Cancer Prediction is the Pathway to Prevention

Examining the benefits of using a systems-based approach to predict and control the evolution of cancer through preventative pathways

Oncology research exposes cancer as a dynamic disease that results from complex interactions between multiple scales of genetic, environmental and constitutional characteristics that are unique to an individual. Currently, the full scope of determinants that cause numerous point mutations to accumulate and/or structural alterations to occur in the process of tumor progression are not fully understood. Shifting from a component to a system-level perspective will help add the context and understanding necessary to make sense of and apply current oncology research innovations.

Preliminary use cases have shown that X-ACT® Health is able to add the missing context of complex cancer processes and promote further understanding of how dynamic interactions between a large number of determinants, such as DNA, pathogens, autoimmune responses, metabolism, environment and aging influence the progression of cancer for an individual patient.

Bridging silos of cancer knowledge will be necessary to help researchers and healthcare providers understand the complex factors that provoke cancer in one individual, and not another. This level of understanding is key to predictively diagnose cancer before any symptoms appear, and would give governments and payers the confidence they need to invest in and standardize personalized preventive pathways.

By using sophisticated algorithms that are computationally efficient and cover many-to-many time dependent relationships, X-ACT Health could revolutionize how we diagnose and treat cancer. The goal isn’t to replace doctors with AI. Instead, we need to build new knowledge and predictive capabilities that enable all healthcare stakeholders—including governments, payers, suppliers and providers—to know when and which actions will help an individual patient avoid cancer. This is the Holy Grail of oncology research and provides the path to cut the long-term costs of cancer care and improve standards of patient care.

 

 

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