers, such as lung cancer, in at-risk individuals and to identify any of multiple cancers in any individual.

"The Delfi team has a unique and groundbreaking approach to early detection of cancer," said Rishi Gupta, Partner at OrbiMed. "If liquid biopsy is to reach its full potential in early cancer detection and save as many lives as we believe it can, tests must be both high performing and broadly accessible in order for large populations to benefit. We believe Delfi's test may be ideally suited for broad adoption based on performance, simplicity, and cost."

Historically, cancer has been characterized by mutations in DNA. These genomic alterations drive tumor growth but are not present in every blood sample and require deep sequencing to detect.

Delfi is developing a new class of liquid biopsy for early detection based on altered genome-wide fragmentation profiles, also known as "fragmentomes," representing aberrant packaging of DNA in cancer cells. By applying advanced machine learning algorithms to these fragment patterns detectable at much lower sequencing cost, Delfi developed a highly sensitive and specific assay intended for wide and cost-effective distribution and adoption. Delfi's technology, first described in Nature in 20191, demonstrated sensitivity from 57% to more than 99% among seven cancer types at 98% specificity in a study of more than 400 individuals.

"We are measuring the consequence of abnormal mitoses, a fundamental hallmark of cancer that is exclusive to cancer," said Delfi's Founder and Chief Executive Officer Victor Velculescu. "This means our assay is highly specific to cancer and only minimally affected by other diseases or aging. Additionally, our simple assay uniquely enables broad distribution, potentially to any clinical laboratory with a sequencer, and the opportunity for continuous improvement as more and more clinical data are generated."

"Over the past 18 months, Delfi has extended its retrospective studies to thousands of individuals. We believe early detection at scale will require lower costs and broader distribution, and we see Delfi's technology as well suited both for common, high risk populations like patients at risk of lung cancer and for early detection of multiple cancers in large populations," said Greg Yap, Partner at Menlo Ventures and board member at Delfi.

At its founding in 2019, Delfi raised a $5.5 million seed financing led by Menlo Ventures and including Samsara BioCapital, Illumina Ventures, Windham Venture Partners, and AV8 Ventures, a venture fund backed by Allianz Group.

About DELFI Diagnostics

Founded in 2019, Delfi Diagnostics is committed to developing high-performing, affordable blood tests for early detection of cancer across multiple tumor types. Leveraging recent advances in cancer biology and machine learning, DELFI's technology can achieve high performance from low-cost, widely available sequencing technology.

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