Forecasting individual pharmacokinetics.
Often drug dosage may be chosen rationally by use of plasma concentration (CP) as the "therapeutic" end point. The ability to accurately forecast the CP resulting from a dosage regimen is central to choosing that regimen. Tradionally forecasting has been attempted only by accounting for known influences on pharmacokinetics, such as sex, age, and renal disease. One must also adjust for previously observed CPs. Herein, we discuss and explain an approach to both of these tasks, mainly focusing on the latter. The approach balances observed outcomes against prior expectations taking account of observation CP error. For digoxin, use of 1 measured CP, as opposed to none, improves forecast precision for future CPs by 40% (decrement in variance of forecast error), and 2 CPs improve it by 67%. There is also an increase in forecast accuracy (decrement in mean of forecast error) as the number of CPs used increases. After only 2, forecast accuracy and precision are as good as theoretically possible. Moreover, information from CPs is far more valuable for forecasting than that from observable patient features-sex, age, and the like; use of all the latter information does not improve accuracy and precision as much as only 1 CP.
D000328:Adult; D001499:Bayes Theorem; D004077:Digoxin / Q000097:blood; D004358:Drug Therapy; D006801:Humans; D007700:Kinetics; D008954:Models, Biological; D004364:Pharmaceutical Preparations / Q000097:blood*
D004364:Pharmaceutical Preparations; D004077:Digoxin