SpectraHow
SpectraHow. Smart Raman sensor to speed up biopharma manufacture
Total Cost €
0EC-Contrib. €
0Partnership
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0SpectraHow project word cloud
Explore the words cloud of the SpectraHow project. It provides you a very rough idea of what is the project "SpectraHow" about.
Project "SpectraHow" data sheet
The following table provides information about the project.
| Coordinator |
DATAHOW AG
Organization address contact info |
| Coordinator Country | Switzerland [CH] |
| Project website | https://www.datahow.ch |
| Total cost | 71˙429 € |
| EC max contribution | 50˙000 € (70%) |
| Programme |
1. H2020-EU.3. (PRIORITY 'Societal challenges) 2. H2020-EU.2.3. (INDUSTRIAL LEADERSHIP - Innovation In SMEs) 3. H2020-EU.2.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies) |
| Code Call | H2020-SMEInst-2018-2020-1 |
| Funding Scheme | SME-1 |
| Starting year | 2019 |
| Duration (year-month-day) | from 2019-07-01 to 2019-09-30 |
Partnership
Take a look of project's partnership.
| # | ||||
|---|---|---|---|---|
| 1 | DATAHOW AG | CH (ZURICH) | coordinator | 50˙000.00 |
Map
Project objective
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.
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The information about "SPECTRAHOW" are provided by the European Opendata Portal: CORDIS opendata.