Drug dosage individualization based on a random-effects linear model.

Role of Statistical Random-Effects Linear Models in Personalized Medicine

Some empirical studies and recent developments in pharmacokinetic theory suggest that statistical random-effects linear models are valuable tools that allow describing simultaneously patient populations as a whole and patients as individuals. This remarkable characteristic indicates that these models may be useful in the development of personalized medicine, which aims at finding treatment regi...

The Mathematics of Drug Dose Individualization Should Be Built With Random-Effects Linear Models

PDC Control of Time Delay Fuzzy T-S modeled HIV-1 System through Drug Dosage

This paper proposes a Time Delay nonlinear dynamic model of HIV-1 (Human Immunodeficiency Virus type 1), introducing the drug consumption efficiencies as the controlling input for the model. The paper also represents the fuzzy T-S representation and the corresponding Fuzzy T-S controller. The controller parameters are tuned using LMIs (Linear Matrix Inequalities). The main focus is on the stabi...

Therapeutic Drug Monitoring of Sirolimus,Correlation With Laboratory Parameters In Transplant Patients

Sirolimus is a potent immunosuppressive agent administered as prophylactic agent to prevent rejection after organ transplantation. Sirolimus must be used within a narrow therapeutic window. Due to inter- and intra-variability, sirolimus blood concentrations may be affected, therefore, there is no possibility of predicting the sirolimus blood concentrations based on the dose patients received. T...

Response to Diaz and de Leon "the mathematics of drug dose individualization should be built with random effects linear models".

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