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Crystallization is a phase transformation process in which crystals are precipitated from a supersaturated solution or formed from other sources. During crystallization, atoms or molecules arrange themselves into a well-defined, rigid crystal lattice to minimize energy.
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Recrystallization is a purification technique used to separate impurities from solid compounds. In this technique, no chemical reactions occur. Instead, it exploits physical properties only, specifically, the solubility differences between the desired compound and impurities, either at a single temperature or at different temperatures, and under other selected conditions. The solid-solution equilibrium (solubility equilibrium) of each component in the solution represents a binary phase...
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Comparative Study on Adaptive Bayesian Optimization for Batch Cooling Crystallization for Slow and Fast Kinetic

Thomas Pickles1, Chantal Mustoe1, Cameron J Brown1

  • 1CMAC Future Manufacturing Research Hub, Technology and Innovation Centre, University of Strathclyde, Glasgow G1 1RD, U.K.

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Summary
This summary is machine-generated.

Adaptive Bayesian optimization (AdBO) accelerates pharmaceutical crystallization development by efficiently predicting experimental conditions. This approach significantly reduces material usage, supporting greener chemistry and Net-Zero manufacturing goals.

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Area of Science:

  • Chemical Engineering
  • Crystallization Science
  • Process Development

Background:

  • Accurate estimation of crystallization kinetic parameters is crucial for pharmaceutical manufacturing.
  • Understanding the influence of supersaturation and temperature on nucleation and growth is key.
  • Lamivudine (slow kinetics) and aspirin (fast kinetics) serve as model compounds.

Purpose of the Study:

  • To investigate the impact of supersaturation and temperature on crystallization kinetics.
  • To apply Adaptive Bayesian optimization (AdBO) for predicting optimal experimental conditions.
  • To compare the efficiency of AdBO with traditional Design of Experiments (DoE).

Main Methods:

  • Utilized Adaptive Bayesian optimization (AdBO) to guide experimental design.
  • Investigated crystallization kinetics (induction time, nucleation rate, growth rate).
  • Employed lamivudine and aspirin as model compounds with distinct kinetic profiles.

Main Results:

  • AdBO effectively predicted experimental conditions for target kinetic values.
  • Material usage was reduced up to 5-fold compared to DoE.
  • Demonstrated AdBO's capability to accelerate process development.

Conclusions:

  • AdBO offers a more efficient method for pharmaceutical crystallization development.
  • Reduced material consumption aligns with Net-Zero and green chemistry principles.
  • Integration of AdBO promotes autonomous data collection and sustainable chemical processes.