Meet The Testa Challenge Participants 2020!

After a comprehensive selection phase, technologies evaluated by industry representatives, investors and technical experts, we are very pleased to present the selected companies for the Testa Challenge 2020! Participants were assessed on their scope, innovative height and feasibility to be integrated into future bioproduction processes.

This year, we invited these companies from the Technology, Digital and Data segments, to integrate, test and verify their innovation alongside industry experts, in a fully funded bioproduction workflow at the Testa Center. The team are extremely excited to observe these innovations in application, at the Testa Center in Uppsala from the 19th – 23rd October, 2020.

We would hereby again want to thank all applicants for your interest in this year’s event, and we look forward to keeping in touch with you for future Challenges!

For more information and to follow the challenge’s journey, please visit: testachallenge.com

/ Testa Challenge team

Participants of Testa Challenge 2020:

(In Alphabetical order)

ArgusEye (Linköping, Sweden) 

ArgusEye have developed a novel optical sensor technology based on nanoplasmonic detection for in-line, real-time monitoring of critical quality attributes during development and production of biopharmaceuticals. For the Testa Challenge, ArgusEye wishes to take part in a complete bioprocess, from start to finish, and evaluate their sensor technology in different bioprocessing steps. The goal is to demonstrate that their novel system can provide more valuable process information compared to existing in-line signals. http://arguseye.se/

atSpiro (Copenhagen, Denmark) 
Based on a unique sensor technology, atSpiro have developed the atSpiro ShakeReactor; a wireless shake flask add-on that upgrades a shake flask into a bioreactor with online monitoring and control but without the time-consuming workflow. During the Testa Challenge, atSpiro would like to use the ShakeReactor for the preculture step, as well as running a downscaled version of the outlined bioprocess in the ShakeReactor to examine the correlation between their small-scale system and the larger bioreactor. https://atspiro.com/

Freesense (Copenhagen, Denmark)
Freesense is bringing flow-following sensor device to provide the next generation of data collection in single-use-bioreactors. The sensor data provides a detailed representation of the bioreactor environment, that can be turned into a digital bioreactor with Freesense software. This platform is used to optimize process performance, provide simulations and increase yields and quality. Freesense is looking forward to demonstrating the device in a single-use-bioreactor at the Testa Challenge. https://www.freesense.dk/

IS Instruments (Kent, United Kingdom)
Deep UV Raman (DUVR) has been identified as a promising tool for studying biological and biochemical samples. This allows signals from previously invisible biological samples to be identified through their Raman fingerprint. For this year’s Challenge, IS Instruments are developing a compact deep UV Raman (DUVR) instrument and wishes to verify their DUVR system to monitor the purification and separation stages of a bioprocess, where the team anticipate this information could be used to optimize the process and thereby achieve efficiency gains. https://is-instruments.com/

Scitara (Marlborough, US)
Scitara is developing a vendor agnostic, cloud-based platform that transforms scientific lab instrument, informatics software and web services connectivity. Scitara Digital Lab Exchange (DLX) has an open architecture and universal connector infrastructure that allows state of the art or legacy instruments and applications to connect into its modern, cloud-based platform for multi-directional data exchange. For the Testa Challenge, Scitara is interested in facilitating digital data exchange between systems and vendors connected to the bioprocess. https://scitara.com/

Unibap (Uppsala, Sweden)
Unibap combines and applies visional solutions with Machine Learning for various industrial processes; an ‘Artificial Operator’ with trained abilities can continuously monitor and act upon anomalies and needs in the process. Unibap is looking to extend their field of applications into a bioprocess setting. The system tested will be based on industrial vision cameras paired with Machine Learning, and the feasibility to control critical process parameters for bioprocesses contained in bags, will be evaluated. https://unibap.com/

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