Bioassay case study applying the maximin D-optimal design algorithm to the four-parameter logistic model.

Cell-based potency assays play an important role in the characterization of biopharmaceuticals but they can be challenging to develop in part because of greater inherent variability than other analytical methods. Our objective is to select concentrations on a dose-response curve that will enhance assay robustness. We apply the maximin D-optimal design concept to the four-parameter logistic (4 PL) model and then derive and compute the maximin D-optimal design for a challenging bioassay using curves representative of assay variation. The selected concentration points from this 'best worst case' design adequately fit a variety of 4 PL shapes and demonstrate improved robustness.