Paul Newton, PhD
Professor of Aerospace & Mechanical Engineering
Professor of Mathematics 
Professor, Norris Comprehensive Cancer Center
  newton@usc.edu
Professor Newton started his teaching career in the Mathematics Department at the University of Illinois Champaign-Urbana (UIUC) and at the Center for Complex Systems Research (CCSR) at the Beckman Institute, where he became an Assistant (1987) and then Associate Professor (1993). In 1993 he moved to the Aerospace & Mechanical Engineering Department and the Mathematics Department at the University of Southern California and was promoted to Full Professor in 1998. He is currently a Professor in the Viterbi School of Engineering (AME), Dornsife College (Mathematics) and Keck School of Medicine (Norris Comprehensive Cancer Center) at USC. He is also Editor-in-Chief of the Journal of Nonlinear Science (SpringerNature).

For the last 10 years, Professor Newton's work and funding has been primarily in the field of computational health sciences, mathematical oncology, medical biophysics, and systems biology. His focus has been primarily on using longitudinal patient data to build quantitative and predictive mathematical and computational dynamical systems models of metastatic cancer progression and the dynamics and control of the tumor- immune ecosystem. His entry into this field began when he functioned as Co-PI on one of the 12 original National Physical Sciences Oncology Centers funded by the National Cancer Institute (NIH) located at The Scripps Research Institute in La Jolla CA. The center’s title was ‘The Physics and Mathematics of Metastasis over Time and Space’ (2009-2014) where he functioned as head of the mathematical modeling group. During that time period, he focused intensively on learning all aspects of the disease, including the biology and genetics of cells and organisms, population genetics, tumor suppressor genes and oncogenes, tumor growth models, invasion and metastasis, tumor immunology and immunotherapy, chemotherapy scheduling, chemotherapeutic resistance and clinical trial design, with the goal of developing ways to add value to the field of medical oncology using mathematical tools.

In 2018 (June-July) he was a Visiting Scientist in the Integrative Mathematical Oncology Department at the Moffitt Cancer Center, Tampa Florida. He currently focuses on using evolutionary game theory models to optimize chemotherapy and immuno-chemotherapy schedules, understanding how heterogeneous collections of cancer cells cooperate to produce volumetric growth and on using Markov chain and network dynamics models to develop predictive metastasis models of breast, prostate and lung cancer. He is generally interested in analyzing all types of medical data in order to extract patterns and build low-dimensional predictive models that help physicians and patients. 

Professor Newton received his B.S. (cum laude) degree in Applied Mathematics/Physics at Harvard University in 1981 and his M.S. (1982) and Ph.D. (1986) in the Division of Applied Mathematics at Brown University. He then moved to the Mathematics Department at Stanford University to work as a post-doctoral scholar under J.B. Keller.


At the Ellison Institute, Dr. Newton is one of 10 affiliate members. 

Research Focus

Mathematical Oncology
Evolutionary Game Theory
Metastatic Forecasting
Tumor Heterogeneity and Entropy

Education

BS

PhD

Mathematics/Physics (cum laude), Harvard University- 1981
Mathematics, Brown University- 1986

Awards

  • Phi Kappa Phi Faculty Recognition Award, University of Southern California- 2017
  • R.M. Nakamura Lecture, Scripps Green Hospital, UC San Diego-2015
  • H. Aref Memorial Lecture, Virginia Tech. School of Engineering-2014
  • Mellon Foundation Mentoring Award, Viterbi School of Engineering, USC-2011
  • Beckman Institute Research Award, UIUC-1993-1994
  • Oakley-Kund University Wide Teaching Award Finalist, University of Illinois-1993
  • Fellow - Center for Advanced Study, University of Illinois-1990
  • Listed in `Teachers ranked excellent by students', University of Illinois-1989-93
  • Brown University Fellowship, Division of Applied Mathematics-1981-1985
  • John Harvard Scholarship for Academic Achievement, Harvard University-1978-1981
  • National Merit Scholar, USA-1977

Leadership 

  • Editor-in-Chief: Journal of Nonlinear Science, 2016- Present
  • Managing Editor: Journal of Nonlinear Science, 2011-2015
  • Editorial Board: Texts in Applied Mathematics, Springer-Verlag, 1998- Present
  • Communicating Editor: Journal of Nonlinear Science, 2001-Present
  • Physical Sciences Oncology Center Advisory Committee: The Scripps Research Institute, 2009-Present
  • Advisory Board: Strategic Analytics Inc., Santa Fe, NM, 2001-2006
  • Scientific Advisor: Applied Mathematics Inc., Gales Ferry, CT, 1996- Present

Selected Publications

J. West, P.K. Newton [2019], Cellular cooperation shapes tumor growth, Proc. Nat'l Acad. Sci. 116(6), 1918-1923.

P.K. Newton, Y. Ma [2019], Nonlinear adaptive control of competitive release and chemotherapeutic resistance, Phys. Rev. E, Editor's Choice, 99(2) 022404.

J. West, Y. Ma, P.K. Newton [2018], Capitalizing on competition: An evolutionary model of competitive release in metastatic castrate resistant prostate cancer treatment, https://www.biorxiv.org/ content/early/2017/10/27/190140, J. Theoretical Bio. 455 249-260.

J. West, P.K. Newton [2017], Chemotherapeutic dose scheduling based on tumor growth rates provides a case for low-dose metronomic high-entropy therapies, Cancer Res. 77(23), 6717-6728.

J. West, Z. Hasnain, P. Macklin, P.K. Newton [2016], An evolutionary model of tumor cell kinetics and the emergence of molecular heterogeneity driving Gompertzian growth, SIAM Review, 58(4), 716-736.

P.K. Newton, J. Mason, N. Venkatappa, M.S. Jochelson, B. Hurt, J. Nieva, E. Comen, L. Norton, P. Kuhn [2015], Spatiotemporal progression of metastatic breast cancer: A Markov chain model highlighting the role of early metastatic sites, NPJ Breast Cancer, 1, 15018.

P.K. Newton, J. Mason, B. Hurt, K. Bethel, L. A. Bazhenova, J. Nieva, P. Kuhn [2014], Entropy, complexity, and Markov diagrams for random walk cancer models, Nature Scientific Reports, 4 doi: 10:1038/srep07558.

L. Bazhenova, P.K. Newton, J. Mason, K. Bethel, J. Nieva, P. Kuhn [2014], Adrenal metastases in lung cancer: Clinical implications of a mathematical model, J. Thoracic Oncology, 9(4), April, 442-446.

P. K. Newton, J. Mason, K. Bethel, L. A. Bazhenova, J. Nieva, L. Norton, P. Kuhn [2013], Spreaders and sponges define metastasis in lung cancer: A Markov chain Monte Carlo model, Cancer Research, 73(9), 2760-2769.

P. K. Newton, J. Mason, K. Bethel, L. A. Bazhenova, J. Nieva, P. Kuhn [2012], A Markov chain mathematical model to describe lung cancer growth and metastasis, PLoS ONE, 7(4), e34637 April.


Paul Newton, PhD
Professor of Aerospace & Mechanical Engineering
Professor of Mathematics
Professor, Norris Comprehensive Cancer Center

newton@usc.edu
Professor Newton started his teaching career in the Mathematics Department at the University of Illinois Champaign-Urbana (UIUC) and at the Center for Complex Systems Research (CCSR) at the Beckman Institute, where he became an Assistant (1987) and then Associate Professor (1993). In 1993 he moved to the Aerospace & Mechanical Engineering Department and the Mathematics Department at the University of Southern California and was promoted to Full Professor in 1998. He is currently a Professor in the Viterbi School of Engineering (AME), Dornsife College (Mathematics) and Keck School of Medicine (Norris Comprehensive Cancer Center) at USC. He is also Editor-in-Chief of the Journal of Nonlinear Science (SpringerNature).

For the last 10 years, Professor Newton's work and funding has been primarily in the field of computational health sciences, mathematical oncology, medical biophysics, and systems biology. His focus has been primarily on using longitudinal patient data to build quantitative and predictive mathematical and computational dynamical systems models of metastatic cancer progression and the dynamics and control of the tumor- immune ecosystem. His entry into this field began when he functioned as Co-PI on one of the 12 original National Physical Sciences Oncology Centers funded by the National Cancer Institute (NIH) located at The Scripps Research Institute in La Jolla CA. The center’s title was ‘The Physics and Mathematics of Metastasis over Time and Space’ (2009-2014) where he functioned as head of the mathematical modeling group. During that time period, he focused intensively on learning all aspects of the disease, including the biology and genetics of cells and organisms, population genetics, tumor suppressor genes and oncogenes, tumor growth models, invasion and metastasis, tumor immunology and immunotherapy, chemotherapy scheduling, chemotherapeutic resistance and clinical trial design, with the goal of developing ways to add value to the field of medical oncology using mathematical tools.

In 2018 (June-July) he was a Visiting Scientist in the Integrative Mathematical Oncology Department at the Moffitt Cancer Center, Tampa Florida. He currently focuses on using evolutionary game theory models to optimize chemotherapy and immuno-chemotherapy schedules, understanding how heterogeneous collections of cancer cells cooperate to produce volumetric growth and on using Markov chain and network dynamics models to develop predictive metastasis models of breast, prostate and lung cancer. He is generally interested in analyzing all types of medical data in order to extract patterns and build low-dimensional predictive models that help physicians and patients.

Professor Newton received his B.S. (cum laude) degree in Applied Mathematics/Physics at Harvard University in 1981 and his M.S. (1982) and Ph.D. (1986) in the Division of Applied Mathematics at Brown University. He then moved to the Mathematics Department at Stanford University to work as a post-doctoral scholar under J.B. Keller.


At the Ellison Institute, Dr. Newton is one of 10 affiliate members. 

Research Focus

Mathematical Oncology
Evolutionary Game Theory
Metastatic Forecasting
Tumor Heterogeneity and Entropy

Education

BS

Mathematics/Physics (cum laude), Harvard University- 1981

PhD

Mathematics, Brown University- 1986

Awards

  • Phi Kappa Phi Faculty Recognition Award, University of Southern California-2017
  • R.M. Nakamura Lecture, Scripps Green Hospital, UC San Diego-2015
  • H. Aref Memorial Lecture, Virginia Tech. School of Engineering-2014
  • Mellon Foundation Mentoring Award, Viterbi School of Engineering, USC-2011
  • Beckman Institute Research Award, UIUC-1993-1994
  • Oakley-Kund University Wide Teaching Award Finalist, University of Illinois-1993
  • Fellow - Center for Advanced Study, University of Illinois-1990
  • Listed in `Teachers ranked excellent by students', University of Illinois-1989-1993
  • Brown University Fellowship, Division of Applied Mathematics-1981-1985
  • John Harvard Scholarship for Academic Achievement, Harvard University-1978-1981
  • National Merit Scholar, USA-1977

Leadership 

  • Editor-in-Chief: Journal of Nonlinear Science, 2016- Present
  • Managing Editor: Journal of Nonlinear Science, 2011-2015
  • Editorial Board: Texts in Applied Mathematics, Springer-Verlag, 1998- Present
  • Communicating Editor: Journal of Nonlinear Science, 2001-Present
  • Physical Sciences Oncology Center Advisory Committee: The Scripps Research Institute, 2009-Present
  • Advisory Board: Strategic Analytics Inc., Santa Fe, NM, 2001-2006
  • Scientific Advisor: Applied Mathematics Inc., Gales Ferry, CT, 1996- Present

Selected Publications

J. West, P.K. Newton [2019], Cellular cooperation shapes tumor growth, Proc. Nat'l Acad. Sci. 116(6), 1918-1923.

P.K. Newton, Y. Ma [2019], Nonlinear adaptive control of competitive release and chemotherapeutic resistance, Phys. Rev. E, Editor's Choice, 99(2) 022404.

J. West, Y. Ma, P.K. Newton [2018], Capitalizing on competition: An evolutionary model of competitive release in metastatic castrate resistant prostate cancer treatment, https://www.biorxiv.org/ content/early/2017/10/27/190140, J. Theoretical Bio. 455 249-260.

J. West, P.K. Newton [2017], Chemotherapeutic dose scheduling based on tumor growth rates provides a case for low-dose metronomic high-entropy therapies, Cancer Res. 77(23), 6717-6728.

J. West, Z. Hasnain, P. Macklin, P.K. Newton [2016], An evolutionary model of tumor cell kinetics and the emergence of molecular heterogeneity driving Gompertzian growth, SIAM Review, 58(4), 716-736.

P.K. Newton, J. Mason, N. Venkatappa, M.S. Jochelson, B. Hurt, J. Nieva, E. Comen, L. Norton, P. Kuhn [2015], Spatiotemporal progression of metastatic breast cancer: A Markov chain model highlighting the role of early metastatic sites, NPJ Breast Cancer, 1, 15018.

P.K. Newton, J. Mason, B. Hurt, K. Bethel, L. A. Bazhenova, J. Nieva, P. Kuhn [2014], Entropy, complexity, and Markov diagrams for random walk cancer models, Nature Scientific Reports, 4 doi: 10:1038/srep07558.

L. Bazhenova, P.K. Newton, J. Mason, K. Bethel, J. Nieva, P. Kuhn [2014], Adrenal metastases in lung cancer: Clinical implications of a mathematical model, J. Thoracic Oncology, 9(4), April, 442-446.

P. K. Newton, J. Mason, K. Bethel, L. A. Bazhenova, J. Nieva, L. Norton, P. Kuhn [2013], Spreaders and sponges define metastasis in lung cancer: A Markov chain Monte Carlo model, Cancer Research, 73(9), 2760-2769.

P. K. Newton, J. Mason, K. Bethel, L. A. Bazhenova, J. Nieva, P. Kuhn [2012], A Markov chain mathematical model to describe lung cancer growth and metastasis, PLoS ONE, 7(4), e34637 April.