Publications by authors named "Andy Koswara"

This study describes an automated system used for high throughput screening of reaction conditions based on accelerated reactions occurring in small volumes of reagents. Reaction mixtures are prepared in array format using a fluid handling robot and spotted on a flat polytetrafluoroethylene plate at densities up to 6144 per plate. The reaction and analysis steps are performed simultaneously using desorption electrospray ionization (DESI) to release microdroplets containing the reaction mixture from the plate for reaction prior to arrival at a mass spectrometer.

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A highly integrated approach to the development of a process for the continuous synthesis and purification of diphenhydramine is reported. Mass spectrometry (MS) is utilized throughout the system for on-line reaction monitoring, off-line yield quantitation, and as a reaction screening module that exploits reaction acceleration in charged microdroplets for high throughput route screening. This effort has enabled the discovery and optimization of multiple routes to diphenhydramine in glass microreactors using MS as a process analytical tool (PAT).

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Control of crystal size and shape is crucially important for crystallization process development in the pharmaceutical industries. In general crystals of large size and low aspect ratio are desired for improved downstream manufacturability. It can be extremely challenging to design crystallization processes that achieve these targets for active pharmaceutical ingredients (APIs) that have very slow growth kinetics and needle-like morphology.

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Preparative electrospray (ES) exploits the acceleration of reactions in charged microdroplets to perform a small scale chemical synthesis. In combination with on-line mass spectrometric (MS) analysis, it constitutes a rapid screening tool to select reagents to generate specific products. A successful reaction in preparative ES triggers a refined microfluidic reaction screening procedure which includes the optimization for stoichiometry, temperature and residence time.

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Nanocrystals are receiving increased attention for pharmaceutical applications due to their enhanced solubility relative to their micron-sized counterpart and, in turn, potentially increased bioavailability. In this work, a computational method is proposed to predict the following: (1) polymorph specific dissolution kinetics and (2) the multiplicative increase in the polymorph specific nanocrystal solubility relative to the bulk solubility. The method uses a combination of molecular dynamics and a parametric particle size dependent mass transfer model.

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Current polymorph prediction methods, known as lattice energy minimization, seek to determine the crystal lattice with the lowest potential energy, rendering it unable to predict solvent dependent metastable form crystallization. Facilitated by embarrassingly parallel, multiple replica, large-scale molecular dynamics simulations, we report on a new method concerned with predicting crystal structures using the kinetics and solubility of the low energy polymorphs predicted by lattice energy minimization. The proposed molecular dynamics simulation methodology provides several new predictions to the field of crystallization.

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