Heng Research Group

@henggroup.bsky.social

Heng Research Group @imperialchemeng #particles #surfaces #nucleation #crystallisation #bioseparation

Congratulations to Lok Hang Wong for his three talks at the 2025 #AIChEAnnual Meeting on using population balance modelling for lysozyme crystallization! Topics included protocol development for data acquisition, proposing rate expressions & deploying a calibrated model for design space exploration🎉

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Congratulations to Izabela Phillips on the successful completion of her PhD and viva, which investigated the impact of particle attributes on pharmaceutical powder tabletability. A huge thank you to Prof. Jerry Heng for his supervision, and to the examiners, Prof. Rongjun Chen and Dr. Colin Hare.👏

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Congratulations to Lok Hang Wong for passing his PhD Early Stage Assessment (ESA) yesterday, focusing on using process modelling to optimize & accelerate the adoption of crystallisation techniques for purifying proteins and peptides!🎉Many thanks to Dr Antonio Del Rio Chanona for being the assessor!

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Deniz Etit recently presented his work on post-breakage crystal regeneration at the Annual Conference of the British Association of Crystal Growth (BACG) in Leeds, UK, which was very well-received! 💎 Congrats Deniz!

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Last month Isha Bade presented her poster on crystal regeneration post-breakage at the 7th David Grant Symposium in Minnesota, highlighting a unique “facet switch-off” behaviour observed during regeneration where crystals appear to exhibit shape memory. Congrats Isha👏#CrystalGrowth

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Check out fresh new work from @danielepessina.bsky.social pubs.acs.org/doi/10.1021/... - We developed an experimentally-validated black-box compatible uncertainty quantification methodology, tailored to protein crystallisation systems with sparse measurements.👏

Integrated In Vitro/In Silico Uncertainty Quantification Method for Protein Crystallization Models

The complexity of protein crystallization and in silico modeling challenges process intensification and the wider adoption of crystallization in biomanufacturing. For computational models to support and replace extensive experiments, they must accurately reflect in vitro experiments. However, parameter estimation can be ineffective due to the highly nonlinear model structure and inaccurate online process analytical technology, which must be addressed. In this work, an experimentally validated and model-driven parametrization methodology is presented, developed for an antisolvent batch protein crystallization system with limited offline measurements. Global sensitivity analysis is performed to assess parameter identifiability during batch operations and inform optimal measurement points. Experiments at three different initial lysozyme concentrations (c0 = 15, 18, 19 mg/mL) are used for estimation. Parameter uncertainty distributions are recovered through an Approximate Bayesian Computation algorithm and propagated to model outputs through Monte Carlo simulations, avoiding linearization or unnecessary assumptions on the parametric and output uncertainty distributions. The methodology was successfully validated under two new experimental conditions. The shapes of the recovered parametric and output uncertainties highlight the need for parameter estimation methodologies specifically tailored to nonlinear models.

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Deniz Etit recently attended the 7th David Grant Symposium in Minneapolis, USA and presented his novel findings on post-breakage crystal growth and regeneration, which was very well-received! 💎 Congrats Deniz!

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Huge congratulations to Hamish Mitchell for passing his PhD viva this week! In his PhD Hamish investigated seeding-based workflows for the crystallisation of pharmaceutical peptides. Big thanks to examiners Prof. Sarah Hudson and Prof. Nilay Shah.🎉👏

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Deniz Etit recently attended the BASF-IConIC Retreat 2025 at the Cumberland Lodge in Windsor, UK and presented his work on shape control of needle-like crystals for industrial applications, which was well-received! 💎 Congrats Deniz!

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