Model-based computational precision medicine to develop combination therapies for autoimmune diseases

ABSTRACT

Introduction

The complex pathophysiology of autoimmune diseases (AIDs) is being progressively deciphered, providing evidence for a multiplicity of pro-inflammatory pathways underlying heterogeneous clinical phenotypes and disease evolution.

Areas covered

Treatment strategies involving drug combinations are emerging as a preferred option to achieve remission in a vast majority of patients affected by systemic AIDs. The design of appropriate drug combinations can benefit from AID modeling following a comprehensive multi-omics molecular profiling of patients combined with Artificial Intelligence (AI)-powered computational analyses. Such disease models support patient stratification in homogeneous subgroups, shed light on dysregulated pro-inflammatory pathways and yield hypotheses regarding potential therapeutic targets and candidate biomarkers to stratify and monitor patients during treatment. AID models inform the rational design of combination therapies interfering with independent pro-inflammatory pathways related to either one of five prominent immune compartments contributing to the pathophysiology of AIDs, i.e. pro-inflammatory signals originating from tissues, innate immune mechanisms, T lymphocyte activation, autoantibodies and B cell activation, as well as soluble mediators involved in immune cross-talk.

Expert opinion

The optimal management of AIDs in the future will rely upon rationally designed combination therapies, as a modality of a model-based Computational Precision Medicine taking into account the patients’ biological and clinical specificities.

KEYWORDS:

• Artificial intelligence
• autoimmune diseases
• combination therapy
• disease model
• immunotherapy
• computational precision medicine
• system immunology

Article highlights

• Systemic autoimmune diseases (AIDs) are complex and heterogenous in terms of severity, organ involvement, local or systemic manifestations, as well as molecular mechanisms underlying their pathophysiology.

• Molecular profiling using multi-omics technologies allows to stratify patients on the basis of distinct endotypes revealing the complexity of AIDs.

• The contribution of multiple pro-inflammatory pathways, often shared across different diseases strongly supports the assumption that combination therapies should be considered as a preferred therapeutic option to treat AIDs.

• The rational design of optimal drug combinations can be supported by model-based approaches relying upon AI-integration of molecular and clinical data obtained from patients to target jointly multiple and well defined dysregulated inflammatory pathways.

Combination therapies represent the future in the management of immuno-inflammatory conditions, in the context of an emerging Computational Precision Medicine.

Declarations of interest

E Desvaux, A Aussy, S Hubert, F Keime-Guibert, A Blesius, P Soret, M Guedj, L Laigle and P Moingeon are employees at Servier. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Additional information

Funding

This paper was not funded.