(1026-C) Cross-platform assessment of high-throughput mass-spectrometry based quality control of compound libraries
Tuesday, February 6, 2024
12:00 PM – 1:00 PM EST
Location: Exhibit Halls AB
Abstract: Mass spectrometry is unparalleled as a detection modality in terms of sensitivity and universality. However, mass spectrometry has found relatively limited use in drug discovery due to the low throughput (1-5 minutes per sample) of LC/MS analysis, which conflicts with the high throughput requirements of modern drug discovery campaigns, which routinely screen synthetic libraries of 10,000-100,000 members. It is an open challenge in drug discovery to assure the integrity of these synthetic libraries. The lack of high quality libraries available to academic and public institutions is a major stumbling block for translational research. Direct sampling techniques are necessary to achieve the < 10s per sample throughput required for quality control of synthetic compound libraries. Currently, a few paradigms exist in mass spectrometry potentially capable of achieving this throughput. Matrix assisted laser desorption ionization coupled to time-of-flight mass spectrometry (MALDI-ToF) is an established method for high throughput compound quality control that has been used in industry for at least 8 years. However, the sample preparation requirements for MALDI spotting and the inherent quantitative variability of matrix-assisted ionization leaves room for next-generation solutions. Recently, acoustic droplet ejection mass spectrometry (ADE-MS) has been utilized for high-throughput analysis in a variety of different applications, and could potentially match the throughput of MALDI-ToF without the aforementioned drawbacks. We constructed a custom ADE-MS platform by coupling an EDC Biosystems acoustic dispenser to an open-port-interface (OPI) connected to a Sciex 6600+ mass spectrometer. In this presentation/poster, we compare this platform with MALDI-ToF mass spectrometry using a pilot library of ~4000 compounds. We report several metrics related to the performance of both platforms, such as the coverage, throughput, consistency, and quantitative sensitivity for a variety of different compound classes.