Repeat Analysis and Incurred Sample Reanalysis: Recommendation for Best Practices and Harmonization from the Global Bioanalysis Consortium Harmonization Team

The A7 harmonization team (A7 HT), a part of the Global Bioanalysis Consortium (GBC), focused on reviewing best practices for repeat analysis and incurred sample reanalysis (ISR) as applied during regulated bioanalysis. With international representation from Europe, Latin America, North America and the Asia Pacific region, the team first collated common practices and guidance recommendations and assessed their suitability from both a scientific and logistical perspective. Subsequently, team members developed best practice recommendations and refined them through discussions and presentations with industry experts at scientific meetings. This review summarizes the team findings and best practice recommendations. The few topics where no consensus could be reached are also discussed. The A7 HT recommendations, together with those from the other GBC teams, provide the basis for future international harmonization of regulated bioanalytical practices

Metabolite Bioanalysis in Drug Development: Recommendations from the IQ Consortium Metabolite Bioanalysis Working Group

The intent of this perspective is to share the recommendations of the International Consortium for Innovation and Quality in Pharmaceutical Development (IQ Consortium) Metabolite Bioanalysis Working Group (WG) on the fit-for-purpose metabolite bioanalysis in support of drug development and registration. This report summarizes the considerations for the trigger, timing, and rigor of bioanalysis in the various assessments to address unique challenges due to metabolites, with respect to efficacy and safety, which may arise during drug development from IND enabling studies, and Phase I, Phase II, and Phase III clinical trials to regulatory submission. The recommended approaches ensure that important drug metabolites are identified in a timely manner and properly characterized for efficient drug development

Sensitive, High-Throughput, and Robust Trapping-Micro-LC-MS Strategy for the Quantification of Biomarkers and Antibody Biotherapeutics

For LC-MS-based targeted quantification of biotherapeutics and biomarkers in clinical and pharmaceutical environments, high sensitivity, high throughput, and excellent robustness are all essential but remain challenging. For example, though nano-LC-MS has been employed to enhance analytical sensitivity, it falls short because of its low loading capacity, poor throughput, and low operational robustness. Furthermore, high chemical noise in protein bioanalysis typically limits the sensitivity. Here we describe a novel trapping-micro-LC-MS (T-μLC-MS) strategy for targeted protein bioanalysis, which achieves high sensitivity with exceptional robustness and high throughput. A rapid, high-capacity trapping of biological samples is followed by μLC-MS analysis; dynamic sample trapping and cleanup are performed using pH, column chemistry, and fluid mechanics separate from the μLC-MS analysis, enabling orthogonality, which contributes to the reduction of chemical noise and thus results in improved sensitivity. Typically, the selective-trapping and -delivery approach strategically removes >85% of the matrix peptides and detrimental components, markedly enhancing sensitivity, throughput, and operational robustness, and narrow-window-isolation selected-reaction monitoring further improves the signal-to-noise ratio. In addition, unique LC-hardware setups and flow approaches eliminate gradient shock and achieve effective peak compression, enabling highly sensitive analyses of plasma or tissue samples without band broadening. In this study, the quantification of 10 biotherapeutics and biomarkers in plasma and tissues was employed for method development. As observed, a significant sensitivity gain (up to 25-fold) compared with that of conventional LC-MS was achieved, although the average run time was only 8 min/sample. No appreciable peak deterioration or loss of sensitivity was observed after >1500 injections of tissue and plasma samples. The developed method enabled, for the first time, ultrasensitive LC-MS quantification of low levels of a monoclonal antibody and antigen in a tumor and cardiac troponin I in plasma after brief cardiac ischemia. This strategy is valuable when highly sensitive protein quantification in large sample sets is required, as is often the case in typical biomarker validation and pharmaceutical investigations of antibody therapeutics