Computationally Derived Points of Fragility of a Human Cascade Are Consistent with Current Therapeutic Strategies

Abstract

The role that mechanistic mathematical modeling and systems biology will play in molecular medicine and clinical development remains uncertain. In this study, mathematical modeling and sensitivity analysis were used to explore the working hypothesis that mechanistic models of human cascades, despite model uncertainty, can be computationally screened for points of fragility, and that these sensitive mechanisms could serve as therapeutic targets. We tested our working hypothesis by screening a model of the well-studied coagulation cascade, developed and validated from literature. The predicted sensitive mechanisms were then compared with the treatment literature. The model, composed of 92 proteins and 148 protein–protein interactions, was validated using 21 published datasets generated from two different quiescent in vitro coagulation models. Simulated platelet activation and thrombin generation profiles in the presence and absence of natural anticoagulants were consistent with measured values, with a mean correlation of 0.87 across all trials. Overall state sensitivity coefficients, which measure the robustness or fragility of a given mechanism, were calculated using a Monte Carlo strategy. In the absence of anticoagulants, fluid and surface phase factor X/activated factor X (fX/FXa) activity and thrombin-mediated platelet activation were found to be fragile, while fIX/FIXa and fVIII/FVIIIa activation and activity were robust. Both anti-fX/FXa and direct thrombin inhibitors are important classes of anticoagulants; for example, anti-fX/FXa inhibitors have FDA approval for the prevention of venous thromboembolism following surgical intervention and as an initial treatment for deep venous thrombosis and pulmonary embolism. Both in vitro and in vivo experimental evidence is reviewed supporting the prediction that fIX/FIXa activity is robust. When taken together, these results support our working hypothesis that computationally derived points of fragility of human relevant cascades could be used as a rational basis for target selection despite model uncertainty.

A probabilistic approach to identify putative drug targets in biochemical networks

“…Despite a surge in the perspectives of using mechanistic mathematical modelling in clinical development [60][61][62][63], parametric uncertainty remains a challenge to mechanistic approaches in medicine [13]. However, contrary to the scarcity of kinetic data, the comprehensive quantification of all concentrations and fluxes within a metabolic system is, at least in principle, experimentally feasible.…”

L’hétérogénéité intraclonale des tumeurs et son impact sur la médecine de précision

“…Les prédictions basées sur les données « omiques », même à l'échelon de cellules individuelles, restent encore aujourd'hui malheureusement très imprécises en partie à cause du caractère rapidement évolutif des résistances tumorales [11], mais aussi parce que ces prédictions sont faites en corrélant une signature génomique ou protéo-mique à une réponse globale de la population tumorale. Cependant, deux cellules génétiquement identiques peuvent avoir un protéome progressivement différent (changements dynamiques) et générer deux réponses opposées : résis-tance ou mort cellulaire (hétérogénéité [10]. Ces modèles peuvent aussi proposer des relations mathématiques entre les niveaux d'expressions de plusieurs protéines, qui individuellement ne représentent pas des biomarqueurs, mais qui, ensemble, acquièrent une valeur prédictive.…”

Incremental parameter evaluation from incomplete data with application to the population pharmacology of anticoagulants

“…The kinetics of the process has been recently described by a comprehensive model (15). The proenzymes and enzymes are coagulation factors, indicated by Roman numerals.…”