Microscale purification in support of high-throughput medicinal chemistry

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.

Identifying opportunities for late-stage C-H alkylation with high-throughput experimentation and in silico reaction screening

Enhancing the properties of advanced drug candidates is aided by the direct incorporation of specific chemical groups, avoiding the need to construct the entire compound from the ground up. Nevertheless, their chemical intricacy often poses challenges in predicting reactivity for C-H activation reactions and planning their synthesis. We adopted a reaction screening approach that combines high-throughput experimentation (HTE) at a nanomolar scale with computational graph neural networks (GNNs). This approach aims to identify suitable substrates for late-stage C-H alkylation using Minisci-type chemistry. GNNs were trained using experimentally generated reactions derived from in-house HTE and literature data. These trained models were then used to predict, in a forward-looking manner, the coupling of 3180 advanced heterocyclic building blocks with a diverse set of sp3-rich carboxylic acids. This predictive approach aimed to explore the substrate landscape for Minisci-type alkylations. Promising candidates were chosen, their production was scaled up, and they were subsequently isolated and characterized. This process led to the creation of 30 novel, functionally modified molecules that hold potential for further refinement. These results positively advocate the application of HTE-based machine learning to virtual reaction screening.

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.

Using a Smartphone-Based Colorimetric Device with Molecularly Imprinted Polymer for the Quantification of Tartrazine in Soda Drinks

The present study reports the development and application of a rapid, low-cost in-situ method for the quantification of tartrazine in carbonated beverages using a smartphone-based colorimetric device with molecularly imprinted polymer (MIP). The MIP was synthesized using the free radical precipitation method with acrylamide (AC) as the functional monomer, N,N'-methylenebisacrylamide (NMBA) as the cross linker, and potassium persulfate (KPS) as radical initiator. The smartphone (RadesPhone)-operated rapid analysis device proposed in this study has dimensions of 10 × 10 × 15 cm and is illuminated internally by light emitting diode (LED) lights with intensity of 170 lux. The analytical methodology involved the use of a smartphone camera to capture images of MIP at various tartrazine concentrations, and the subsequent application of the Image-J software to calculate the red, green, blue (RGB) color values and hue, saturation, value (HSV) values from these images. A multivariate calibration analysis of tartrazine in the range of 0 to 30 mg/L was performed, and the optimum working range was determined to be 0 to 20 mg/L using five principal components and a limit of detection (LOD) of 1.2 mg/L was obtained. Repeatability analysis of tartrazine solutions with concentrations of 4, 8, and 15 mg/L (n = 10) showed a coefficient of variation (% RSD) of less than 6%. The proposed technique was applied to the analysis of five Peruvian soda drinks and the results were compared with the UHPLC reference method. The proposed technique showed a relative error between 6% and 16% and % RSD lower than 6.3%. The results of this study demonstrate that the smartphone-based device is a suitable analytical tool that offers an on-site, cost-effective, and rapid alternative for the quantification of tartrazine in soda drinks. This color analysis device can be used in other molecularly imprinted polymer systems and offers a wide range of possibilities for the detection and quantification of compounds in various industrial and environmental matrices that generate a color change in the MIP matrix.

Nanoliter Scale Parallel Liquid-Liquid Extraction for High-Throughput Purification on a Droplet Microarray

In the current drug discovery process, the synthesis of compound libraries is separated from biological screenings both conceptually and technologically. One of the reasons is that parallel on-chip high-throughput purification of synthesized compounds is still a major challenge. Here, on-chip miniaturized high-throughput liquid-liquid extraction in volumes down to 150 nL with efficiency comparable to or better than large-scale extraction utilizing separation funnels is demonstrated. The method is based on automated and programmable merging of arrays of aqueous nanoliter droplets with organic droplets. Multi-step extraction performed simultaneously or with changing conditions as well as handling of femtomoles of compounds are demonstrated. In addition, the extraction efficiency is analyzed with a fast optical readout as well as matrix-assisted laser desorption ionization-mass spectrometry on-chip detection. The new massively parallel and miniaturized purification method adds another important tool to the chemBIOS concept combining chemical combinatorial synthesis with biological screenings on the same miniaturized droplet microarray platform, which will be essential to accelerate drug discovery.

'Chemistry at the speed of sound': automated 1536-well nanoscale synthesis of 16 scaffolds in parallel

Screening of large and diverse libraries is the 'bread and butter' in the first phase of the discovery of novel drugs. However, maintenance and periodic renewal of high-quality large compound collections pose considerable logistic, environmental and monetary problems. Here, we exercise an alternative, the 'on-the-fly' synthesis of large and diverse libraries on a nanoscale in a highly automated fashion. For the first time, we show the feasibility of the synthesis of a large library based on 16 different chemistries in parallel on several 384-well plates using the acoustic dispensing ejection (ADE) technology platform. In contrast to combinatorial chemistry, we produced 16 scaffolds at the same time and in a sparse matrix fashion, and each compound was produced by a random combination of diverse large building blocks. The synthesis, analytics, resynthesis of selected compounds, and chemoinformatic analysis of the library are described. The advantages of the herein described automated nanoscale synthesis approach include great library diversity, absence of library storage logistics, superior economics, speed of synthesis by automation, increased safety, and hence sustainable chemistry.

Integrated and automated high-throughput purification of libraries on microscale

We herein report the development of an automation platform for rapid purification and quantification of chemical libraries including reformatting of chemical matter to 10 mM DMSO stock solutions. This fully integrated workflow features tailored conditions for preparative reversed-phase (RP) HPLC-MS on microscale based on analytical data, online fraction QC and CAD-based quantification as well as automated reformatting to enable rapid purification of chemical libraries. This automated workflow is entirely solution-based, eliminating the need to weigh or handle solids. This increases process efficiency and creates a link between high-throughput synthesis and profiling of novel chemical matter with respect to biological and physicochemical properties in relevant assays.