In silico modeling: methods and applications to trauma and sepsis

Abstract

Objectives: To familiarize clinicians with advances in computational disease modeling applied to trauma and sepsis.

Data sources: PubMed search and review of relevant medical literature.

Summary: Definitions, key methods, and applications of computational modeling to trauma and sepsis are reviewed.

Conclusions: Computational modeling of inflammation and organ dysfunction at the cellular, organ, whole-organism, and population levels has suggested a positive feedback cycle of inflammation → damage → inflammation that manifests via organ-specific inflammatory switching networks. This structure may manifest as multicompartment "tipping points" that drive multiple organ dysfunction. This process may be amenable to rational inflammation reprogramming.

Figure 1. The progression from measurement to modeling to modulation in sepsis and trauma

Quantitative (in silico) methods have progressed from purely association-based statistical methods to dynamic mechanistic modeling capable of predicting the responses of patient cohorts and individuals as well as suggesting novel therapies. Data-driven and mechanistic modeling methods are now being integrated. Future possibilities include the design of novel diagnostics and therapies based on in silico modeling.