PGEN | Automated evaluation and correction of generation bias in immune receptor repertoires

Summary
Personalized medicine is promising to change the health and prophylactics sectors, already showing large societal and economic impact. High throughput immune sequencing technologies give us insight into a unique personal medical record - our immune system’s memory of all encountered infections and the successful solutions our body found. Unfortunately, reading this record requires advanced statistical tools making it often inaccessible to biologists and medical practitioners. PGEN offers a solution that will fill this gap between modern technology and applications by developing commercialisation solutions for an immune repertoire analysis software. PGEN builds on the methodologies developed during the ERC Starting Grant RECOGNIZE to provide a user-friendly versatile software prototype that will give researchers in the life scientists and medical practitioners without bioinformatic training an overview of the statistical properties of the immune repertoires they are studying. PGEN will explore the impact on medicine and biotechnology of this software platform that identifies non-standard immune responses that can be exploited in vaccine design and novel personalised therapies. Currently no software exists that a medical practitioner can use to characterize the baseline immune repertoire of a healthy person. Knowing this baseline is essential for identifying immune system disfunction and applying immune repertoire sequencing technologies in biotechnology and medicine. The PGEN software platform will provide doctors and biologists with a statistical tool that will help them make informed decisions about treatment, prophylactics and future research. PGEN will pursue commercialization and market solutions both within academia, the biotechnology and medical sectors.
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More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/824735
Start date: 01-03-2019
End date: 30-11-2020
Total budget - Public funding: 149 906,00 Euro - 149 906,00 Euro
Cordis data

Original description

Personalized medicine is promising to change the health and prophylactics sectors, already showing large societal and economic impact. High throughput immune sequencing technologies give us insight into a unique personal medical record - our immune system’s memory of all encountered infections and the successful solutions our body found. Unfortunately, reading this record requires advanced statistical tools making it often inaccessible to biologists and medical practitioners. PGEN offers a solution that will fill this gap between modern technology and applications by developing commercialisation solutions for an immune repertoire analysis software. PGEN builds on the methodologies developed during the ERC Starting Grant RECOGNIZE to provide a user-friendly versatile software prototype that will give researchers in the life scientists and medical practitioners without bioinformatic training an overview of the statistical properties of the immune repertoires they are studying. PGEN will explore the impact on medicine and biotechnology of this software platform that identifies non-standard immune responses that can be exploited in vaccine design and novel personalised therapies. Currently no software exists that a medical practitioner can use to characterize the baseline immune repertoire of a healthy person. Knowing this baseline is essential for identifying immune system disfunction and applying immune repertoire sequencing technologies in biotechnology and medicine. The PGEN software platform will provide doctors and biologists with a statistical tool that will help them make informed decisions about treatment, prophylactics and future research. PGEN will pursue commercialization and market solutions both within academia, the biotechnology and medical sectors.

Status

CLOSED

Call topic

ERC-2018-PoC

Update Date

27-04-2024
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Horizon 2020
H2020-EU.1. EXCELLENT SCIENCE
H2020-EU.1.1. EXCELLENT SCIENCE - European Research Council (ERC)
ERC-2018
ERC-2018-PoC