Biotherapeutic drug development

Principal supervisor:

• Dr Hanieh Khalili  

• Contact hanieh.khalili@uwl.ac.uk

New classes of protein-based medicines are being investigated with the focus on increasing the functionality and stability. We have so far developed mono-specific antibody-based mimetic which act as IgG mimetics with similar solution size and binding affinity.  There is much interest to explore the benefit of using bispecific IgG mimetic in inflammation and fibrosis disease. The mimetic that we have been working on, does not have Fc fragment which its presence may cause immune-related effector functions to drive (rather than inhibit) inflammation.

This PhD proposal is a collaborative work with UCL School of Pharmacy and Institute of Ophthalmology to develop stable, and Fc-free bispecific antibody-based mimetic to be more efficacious than mono specific antibody and even better than simply mixing mono-specific antibodies because of synergistic effect. PhD candidate will work alongside a team of chemist, and pharmacist to develop novel bispecific antibody mimetic and will be trained to work with complex biopharmaceutical formulation techniques and biological assays (protein conjugation, characterisation, purification, protein-protein binding interaction techniques, cell-based in-vitro assays). As part of the project, the student will be given the opportunity to spend a period at UCL School of Pharmacy, to undertake collaborative research using state of art pharmaceutical facilities such as Biacore and ITC.

Principal and co-supervisors:

• Dr Hanieh Khalili and Prof Massoud Zolgharni 

• Contact hanieh.khalili@uwl.ac.uk

Retinal tissue engineering is representing a new approach to treat retinal diseases through the development of a biological substitute; the so-called scaffold. A tissue scaffold is a 3-dimentional (3D) structure with interconnected pores which are used to deliver cells, drugs and genes into the local tissue. Scaffold should provide a suitable space in which retinal pigment epithelium (RPE) can grow and generate their own extracellular matrix (ECM). Collagen is the most abundant structural protein that play critical role in maintaining the ECM which has been widely used to fabricate scaffolds for tissue engineering because of its biodegradability, superior biocompatibility and weak antigenicity. Some limitations exist with cross-linked collagens including the use of leachable toxic crosslinkers, a short duration of action, activation of T-cells and difficult injection of the polymerised networked materials. To address these limitations, an in-situ polymerizable collagen (IPC), which is fibrilised without uses of a  chemical cross linker, is proposed to use  as a scaffold for this PhD proposal.  

To fabricate 3D IPC scaffolds with specific shapes and sizes, different methods will be applied such as freeze-drying and 3D bioprinting. Multi-objective optimisations are, however, required to identify suitable freeze-drying and printing conditions and material composition (percentage of cells to IPC) to achieve optimal mechanical and porous constructions properties. This requires extensive experimentation time that is resource demanding. Artificial intelligence (AI) and machine learning (ML) methods have already been applied in tissue engineering and have been shown to be transformative resources to support researchers in the field of regenerative medicine. The ML-based framework takes the material composition and the printing parameters as input to (i) predict printing parameters to optimise the structure’s properties, (ii) assess the quality of the prints and (iii) optimise printability of the material.  

This PhD proposal is a collaborative work between the School of Biomedical Science and School of Computing and Engineering to investigate the feasibility of using AI to predict/optimise the physicochemical and mechanical properties of 3D printed IPC cells scaffolds, thereby reducing the time and data needed for experimentations.  

Prospective student will have good first degree in Pharmacy, Chemistry or another pharmaceutical-related discipline.

Principal and co-supervisors

• Dr Hanieh Khalili (contact detail: hanieh.khalili@uwl.ac.uk)  

• Dr Karolina Dziemidowicz (contact detail: k.dziemidowicz@ucl.ac.uk) 

Project summary

This PhD proposal is a collaborative work between the School of Biomedical Sciences and School of Computing and Engineering at University of West London and School of Pharmacy at University College London (UCL) to investigate the feasibility of using AI to predict/optimise the physicochemical and mechanical properties of 3D printed immunostimulatory scaffolds for cancer T-cells therapy.

T cell therapy is a promising approach in combating certain blood cancers. However, the conventional intravenous delivery of T cells shows limited efficacy against solid tumours. This is primarily attributed to the considerable challenges these cells face in locating, infiltrating and proliferating within the typically immunosuppressive tumour microenvironment following systemic administration.

Implantable biomaterials can potentially enhance T cell therapy outcomes in solid tumours by enabling localised delivery of T cells and immunostimulatory molecules necessary for the maintenance of their function. This PhD project therefore focuses on developing 3D implantable collagen scaffold to facilitate localised delivery of T cell therapy in solid cancers.

Advanced techniques such as 3D bioprinting will be employed to create specific scaffold shapes and sizes. To optimise these scaffolds and ensure T cell viability, various mechanical and physicochemical aspects will be considered. This optimisation will be achieved through machine learning and AI-based framework, which will assess the scaffold properties, evaluate print quality and optimise T cell viability within the 3D printed scaffold.  Additionally, the scaffolds will be loaded with microparticles functionalised immunostimulatory biomolecules (cytokines or antibodies) to maintain T cell function and viability in situ.

The interdisciplinary nature of this research involves collaboration with Pharmaceutics, Biomedical Science and Computing and Engineering. The project includes  fabricating  biomolecule-functionalised microparticles and conducting cellular assays at UCL School of Pharmacy, under supervision of Dr Dziemidowicz. Techniques such as x-ray photoelectron spectroscopy, scanning electron microscopy, cell culture, flow cytometry and confocal microscopy will be used. Additionally, the 3D bioprinting of collagen scaffold will take place in Dr’s Khalili research lab. Finally, machine learning will be designed in Prof Zolgharni’s research group, Intelligent Sensing and Vision (IntSaV).