Analysis of PK information from a patient pool that is reflective of the intended target population (i.e., not just healthy subjects or narrowly selected patients), including an assessment of inter-individual variability, which is often intentionally minimized in traditional clinical trial designs (and therefore missed by noncompartmental PK analysis).Population PK modeling approaches often provide advantages over standard noncompartmental PK analysis, including: The FDA guidance on Population Pharmacokinetics provides a framework for population PK modeling. With appropriate sampling design and model selection, the resulting PK data can be pooled and analyzed to support conclusions about PK variability and the influence of covariates. Using sparse PK sampling, only a limited number of samples are taken from any given patient. Population PK analysis involves collecting sparse PK samples (i.e., drug concentration data in a relevant matrix, which is most often plasma) from many patients and often across multiple clinical studies, and then building mathematical models to describe those data. Because patient characteristics (“covariates”), such as age, disease state, demographics, sex, concomitant medications, or presence of renal or hepatic impairment, can affect drug pharmacokinetics (PK) and pharmacodynamics (PD), understanding this variability can help establish a robust PK/PD profile and inform safe and effective dosing regimens. Population pharmacokinetics, also referred to as population PK or popPK, seeks to understand the variability in drug concentrations among individuals in a group of interest (the “population”) receiving clinically relevant doses of a drug.
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