Computational oncology utilizes computer models for population screening, individual cancer cell modeling, and to develop tumor marker analytics useful in the area of precision medicine. This information contributes to the predictability that certain pharmaceuticals or therapeutic approaches will provide long term solutions to disease in an individual with cancer
2. Presented By
Tamal Joyti Roy
ID:2171502
Institute of Information and Communication Technology
Khulna University of Engineering and Technology
Course Teacher
Dr. A. B. M. Aowlad Hossain
Professor
Department of Electronics and Communication Engineering
Khulna University of Engineering & Technology (KUET)
Computational Oncology
4. Introduction
It is a semi-new phrase that is beginning to gain speed in
medicine
utilizes computer models for population screening
individual cancer cell modeling
develop tumor marker analytics useful in the area of precision
medicine
contributes to the predictability that certain pharmaceuticals
or therapeutic approaches
People are dying of Cancer every single day.
We have the technology to outsmart the cancer cells
Computational Oncology
5. History
Leonardo da vinci used to spend nights with death people to
understand the death.
Humans were ever curious about mortality.
In 1825, Benjamin Gompertz published a demographic model
of mortality, which was widely used for life insurance cost
calculations
Erwin Schrödinger (Nobel Prize, Physics, 1933) delivered a
series of three lectures at Trinity College (Dublin) to explain
to the public how the laws of physics, and especially
thermodynamics, may be used to better understand the
human organism
In 1954, Armitage and Doll developed a two-stage
mathematical model of carcinogenesis.
Computational Oncology
6. Application in ICT
Figure: Computational Medicine within the framework of
hypothesis-driven research in systems biology.
Computational Oncology
7. Application in ICT
Cancer database analysis to establish trends in diseases and
identify gene targets for new therapeutic approaches
Evaluation of genomics data for the design of cancer clinical
trials
Treatment planning using imaging data for the resection of
tumors
Tumor growth models to optimize treatment timing and
develop personalized therapy
Development of new anti-cancer drugs by mass screening with
computers
Analysis of data sets to predict tumor recurrence
Breast modeling—imaging for breast conserving surgery
planning
Computational Oncology
8. How Computational Oncology Works
Compu-
tational
Oncology
Data
Analysis
Tumor
Model
Computational Oncology
9. How Computational Oncology Works
Data
Analysis
Cellular
Pathways
Micro
Array
Analysis
Image
Analysis
Database
Studies
Computational Oncology
10. How Computational Oncology Works
Data
Analysis
Cellular
Pathways
Micro
Array
Analysis
Image
Analysis
Database
Studies
Computational Oncology
11. How Computational Oncology Works
Data
Analysis
Cellular
Pathways
Micro
Array
Analysis
Image
Analysis
Database
Studies
Computational Oncology
12. How Computational Oncology Works
Data
Analysis
Cellular
Pathways
Micro
Array
Analysis
Image
Analysis
Database
Studies
Computational Oncology
13. How Computational Oncology Works
Data
Analysis
Cellular
Pathways
Micro
Array
Analysis
Image
Analysis
Database
Studies
Computational Oncology
14. Future Of Oncology
1 Big data analysis
2 Will Produce more accurate results
3 Treatment will be more affordable
4 Blockchain technology will be used
Computational Oncology
15. Conclusion
The situation in the development of complex tumor models using
systems of partial differential equations is remarkably similar, and
we can only hope that the future of this exciting new field will
ultimately provide a benefit to our patients from the synergistic
activity between investigators in the physical sciences and those in
oncology
Computational Oncology