ALBERT

Description: This article provides an overview of four case studies to demonstrate the utility of pharmacometric analysis in biosimilar development to help design sensitive clinical pharmacology studies for the demonstration of biosimilarity. The two major factors that determine the sensitivity of a clinical pharmacokinetic/pharmacodynamic (PK/PD) study to demonstrate biosimilarity are the size of the potential difference to be detected (signal) and the inter-subject variability (noise), both of which can be characterized and predicted using pharmacometric approaches. To maximize the chance to detect any potential difference between the proposed biosimilar and the reference drug, the dose selected for the clinical pharmacology study should fall on the steep part of the dose-response curve. Pharmacometric analysis can be used to characterize the dose-response relationship using PD- or PK/PD-linked models. The understanding of the PD endpoints in terms of dynamic range of the response and the location of the studied dose on the dose-response curve can provide strategic advantage in the trial design. To reduce the inter-subject variability (noise), pharmacometric analysis can help avoid high variability associated with low doses, and decrease variability by controlling certain covariates in the inclusion/exclusion criteria. Pharmacometric analysis also can help select or justify margins for the equivalence test of PD endpoints. Pharmacometric analysis will assume an ever-increasing role in the clinical development of biosimilar drugs, as it helps to ensure that sufficient sensitivity is built into the study design to detect potential PK and PD differences.