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Small- and large-scale biosimulation applied to drug discovery and development
C J Musante1, Annette K Lewis, Kevin Hall
1Entelos, Inc.,4040 Campbell Ave., Ste. 200, Menlo Park, CA 94025, USA. musante@entelos.com
Drug Discovery Today
|January 28, 2003
Summary
Biosimulation, using mathematical models, aids drug discovery by analyzing biological systems. Both small-scale and large-scale models offer unique insights for developing new therapies and understanding diseases.
Area of Science:
- Computational biology and mathematical modeling.
- Application of quantitative methods to biological systems.
Background:
- Biosimulation employs mathematical representations to analyze and predict biological system dynamics.
- Models range from small-scale for specific issues to large-scale for broad regulatory mechanisms.
Purpose of the Study:
- To review the application of biosimulations in drug discovery and development.
- Highlighting the utility of both small- and large-scale models.
Main Methods:
- Classification of biosimulations into small-scale and large-scale models.
- Review of case studies in drug development across various diseases.
Main Results:
- Small-scale biosimulations excel at clinical data interpretation and biomarker development.
- Large-scale biosimulations provide insights into complex biological regulation and predict therapeutic effects.
Conclusions:
- Biosimulations are valuable tools in drug discovery, offering predictive power for therapeutic interventions.
- Both model types contribute significantly to understanding and treating diseases like diabetes, HIV, heart disease, and asthma.
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