According to the Canadian Cancer Society, nearly 1 in 2 Canadians will be diagnosed with cancer in their lifetime, and the disease continues to be the leading cause of death in Canada – 1 in 4 Canadians will die of cancer or cancer-related illnesses. When it comes to the diagnosis and treatment of cancer, every day is critical. Cancer patients have very little room for miscalculation, delays, or human error.

Advancements in technology have led to new opportunities to improve cancer care with personalized treatment plans, also known as precision medicine – however, there are many challenges to identifying the most precise and effective treatment. Massive storage and compute power are required to analyze hundreds of thousands of cancer cells. Cancer researchers lack a shared data environment to bring together siloed datasets and the wealth of existing genomics research outcomes. Clinicians have also faced challenges in accessing the data from researchers to inform patient care.

Enter Drs. Benjamin Haibe-Kains and Trevor Pugh, both Senior Scientists at Princess Margaret Cancer Centre at Toronto’s University Health Network (UHN). They are leveraging Microsoft Azure as the foundation of their using machine learning tools to address these challenges and solve one of the most complex and deadly problems facing humans today.

Together, they are committed to bringing cancer research to clinicians in real time and are developing a shared data platform for precision medicine allowing clinicians to analyze large panels of cancer cells to determine the genomic aberrations that are predictive of drug response. This so-called companion diagnostics are crucial to devise personalized treatment plans with greater accuracy in mere minutes – something that in the past would not be possible for many anticancer therapies.

The Microsoft Cloud is at the heart of this breakthrough. Leveraging Microsoft’s cutting-edge Azure cloud technology, the shared database will be available to clinicians around the world. This incredible advancement in personalized treatment is quickly moving from research into real practice due to reduced processing time.

The ability to harness the power of complex data and AI at the point of care to provide a personalized treatment plan for cancer patients could improve their outcomes. Receiving the right plan the first time means better, faster, more accurate treatment, less likelihood of growing resistance to chemotherapy, and lower chance of relapse as the entire tumor is attacked.

In healthcare, Digital Transformation is an inherently people-oriented initiative – one that connects research innovation, trust, and a culture of collaboration to an external vision for patient care. At UHN, this is coming to life in the strong collaboration between the Microsoft team supporting UHN, the researchers at the lab developing the database, and the clinicians using the data – all with the singular focus on delivering the best possible care.

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