Considerations for Use of Pharmacodynamic Biomarkers to Support Biosimilar Development – (II) A Randomized Trial with IL‐5 Antagonists

Abstract

The US Food and Drug Administration (FDA) guidance describes how pharmacodynamic (PD) biomarkers can be used to address residual uncertainty and demonstrate no clinically meaningful differences between a proposed biosimilar and its reference product without relying on clinical efficacy end point(s). Pilot studies and modeling can inform dosing for such PD studies. To that end, we conducted a randomized, double-blinded, placebo-controlled, single-dose, parallel-arm clinical study in healthy participants to evaluate approaches to address information gaps, inform best practices for analysis of biomarker samples and study results, and apply emerging technologies in biomarker characterization. Seventy-two healthy participants (n = 8 per arm) received either placebo or 1 of 4 doses of the interleukin-5 inhibitors mepolizumab (3-24 mg) or reslizumab (0.1-0.8 mg/kg). A clinical study using doses lower than approved therapeutic doses was combined with modeling and simulation to evaluate the dose-response relationship of the biomarker eosinophils. There was no dose-response relationship for eosinophil counts due to variability, although the mepolizumab 24 mg and reslizumab 0.8 mg/kg doses showed clear effects. Published indirect-response models were used to explore eosinophil data across doses from this study and the unstudied therapeutic doses. Simulations were used to calculate typical PD metrics, such as baseline-adjusted area under the effect curve and maximum change from baseline. The simulation results demonstrate sensitivity of eosinophils as a PD biomarker and indicate doses lower than the approved doses would have PD responses overlapping with variability in the placebo arm. The simulation results further highlight the utility of model-based approaches in supporting use of PD biomarkers in biosimilar development.

New science, drug regulation, and emergent public health issues: The work of FDA’s division of applied regulatory science

“…Many of DARS' current initiatives (Figure 7) will inform the Agency's thinking on the use of pharmacodynamic (PD) biomarkers to demonstrate biosimilarity that may streamline or negate the need for comparative clinical studies (56,57). This included conducting three clinical studies (58)(59)(60) to define best practices on characterizing PD biomarkers for different classes of drugs and to develop general considerations applicable to all types of biomarkers for biological products. These studies included assessments to evaluate uses of proteomic and transcriptomic analysis of human plasma to identify novel biomarkers for biosimilar development (61).…”

Pharmacodynamic Biomarkers Evidentiary Considerations for Biosimilar Development and Approval

“…The three primary results papers and a separate proteomics analysis are reported separately in this journal. 13 , 14 , 15 …”

“…In addition to characterizing the values and variability of standard PD metrics and model parameters of prespecified biomarkers, these studies aim to contextualize the utility of omics technologies to identify and characterize biomarkers that could be used for a PD similarity assessment. The three primary results papers and a separate proteomics analysis are reported separately in this journal 13–15 …”

Advancing Innovations in Biosimilars

“…As reported in this themed issue of Clinical Pharmacology & Therapeutics ( CPT ) on Innovations in Biosimilars ( Figure ), there is an opportunity to leverage innovations in clinical pharmacology and related disciplines to improve the efficiency of biosimilar development and approval ( Figure ). One way to do this is to leverage the use of pharmacodynamic (PD) biomarkers in clinical pharmacology studies in place of comparative clinical studies with efficacy end point(s), which is discussed in multiple articles in this issue 1–5 . These articles and others 6 also discuss how modeling and simulation (or model‐informed drug development (MIDD)) can be used to optimize study design and analyses.…”

“…(PSCK9 inhibitors), 5 Gershuny et al . (IL‐5 antagonists), 4 and Florian et al . (interferon beta‐1a products), 3 and Hyland et al .…”