Two-part drug discovery system
First Claim
1. A method for prognosing the life or death outcome of an animal or patient in which bacterial infection or inflammation is present, comprising measuring at least two physiological factors significant to the progress of bacterial infection or inflammation and predicting the likelihood of death.
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Abstract
A mathematical prognostic in which changes in a number of physiologically significant factors are measured and interpolated to determine a “damage fluction” incident to bacterial infection or other serious inflammation, followed by either or both of in vitro or in vivo investigations of a particular active agent (drug) and adjustment of the model so as better to evaluate the particular active agent. By measuring a large number of physiologically significant factors including, but not limited to, Interleukin 6 (IL-6), Interleukin 10 (IL-10), Nitric Oxide (NO), and others, it is possible to predict life versus death by the damage function, dD/dt. To evaluate one or more drug candidates against inflammation, the mathematical model is applied first, followed by in vivo and/or in vitro investigations, and the in vivo and/or in vitro investigations are in turn used to adjust or to enhance, if applicable, the mathematical model as it is applied to the particular drug candidate.
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Citations
12 Claims
- 1. A method for prognosing the life or death outcome of an animal or patient in which bacterial infection or inflammation is present, comprising measuring at least two physiological factors significant to the progress of bacterial infection or inflammation and predicting the likelihood of death.
- 7. A method for evaluating a drug candidate, comprising enhancing the meaning of an animal model study by comparing inflammation or infection data from said animal study with human data collected from human clinical trials, said human data being considered according to the equations:
- 10. A method for evaluating a drug candidate, comprising enhancing the meaning of an animal model study by comparing inflammation or infection data from said animal study with human data collected from human clinical trials, said human data being considered according to the equations
Specification