How math fights cancer
For decades, researchers have used mathematics to better understand cancer. Click “+ Read More” on each card to explore how these methods are helping drive progress in this research.
Developing Personalized Treatments
Estimating Tumor Age
Analyzing Mutations
Modeling Cancer Growth
Math models help researchers simulate cancer growth and test treatments virtually, cutting down on time and costs compared to real world trials.
Probabilistic and statistical methods help researchers analyze random cancer cell mutations andhow they lead to drug resistance.
Using a patient’s unique genetics and tumor characteristics, researchers can predict the most effective drug ordrug combination through advanced mathematical analysis.
By analyzing cancer growth patterns, researchers can estimate how long a tumor has developed in the body, even if only recently diagnosed.
Read More
Read More
Read More
+ Read More
Animated Graphic: Nicole Borman/WUFT News
How the Tumor Is Given an Age
"Current mathematical models of tumorigenesis are notoriously inaccurate ... Eventually, we may be able to help patients estimate their risk far more precisely, giving them an opportunity to act long before they’re in danger."
Recent advances in medical research have made DNA sequencing more common in cancer care, revealing the genetic mutations in a patient’s tumor.When combined with mathematical analysis, this can help estimate how long the cancer has been growing, an insight that’s key to improving early detection.
Cristian Tomasetti, Ph.D. Associate Professor of Oncology Johns Hopkins University
Source: National Institutes of Health
Source: John Hopkins Medicine
Math Models Can Personalize Treatment Plans
Math models aim to improve outcomes and make cancer care more precise by predicting the most effective drug combinations for each patient and identifying the optimal doses and timing.These models can also reduce harmful side effects by avoiding unnecessary or ineffective treatments.
Source: National Institutes of Health
Source: TED
Math Models can Personalize Treatment Plans
Math models aim to improve outcomes and make cancer care more precise by predicting the most effective drug combinations for each patient and identifying the optimal doses and timing.These models can also reduce harmful side effects by avoiding unnecessary or ineffective treatments.
Source: National Institutes of Health
Source: TED
How a Cell Mutation is Studied
"How can we measure a process that can’t be observed in humans? Math is a powerful tool to try and understand that process. We can use math, along with clinical observations, to infer what is happening.”
Most mutations during cell division areharmless, but when that cell continues to duplicate, it carries that mutation. Over time, the accumulation of certain harmful mutations can drive cancer development and contribute to treatment resistance. These often random (stochastic) mutations can't be precisely predicted but can be analyzed using probabilistic and statistical techniques.
Ivana Bozic, Assistant Professor of Applied Mathematics University of Washington
Source: University of Washington College of Arts and Sciences
Computational biologists can use mathematical models to study how tumors grow and interact with their environment. This research helps improve drug development and delivery to make cancer treatments more effective.
Source: Oxford Mathematics
Computational biologists can use mathematical models to study how tumors grow and interact with their environment. This research helps improve drug development and delivery to make cancer treatments more effective.
Source: Oxford Mathematics
Computational biologists can use mathematical models to study how tumors grow and interact with their environment. This research helps improve drug development and delivery to make cancer treatments more effective.
Source: Oxford Mathematics
How a Cell Mutation Is Studied
"How can we measure a process that can’t be observed in humans? Math is a powerful tool to try and understand that process. We can use math, along with clinical observations, to infer what is happening.”
Most mutations during cell division are harmless, but when a cell keeps duplicating, it can pass along harmful mutations. Over time, these random mutations can contribute to cancer and treatment resistance, and while they can’t be precisely predicted, they can be studied using probability and statistics.
Ivana Bozic Assistant Professor of Applied Mathematics University of Washington
Source: University of Washington College of Arts and Sciences
How the Tumor is Given an Age
"Current mathematical models of tumorigenesis are notoriously inaccurate... Eventually, we may be able to help patients estimate their risk far more precisely, giving them an opportunity to act long before they’re in danger."
Recent advances in medical research have led to a surge in DNA sequencing, including for cancer. This technology reveals the genetic mutations in a patient’s tumor. Combined with math, this can help estimate how long the cancer has been growing, even if it was only just diagnosed. This is an insight that’s crucial for improving early detection efforts.
Cristian Tomasetti, Ph.D. Associate Professor of Oncology Johns Hopkins University
Source: National Institutes of Health
Source: John Hopkins Medicine
How math fights cancer
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Transcript
How math fights cancer
For decades, researchers have used mathematics to better understand cancer. Click “+ Read More” on each card to explore how these methods are helping drive progress in this research.
Developing Personalized Treatments
Estimating Tumor Age
Analyzing Mutations
Modeling Cancer Growth
Math models help researchers simulate cancer growth and test treatments virtually, cutting down on time and costs compared to real world trials.
Probabilistic and statistical methods help researchers analyze random cancer cell mutations andhow they lead to drug resistance.
Using a patient’s unique genetics and tumor characteristics, researchers can predict the most effective drug ordrug combination through advanced mathematical analysis.
By analyzing cancer growth patterns, researchers can estimate how long a tumor has developed in the body, even if only recently diagnosed.
Read More
Read More
Read More
+ Read More
Animated Graphic: Nicole Borman/WUFT News
How the Tumor Is Given an Age
"Current mathematical models of tumorigenesis are notoriously inaccurate ... Eventually, we may be able to help patients estimate their risk far more precisely, giving them an opportunity to act long before they’re in danger."
Recent advances in medical research have made DNA sequencing more common in cancer care, revealing the genetic mutations in a patient’s tumor.When combined with mathematical analysis, this can help estimate how long the cancer has been growing, an insight that’s key to improving early detection.
Cristian Tomasetti, Ph.D. Associate Professor of Oncology Johns Hopkins University
Source: National Institutes of Health
Source: John Hopkins Medicine
Math Models Can Personalize Treatment Plans
Math models aim to improve outcomes and make cancer care more precise by predicting the most effective drug combinations for each patient and identifying the optimal doses and timing.These models can also reduce harmful side effects by avoiding unnecessary or ineffective treatments.
Source: National Institutes of Health
Source: TED
Math Models can Personalize Treatment Plans
Math models aim to improve outcomes and make cancer care more precise by predicting the most effective drug combinations for each patient and identifying the optimal doses and timing.These models can also reduce harmful side effects by avoiding unnecessary or ineffective treatments.
Source: National Institutes of Health
Source: TED
How a Cell Mutation is Studied
"How can we measure a process that can’t be observed in humans? Math is a powerful tool to try and understand that process. We can use math, along with clinical observations, to infer what is happening.”
Most mutations during cell division areharmless, but when that cell continues to duplicate, it carries that mutation. Over time, the accumulation of certain harmful mutations can drive cancer development and contribute to treatment resistance. These often random (stochastic) mutations can't be precisely predicted but can be analyzed using probabilistic and statistical techniques.
Ivana Bozic, Assistant Professor of Applied Mathematics University of Washington
Source: University of Washington College of Arts and Sciences
Computational biologists can use mathematical models to study how tumors grow and interact with their environment. This research helps improve drug development and delivery to make cancer treatments more effective.
Source: Oxford Mathematics
Computational biologists can use mathematical models to study how tumors grow and interact with their environment. This research helps improve drug development and delivery to make cancer treatments more effective.
Source: Oxford Mathematics
Computational biologists can use mathematical models to study how tumors grow and interact with their environment. This research helps improve drug development and delivery to make cancer treatments more effective.
Source: Oxford Mathematics
How a Cell Mutation Is Studied
"How can we measure a process that can’t be observed in humans? Math is a powerful tool to try and understand that process. We can use math, along with clinical observations, to infer what is happening.”
Most mutations during cell division are harmless, but when a cell keeps duplicating, it can pass along harmful mutations. Over time, these random mutations can contribute to cancer and treatment resistance, and while they can’t be precisely predicted, they can be studied using probability and statistics.
Ivana Bozic Assistant Professor of Applied Mathematics University of Washington
Source: University of Washington College of Arts and Sciences
How the Tumor is Given an Age
"Current mathematical models of tumorigenesis are notoriously inaccurate... Eventually, we may be able to help patients estimate their risk far more precisely, giving them an opportunity to act long before they’re in danger."
Recent advances in medical research have led to a surge in DNA sequencing, including for cancer. This technology reveals the genetic mutations in a patient’s tumor. Combined with math, this can help estimate how long the cancer has been growing, even if it was only just diagnosed. This is an insight that’s crucial for improving early detection efforts.
Cristian Tomasetti, Ph.D. Associate Professor of Oncology Johns Hopkins University
Source: National Institutes of Health
Source: John Hopkins Medicine