2023-07-27 22:00:10
According to the Ministry of Health, during 2021, 90,123 deaths from tumors were registered in Mexico.
This mathematical model is designed to predict individual patient responses and quantify the precise sensitivity of a drug and cancer.
So far it has predicted outcomes for cancer patients with greater than 90% accuracy.
Immunotherapy is a type of treatment that helps the immune system fight cancer. The immune system helps the body against infections and other chronic degenerative diseases, including tumors. It is made up of white blood cells, organs and tissues of the lymphatic system.
Medicine and mathematics are compatible
In this regard, the Dr. Vittorio Cristiniprofessor of Mathematics in Medicine and director of the Mathematics in Medicine program at Houston Methodist Hospital, has designed a mathematical model with the potential to boost success rates of cancer immunotherapy.
This mathematical model is designed to predict individual patient responses and quantify precise drug and cancer sensitivity.
Dr. Vittorio Cristini along with the study’s lead author, Dr. Joseph D. Butner, and co-author, Dr. Zhihui Wang, detailed how this mathematical model can be used to tailor training strategies. immunotherapy to maximize the eradication of cancer.
The model has been evaluated with retrospective studies, but it needs to be validated through prospective clinical trials. Dr. Cristini and his colleagues, in collaboration with oncologists from the MD Anderson Cancer Centerplan to participate in a prospective clinical trial to test the validity of this model in the real world.
If successful, a patient-facing application will be designed to predict and explain the likelihood of your treatment being successful with personalized immunotherapy approaches before embarking on treatment. This may revolutionize not only the chances of success with cancer immunotherapy, but also the collective philosophy and sentiment surrounding cancer as a deadly disease.
Decision support for physicians
The mathematical model designed by Dr. Cristini can serve as a decision-making tool for patients who respond to immunotherapy. Such a model has predicted outcomes for patients with greater than 90% accuracy and can be used to tailor treatments to design better outcomes.
Tumors are physical systems and obey fundamental laws of physics. Regardless of genetics, cancer cells must still obey the conservation laws of physics, since they belong in the physical realm.
“What is unique about this mathematical model is that it is historically and fundamentally based on patient data. According to our model, what really matters is the specific combination of all measurable quantities that we call super-parameters. This mathematical model can generate unique and valuable information that cannot be learned empirically. It would be like finding a needle in a haystack,” explained the Houston Methodist Hospital mathematician.
Currently used cancer therapies fail to achieve complete eradication of tumor cells, and immunotherapy is generally used as a last resort when standard clinical approaches are unsuccessful. Dr. Cristini suggests an approach that involves identifying the strength of treatment intervention necessary for complete eradication of tumors based on the patient.
Personalized treatments suggested by the model, based on available patient data, can be used in conjunction with other treatments such as radiation or chemotherapy. Based on the mathematical model, Dr. Cristini suggests that immunotherapy should be the treatment of choice from the outset.
Also read:
Immunotherapy manages to eliminate breast cancer for the first time
They discover that intestinal microbes influence cancer patients before immunotherapy
New technique could help improve the effectiveness of cancer immunotherapy
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