Statistical Approaches for Establishing Appropriate Immunogenicity Assay Cut Points: Impact of Sample Distribution, Sample Size, and Outlier Removal.

The statistical assessments needed to establish anti-drug antibody (ADA) assay cut points (CPs) can be challenging for bioanalytical scientists. Poorly established CPs that are too high could potentially miss treatment emergent ADA or, when set too low, result in detection of responses that may have no clinical relevance. We evaluated 16 validation CP datasets generated with ADA assays at Regeneron's bioanalytical laboratory and compared results obtained from different CP calculation tools. We systematically evaluated the impact of various factors on CP determination including biological and analytical variability, number of samples for capturing biological variability, outlier removal methods, and the use of parametric vs. non-parametric CP determination. In every study, biological factors were the major component of assay response variability, far outweighing the contribution from analytical variability. Non-parametric CP estimations resulted in screening positivity in drug-naïve samples closer to the targeted rate (5%) and were less impacted by skewness. Outlier removal using the boxplot method with an interquartile range (IQR) factor of 3.0 resulted in screening positivity close to the 5% targeted rate when applied to entire drug-naïve dataset. In silico analysis of CPs calculated using different sample sizes showed that using larger numbers of individuals resulted in CP estimates closer to the CP of the entire population, indicating a larger sample size (~ 150) for CP determination better represents the diversity of the study population. Finally, simpler CP calculations, such as the boxplot method performed in Excel, resulted in CPs similar to those determined using complex methods, such as random-effects ANOVA.

Identification of quaternary ammonium compounds as potent inhibitors of hERG potassium channels.

The human ether-a-go-go-related gene (hERG) channel, a member of a family of voltage-gated potassium (K(+)) channels, plays a critical role in the repolarization of the cardiac action potential. The reduction of hERG channel activity as a result of adverse drug effects or genetic mutations may cause QT interval prolongation and potentially leads to acquired long QT syndrome. Thus, screening for hERG channel activity is important in drug development. Cardiotoxicity associated with the inhibition of hERG channels by environmental chemicals is also a public health concern. To assess the inhibitory effects of environmental chemicals on hERG channel function, we screened the National Toxicology Program (NTP) collection of 1408 compounds by measuring thallium influx into cells through hERG channels. Seventeen compounds with hERG channel inhibition were identified with IC(50) potencies ranging from 0.26 to 22µM. Twelve of these compounds were confirmed as hERG channel blockers in an automated whole cell patch clamp experiment. In addition, we investigated the structure-activity relationship of seven compounds belonging to the quaternary ammonium compound (QAC) series on hERG channel inhibition. Among four active QAC compounds, tetra-n-octylammonium bromide was the most potent with an IC(50) value of 260nM in the thallium influx assay and 80nM in the patch clamp assay. The potency of this class of hERG channel inhibitors appears to depend on the number and length of their aliphatic side-chains surrounding the charged nitrogen. Profiling environmental compound libraries for hERG channel inhibition provides information useful in prioritizing these compounds for cardiotoxicity assessment in vivo.

Bridging immunogenicity assays for IgG4 therapeutics: mitigating interference from Fc-Fc interactions.

AIM: A bridging immunogenicity assay for a human IgG4 mAb therapeutic was transferred to an automation system to increase throughput. However, background signal increased five- to six-fold during the 6- to 8-h run. RESULTS: Noncovalent Fc contacts formed between labeled IgG4 drugs in reagent solutions stored during the automation run. This generated substantial background signal, reducing assay sensitivity by approximately sixfold. Fc interactions also significantly impacted the confirmation assay. Fc contacts formed between labeled and unlabeled drug, significantly increasing signal inhibition (∼7-70%) in the 6-h run. CONCLUSION: Storing labeled antibody solutions separately and combining them immediately before adding to samples reduced interference from Fc interactions. Preincubation time for reagent solutions should be strictly controlled for anti-drug antibody assays with IgG4 drugs to avoid false-positive results.