In silico trials and personalized therapy for sepsis and trauma

Randomized, placebo-controlled clinical trials are the current gold standard for proof of clinical efficacy of a given drug or device. Unfortunately, recent history is littered with therapeutics being withdrawn despite having been proven efficacious and safe in pivotal (Phase III) clinical trials. Moreover, many drug candidates fail at various stages before reaching such pivotal trials. Together, these failures contribute significantly to the overall lack of therapeutics for the complex diseases that affect both developing and industrialized nations. Inflammation is a common etiologic feature of these complex diseases. We have suggested that mechanistic computational modeling can provide a rational strategy for enhancing and integrating the currently fragmented process by which therapeutic targets and candidates are selected, by which clinical trials of existing and emerging therapeutics could be tailored to a given disease, and by which diagnosis and therapy could be tailored to the individual patient. Herein, we review the rationale, background, and key developments of this Translational Systems Biology approach.