Liz Moyles: The start-up on a mission to shake up metastatic breast cancer management
Liz Moyles, Global Recruitment Consultant at
“The start-up on a mission to shake up metastatic breast cancer management – OncoGenomX. More than two million women globally were diagnosed with breast cancer in 2022 alone. I was one of them.
1 in 8 women in the US will be diagnosed with breast cancer in their lifetime and one in 39 will die from it. We are hearing more about it, but I like to think it is because we are getting better at detecting it. Not sure if I am right about that but I like to think so. .
One of the questions which troubles oncologists, is the choice of the most effective treatment combination for a particular tumour or patient.
Currently there is nothing to assess whether a certain treatment works in a specific tumour and oncologists can only be certain about that after the entire treatment journey, which can take months, sometimes years.
Many patients are still over-treated with excessive and excessively harsh chemotherapy mixes , for fear of being under-treated.
However, Dr. Wolfgang Hackl, founder and CEO of OncoGenomX is developing PredictionStar, a decision support technology which uses AI and machine learning algorithms, identifies whether a certain therapy works in a particular tumour and finds the treatments proven to be the most effective for each patient and their specific tumour.
For the first time, oncologists will be able to understand which treatment combination will work the best for a patient and their tumour.
“PredictionStar takes away the uncertainty around breast cancer treatment decisions and increases the likelihood of opting for the most effective treatment combination without delay and without exposing the patient to the side effects of an ineffective treatment.” said Dr. Wolfgang Hackl
“The whole technology is designed as an instrument agnostic which can work with any other existing technologies to allow for seamless interactions, irrespective of the systems that already exist in hospitals.”
The fascinating part is that the tool has a feedback loop which means the technology improves, the more information it gets, refining its therapy guidance.
Based on the data PredictionStar could reduce treatment expenses by at least 20 per cent. It is anticipated that PredictionStar could also be used with other cancer types.
If everything goes according to plan, PredictionStar could be ready for use in clinical and translational studies in the next 15-18 months, the founder adds.
I am really excited about this technology! Well done.”
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Source: Liz Moyles/LinkedIn