Oncologists think about the natural history of tumors in interaction with treatments using informal reasoning that can lead to incorrect conclusions. The biological assumptions and hypotheses that oncologists use often have counterintuitive consequences. A substantial body of research literature exists describing the calculation of the whole-person consequences of hypotheses at the cellular level, but this knowledge has been largely inaccessible to oncologists, and has generally failed to affect their thinking or improve their intuition. As a result, the ability of oncologists to make optimal use of currently available anticancer agents has been impeded. Consequently, we propose the development of a resource package consisting of biomathematical modelling software, tutorials, and documentation. The goal is to train current and future research oncologists in the theory of tumor cell population kinetics as applied to cancer treatment, leading to improved selection of new hypotheses to test in clinical and laboratory studies, as well as improved interpretation of results. Objective 1: For training medical students, a short introductory module on tumor heterogeneity will be developed for use in classroom training. The module will consist of lecture materials, printed study materials and simulation-based exercises. Objective 2: For training oncology fellows, a suite of self-directed study modules will be developed. The goal is a set of tutorial lessons developed with integral contributions from outstanding researchers in clinical oncology. Tutorials will demonstrate key lessons in tumor cell kinetics, while teaching the use of the program for incorporating specific biological phenomena (metastasis, differentiation, nonlinear dose-response and drug interactions, pleiotropic resistance, multiple resistance mechanisms, angiogenesis, treatment-induced mutation, toxicity, etc.). Objective 3: For active cancer researchers, a flexible hypothesis-neutral modeling resource will be developed. Building on the tutorials developed for training of fellows, we will provide a software suite which will allow researchers facing a particular treatment question to describe, in a most natural way, their own conceptions of the disease natural history, and to train themselves, developing insights into the consequences of their hypotheses.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Education Projects (R25)
Project #
5R25CA063548-03
Application #
2458114
Study Section
Cancer Research Manpower and Education Review Committee (CRME)
Project Start
1995-09-30
Project End
1999-07-31
Budget Start
1997-08-01
Budget End
1998-07-31
Support Year
3
Fiscal Year
1997
Total Cost
Indirect Cost
Name
University of Pittsburgh
Department
Biostatistics & Other Math Sci
Type
Schools of Public Health
DUNS #
053785812
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213