Grant: Enabling rapid liquid and freeze-dried formulation design for the manufacture and delivery of novel biopharmaceuticals
PIs: Dr Robin Curtis, The University of Manchestr & Professor Paul Dalby, University College London

Enabling rapid liquid and freeze-dried formulation design for the manufacture and delivery of novel biopharmaceuticals - pdf
Prof Paul Darby, University College London

Protein stability is a critical factor for the successful development of non-aggregating biopharmaceuticals and enzymes. Routes to predictably engineer protein stability are therefore crucial. We have combined a wide range of biophysical analyses, protein engineering, formulation screening, and molecular modelling approaches, to characterise some of the many factors that influence protein aggregation. The increased understanding gained is now also being used to develop improved protein engineering and formulation design strategies for the minimisation of aggregation in liquid and freeze-dried forms.

Q&A

Question (Tim Akerman): @Paul Dalby re the impact of STPP I have seen a similar effect in pigment ink systems. What we observed was that the pigment agglomerated then dispersed as you increase the surfactant concentration. The agglomeration seems to be due to minimising the surface area. Is it possible that rather than forming salt bridges between protein particles, the STPP is stabilising an agglomeration of protein particles?

Verbally answered by Paul/Robin

Response (Robin Curtis): @Tim, we have measured the two body interaction between lysozyme particles along the phase boundary and show that the attraction in the presence of TPP is much stronger than would be expected in the absence of any electrostatic repulsion, which suggests that the precipitation is driven by attractive interactions between the proteins

Question (Tim Akerman): @Paul Dalby, with only 137 data sets for machine learning is there not a risk of overfitting to that dataset to too few scenarios and limiting the ability to give accurate answers to new scenarios?

Response (Paul Dalby): @Tim Akerman.  Overfitting with ML is always a risk yes, but use of ML on smaller datasets is still possible without overfitting.

Poster: Supercharging proteins with small polyvalent anions offset aggregation - pdf
Jordan W. Bye, Kiah Murray and Robin A. Curtis, The University of Manchester

RSC FST Future Formulation IV - The Conference

Grant Page: Predictive formulation of high-solid-content complex dispersions
PIs: Dr Jin Sun, University of Edinburgh & Dr Mark Haw, University of Strathclyde

Grant Page: Virtual Formulation Laboratory for prediction and optimisation of manufacturability of advanced solids based formulations
PI: Dr Csaba Sinka, University of Leicester

Grant Page: Evaporative Drying of Droplets and the Formation of Micro-structured and Functional Particles and Films
PI: Professor Colin Bain, Durham University

Grant Page: Enabling rapid liquid and freeze-dried formulation design for the manufacture and delivery of novel biopharmaceuticals
PIs: Dr Robin Curtis, The University of Manchestr & Professor Paul Dalby, University College London

Grant Page: Complex ORAL health products (CORAL): Characterisation, modelling and manufacturing challenges
PI: Professor Panagiota Angeli, University College London

Grant Page: Formulation for 3D printing: Creating a plug and play platform for a disruptive UK industry
PI: Professor Ricky Wildman, University of Nottingham

Grant Page: INFORM 2020 - Molecules to Manufacture: Processing and Formulation Engineering of Inhalable Nanoaggregates and Microparticles
PI: Professor Darragh Murnane, University of Hertfordshire