Optimization and Standardization of Liquid Chromatography‐Mass Spectrometry Systems for the Analysis of Drug Discovery Compounds

A KNIME Workflow for Automated Structure Verification

Adequate characterization of chemical entities made for biological screening in the drug discovery context is critical. Incorrectly characterized structures lead to mistakes in the interpretation of structure-activity relationships and confuse an already multidimensional optimization problem. Mistakes in the later use of these compounds waste money and valuable resources in a discovery process already under cost pressure. Left unidentified, these errors lead to problems in project data packages during quality review. At worst, they put intellectual property and patent integrity at risk. We describe a KNIME workflow for the early and automated identification of these errors during registration of a new chemical entity into the corporate screening catalog. This Automated Structure Verification workflow provides early identification (within 24 hours) of missing or inconsistent analytical data and therefore reduces any mistakes that inevitably get made. Automated identification removes the burden of work from the chemist submitting the compound into the registration system. No additional work is required unless a problem is identified and the submitter alerted. Before implementation, 14% of samples within the existing sample catalog were missing data on initial pass. A year after implementation, only 0.2% were missing data.

Automated open-access liquid chromatography high resolution mass spectrometry to support drug discovery projects

The need of a continuous productivity increases in medicinal chemistry laboratories of the pharmaceutical industry motivated the development, over the years, of new software solutions to enable Open-Access in many analytical techniques such as NMR or LC, among others, to characterize and assess the purity of new molecules. These approaches have been widely spread in LC with low resolution MS systems, but similar automated platforms have been rather less explored with high resolution MS. In this work, an improved Automated Open-Access methodology on an UHPLC with DAD coupled to ESI and quadrupole time-of-flight MS system is described. Detailed reports from standard UHPLC-MS runs containing chromatograms and different spectra (MS with different fragmentation) are automatically sent to the chemists. High resolution MS data is typically achieved within ± 1 mDa mass accuracy regardless of sample concentration. Upon training, chemists log-in samples into the system by selecting appropriate methods, being able to interpret the results by themselves in 95% of the cases. The instrument is working unattended, except for a limited number of samples (5%) which require more complex experiments. To the best of our knowledge, this is the first time a completely automated Open-Access LC-HRMS approach has been implemented for medicinal chemists of a pharmaceutical industry.

Reversed phase HPLC with high temperature ethanol/water mobile phases as a green alternative method for the estimation of octanol/water partition coefficients

High temperature ethanol/water was explored as a green eluent in the reversed-phase liquid chromatographic approximation of pure water retention (log k_w) and subsequent estimation of the octanol/water partition coefficient (log P) via the Collander equation and the Leave-One-Out method. As part of this work, linear solvation energy relationships were employed to compare the log k_w extrapolated systems based on high temperature ethanol/water, ambient acetonitrile/water, and ambient methanol/water mobile phases. Based on the comparisons of the three organic modifiers, high temperature ethanol/water mobile phases were observed to provide the best estimation of log P. This conclusion is based on a high log P correlation of 0.968 R² and a near unity cos θ value of 0.997 between LSER coefficient vectors of ethanol/water estimated log P and octanol/water log P systems. The method employed in this work, further, provided high correlation for the hydrogen-bonding basicity term between the two systems.