Streamline Genomics was founded in Montréal in 2017 by Dr Josette-Renée Landry with a mission to democratize precision medicine by developing a secure cloud-based platform that empowers clinicians and researchers to leverage the power of genomic data to improve treatment options.
Along with co-founders Dr Brian Wilhelm and Amir Kadivar, and chief executive officer Curtis Duggan (former CEO of Blue Mesa Health), the team at Streamline Genomics has addressed the challenge of how to help doctors makes sense of the extremely complex data that is generated when a patient’s DNA is sequenced. While it has become inexpensive to sequence the genome of an individual patient with cancer or a rare disease, doctors don’t have the right tools to find the genetic “needle-in-a-haystack” for each patient, or to stay up-to-date with the thousands of new research papers published weekly in the field of human genomics.
Users of the Streamline Genomics flagship platform (who may be oncologists, researchers, analysts) can view genomic sequencing analysis, incorporate the collective extant knowledge base from open-source and peer-generated data and commentary, and generate time-saving actionable insights. This ability to provide rapid ‘clinical decision support’ in complex fields like oncology is one facet of a rich and intuitive product that, like many great ventures before it, aims to draw meaning from extremely complex datasets and augment and empower the abilities of highly trained specialists in clinical practice and in relevant fields of research.
Streamline is proud to be based in Québec and to leverage the power of the Montréal research community. Montréal and Québec are leaders in the field of AI and Streamline is thrilled to incorporate natural language processing and artificial intelligence projects into its core product roadmap, with the help of academic institutions. In addition to a residency at CHU SainteJustine and institut TransMedTech as the inaugural Innovators in Residence, Streamline has partnered with Prompt and MEI in 2020 to help accelerate the commercial applicability of AI algorithms to generate insights on gene variants.
