Model-informed precision dosing (MIPD) involves modeling and simulation to predict the necessary drug dose for a given patient based on their individual characteristics that are most likely to improve efficacy and/or lower toxicity in comparison to traditional dosing.
The standard label-recommended dosing regimens may not be effective and safe in all patients due to interpatient variability in exposure and response. The goal of precision dosing is to develop tools to replace the “one drug fits all” approach that is designed for the “average person” with a new targeted paradigm for patient care.
Dosing with Bayesian Models
Model-informed precision dosing involves the application of mathematical and statistical algorithms using Bayesian models that use patient data and laboratory results to estimate a patient’s ability to absorb, process, and clear a drug from their system. Bayesian algorithms are used to forecast individualized troughs and determine optimal dosing to maintain target trough concentrations.
Using a published population model, iDose algorithms adjust the pharmacokinetic and/or pharmacodynamic parameters so that a patient-specific, individualized drug model is built. This model is used to provide a patient-specific dosing recommendation to reach a therapeutic target in which the individual will receive the right dose at the right time.
Treating adult and pediatric IBD patients with iDose
Baysient’s patented iDose system uses Bayesian models, laboratory data, and demographics to individualize infliximab dosing, effectively improving inflammatory bowel disease (IBD) patient outcomes. The standard of care dosing of infliximab is associated with significant loss of response. Research indicates that dashboards using covariates that influence infliximab pharmacokinetics may be a more precise way of optimizing anti-TNF dosing.
Marla Dubinsky, MD, compared iDose dosing with actual administered dosing regimens in the standard-of-care setting. iDose indicated that 80% of patients in Dukinsky’s trial that started on the standard dose on the label for Infliximab, were forecasted to need a different dosing regimen than what the standard dose label says.
Dubinsky stated in a recent podcast on Podcasts360, “These dashboards [using iDose] allow you to integrate the drug concentration of that individual patient and count in all factors that influence the clearance of these drugs.” When a patient is given a dose based on their individual characteristics, their response variability will decrease and improve the chances of successful drug therapy.
iDose, our cloud-based software, uses Bayesian models, routine lab results, and demographic information to allow physicians to individualize dosing to a specific target trough level. Interested in how iDose can improve your patient outcomes? Schedule a Demo today!