When viewing the historical plot, if a laboratory result (black cross) is a far outlier in the range of probable results based on the population drug model, the Bayesian dosing method will assess how likely it is that this value is correct. If it is highly unlikely to be true, DoseMeRx will assume that there has been an error with the laboratory result and will weight it minimally when building the model for your individual patient. Essentially, the further any laboratory result is from what DoseMeRx considers likely, the less impact that result will have on the individual model. 

DoseMeRx is able to learn over time, meaning each subsequent lab result increases DoseMeRx’s interpretation of any outlying data. 

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