PhysioLab Models

Quantitative Physiology

PhysioLab® models are the foundation of the company’s products and services. The models provide researchers with a tool to both understand the mechanisms driving untreated disease progression and to predict physiological responses to therapeutic interventions, including variability across different patient phenotypes.

The complex models are developed using top-down methodology. First, key clinical outputs are mapped to biological mechanisms. Then increasing detail on the underlying systems biology and physiology is added to enable accurate predictions and quantify clinical and sub-clinical outcomes.

Underlying the predictive ability of PhysioLab models is the diligent curation of literature, public and proprietary data and the integration of knowledge from therapeutic area experts. The models are calibrated and validated against published clinical studies to insure their accuracy and robustness.

PhysioLabs mathematically model physiological responses, biological pathways and molecular networks, diverse patient phenotypes and therapeutic interventions. Researchers use the models to rapidly and iteratively test therapeutic hypotheses by simulating diverse patient phenotypes and populations representing relevant clinical and biological variability in the models. Researchers can then evaluate quantitative and qualitative outcomes of various therapies and simulate patient response over time.

Solutions and Services

PhysioLab models are available for  for internal deployment and use via licensing. PhysioLab software can also be licensed separately to enable researchers to view the model and references or customize the model and run simulations or build one’s own model.

Predict More, Study Less

Entelos biosimulation provides predictive quantitative and qualitative insight that supports better decision-making throughout the research and development process. Entelos products support project teams in making critical decisions during target and biomarker selection, species translation, trial design, and patient stratification.

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