title: Quantitative pharmacology approach in Alzheimer's disease: efficacy modeling of early clinical data to predict clinical outcome of tesofensine.
abstract: Effective therapeutic options for Alzheimer's disease (AD) are limited and much research is currently ongoing. The high attrition rate in drug development is a critical issue. Here, the quantitative pharmacology approach (QP-A) and model-based drug development (MBDD) provide a valuable opportunity to support early selection of the most promising compound and facilitate a fast, efficient, and rational drug development process. The aim of this analysis was to exemplify the QP-A by eventually predicting the clinical outcome of a proof-of-concept (PoC) trial of tesofensine in AD patients from two small phase IIa trials. Retrospective population pharmacokinetic/pharmacodynamic (PK/PD) modeling of tesofensine, its metabolite M1, and assessment scale-cognitive subscale data from two 4-week placebo-controlled studies in 62 mild AD patients was performed using non-linear mixed effects modeling. The final PK/PD model was used to predict data of a negative 14-week phase IIb PoC trial (430 AD patients). For the PK, one-compartment models for tesofensine and M1 with first-order absorption and elimination were sufficient. An extended Emax model including disease progression best described the PK/PD relationship using effect compartments. The placebo effect was also implemented in the final PK/PD model based on a published placebo model developed in a large AD cohort. Various internal evaluation techniques confirmed the reliability and predictive performance of the PK/PD model, which also successfully predicted the 14-week PoC data. For tesofensine, the dose concentration-effect relationship has successfully been described in mild AD patients demonstrating the supportive value of PK/PD models in QP-A/MBDD in early phases of clinical development for decision-making.
authors.affiliation: Institute of Pharmacy, Department of Clinical Pharmacy, Martin-Luther-Universitaet Halle-Wittenberg, 06120 Halle, Germany.
authors.forename: Thorsten
authors.initials: T
authors.lastname: Lehr
authors.forename: Alexander
authors.initials: A
authors.lastname: Staab
authors.forename: Dirk
authors.initials: D
authors.lastname: Trommeshauser
authors.forename: Hans Guenter
authors.initials: HG
authors.lastname: Schaefer
authors.forename: Charlotte
authors.initials: C
authors.lastname: Kloft
mesh_terms: D000465:Algorithms; D000544:Alzheimer Disease / Q000188:drug therapy*; D015306:Biogenic Monoamines / Q000037:antagonists & inhibitors*; D019086:Bridged Bicyclo Compounds, Heterocyclic / Q000493:pharmacokinetics* / Q000627:therapeutic use*; D002986:Clinical Trials as Topic; D003071:Cognition / Q000187:drug effects / Q000502:physiology; D003198:Computer Simulation; D016208:Databases, Factual; D018450:Disease Progression; D004305:Dose-Response Relationship, Drug; D004311:Double-Blind Method; D005544:Forecasting; D006801:Humans; D015233:Models, Statistical; D009483:Neuropsychological Tests; D017711:Nonlinear Dynamics; D011153:Population; D016896:Treatment Outcome
chemical_list: D015306:Biogenic Monoamines; D019086:Bridged Bicyclo Compounds, Heterocyclic; C518479:Tesofensine