Annals of Biomedical Engineering

, Volume 28, Issue 8, pp 1043–1058 | Cite as

Strategies for the Physiome Project

  • James B. Bassingthwaighte

Abstract

The physiome is the quantitative description of the functioning organism in normal and pathophysiological states. The human physiome can be regarded as the virtual human. It is built upon the morphome, the quantitative description of anatomical structure, chemical and biochemical composition, and material properties of an intact organism, including its genome, proteome, cell, tissue, and organ structures up to those of the whole intact being. The Physiome Project is a multicentric integrated program to design, develop, implement, test and document, archive and disseminate quantitative information, and integrative models of the functional behavior of molecules, organelles, cells, tissues, organs, and intact organisms from bacteria to man. A fundamental and major feature of the project is the databasing of experimental observations for retrieval and evaluation. Technologies allowing many groups to work together are being rapidly developed. Internet II will facilitate this immensely. When problems are huge and complex, a particular working group can be expert in only a small part of the overall project. The strategies to be worked out must therefore include how to pull models composed of many submodules together even when the expertise in each is scattered amongst diverse institutions. The technologies of bioinformatics will contribute greatly to this effort. Developing and implementing code for large-scale systems has many problems. Most of the submodules are complex, requiring consideration of spatial and temporal events and processes. Submodules have to be linked to one another in a way that preserves mass balance and gives an accurate representation of variables in nonlinear complex biochemical networks with many signaling and controlling pathways. Microcompartmentalization vitiates the use of simplified model structures. The stiffness of the systems of equations is computationally costly. Faster computation is needed when using models as thinking tools and for iterative data analysis. Perhaps the most serious problem is the current lack of definitive information on kinetics and dynamics of systems, due in part to the almost total lack of databased observations, but also because, though we are nearly drowning in new information being published each day, either the information required for the modeling cannot be found or has never been obtained. “Simple” things like tissue composition, material properties, and mechanical behavior of cells and tissues are not generally available. The development of comprehensive models of biological systems is a key to pharmaceutics and drug design, for the models will become gradually better predictors of the results of interventions, both genomic and pharmaceutic. Good models will be useful in predicting the side effects and long term effects of drugs and toxins, and when the models are really good, to predict where genomic intervention will be effective and where the multiple redundancies in our biological systems will render a proposed intervention useless. The Physiome Project will provide the integrating scientific basis for the Genes to Health initiative, and make physiological genomics a reality applicable to whole organisms, from bacteria to man. © 2000 Biomedical Engineering Society.

PAC00: 8710+e

Simulation analysis Biological systems modeling Complexity Chaos Dynamic Systems Milieu interieure Homeodynamics Homeostasis Metabolism Control 

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References

  1. 1.
    Bassingthwaighte, J. B., and H. Reuter. Calcium movements and excitation-contraction coupling in cardiac cells. In: Elec-trical Phenomena in the Heart, edited by W. C. DeMello. New York: Academic, 1972, pp. 353-395.Google Scholar
  2. 2.
    Bassingthwaighte, J. B., R. B. King, and S. A. Roger. Fractal nature of regional myocardial blood flow heterogeneity. Circ. Res. 65:578-590, 1989.Google Scholar
  3. 3.
    Bassingthwaighte, J. B., C. Y. Wang, and I. S. Chan. Blood-tissue exchange via transport and transformation by endothe-lial cells. Circ. Res. 65:997-1020, 1989.Google Scholar
  4. 4.
    Bassingthwaighte, J. B., L. S. Liebovitch, and B. J. West. Fractal Physiology. New York: Oxford University Press, 1994, p. 364.Google Scholar
  5. 5.
    Bassingthwaighte, J. B. and D. A. Beard. Fractal 15 O-water washout from the heart. Circ. Res. 77:1212-1221, 1995.Google Scholar
  6. 6.
    Bassingthwaighte, J. B., C. A. Goresky, and J. H. Linehan, Editors. Whole Organ Approaches to Cellular Metabolism. 1057 Strategies for the Physiome Project.Capillary Permeation, Cellular Uptake and Product Forma-tion. New York: Springer, 1998, p. 575.Google Scholar
  7. 7.
    Beadle, G. W. and E. L. Tatum. Genetic control of biochemi-cal reactions in Neurospora. Proc. Natl. Acad. Sci. U.S.A. 27:499-506, 1941.Google Scholar
  8. 8.
    Beard, D. and J. B. Bassingthwaighte. Advection and diffu-sion of substances in biological tissues with complex vascular networks. Ann. Biomed. Eng. 28:253-268, 2000.Google Scholar
  9. 9.
    Beard, D. A. and J. B. Bassingthwaighte. Fractal nature of myocardial blood flow described by a whole-organ model of arterial network. J. Vasc. Res. 37:282-296, 2000.Google Scholar
  10. 10.
    Beeler, Jr., G. W. and H. Reuter. Reconstruction of the action potential of ventricular myocardial fibers. J. Physiol. (Lon-don) 268:177-210, 1977.Google Scholar
  11. 11.
    Blinks, J. R., R. Rudel, and S. R. Taylor. Calcium transients in isolated amphibian skeletal muscle fibers: detection with aequorin. J. Physiol. (London) 277:291-323, 1978.Google Scholar
  12. 12.
    Boyd, C. A. R. and D. Noble. The Logic of Life: The Chal-lenge of Integrative Physiology. New York: Oxford Univer-sity Press, 1993, p. 226.Google Scholar
  13. 13.
    Caldwell, J. H., G. V. Martin, G. M. Raymond, and J. B. Bassingthwaighte. Regional myocardial flow and capillary permeability-surface area products are nearly proportional. Am. J. Phys. 267 ~Heart Circ. Physiol. 36!:H654-H666, 1994.Google Scholar
  14. 14.
    Ch'en, F. F., R. D. Vaughan-Jones, K. Clarke, and D. Noble. Modeling myocardial ischaemia and reperfusion. Prog. Bio-phys. Mol. Biol. 69:515-538, 1998.Google Scholar
  15. 15.
    Cowley, Jr., A. W., M. Stoll, A. S. Greene, M. L. Kaldunski, R. J. Roman, P. J. Tonellato, N. J. Schork, P. Dumas, and H. J. Jacob. Genetically defined risk of salt sensitivity in an intercross of Brown Norway and Dahl S rats. Physiological Genomics 2:107-115, 2000.Google Scholar
  16. 16.
    DiFrancesco, D. and D. Noble. A model of cardiac electrical activity incorporating ionic pumps and concentration changes. Philos. Trans. R. Soc. London, Ser. B 307:353-398, 1985.Google Scholar
  17. 17.
    Gillis, H.L. and K. R. Lutchen. How heterogeneous broncho-constriction affects ventilation and pressure distributions in human lungs: a morphometric model. Ann. Biomed. Eng. 27:14-22, 1999.Google Scholar
  18. 18.
    Gillis, H. L. and K. R. Lutchen. Airway remodeling in asthma amplifies the heterogeneous smooth muscle shorten-ing causing hyperresponsiveness. J. Appl. Physiol. 86:2001-2012, 1999.Google Scholar
  19. 19.
    Glass, L., P. Hunter, and A. McCulloch. Theory of Heart: Biomechanics, Biophysics, and Nonlinear Dynamics of Car-diac Function. New York: Springer, 1991, p. 611.Google Scholar
  20. 20.
    Guyton, A. C., T. G. Coleman, and H. J. Granger. Circula-tion: overall regulation. Annu. Rev. Physiol. 34:13-46, 1972.Google Scholar
  21. 21.
    Hodgkin, A. L. and B. Katz. The effect of sodium ions on the electrical activity of the giant axon of the squid. J. Physiol. (London) 108:37-77, 1949.Google Scholar
  22. 22.
    Hodgkin, A. L. and A. F. Huxley. A quantitative description of membrane current and its application to conduction and excitation in nerve. J. Physiol. (London) 117:500-544, 1952.Google Scholar
  23. 23.
    Jafri, M. S., J. J. Rice, and R. L. Winslow. Cardiac Ca 21 dynamics: The roles of ryanodine receptor adaptation and sarcoplasmic reticulum load. Biophys. J. 74:1149-1168, 1998.Google Scholar
  24. 24.
    Jalife, J., J. M. Davidenko, and D. C. Michaels. A new perspective on the mechanisms of arrhythmias and sudden cardiac death: Spiral waves of excitation in heart muscle. J. Cardiovasc. Electrophysiol. 2:S133-S152, 1991.Google Scholar
  25. 25.
    Kassab, G. S., C. A. Rider, N. J. Tang, and Y. B. Fung. Morphometry of pig coronary arterial trees. Am. J. Physiol. 265 (Heart Circ. Physiol. 34):H350-H365, 1993.Google Scholar
  26. 26.
    Koshland, Jr., D. E. Switches, thresholds and ultrasensitivity. TIBS 12:225-229, 1987.Google Scholar
  27. 27.
    Koshland, Jr., D. E. The era of pathway quantification. Sci-ence 280:852-853, 1998.Google Scholar
  28. 28.
    LeGrice, I. J., B. H. Smaill, L. Z. Chai, S. G. Edgar, J. B. Gavin, and P. J. Hunter. Laminar structure of the heart: Ventricular myocyte arrangement and connective tissue ar-chitecture in the dog. Am. J. Physiol. 269 (Heart Circ. Physiol. 38):H571-H582, 1995.Google Scholar
  29. 29.
    Luo, C.H. and Y. Rudy. A dynamic model of the cardiac ventricular action potential I. Simulations of ionic currents and concentration changes. Circ. Res. 74:1071-1096, 1994.Google Scholar
  30. 30.
    Luo, C. H. and Y. Rudy. A dynamic model of the cardiac ventricular action potential: II: Afterdepolarizations, triggered activity, and potentiation. Circ. Res. 74:1097-1113, 1994.Google Scholar
  31. 31.
    McCulloch, A., J. B. Bassingthwaighte, P. Hunter, and D. Noble. Computational Biology of the Heart: From Structure to Function Progress in Biophysics and Molecular Biology New York: Elsevier, 1998, Vol. 69, pp. 151-572.Google Scholar
  32. 32.
    Montani, J. P., T. H. Adair, R. L. Summers, T. G. Coleman, and A. C. Guyton. A simulation support system for solving large physiological models on microcomputers. Int. J. Bio-Med. Comput. 24:41-54, 1989.Google Scholar
  33. 33.
    Noble, D. and R. W. Tsien. Outward membrane currents activated in the plateau range of potentials in cardiac Purkinje fibers. J. Physiol. (London) 200:205-231, 1969.Google Scholar
  34. 34.
    Platt, J. R.. Strong inference. Science 146:347-353, 1964.Google Scholar
  35. 35.
    Ringer, S.. A further contribution regarding the influence of the different constituents of the blood on the contraction of the heart. J. Physiol. (London) 4:29-42, 1883.Google Scholar
  36. 36.
    Schomburg, D., M. Saltzmann, and D. Stephen. Enzyme Handbook. Berlin: Springer, 1990.Google Scholar
  37. 37.
    Vetter, F. J. and A. D. McCulloch. Three-dimensional analy-sis of regional cardiac function: a model of rabbit ventricular anatomy. Prog. Biophys. Mol. Biol. 69:157-183, 1998.Google Scholar
  38. 38.
    Vetter, F. J. and A. D. McCulloch. Three-dimensional stress and strain in passive rabbit left ventricle: A model study. Ann. Biomed. Eng. 28:781, 2000.Google Scholar
  39. 39.
    Weidmann, S.. The electrical constants of Purkinje fibers. J. Physiol. (London) 118:348-360, 1952.Google Scholar
  40. 40.
    Wilson, E. O. Consilience: The Unity of Knowledge.New York: Alfred A. Knopf, 1998, p. 332.Google Scholar
  41. 41.
    Winslow, R. L., J. Rice, S. Jafri, E. Marba´n, and B. O'Rourke. Mechanisms of altered excitation-contraction cou-pling in canine tachycardia-induced heart failure, II: Model studies. Circ. Res. 84:571-586, 1999.Google Scholar
  42. 42.
    Winslow, R. L., D. F. Scollan, A. Holmes, C. K. Yung, J. Zhang, and M. S. Jafri. Electrophysical modeling of cardiac ventricular function: From cell to organ. Ann. Biomed. Eng. 2:119-155, 2000.Google Scholar
  43. 43.
    Wood, E. H., R. L. Heppner, and S. Weidmann. Inotropic effects of electric currents. I. Positive and negative effects of constant electric currents or current pulses applied during cardiac action or potentials. II. Hypotheses: calcium move-ments, excitation-contraction coupling and inotropic effects. Circ. Res. 24:409-445, 1969.Google Scholar
  44. 44.
    Zamir, M. and H. Chee. Segment analysis of human coronaryarteries. Blood 24:76-84, 1987.Google Scholar

Copyright information

© Biomedical Engineering Society 2000

Authors and Affiliations

  • James B. Bassingthwaighte
    • 1
  1. 1.Department of BioengineeringUniversity of WashingtonSeattle

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