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Model-based computational precision medicine to develop combination therapies for autoimmune diseases
Emiko Desvaux1,2, Audrey Aussy1, Sandra Hubert1
1Servier, Research and Development, Suresnes Cedex, France.
Expert Review of Clinical Immunology
|November 29, 2021
Summary
Precision medicine for autoimmune diseases (AIDs) uses Artificial Intelligence (AI) to model complex inflammation. This approach enables rational drug combinations for better patient stratification and treatment targeting.
Area of Science:
- Immunology
- Computational Biology
- Precision Medicine
Background:
- Autoimmune diseases (AIDs) exhibit complex pathophysiology with multiple pro-inflammatory pathways.
- Heterogeneous clinical phenotypes and disease progression are observed in AIDs.
Purpose of the Study:
- To explore the use of Artificial Intelligence (AI) and multi-omics data for modeling autoimmune diseases.
- To inform the rational design of combination therapies for AIDs.
- To support patient stratification and identify therapeutic targets and biomarkers.
Main Methods:
- Comprehensive multi-omics molecular profiling of patients.
- Artificial Intelligence (AI)-powered computational analyses for AID modeling.
- Integration of data from five key immune compartments involved in AIDs.
Main Results:
- AID models facilitate patient stratification into homogeneous subgroups.
- Models elucidate dysregulated pro-inflammatory pathways.
- Hypotheses generated for therapeutic targets and biomarkers for patient monitoring.
Conclusions:
- Rationally designed combination therapies are crucial for future AID management.
- Computational Precision Medicine, integrating patient-specific data, is key.
- Model-based approaches enhance the understanding and treatment of AIDs.
