Integrated and automated high-throughput purification of libraries on microscale

Microtiter Plate Cultivation Systems Enable Chemically Diverse Metabolic Footprints During Bacterial Natural Product Discovery

Rediscovery of known structures is a frequent problem in screening for bioactive bacterial natural products (NPs). Highly parallelized microtiter plate cultivation systems (MPCS) can improve the chance to discover novel NPs by testing a multitude of cultivation conditions simultaneously. An in-depth analysis and comparison of cultivation systems for NP discovery, however, has not been carried out so far. We compared the growth and metabolic footprint of four distinct bacterial species in three MPCS, shake flasks, and stirred tank bioreactors (STR). While the big majority of the cultivation systems provided good growth, we found a considerable divergence in secondary metabolite (SM) formation. The SM space was approximated by the appearance of unique mass features (MFs) in the supernatant extracts throughout the cultivation period. Molecular network analysis was applied to visualize the changes from detected MFs at the molecular level. The cultivation systems had a minor impact on the unicellular growing Bacillus amyloliquefaciens. This impact was more pronounced for the tested filamentous bacteria, resulting in a diversified metabolic footprint. The maximal overlap of 31% of produced MFs indicates a lack of comparability between the cultivation systems, resulting in different entries of growth phases and the formation of associated SMs. The detected SMs and its derivatives exhibited structural modification depending on the cultivation system. A comparison of Streptomyces griseochromogenes NP profile revealed that MPCS yielded less divergent SM formation than shake flasks. Our comprehensive assessment is the first to demonstrate the impact of cultivation systems on the bacterial metabolic footprint, confirming that MPCS provide a robust platform for the parallelization of bacterial cultivations for the discovery of bacterial NPs and accessing the chemical NP space more broadly.

A 'One-Shot' strategy for preparative chiral sub/supercritical fluid chromatography with chiroptical detection accelerates purification and enhances characterization for drug discovery

The advantages of a streamlined SFC chiral workflow for preparative chromatographic resolution of the enantiomers of investigational new compounds for pharmaceutical discovery on 10-20 mg scale with on-line chiroptical detection is described. The workflow has been designed to supply milligram amounts of enantiopure material using a universal gradient elution approach. Implementation of a faster and more labor efficient chiral purification workflow was the primary objective, with the secondary objective being an on-line collection of stereochemical information for separated enantiomers with the return of weighed compounds with acceptable purity. Column selection is carried out by gradient analytical SFC screening of six columns in 20 mins, while preparative resolution is carried out in a single injection using an 8-minute gradient with on-line polarimetric detection to assign and confirm the unique optical rotations of each of the eluted enantiomers. Additionally, electrospray ionization mass spectrometry detection is employed to facilitate fraction collection as well as product identification. The new workflow was piloted over a several month period and has proved to be an effective strategy for small scale preparative enantioseparations. Although these smaller-scale chiral separations currently constitute only a sixth of submissions in our laboratory, the one-shot workflow offers clear advantages for rapidly providing enantiopure material for initial in-vitro testing, reducing purification and evaporation cycle times and labor requirements.

Automated high-throughput RP-HPLC-MS and SFC-MS analytical and purification platforms to support drug discovery

In recent years, the need to accelerate drug discovery processes in the pharmaceutical industry has revived the interest of implementing automated workflows, allowing the simultaneous processing of multiple samples on global processes that are referred as High-Throughput Purification (HTP). In this work, SAPIO Laboratory Information Management System (SAPIO LIMSSM) has been customized at the HTP laboratories of Janssen R&D to accommodate the needs of global purification groups on several automated HTP workflows, integrating Analytical Studio™ data processing tool on multiple steps. Herein we describe the workflow details from crude analysis via RP-LC-MS or SFC-MS systems to sample redissolution and delivery to Compound Logistics (CL) in tubes ready for assay plate preparation. This includes robotic platforms to streamline sample handling and automation tools to facilitate chromatographic and Nuclear Magnetic Resonance (NMR) analyses. The combination of Analytical StudioTM and the SAPIO LIMSSM has increased the productivity of Janssen HTP teams since 2020, having a big impact on reducing the Design-Make-Test-Analyze (DMTA) cycles. To the best of our knowledge, this is the first time that a complete HTP workflow with a LIMS is being reported, including RP-HPLC and/or SFC, High-Throughput Nuclear Magnetic Resonance (HT-NMR), redissolution and submission as DMSO solutions of registered compounds to CL, ready for biological assay distribution.

An Automated Purification Workflow Coupled with Material-Sparing High-Throughput 1H NMR for Parallel Medicinal Chemistry

In medicinal chemistry, purification and characterization of organic compounds is an ever-growing challenge, with an increasing number of compounds being synthesized at a decreased scale of preparation. In response to this trend, we developed a parallel medicinal chemistry (PMC)-tailored platform, coupling automated purification to mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (NMR) on a range of synthetic scales (∼3.0-75.0 μmol). Here, the generation and acquisition of 1.7 mm NMR samples is fully integrated into a high-throughput automated workflow, processing 36 000 compounds yearly. Utilizing dead volume, which is inaccessible in conventional liquid handling, NMR samples are generated on as little as 10 μg without consuming material prioritized for biological assays. As miniaturized PMC synthesis becomes the industry standard, we can now obtain quality NMR spectra from limited material. Paired with automated structure verification, this platform has the potential to allow NMR to become as important for high-throughput analysis as ultrahigh performance liquid chromatography (UPLC)-MS.

Predictions of Chromatography Methods by Chemical Structure Similarity to Accelerate High-Throughput Medicinal Chemistry

We introduce a new workflow that relies heavily on chemical quantitative structure-retention relationship (QSRR) models to accelerate method development for micro/mini-scale high-throughput purification (HTP). This provides faster access to new active pharmaceutical ingredients (APIs) through high-throughput experimentation (HTE). By comparing fingerprint structural similarity (e.g., Tanimoto index) with small training data sets containing a few hundred diverse small molecule antagonists of a lipid metabolizing enzyme, we can predict retention time (RT) of new compounds. Machine learning (ML) helps to identify optimal separation conditions for purification without performing the traditional crude QC step involving ultrahigh performance liquid chromatography (UHPLC) analyses of each compound. This green-chemistry approach with the use of predictive tools reduces cost and significantly shortens the design-make-test (DMT) cycle of new drugs by way of HTE.

Data processing for high-throughput mass spectrometry in drug discovery

INTRODUCTION

High-throughput mass spectrometry that could deliver > 10 times faster sample readout speed than traditional LC-based platforms has emerged as a powerful analytical technique, enabling the rapid analysis of complex biological samples. This increased speed of MS data acquisition has brought a critical demand for automatic data processing capabilities that should match or surpass the speed of data acquisition. Those data processing capabilities should serve the different requirements of drug discovery workflows.

AREAS COVERED

This paper introduced the key steps of the automatic data processing workflows for high-throughput MS technologies. Specific examples and requirements are detailed for different drug discovery applications.

EXPERT OPINION

The demand for automatic data processing in high-throughput mass spectrometry is driven by the need to keep pace with the accelerated speed of data acquisition. The seamless integration of processing capabilities with LIMS, efficient data review mechanisms, and the exploration of future features such as real-time feedback, automatic method optimization, and AI model training is crucial for advancing the drug discovery field. As technology continues to evolve, the synergy between high-throughput mass spectrometry and intelligent data processing will undoubtedly play a pivotal role in shaping the future of high-throughput drug discovery applications.

Parallel purification of microscale libraries via automated solid phase extraction

High-throughput experimentation (HTE) has become more widely utilized in drug discovery for rapid reaction optimization and generation of large synthetic compound arrays. While this has accelerated medicinal chemistry design, make, test (DMT) iterations, the bottleneck of purification persists, consuming time and resources. Herein we describe a general parallel purification approach based on solid phase extraction (SPE) that provides a more efficient and sustainable workflow producing compound libraries with significantly upgraded purity. This robust, user-friendly workflow is fully automated and integrated with HTE library synthesis, as demonstrated by its application to a diverse parallel library compound array generated via amide-bond coupling in HTE microscale format.

MicroCycle: An Integrated and Automated Platform to Accelerate Drug Discovery

We herein describe the development and application of a modular technology platform which incorporates recent advances in plate-based microscale chemistry, automated purification, in situ quantification, and robotic liquid handling to enable rapid access to high-quality chemical matter already formatted for assays. In using microscale chemistry and thus consuming minimal chemical matter, the platform is not only efficient but also follows green chemistry principles. By reorienting existing high-throughput assay technology, the platform can generate a full package of relevant data on each set of compounds in every learning cycle. The multiparameter exploration of chemical and property space is hereby driven by active learning models. The enhanced compound optimization process is generating knowledge for drug discovery projects in a time frame never before possible.

High-throughput synthesis provides data for predicting molecular properties and reaction success

The generation of attractive scaffolds for drug discovery efforts requires the expeditious synthesis of diverse analogues from readily available building blocks. This endeavor necessitates a trade-off between diversity and ease of access and is further complicated by uncertainty about the synthesizability and pharmacokinetic properties of the resulting compounds. Here, we document a platform that leverages photocatalytic N-heterocycle synthesis, high-throughput experimentation, automated purification, and physicochemical assays on 1152 discrete reactions. Together, the data generated allow rational predictions of the synthesizability of stereochemically diverse C-substituted N-saturated heterocycles with deep learning and reveal unexpected trends on the relationship between structure and properties. This study exemplifies how organic chemists can exploit state-of-the-art technologies to markedly increase throughput and confidence in the preparation of drug-like molecules.

High-Throughput Purification in Drug Discovery: Scaling New Heights of Productivity

With the "low hanging fruit" of early drug discovery gone, pharmaceutical companies are increasingly turning to developing high-throughput synthetic platforms capable of greatly shortening the design-make-test cycle of new drugs. Purification has long been considered the bottleneck of this procedure; however, new technologies and systems are now being integrated into these high-throughput synthetic workflows, providing compounds of high purity capable of being used directly in biological screening.