Trial Design and Statistical Considerations on the Assessment of Pharmacodynamic Similarity

Pharmacodynamic Biomarkers Evidentiary Considerations for Biosimilar Development and Approval

A biosimilar is a biological product that is highly similar to and has no clinically meaningful differences from a US Food and Drug Administration (FDA)-approved reference product. The development and approval of biosimilars is critical to enhancing the availability of safe, effective, and affordable treatment options for patients. Utilization of pharmacodynamic (PD) biomarkers can help streamline biosimilar development programs as the current process can be costly and time-consuming. Whereas PD biomarkers have not been prominently used across biosimilar approvals to date, moving forward, there is ample opportunity to increase the use of PD biomarkers in biosimilar development programs in place of comparative clinical studies with efficacy end point(s). This includes utilizing PD biomarkers that were not used as surrogate end points in approval of reference products. This mini-review summarizes how PD biomarkers have been used in biosimilar development programs to date and then discusses evidentiary considerations for PD biomarkers. In addition, study design considerations for clinical pharmacokinetic and PD assessment of proposed biosimilars are discussed. Finally, the FDA's applied regulatory science activities related to PD biomarkers for biosimilars conducted in support of the FDA's Biosimilars Action Plan are reviewed. This included conducting three clinical studies to address information gaps about PD biomarkers for biosimilars and inform general methodological best practices. In summary, enhancing our understanding of key evidentiary considerations and optimal study designs for incorporating PD biomarkers in the evaluation of proposed biosimilars can help bring more treatment options to patients faster.

Application of Trial Simulation in the Design of a Prospective Study for Concentration-QTc Analysis in Support of a Thorough QT Study Waiver

The concentration-QTc (C-QTc) analysis is often applied in the first-in-human (FIH) study to demonstrate the absence of a QTc effect in support of a TQT waiver. However, a C-QTc analysis without properly designed sensitivity could fail to conclude the absence of a QTc effect at high concentrations, even though the compound is QTc negative. This is because the 90% confidence interval (CI) of the model-derived ∆∆QTc grows wider with increasing concentration, and the upper-bound could cross the 10-ms threshold, even though the slope is close to 0. So far, there is no simple math formula to calculate the sensitivity/specificity of a C-QTc analysis. A PK/QTc trial simulation scheme was applied to optimize the design features of a C-QTc trial in FIH studies by evaluating the study's sensitivity over a wide concentration range, circumventing the problem of not knowing the target concentration during FIH studies. It was also used to ensure that the specificity of the trial was well-controlled. Simulation showed that the study sensitivity can be quantitatively gauged by optimizing the dose range, the number of samples per subjects or subject number, and by sampling around Tmax, and at steady-state. The specificity of the trial can also be evaluated with this approach, and it is important to combine model-derived ∆∆QTc and slope estimate in the evaluation. The trial simulation approach helps maximize the probability of success of C-QTc analyses in FIH studies intended to support a TQT waiver.