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Predictive Biomarkers for Linking Disease Pathology and Drug Effect
Bernd Mayer1, Andreas Heinzel, Arno Lukas
1Emergentec Biodevelopment GmbH, Gersthoferstrasse 29-31, 1180 Vienna, Austria.
Current Pharmaceutical Design
|October 11, 2016
Summary
Drug development faces high attrition, especially for chronic diseases. Systems Biology and predictive biomarkers offer a path forward by linking molecular data to clinical outcomes, improving drug response prediction and patient stratification.
Area of Science:
- Drug Development
- Systems Biology
- Biomarker Discovery
Background:
- Drug R&D faces significant attrition in clinical trials, slowing new molecular entity approvals, particularly for chronic, age-related diseases.
- Novel conceptual, methodological, and organizational approaches are needed to improve drug development efficiency.
Purpose of the Study:
- To explore the potential of Systems Biology and detailed phenotyping to bridge molecular disease specifics with clinical outcomes.
- To investigate the use of integrative analytics for predicting drug response and improving patient stratification.
Main Methods:
- Utilized detailed disease phenotyping and drug mechanism of action representation.
- Employed Systems Biology approaches for integrative analytics to establish causal relationships.
- Applied network analytics on protein-coding genes and computational hypothesis generation.
Main Results:
- Bottom-up modeling, specifically dynamical hierarchies, can represent clinical findings as emergent properties of molecular networks.
- Biomarker candidates act as proxies for molecular processes, enabling patient stratification and drug response prediction.
- Network analytics and optimized workflows have demonstrated success in matching disease presentation with drug effects.
Conclusions:
- Biomarker-based enrichment strategies in adaptive clinical trials can mitigate development attrition.
- Predictive biomarkers enhance precision in drug development and serve as companion diagnostics in clinical practice.
Keywords:
Clinical phenotypingbig datacausalitydisease pathologydrug developmentprecision medicinestudy designMore Related Videos
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