Previous patient data are stored in the database. Patient data can be retrieved using the patient's name or hospital identification number. The search feature allows for partial name searches using the first few characters of the patient's name.

 
 
 

 

On this initial screen, the user enters demographic data for the patient or update the patient information for the patients saved in the database. These data are used to calculate the population pharmacokinetic values specific to this patient for the drug selected.
 

This screen allows the user to enter various patient factors that are known to modify the drug's population pharmacokinetic parameters. Initial population values (priors) are modified accordingly.


This screen displays the estimated population pharmacokinetic values at the top and the exact estimates for the dose and interval required to attain the desired serum concentrations that the user has entered. The loading dose required to achieve the desired peak concentration is displayed on the bottom right of the screen.


 

On this screen, the user enters a trial dosage regimen and T.D.M.S.2000 estimates the resulting serum concentrations based on population pharmacokinetic values. Pharmacodynamic targets are calculated for antibiotics if an MIC is entered.


Once a dose or doses have been administered and blood samples have been analyzed, the dosage regimen and serum concentrations are entered on this spreadsheet screen. The screen is easy to navigate with the computer's arrow keys and individual cells can be changed to correct input errors.


After entering dosage and serum concentration data, T.D.M.S.2000 fits the data using Bayesian and nonlinear least-squares fitting algorithms. The post-fitting pharmacokinetic parameters by each method are displayed at the top of the screen, and graphical representations of serum concentrations with each method are displayed at the bottom. The red line represents the population estimates, allowing the user to readily compare the population results with the fitted results. The graphics are useful for visually spotting data entry errors.

 





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