Advanced computer programs for drug dosing that combine pharmacokinetic and symbolic modeling of patients.
In this paper, we describe our design for advanced drug dosing programs that "reason" using a combination of Bayesian pharmacokinetic modeling and symbolic modeling of patient status and drug response. Our design is similar to the design of the Digitalis Therapy Advisor program, but extends this previous work by incorporating a Bayesian pharmacokinetic model, performing a "meta-level" analysis of drug concentrations to identify sampling errors and changes in pharmacokinetics, and including the results of this analysis in reasoning for dosing and therapeutic monitoring recommendations. The design has been implemented in a program for aminoglycoside antibiotics called Aminoglycoside Therapy Manager. The program is user-friendly and runs on low-cost general-purpose hardware. The initial validation study showed that the program was as accurate in predicting future drug concentrations as an expert using commercial Bayesian forecasting software and that its dosing recommendations were similar to those of an expert.
Lenert
L A
LA
Division of Clinical Pharmacology, Stanford University, California 94305.
Lurie
J
J
Sheiner
L B
LB
Coleman
R
R
Klostermann
H
H
Blaschke
T F
TF
D000617:Aminoglycosides; D000900:Anti-Bacterial Agents / Q000627:therapeutic use; D001499:Bayes Theorem; D003198:Computer Simulation; D004360:Drug Therapy, Computer-Assisted; D006801:Humans; D004364:Pharmaceutical Preparations / Q000008:administration & dosage*; D010599:Pharmacokinetics; D012984:Software
D000617:Aminoglycosides; D000900:Anti-Bacterial Agents; D004364:Pharmaceutical Preparations