1. model-based dose selection for next dose- finding trial 1. Introduction Exploratory clinical development trials often include biomarkers or clinical readout (safety or efficacy) that exhibit significant within-subject variability in their time courses. This variability is due in part to systemic diurnal patterns as well as apparent random changes. Typical examples include heart rate, blood pressure, cortisol and histamine. Applying mixed-effects modeling to analyze data from the entire time-course is appealing because it allows simultaneous quantification of fixed and random effects. This model-based approach is used here to extract a small drug effect signal from very noisy lung function data; previously, a primary analysis based on single measurement at 24 hours post dose had failed to establish a dose-response relationship. Model-based characterization of dose-response relationship in exploratory clinical development – extracting a small signal from noisy response data Kai Wu 1, Michael Looby 1, Per Olsson Gisleskog 2, Justin Wilkins 1, Didier Renard 1, Marie-Odile Lemarechal 1, Steve Pascoe 1 (1) Novartis Pharma, AG, Basel, Switzerland; (2) Exprimo NV, Berenlaan, 4, Beerse, B-2340, Belgium. 4. Model Parameter Estimates ParameterEstimate (% RSE)IIV (% RSE)IOV (% RSE) A: rhythm adjusted 24-hour mean FEV 1 [L]1.88 (5)32.4 (18)5.2 (19) B1: 24-hour period amplitude0.114 (10.8)39.3 (31.7)NE C1: 24-hour period phase shift [hr in clock time]14.6 (1)5.4 (36.4)NE B2: 12-hour period amplitude0.04 (13.2)NENT C1: 12-hour period phase shift [hr in clock time]9 (1.4)NENT KA [hr -1 ]0.313 (41.2)NENT KE [hr -1 ]0.094 (16.9)NE53.8 (28.1) EDK50 [μg. hr -1 ]4.05 (23.7)NE75.8 (43.1) Emax [L]0.466 (10.3)NE41.5 (42.6) Residual variability [CV%]6.2 (11.2) 2. Data Forced expiratory volume in one second (FEV 1 ) was measured in patients at pre-dose baseline and a range of time points up to 48 hours post dose in a Phase I trial: Part A and B: 34 patients; Part A only: 4 patients; Part B only: 6 patients Part A: 400 μg of Drug X, placebo, or positive control in randomized order Period 1 washoutPeriod 2 washoutPeriod 3 Part B: One of four selected dose levels of Drug X or placebo, in randomized order Period 1 washout Period 2 3. Model Structure Log-transformed FEV 1 measurements (excluding the positive control group) were analyzed simultaneously to develop a population kinetic-pharmacodynamic (K-PD) model [1] using NONMEM, Version 1.1. Model components included:  Two cosine functions with periods of 24 hours and 12 hours to account for circadian variation at baseline  A 2-compartment model with first order absorption and elimination to account for the kinetics of drug amount in the virtual effect compartment  An E max function to relate the longitudinal drug input function with the response  Exponential error models to allow for inter-individual variability (IIV) and inter-occasion variability (IOV); and an additive error model for residual variability. 5. Model Evaluation References [1] Jacqmin P. et al, Modeling response time profiles in the absence of drug concentrations; definition and performance evaluation of the K-PD model. J Pharmacokinet Pharmacodyn 2006 34: 57-85 [2] Lindbom L. et al, PsN-Toolkit-A collection of computer intensive statistical methods for non-linear mixed effect modeling using NONMEM. Comput Methods Programs Biomed 2005 79: 241-257 7. Conclusions The large between- and within-patient variability typically seen in FEV 1 data can confound a small treatment signal. Standard statistical approaches, therefore, often fail to characterize dose-response relationships, particularly in small exploratory trials. A model-based approach which accounts for systematic and random sources of variability appears to improve the signal-to-noise ratio of the efficacy signal sufficiently to enable characterization of the dose-response relationship. Goodness-of-fits Plots  From a 200-iteration bootstrap analysis using PsN [2], the model failed to converge only once, suggesting good stability. Bootstrap estimates of the mean for all model parameters indicated very small bias compared with original estimates: smaller than 10% for all fixed effects parameters, smaller than 18% for all random effects parameters.  Case-deletion diagnostics using PsN did not identify any influential subjects. NE: not estimated; NT: not tested Visual Predictive Checks where the blue shaded area represents the 95% prediction interval 6. Simulation of dose-response with FEV 1@24hr post dose as end point % of 400 μg response Predicted doses (95% CI) [μg] 90 316 (196 – NA) 75 222 (138 – 305) 50 117 (73 – 161) 10 18 (11 -24) NA: not estimable