Research

The Self-Assembled Virus-like Vectors for Stem Cell Phenotyping (SAVVY) project seeks to use hierarchical, multi-scale assembly of intrinsically dissimilar nanoparticles (NP) (SAVVY reporters) to develop novel types of multifunctional Raman probes for analysis and phenotyping of heterogeneous stem cell populations using microfluidic devices (SAVVY sorter).

In WP1, we will use hierarchical self-assembly to develop a number of integrated SAVVY reporter designs and will validate and optimize them. The outcomes of the validation work in model systems will directly influence the work done under WP5 (Process engineering of SAVVY reporters). In WP2, we will develop the conceptual framework for Raman-based cell phenotyping taking into consideration software and hardware aspects of ultra-fast Raman signal acquisition, data mining and cell classification, as well as a feedback control. In parallel, the necessary components for an automated SAVVY sorter will be developed in WP3 and WP4. Once, our team has established the fundamental rules for SAVVY reporters and sorters, we will undergo an iterative optimization approach to engineer scalable, environmentally benign and cost effective processes for production, purification, storage and handling of SAVVY reporters and their constituent NP (WP5). WP6 aims at validating increasingly integrated detection schemes for SAVVY-based cell analysis.

We note that all work packages are designed to strive for the highest possible knowledge gain and that it is our genuine intend to share insights obtained under this project with the scientific community as well as interested industrial partners (WP7).

WP1

Hierarchical self-assembly of SAVVY reporters

EPFL

WP2

SAVVY enabled cell phenotyping

IMPERIAL

WP3

Automation 1: Microfluidics for SAVVY sorters

MFCS

WP4

Automation 2: Raman microscopy for SAVVY sorter

OMT

WP5

Optimization of the fabrication processes

KIT

WP6

Integration of SAVVY sorter

CICbio

WP7

Dissemination, training and exploitation

CICbio

WP8

Project management

KIT