The right dose of medicine is crucial when it comes to the treatment process. For patients with inflammatory bowel disease (IBD), the wrong dose can cause patients to lose response to Infliximab (IFX), a highly effective drug used to treat ulcerative colitis, Crohn’s disease and other inflammatory diseases. 

Instead of using a “one-size-fits-all” approach for disease treatment, physicians are beginning to adopt precision dosing as a way to treat patients. Precision medicine allows physicians to predict more accurately which treatment and prevention strategies will work for that specific individual. 

To ensure patients are getting the right dose at the right time based on their individual characteristics, Baysient’s software uses Bayesian models, routine lab results and demographic information to allow physicians to individualize dosing to a specific target trough level. 

What is Bayesian Modeling for Improved Patient Outcomes?

There are many different terms to describe this concept, such as Bayesian dosing, Bayesian modeling, and model-informed precision dosing (MIPD). Bayesian modeling works by using actual patient data that is input into the model. Physicians enter individual patient data, such as clinical characteristics, previous IFX dosing history, drug concentrations and lab results. 

Bayesian forecasting then processes that patient-specific information via a pharmacokinetic/pharmacodynamic (PK) model. This model estimates the patient’s ability to absorb, process and clear a drug from their system. The bayesian algorithms are then used to forecast individualized troughs and determine optimal dosing to maintain the selected target trough concentrations. 

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The variations seen in the individual pharmacokinetics of biologics highlight the need for more prospective data to further support effective personalized dosing. By focusing on important, modifiable factors for regulating drug levels, we can improve the efficacy of inflammatory disease treatments in clinical settings.

iDose is a cloud-based software developed to facilitate the dosing of biological agents by integrating real patient’s clinical characteristics. Our software was retrospectively validated and has undergone prospective clinical trials to investigate the utility and improvement in patient outcomes.

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