Combining biophysical analysis and computational methods to understand critical molecular attributes

Lead Research Organisation: University College London
Department Name: Biochemical Engineering

Abstract

Context & impact: New antibodies and novel formats such as bispecifics continue to pose challenges in downstream processing and formulation that are highly dependent on molecular sequence and structure. Key challenge behaviours include aggregation, particle formation, gelation and increased viscosity, as a result of stresses. Such stresses can include elevated temperature, increased protein concentration, the presence of silicone oil or other packing components, or the dilution of formulations into infusion bags.
It is desirable to gain increased understanding of the critical molecular attributes that influence their behaviours in DSP, formulation and final drug administration steps. This would ultimately enable such properties to be engineered out an early stage of development.

Aims and objectives: The aim of this project will be to explore the combination of biophysical analysis approaches with the use of machine-learning / statistical analyses, as well as all-atom molecular dynamics simulations, and molecular docking approaches to gain insights into the molecular attributes and underlying mechanisms of protein aggregation, viscosity and gelation, particularly at high protein concentrations, elevated temperature, and in the presence of tungsten and silicone oil.

Research methodology: including new knowledge or techniques in engineering and physical sciences that will be investigated

The project will collaborate with Kymab/Sanofi to define a platform of biophysical analytical approaches to characterise molecular formulations for a range of molecular variants. This will then be used in a DoE-driven formulation screen, assessed for Tm, aggregation, viscosity and gelation effects, under stress conditions. State of the art MD simulations and molecular docking will also be performed for selected biologic-buffer-excipient conditions, under stress conditions.
Statistical and ML analyses will then be used to link molecular features and properties obtained from MD simulations, docking, and biophysical measurements, with the performance under each stress condition, including manufacturing conditions. Thus, the project will generate new knowledge in the characteristics of protein solutions that govern stability, and enable the rapid selection of optimal formulations and manufacturable molecular variants. It will also train the student in digital skills. The project is aligned directly to the EPSRC Manufacturing the Future theme.

Planned Impact

The CDT has a proven track record of delivering impact from its research and training activities and this will continue in the new Centre. The main types of impact relate to: (i) provision of highly skilled EngD and sPhD graduates; (ii) generation of intellectual property (IP) in support of collaborating companies or for spin-out company creation; (iii) knowledge exchange to the wider bioprocess-using industries; (iv) benefits to patients in terms of new and more cost effective medicines, and (v) benefits to the wider society via involvement in public engagement activities and impacts on policy.

With regard to training, provision of future bioindustry leaders is the primary output of the CDT and some 96% of previous EngD graduates have progressed to relevant bioindustry careers. These highly skilled individuals help catalyse private sector innovation and biomanufacturing activity. This is of enormous importance to capitalise on emerging markets, such as Advanced Therapy Medicinal Products (ATMPs), and to create new jobs and a skilled labour force to underpin economic growth. The CDT will deliver new, flexible on-line training modules on complex biological products manufacture that will be made available to the wider bioprocessing community. It will also provide researchers with opportunities for international company placements and cross-cohort training between UCL and SSPC via a new annual Summer School and Conference.

In terms of IP generation, each industry-collaborative EngD project will have direct impact on the industry sponsor in terms of new technology generation and improvements to existing processes or procedures. Where substantial IP is generated in EngD or sPhD programmes, this has the potential to lead to spin-out company creation and job creation with wider economic benefit. CDT research has already led to creation of a number of successful spin-out companies and licensing agreements. Once arising IP is protected the existing UCL and NIBRT post-experience training programmes provide opportunities for wider industrial dissemination and impact of CDT research and training materials.

CDT projects will address production of new ATMPs or improvements to the manufacture of the next generation of complex biological products that will directly benefit healthcare providers and patients. Examples arising from previous EngD projects have included engineered enzymes for greener pharmaceutical synthesis, novel bioprocess operations to reduce biopharmaceutical manufacturing costs and the translation of early stem cell therapies into clinical trials. In each case the individual researchers have been important champions of knowledge exchange to their collaborating companies.

Finally, in terms of wider public engagement and society, the CDT has achieved substantial impact via involvement of staff and researchers in activities with schools (e.g. STEMnet), presentations at science fairs (Big Bang, Cheltenham), delivery of high profile public lectures (Wellcome Trust, Royal Institution) as well as TV and radio presentations. The next generation of CDT researchers will receive new training on the principles of Responsible Innovation (RI) that will be embedded in their research and help inform their public engagement activities and impact on policy.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/S021868/1 01/10/2019 31/03/2028
2585864 Studentship EP/S021868/1 01/10/2021 30/09/2025 Tania Mahmood