EPSRC success for Gowsh

Dr Gowsh Poologasundarampillai was successful at the interview stage of the Adventurous Manufacturing call as confirmed by the Engineering and Physical Sciences Research Council (EPSRC) and has been awarded £250k. Congratulations to Gowsh.

Gowsh writes:

Our vision is to develop an adventurous manufacturing workflow to recapitulate the blood vessel structural and cellular complexity by employing digital manufacturing strategies

 by combining advanced materials, additive manufacturing and image-guided monitoring to provide transformative solutions to key healthcare challenges facing our ageing society.

The manufacturing research challenge 

being addressed here is the growing demand for functional tissue grafts and organs for transplantation and drug discovery. To date, a major hurdle in engineering artificial tissue has been the inability to reproduce the blood vessel micro- and macro-architecture.

The novel manufacturing research idea

is to develop integrated fluidic chip nozzles, based on microfluidic mixers and hydrodynamic flow focusing components (Fig. 1B) to 3D extrusion-printing organic-inorganic hybrid hydrogel-based bioinks to create blood vessels. Our ambition is to establish an agile digital factory that will enable high-throughput fabrication of blood vascular trees (Fig. 1A) from single cell resolution (20 µm) to muscle arteries (several millimetres) via fluidic chip nozzles. The fluidic chip nozzle dimensions will be sufficiently large (2mm) to be stereolithography (SLA) printed thus avoiding the labour-intensive and expensive microfabrication platforms required to produce microfluidic chips. Importantly, our design optimisation and extrusion parameters will be guided by 4D light-sheet fluorescence (LSFM) microscopic imaging (Fig. 1C) of flow profiles of various fluids (Fig. 1D) in the novel fluidic chip nozzles.”
Fig. 1. This proposal aims to recreate natural blood vessel structure/cellular microenvironment (A) by developing a fluidic chip nozzle (FCN) extrusion-printing platform (B). It will use LSFM based advanced imaging (C) to optimise design of the FCN & print parameters. Cells and microparticles encapsulated in the fluids will be detected and quantified in real-time(D).