Venture Kick stage 1 brings new innovations to light
16.07.2018
A wide range of projects from biotech to robotics convinced the Venture Kick jury of their potential. Each startup brings home CHF 10,000 as a reward for their innovative ideas. Following the initial excitement, it is now time for them to prepare their cases for the next step and compete to win CHF 20,000.
 Araris Biotech
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 E-METS
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 MOBBOT
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 Prediva
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Araris Biotech (PSI) – Biotech
Araris Biotech is focused on the development of antibody-drug conjugates (ADCs) having a well-defined and optimal antibody-to-drug ratio. The technology of Araris enables to rapidly generate highly efficient ADCs which do not require any antibody engineering. The startup aims to create a drug development platform for targeted therapies and diagnostic applications.
E-METS (EPFL) – Renewable water, cleantech, fluid mechanics
Enhanced – Multi-Effect Thermal Separation (E-METS) focuses on developing a thermal separation system for desalination, brine concentration or industrial wastewater treatments. The startup’s technology employs novel distillation concepts to reduce energy consumption and can be integrated with renewable energy sources. Environmentally friendly with a negligible footprint, the solution aims at being efficient yet scalable.
MOBBOT – Robotics, material sciences
Mobbot develops and wants to provide mobile 3D concrete printing systems for construction companies and concrete manufacturers. Custom-made concrete products are time consuming and resources intensive for the concrete manufacturers. Mobbot’s technology offers mass customization products with conventional concrete material without using any formwork.Digital fabrication with 3D concrete printing replaces traditional mold technology and allows producing mass custom-made products with 40% direct cost reduction, 30% material waste reduction, and speeds up project realization typically from 1 month to one day.
Prediva (EPFL) – Medtech, machine learning, AI
Prediva conceives a predictive machine learning software for coronary artery disease diagnostics and treatments. Combining image analysis with machine learning models and computational fluid dynamics simulations, the software provides insightful patient analysis and generates a personalized 3D physiological model of coronary arteries. It provides recommendations for stent placement, treatment planning and for reduction of plaque progression, enabling clinicians to determine the best course of treatment while reducing costs and procedure times.
Araris Biotech is focused on the development of antibody-drug conjugates (ADCs) having a well-defined and optimal antibody-to-drug ratio. The technology of Araris enables to rapidly generate highly efficient ADCs which do not require any antibody engineering. The startup aims to create a drug development platform for targeted therapies and diagnostic applications.
E-METS (EPFL) – Renewable water, cleantech, fluid mechanics
Enhanced – Multi-Effect Thermal Separation (E-METS) focuses on developing a thermal separation system for desalination, brine concentration or industrial wastewater treatments. The startup’s technology employs novel distillation concepts to reduce energy consumption and can be integrated with renewable energy sources. Environmentally friendly with a negligible footprint, the solution aims at being efficient yet scalable.
MOBBOT – Robotics, material sciences
Mobbot develops and wants to provide mobile 3D concrete printing systems for construction companies and concrete manufacturers. Custom-made concrete products are time consuming and resources intensive for the concrete manufacturers. Mobbot’s technology offers mass customization products with conventional concrete material without using any formwork.Digital fabrication with 3D concrete printing replaces traditional mold technology and allows producing mass custom-made products with 40% direct cost reduction, 30% material waste reduction, and speeds up project realization typically from 1 month to one day.
Prediva (EPFL) – Medtech, machine learning, AI
Prediva conceives a predictive machine learning software for coronary artery disease diagnostics and treatments. Combining image analysis with machine learning models and computational fluid dynamics simulations, the software provides insightful patient analysis and generates a personalized 3D physiological model of coronary arteries. It provides recommendations for stent placement, treatment planning and for reduction of plaque progression, enabling clinicians to determine the best course of treatment while reducing costs and procedure times.