Half of all protein-based drugs in clinical trials must be freeze-dried because they cannot be formulated as stable liquids within the months-long development window. This project tackles that bottleneck head-on. The problem is that next-generation biopharmaceuticals—complex engineered proteins for cancers, arthritis, and other diseases—tend to clump, thicken, or separate when concentrated for injection. Current formulation methods rely on trial-and-error screens that poorly predict whether a drug will remain stable on the shelf for two years. Industry leaders have identified this as a critical gap. The researchers will combine automated microplate and microfluidic analytics with a pilot-scale freeze-drying facility to generate large datasets on how proteins degrade, aggregate, and change viscosity under different conditions. Novel dipeptide excipients will expand the toolkit for stabilising formulations. All data will feed a web-accessible database, allowing new proteins to be compared computationally to existing ones, predicting which formulations are likely to work before any wet-lab testing begins. If successful, this work will replace slow, material-hungry trial-and-error with rapid, predictive formulation design. The immediate impact is on manufacturing efficiency and drug development timelines—not on patients’ daily lives directly, but on the speed and reliability with which new biologic medicines reach them.
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Biopharmaceuticals have been approved to treat diseases including cancers, rheumatoid arthritis, multiple sclerosis, diabetes, leukemia and neutropenia. The next-generation of protein-based therapies, or biopharmaceuticals, are of increasingly complex engineered forms, with unpredictable solution properties. Proteins are formulated at high concentrations for clinical use, leading often to undesirable aggregate formation, high viscosity, opalescence, or phase separation, rendering them unsafe, or difficult to inject or manufacture. This is a major challenge to the biopharmaceuticals industry as approximately 50% of proteins in clinical trials have been freeze-dried as they were not readily liquid-formulated on timescales of months required during development. Formulation is an empirical process using combinatorial screens that aim to optimise stability, potency and ease of delivery to patients. Engagement with 36 industry leaders at a UCL EPSRC Centre for Innovative Manufacturing workshop identified the most significant protein formulation challenges such as the prediction of shelf stability over a two year period, at a time in development when not much material is available. Current surrogate techniques that accelerate protein degradation and minimize sample consumption provide poor indicators of 2-year shelf-life. Industry would benefit significantly from i) rapid analyses that more accurately determine long-term shelf-life, ii) low concentration analyses that indicate high-concentration solution behaviour, and iii) a better ability to use calculated protein and excipient properties to predict those formulations that are most likely to meet the required attributes. State-of-the-art automated microplate and microfluidic analytics, purchased or established recently via EPSRC and BBSRC/BRIC awards at UCL and UoM provide a timely platform for generating large experimental datasets of aggregation kinetics spanning many different timescales, conformational and colloidal stabilities, rheological properties, phase-transition and glass transition temperatures, for liquid and freeze-dried formulations. A recent EPSRC funded £500k pilot-scale freeze-drying facility at UCL (EP/M028100/1), combined with DoE and 3D process simulations, will generate freeze-drying process models that elucidate the mechanisms linking critical process parameters to critical quality attributes for new formulations. Novel dipeptides emerging from recent UoM work will significantly expand the range of industry-accepted formulation excipients available. Novel microfluidic analytics will be tailored for formulation needs, bringing earlier, more sensitive, and lower-volume assessments of formulated protein heterogeneity and storage kinetics, ultimately in a high-throughput format using sealed microwells. All data will populate a web-access database at UoM to provide modeling groups access to a much-needed experimental dataset. Informatics techniques initiated at UoM in a BioProNet PoC award will enable new proteins to be compared (via properties calculated from sequence and structure) to those in the database, and use their experimentally determined formulation behaviours in a predictive manner. Correlations between calculated protein properties and critical formulation attributes will identify the molecular basis of excipient behaviour. Overall, this will benefit the biopharmaceutical formulation community with an ability to: a) identify better excipient combinations for input into formulation screens; b) predict those protein candidates most readily formulatable with current excipients and solution conditions; c) inform the rational design of novel peptide-based excipients through defined chemical modifications, d) predict long-term storage stability and concentrated solution behaviour from accessible experiments using minimal sample.
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