Objectives

In recent years, a new paradigm has emerged for concept development, experimentation, simulation and implementation in engineering design, management science, economics and the physical and life sciences.

This new paradigm for concept development, experimentation, simulation and implementation in engineering design, management science, economics and the physical and life sciences has arisen because, with the availability of powerful new computers, the combination of mathematical modeling and modern scientific computing techniques is available to a greater than ever number of researchers. Increased efficiency, better understanding of systems that continually evolve in both size and complexity, and more accurate approximations of the underlying phenomena are needed.

We contend that the full impact of this paradigm shift has not reached the biomedical research community. The problem involves both tools and education, and the development of new software tools or new educational programs in isolation will not resolve this problem. A program integrating both software development and education must be designed to answer this need.

RFPK will directly address this problem through its specific aims, which are to:

(1) Develop new modeling methodologies and use them to study biological systems.

In the first cycle, we have concentrated upon population kinetic analysis, the study of between-individual differences in dynamic studies of, e.g. drug biodistribution and efficacy and metabolic pathways. Recently, we have extended our scope to include sophisticated applications of the inverse problem such as:

• system deconvolution,
• parametric and nonparametric modeling analysis of biomedical problems,
• the investigation and integration of various kinds of Bayesian statistics.

(2) Specify, design, develop, test, validate and maintain new software tools incorporating cutting-edge mathematics, statistics and computer science.

We are preparing to make available to the scientific community state of the art numerical libraries for biomedical research such as the System for Population Kinetics. These libraries will include and integrate all the methods and technologies being investigated under (1) develop new modeling methodologies. We have contacted professional software developers about the distribution of these libraries, which we would like to become an universally accepted standard.

(3) Provide service to the research community through collaboration and consultation.

Our list of collaborators includes worldwide renowned scientists in the fields of:

• Intermediary metabolism, glucose-insulin regulation in normal and diabetic states;
• Lipid metabolism, with applications in studying obesity and atherosclerosis;
• Pharmacokinetics-pharmacodynamics, where we address key methodological questions;
• Environmental toxicology, where models can lead to quantification of exposure;
• Cellular biochemical networks, researching the living cell during rest and activation;
• Parametric imaging, with applications in diabetes, cancer research and fracture healing.

(4) Provide educational programs for the research community in systems modeling application.

We will not only integrate RFPK research in graduate University courses and organize targeted workshops in Seattle, but also try to substantially increase visibility within professional societies (such as, AAPS, BMES, ADA and AHA) through our network of scientific collaborations.

(5) Disseminate RFPK technology and expertise via educational paradigms which integrate medicine, statistics, computer science and bioengineering in a comprehensive problem-solving approach.

Our website is central to this scope, but other approaches that we will use are individual and group training, workshops and the establishment of freely available educational resources such as data sets and modeling tutorials.

Making this new paradigm available to a broad audience through the deployment these specific aims is a complex problem that is best accomplished on a University campus. RFPK has assembled a strong multidisciplinary team consisting of scientists expert in biomedical model development and testing working in concert with mathematicians, statisticians, and professional software engineers.