Descrizione del progetto
Spettroscopia Raman per migliorare la bioterapia
La bioterapia è il settore in più rapida crescita dell’industria farmaceutica, ma si trova ad affrontare richieste cruciali di costi inferiori, tempi di biotrasformazione più efficienti e risultati stabili. La spettroscopia Raman è una tecnologia in grado di migliorare la biotrasformazione. Il progetto SpectraHow, finanziato dall’UE, sta sviluppando un software scalabile basato su tecniche innovative di apprendimento automatico per elaborare dati, misurare automaticamente le dinamiche di processo e trasmettere informazioni. Il progetto si propone di migliorarne l’uso, perfezionare i modelli e gli algoritmi e dimostrarne la compatibilità con altri strumenti software e tecnologie di spettroscopia.
Obiettivo
Today, biopharmaceuticals generate global revenues of €145 billion, representing about 20% of the pharma market. The growth rate of biopharma, 8%, currently doubles that of conventional pharma. However, biopharma companies are facing an increased pressure for cheaper process development, faster time to market as well as more consistent production (reducing failure). Raman spectroscopy is a promising technology to improve bio processing and manufacture. Nevertheless, the corresponding data analysis of the complex spectra in biopharma is more challenging that conventional pharma, taking 2-5 months in order to acquire enough data and train a reliable predictive model. Founded in 2017, DataHow is a spin-off from the ETH Zürich, with the aim to accelerate biopharmaceutical process development and reduce risks in production through advanced algorithm-enabled digital solutions; SpectraHow is our scalable software based on advanced machine learning techniques, capable of accurately handling the large amounts of data generated, to automatically quantify the process dynamics and translate the information into direct decision support. Our algorithmic toolbox at TRL6 has been already tested in operational environment for different processes with several pharma companies, with a precision of up to 35% more accurate compared to commercial tools, and a smaller effort due to our automated calibration procedure. Next steps to take forward SpectraHow to commercialization are: improve usability with a Graphical User Interface, fine-tune our models and algorithms to further automate analysis, and show compatibility of our solution with third-party software tools to expand its functionality from R&D to production and to other spectroscopy techniques. In the booming Raman for pharma market valued at 2.5 billion in 2015, we forecast generate €21 Million in revenues in 2026 while creating 14 new jobs.
Campo scientifico
CORDIS classifica i progetti con EuroSciVoc, una tassonomia multilingue dei campi scientifici, attraverso un processo semi-automatico basato su tecniche NLP.
CORDIS classifica i progetti con EuroSciVoc, una tassonomia multilingue dei campi scientifici, attraverso un processo semi-automatico basato su tecniche NLP.
- natural sciencescomputer and information sciencessoftware
- engineering and technologyenvironmental biotechnologybioremediationbioreactors
- natural sciencescomputer and information sciencesdata sciencebig data
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors
- natural sciencesphysical sciencesopticsspectroscopy
Programma(i)
Argomento(i)
Invito a presentare proposte
Vedi altri progetti per questo bandoBando secondario
H2020-SMEInst-2018-2020-1
Meccanismo di finanziamento
SME-1 - SME instrument phase 1Coordinatore
8093 Zurich
Svizzera
L’organizzazione si è definita una PMI (piccola e media impresa) al momento della firma dell’accordo di sovvenzione.