title: Pharmacokinetic-pharmacodynamic modeling of antipsychotic drugs in patients with schizophrenia Part I: the use of PANSS total score and clinical utility.
abstract: BACKGROUND
  To develop a pharmacokinetic-pharmacodynamic (PK-PD) model using individual-level data of Positive and Negative Syndrome Scale (PANSS) total score to characterize the antipsychotic drug effect taking into account the placebo effect and dropout rate. In addition, a clinical utility (CU) criterion that describes the usefulness of a drug therapy was calculated using the efficacy of the drug and dropout rates.
  
  
  METHODS
  Data from 12 clinical trials in schizophrenia patients was used to quantify the effects of the antipsychotic drugs (APs), namely, haloperidol, risperidone, olanzapine, ziprasidone and paliperidone. Compartmental PK models were used to describe the time course of plasma drug concentrations. The combination of an Emax and the Weibull model was used to describe the drug and placebo effects. The steady-state drug concentrations were assumed to be the drivers of the exposure-response relationship. An exponential model was utilized to identify the predictors of probability of dropout. Simulations were performed to check the predictability of the model, and to calculate the CU of the drugs based on PANSS scores and dropout rates.
  
  
  RESULTS
  The maximal drug effect (E(max)) was highest for olanzapine whilst it was lowest for ziprasidone. Higher observed PANSS scores resulted in a greater likelihood of dropout. Taking into account the efficacy and the drop-out rate, all APs possessed a comparable CU at the therapeutic doses. The resulting PK-PD model parameters were used to compute the effective concentration and dose required to produce a clinically meaningful 30% drop in PANSS score from the baseline.
  
  
  CONCLUSIONS
  The developed PK-PD model and the associated CU score allow the evaluation of the time course of the PANSS scores of the different APs and a proper comparison of their clinically relevant treatments effects.
authors.affiliation: Division of Pharmacokinetics, Toxicology and Targeting, University Centre for Pharmacy, University of Groningen, The Netherlands.
authors.forename: Venkatesh
authors.initials: V
authors.lastname: Pilla Reddy
authors.forename: Magdalena
authors.initials: M
authors.lastname: Kozielska
authors.forename: Ahmed Abbas
authors.initials: AA
authors.lastname: Suleiman
authors.forename: Martin
authors.initials: M
authors.lastname: Johnson
authors.forename: An
authors.initials: A
authors.lastname: Vermeulen
authors.forename: Jing
authors.initials: J
authors.lastname: Liu
authors.forename: Rik
authors.initials: R
authors.lastname: de Greef
authors.forename: Geny M M
authors.initials: GM
authors.lastname: Groothuis
authors.forename: Meindert
authors.initials: M
authors.lastname: Danhof
authors.forename: Johannes H
authors.initials: JH
authors.lastname: Proost
mesh_terms: D014150:Antipsychotic Agents / Q000493:pharmacokinetics* / Q000627:therapeutic use*; D002986:Clinical Trials as Topic; D005260:Female; D006801:Humans; D008297:Male; D008962:Models, Theoretical; D009010:Monte Carlo Method; D015337:Multicenter Studies as Topic; D010352:Patient Dropouts / Q000706:statistics & numerical data; D015990:Placebo Effect; D011569:Psychiatric Status Rating Scales; D015203:Reproducibility of Results; D012189:Retrospective Studies; D012559:Schizophrenia / Q000097:blood / Q000188:drug therapy*; D016896:Treatment Outcome
chemical_list: D014150:Antipsychotic Agents