FDNA was incorporated with a mission to give hope to children with rare diseases, and their families.

Imagine a world where every person’s genome serves as their medical record to guide health decisions. We’re well on our way—genomic analysis is becoming the clinical standard in diagnostic evaluations, and artificial intelligence is the cornerstone of technologies that enable it.

Used by 70% of the world’s geneticists across 2,000 clinical sites in over 130 countries, FDNA’s next-generation phenotyping (NGP) technologies capture, structure and analyze complex human physiological data to produce actionable genomic insights. FDNA’s database includes an unprecedented depth of phenotypic and genotypic information associated with more than 10,000 diseases, crowdsourced from real-world patient cases through our broad network of users. This de-identified data is collected and stored in a private and secure cloud-based clinical warehouse, and integrated to LIMS, EMR and variant interpretation systems through a set of open APIs.

While our roots stem from facial recognition, our future lies in the phenotype, and as a leader in AI we aim to always provide innovative, impactful solutions. Since its founding in 2011, FDNA continues to aid clinicians, researchers and genetic testing labs in finding answers and treatments for hundreds-of-millions of patients globally living with a genetic disease.

For Patients
Timing is critical for rare diseases. The time patients wait for a diagnosis. The time a clinician spends searching for answers. The time it takes to develop new treatments. What if we could speed that up? We could save lives. We could improve the quality of life for hundreds of millions of people. Every patient has their own story: their own journey, their own symptoms, their own genes, their own face and voice.

Technology now exists to learn from those stories to help recognize these syndromes and find answers faster. We are devoted to using this technology to find answers for you. Every time a patient’s photo and information are analyzed by Face2Gene, our flagship product for clinicians, labs and researchers, the de-identified information “teaches” our system to recognize new syndromes, facial characteristics and genes.

Learn more at www.FDNA.com

Face2Gene User Community Includes Users From:

  • Using Face2Gene to reference all my department’s cases, share information with my colleagues and quickly look up relevant information in the London Medical Databases Online saves me hours of work every week and allows me to focus on my patients.

    Dr. Ibrahim Akalin

    Assoc. Prof. Ibrahim Akalin, MD, Medical Geneticist from the Istanbul Medeniyet University, Istanbul, Turkey

  • FDNA’s game-changing technology introduces an objective computer-aided dimension to the “art of dysmorphology”, transforming the analysis into an evidence-based science.

    Dr. Michael R. Hayden

    Chairman of FDNA’s Scientific Advisory Board & Steering Committee and Editor in Chief of Clinical Genetics

  • FDNA is developing technology that has the potential to help so many physicians and families by bringing them closer to a diagnosis- there are literally millions of individuals with unusual features around the world that lack a diagnosis and therefore lack information on natural history, recurrence risk and prevention of known complications.

    Dr. Judith G. Hall

    Professor Emerita of Pediatrics & Medical Genetics UBC & Children's and Women's Health Centre of BC

  • FDNA has been “right on the money”, providing me with relevant, accurate and insightful information for differential diagnoses.

    Dr. Cynthia J.R. Curry

    Professor of Pediatrics UCSF, Adjunct Professor of Pediatrics Stanford

  • I am excited to be a part of the FDNA community, promoting broad information sharing with my peers to amplify the scientific and clinical value of our community’s accumulated knowledge for the purpose of efficiently diagnosing individuals with rare genetic disorders.

    Dr. Karen W. Gripp

    Chief, Division of Medical Genetics A.I. duPont Hospital for Children

  • FDNA's idea of incorporating several dysmorphology resources (OMIM, GeneReviews), supported by their visual analytic technology, will be able to improve researching of genetic syndromes - all within a single mobile app.

    Dr. Chad Haldeman-Englert

    Assistant Professor Pediatrics at Mission Fullerton Genetics

  • Given the advancement of visual analytical technology, it’s about time Dysmorphology is supported with computational capabilities and moving this to mobile support, is simply the next logical step.

    Dr. Chanika Phornphutkul

    Associate Professor of Pediatrics Director, Division of Human Genetics Department of Pediatrics Warren Alpert Medical School of Brown University

  • Having an archive of cases easily accessible from my mobile device anytime and anywhere is a long-time unmet need.

    Dr. Lynne Bird

    Rady Children's Specialists of San Diego

  • FDNA's solution is a huge leap forward for dysmorphology. It saves me significant time when I’m evaluating patients in my clinic and provides me with insightful tools that help me generate a differential diagnosis.

    Dr. David A. Chitayat

    Head of the Prenatal Diagnosis and Medical Genetics Program at Mount Sinai Hospital, Toronto

  • Shortly after learning about Face2Gene, I’ve started to incorporate this amazing tool into my workflow. Soon enough, Face2Gene’s analysis flushed out references that I would not have considered for several of my patients, which turned out to be their correct diagnosis

    Dr. Zvi U. Borochowitz

    Chairman (Retired) of The Simon Winter Institute for Human Genetics at Bnai-Zion Medical Center, Technion-Rappaport Faculty of Medicine

  • The Unknown Forum from Face2Gene is a great community platform for exchanging opinions regarding undiagnosed cases. It is straightforward to use and safe for exchange of medical data, thanks to the efforts of its developers and to the involvement of geneticists worldwide.

    Dr. Oana Moldovan

    Clinical Geneticist at the Hospital Santa Maria, CHLN, Lisbon, Portugal