Predictive design of crystallographic chiral separation

The efficient separation of chiral molecules is a fundamental challenge in the manufacture of pharmaceuticals and light-polarising materials. We developed an approach that combines machine learning with a physics-based representation to predict resolving agents for chiral molecules, using a transformer-based neural network. On historical data, our approach is 4-6 times more accurate than current practice. We further validate the model in a prospective experiment, where we use the model to design a resolution screen for six unseen racemates. We successfully resolved three of the six mixtures in a single round of experiments and obtained an overall 8-to-1 true positive to false negative ratio. Together with this study, we release a previously proprietary dataset of over 6,000 resolution experiments, the largest diastereomeric salt crystallisation dataset to date. More broadly, our approach and open crystallization data lay the foundation for accelerating and reducing the costs of chiral resolutions.

Methods
High-Throughput Experimentation reactions were set up inside of an INERT Inc. triple double sized glove box with O2 and H2O levels  <20 ppm. Glass vials (0.7 mL, 8 x 30 mm) pre-equipped with stir bars were used for each reaction. The reactions were set up with the components and conditions described by each dataset entry at 0.04~mmol scale and 0.2 M final concentration with a 1:1 ratio of acid to base and 200 μL total volume. The reaction vials were sealed by crimp under the glove-box environment and placed in a metal Chemglass Optichem 96-well heating plate atop a general IKA stirrer heater plate with an external temperature probe to accurately and evenly control the plate. The vials were heated for 1 hour at 80 C before being cooled over 3 hours and left to stir for a further 15hrs at 25 C. Solubility observations were made after the hour at 80 C and after the 15hr stir period at 25 C. At the reaction end point, the vials were centrifuged to settle any precipitates and the liquors sampled and analysed by chiral SFC-MS for the determination of the liquor e.e. and the calculation of solids m.frac. and e.e.

For any enriched liquor hits, the liquor was manually pipetted away from the centrifuged solid and the solid re-slurried in fresh solvent (using the same solvent choice as the reaction, half volume, 100 μL) to rinse off residual liquor. The vial was centrifuged a second time and the liquor (100 μL) again removed from the centrifuged solid and combined with the original. Both the combined liquors and the residual solid were brought to an equal volume of 500 μL using MeOH to ensure solution before being analysed by chiral SFC-MS.  Measurement of the crystallised salt product % enantiomeric enrichment (ee) from isolated solids superseded the product % ee calculated based on SFC-MS analysis of uncrystallised material in the liquors.  iChem explorer (Reaction Analytics, US) and Virscidian Analytical Studio™ software were used for data analysis.

HPLC grade methanol, isopropanol,  ammonium formate, ammonia (Fisher Scientific, Pittsburgh, PA, USA) and bulk grade carbon dioxide (AirGas West (Escondido, California, USA) were used in this study.  The CO2 was purified and pressurised to 1500 psig using a custom booster and purifier system from FLW, Inc. (Huntington Beach, CA, USA).

Analysis was performed using an Agilent 1260 SFC/MS system consisting of a binary pump, SFC control module, UV/DAD detector, and column compartment with an internal 6-position, 12-port valve, and 6120 MSD with an APCI source (Agilent, Inc., Santa Clara, CA, USA). A Gerstel MPS autosampler (Gerstel USA, MD, USA) was equipped with a 25 μL syringe and a 50 nL internal loop with a control method to vent CO2 from the loop prior to sample introduction. The effluent of the SFC is split to the MSD using a 3-way tee (Valco, Houston, TX, USA) and a 50 cm long, 50 μm i.d. PEEKsil capillary tubing (Trajan Scientific, NC, USA) located between the column outlet and BPR. All data was acquired using Agilent 64-bit ChemStation (Version C.01.10).