The complex structure of these drugs makes them difficult to separate and detect by conventional analytical methods. These drugs’ low stability means they can degrade or lose their activity during sample preparation, storage, or analysis. The high susceptibility to matrix interference means that the presence of exogenous or endogenous compounds in the biological samples can affect the accuracy and precision of the measurement. Therefore, there is a need for a sensitive, selective, and robust analytical method that can overcome these challenges and accurately quantify the peptides linked with payloads in plasma samples.
Solution
A liquid chromatography-tandem mass spectrometry (LC–MS/MS) method was developed to analyze a peptide linked with a warhead in rat, non-human primate (NHP), and human plasma. The method involved a simple protein precipitation step followed by chromatographic separation and detection using a triple-quadrupole mass spectrometer. A stable isotope-labeled peptide was used as an internal standard (IS) to correct for analyte losses and matrix effects.
The protein precipitation step was performed by adding acetonitrile to the plasma samples. This resulted in the precipitation of proteins and other interfering substances while retaining the peptide linked with the warhead and the internal standard in the supernatant. The supernatant was then injected into the LC–MS/MS system, where the peptide linked with the warhead and the internal standard (IS) were separated on a reversed-phase C18 column using a gradient elution of water and acetonitrile, both containing 0.1% formic acid.
Detection was performed by the mass spectrometer in the positive electrospray ionization mode (ESI+), using multiple reaction monitoring (MRM) of the precursor and product ions of the peptide linked with the warhead and the internal standard. The MRM transitions were optimized to achieve the highest sensitivity and specificity for the analyte and the internal standard. The developed workflow was designed to provide a robust, reproducible, and sensitive assay suitable for peptide quantification across multiple species and to support bioanalytical studies in both preclinical and clinical drug development.
Outcome
The peptide LC–MS/MS method was successfully validated according to the US FDA guidance for bioanalytical method validation. The assay demonstrated excellent linearity, accuracy, precision, selectivity, sensitivity, recovery, and stability for the peptide linked with the warhead in rat, non-human primate, and human plasma.
The calibration curves were linear over the 0.5–500 ng/mL concentration range, with correlation coefficients greater than 0.99. The accuracy and precision of the method were within the acceptance criteria of ±15% for the quality control samples and ±20% for the lower limit of peptide quantification. The method’s selectivity was demonstrated by the absence of any significant interference from blank plasma samples or plasma samples spiked with other drugs, including matrices from non-human primate studies.
The method’s sensitivity was sufficient to quantify the peptide linked with the warhead at the lower limit of quantification of 0.5 ng/mL. Recovery was consistent and reproducible, with values ranging from 85% to 95% for the peptide linked with the warhead and 90% to 100% for the internal standard. Stability was confirmed under a range of storage and handling conditions, including freeze–thaw cycles, short-term and long-term storage, and post-preparative storage, with no significant degradation observed.
The validated method was successfully applied to support pharmacokinetic studies in both preclinical and clinical settings. It demonstrated its utility and reliability for peptide quantification in plasma samples and provided valuable information for assessing the drug’s safety, efficacy, and pharmacological properties. In addition, the experimental LC–MS/MS strategy proved to be a robust platform for the quantitative analysis of peptides, proteins, and related metabolites, ensuring accurate and reproducible results across all study matrices.
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