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Oncology in vivo data integration for hypothesis generation
1AstraZeneca Innovation Center China, R&D Information China, Building 7, No.898 Halei Road, Zhangjiang Hi-Tech Park, Shanghai 201203, China. jenny.wei@astrazeneca.com
Journal of Integrative Bioinformatics
|July 10, 2012
Summary
AstraZeneca
Area of Science:
- Oncology
- Pharmacology
- Bioinformatics
Background:
- Integrating diverse in vivo data is crucial for oncology drug development.
- Existing data silos hinder comprehensive analysis of animal model studies.
Purpose of the Study:
- To present AstraZeneca's Oncology in vivo data integration platform.
- To enable scientists to analyze multidimensional in vivo data for drug discovery.
Main Methods:
- The platform integrates efficacy, pharmacokinetic (PK), pharmacodynamic (PD), and profiling data.
- It incorporates data from internal animal models and public in vivo studies.
- Meta-analysis tools facilitate comparisons of treatment strategies.
Main Results:
- The platform allows clustering of model efficacy and profiling data.
- It enables rapid identification of responder profiles.
- Correlation of molecular characteristics with pharmacological response is facilitated.
- Comparative pharmacology of different treatment regimens is possible.
Conclusions:
- The data integration platform enhances in vivo study analysis in oncology.
- It supports informed decision-making in preclinical drug development.
- Facilitates optimization of combination therapies and dosing strategies.
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