Introduction to Silico Trials

Although the cost of clinical trials is ever-increasing, in-silico trials, which rely on virtual populations and interventions simulated using patient-specific models, may offer a solution to contain these costs.

In order to improve ischaemic stroke treatments, such as thrombolysis and thrombectomy, we target the development of computational tools for in silico trials which can partially replace these animal and human experiments with fast simulations.

Here, we review the current and potential use of in silico trials and causal AI to increase the efficacy and safety of traditional clinical trials.

cana) methanol extract in In-silico trials and laboratory animal models.

Results: Successful use of in silico trials was observed in many of the reviewed evidence.

As In Silico Trials are a disruptively innovative class of new methodologies, it is important to have a list of possible CoUs highlighting potential applications for the development of the relative regulatory science.

Conclusion In silico trials have three significant implications for immuno-oncology.

In silico trials have the potential to refine, reduce cost, and partially replace current in vivo studies, namely clinical trials and animal testing.

In silico trials is an emerging and innovative field that can be applied to predict and simulate immune, molecular, clinical, and epidemiological outcomes of vaccines to refine, reduce, and partially replace steps in vaccine development.

Quantitative systems pharmacology (QSP) is an important approach in pharmaceutical research and development that facilitates in silico generation of quantitative mechanistic hypotheses and enables in silico trials.

The proof of the reliability of a numerical model is becoming of paramount importance in the era of in silico trials.

This paper addresses the problem of generating virtual patient cohorts of thoracic aorta geometries that can be used for in-silico trials.

The developed model together with the CARTmath platform have potential use in assessing different CAR-T cell immunotherapy protocols and its associated efficacy, becoming an accessory for in silico trials.

BACKGROUND Numerical simulations, also referred to as in silico trials, are nowadays the first step toward approval of new artificial pancreas (AP) systems.

This modeling study shows that DSS-based treatment decisions will result in a clinically relevant increase in the patients’ quality of life and can be used for in silico trials.

22 The developed model, together with the CARTmath platform, provides potential use for assessing 23 different CAR-T cell immunotherapy protocols and associated efficacy, becoming an accessory 24 towards in silico trials.

In-silico trials rely on virtual populations and interventions simulated using patient-specific models and may offer a solution to lower these costs.