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Clinical trial simulation elements

Complex pharmacokinetic/pharmacodynamic (PK/PD) simulations are usually developed in a modular manner. Each component or subsystem of the overall simulation is developed one-by-one and then each component is linked to run in a continuous manner (see Figure 33.2). Simulation of clinical trials consists of a covariate model and input-output model coupled to a trial execution model (10). The covariate model defines patient-specific characteristics (e.g., age, weight, clearance, volume of distribution). The input-output model consists of all those elements that link the known inputs into the system (e.g., dose, dosing regimen, PK model, PK/PD model, covariate-PK/PD relationships, disease progression) to the outputs of the system (e.g., exposure, PD response, outcome, or survival). In a stochastic simulation, random error is introduced into the appropriate subsystems. For example, between-subject variability may be introduced among the PK parameters, like clearance. The outputs of the system are driven by the inputs... [Pg.854]

Elemental considerations may be broad comparisons, such as parallel group versus randomized crossover designs. Simulation also may assist in assigning the trial s primary endpoint, where the simulated probabilities of a successful trial for several clinically meaningful outcomes could be used to determine the most appropriate primary endpoint. [Pg.886]


See other pages where Clinical trial simulation elements is mentioned: [Pg.346]    [Pg.8]    [Pg.384]    [Pg.545]    [Pg.2807]    [Pg.68]    [Pg.294]    [Pg.450]   
See also in sourсe #XX -- [ Pg.854 , Pg.855 , Pg.856 , Pg.857 ]




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