Drug delivery optimization through Bayesian networks.
This paper describes how Bayesian Networks can be used in combination with compartmental models to plan Recombinant Human Erythropoietin (r-HuEPO) delivery in the treatment of anemia of chronic uremic patients. Past measurements of hematocrit or hemoglobin concentration in a patient during the therapy can be exploited to adjust the parameters of a compartmental model of the erythropoiesis. This adaptive process allows more accurate patient-specific predictions, and hence a more rational dosage planning. We describe a drug delivery optimization protocol, based on our approach. Some results obtained on real data are presented.
Bellazzi
R
R
Dpt. Informatica e Sistemistica, Universitá di Pavia, Italy.
D000740:Anemia / Q000188:drug therapy / Q000209:etiology; D001499:Bayes Theorem; D003198:Computer Simulation; D004360:Drug Therapy, Computer-Assisted; D004921:Erythropoietin / Q000008:administration & dosage* / Q000627:therapeutic use; D006801:Humans; D011994:Recombinant Proteins / Q000008:administration & dosage / Q000627:therapeutic use; D014511:Uremia / Q000150:complications / Q000188:drug therapy*
D011994:Recombinant Proteins; D004921:Erythropoietin