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| Titel Sort descending | Periode | Program | |
|---|---|---|---|
| SupplyBase - digitaliserer fremstillingsindustrien | 2022 - 2023 | Innofounder
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SupplyBase - digitaliserer fremstillingsindustrien
Period
2022 - 2023
Region
Region Syddanmark Program
Innofounder Area
Ikke defineret Investment
Percentage
100 Invested
430.000 Budget
430.000 Partners
SupplyBase ApS People
SupplyBase ApS
Read more about the project
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| Supporting a clinical titration trial of intralymphatic immunotherapy with real time image analysis | 2026 - 2027 | Innofounder
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Supporting a clinical titration trial of intralymphatic immunotherapy with real time image analysis
Period
2026 - 2027
Region
Program
Innofounder Area
Ikke defineret Investment
Percentage
100 Invested
430.000 Budget
430.000 Innofounder-bevilling til AITSU – Bedre allergibehandling med AI-guidet ILIT
Innofounder-bevillingen vil give AITSU mulighed for at løse en central udfordring ved allergibehandling: den høje tekniske præcision, der kræves ved intralymfatisk immunterapi (ILIT).
ILIT er et hurtigt og effektivt alternativ til traditionel immunterapi. Behandlingen tager kun to måneder (mod tre år), har milde bivirkninger og giver lige så god effekt. Men den kræver, at nålen placeres præcist i lymfeknudens ydre cortex – noget der i dag kræver stor ekspertise (patent indsendt).
Vores løsning er en AI-baseret software, der guider sundhedspersonalet i realtid under ultralydsvejledt injektion. Systemet identificerer lymfeknude og nålespids og giver klar visuel feedback, så placeringen bliver optimal.
Løsningen omfatter:
Samarbejde med producenter (MAH) om tilpasset allergenekstrakt til ILIT.
CE-mærket AI-software til realtidsvejledning, kvalitetsstyring og refusion.
Fordi ILIT er kortvarig og skånsom, forventer vi højere gennemførselsrate og flere patienter, der vælger behandlingen. Det vil lette symptomerne for den enkelte og reducere belastningen på sundhedsvæsenet.
Med bevillingen kan vi modne den tekniske løsning og løfte kvaliteten af ILIT-behandlinger markant – så flere får glæde af en hurtig, sikker og effektiv allergibehandling.
Partners
AITSU Operations ApS People
AITSU Operations ApS
Read more about the project
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| Supporting in vivo drug discovery through machine learning-based analysis of behavioural and electrophysiological data | 2025 - 2028 | Industrial Researcher
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Supporting in vivo drug discovery through machine learning-based analysis of behavioural and electrophysiological data
Period
2025 - 2028
Region
Program
Erhvervsforsker Area
Ikke defineret Investment
Percentage
51.54 Invested
1.1 mill. Budget
2.1 mill. Dette projekt udforsker gennemførligheden og fordelene ved at bruge maskinlæring i forbindelse med ikke-klinisk in vivo lægemiddelopdagelse. Projektet fokuserer på at udvikle overvågede maskinlæringsmodeller til automatisk og kontinuerligt at detektere adfærdsmæssige og elektrofysiologiske ændringer induceret af specifikke genetiske og farmakologiske indgreb i gnavere, og vurdere modelydelse sammenlignet med standard in vivo neurofunktionelle vurderinger udført hos Lundbeck.
Partners
H. Lundbeck A/S, Technical University of Denmark People
Technical University of Denmark
Read more about the project
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| Supporting water infrastructure investment planning with hydroeconomic optimization models | 2017 - 2021 | Industrial Researcher
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Supporting water infrastructure investment planning with hydroeconomic optimization models
Period
2017 - 2021
Region
Region Hovedstaden Program
Erhvervsforsker Area
Energi, Klima og Miljø Investment
Percentage
60.22 Invested
1.1 mill. Budget
1.8 mill. Partners
COWI A/S People
COWI A/S
Read more about the project
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| SupStainAM - Super Stainless Steel by Additive Manufacturing | 2021 - 2021 | Innoexplorer
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SupStainAM - Super Stainless Steel by Additive Manufacturing
Period
2021 - 2021
Region
Region Hovedstaden Program
Innoexplorer Area
Produktion, Materialer, Digitalisering og IKT Investment
Percentage
100 Invested
1.5 mill. Budget
1.5 mill. Partners
Danmarks Tekniske Universitet People
Danmarks Tekniske Universitet
Read more about the project
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| SupWiz - automatiseret support ved brug af machine learning | 2017 - 2018 | Innobooster
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SupWiz - automatiseret support ved brug af machine learning
Period
2017 - 2018
Region
Region Hovedstaden Program
Innobooster Area
Ikke defineret Investment
Percentage
33 Invested
1.3 mill. Budget
4.0 mill. Partners
Sup Wiz ApS People
SupWiz ApS
Read more about the project
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| SupWiz ApS | 2021 - 2021 | Innobooster
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SupWiz ApS
Period
2021 - 2021
Region
Region Hovedstaden Program
Innobooster Area
Ikke defineret Investment
Percentage
100 Invested
1.0 mill. Budget
1.0 mill. Partners
SupWiz ApS People
SupWiz ApS
Read more about the project
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| SureShot | 2025 - 2026 | Innobooster
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SureShot
Period
2025 - 2026
Region
Program
Innobooster Area
Ikke defineret Investment
Percentage
33.84 Invested
999.972 Budget
3.0 mill. Partners
SureShot ApS People
SureShot ApS
Read more about the project
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| Surface engineering of aluminium alloys used in prosthetics | 2018 - 2021 | Industrial Researcher
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Surface engineering of aluminium alloys used in prosthetics
Period
2018 - 2021
Region
Region Sjælland Program
Erhvervsforsker Area
Produktion, Materialer, Digitalisering og IKT Investment
Percentage
47.94 Invested
1.1 mill. Budget
2.2 mill. Partners
Technical University of Denmark, Aluline A/S People
Aluline A/S
Read more about the project
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| Surface hardening of titanium: new applications and business opportunities | 2022 - 2025 | Industrial Researcher
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Surface hardening of titanium: new applications and business opportunities
Period
2022 - 2025
Region
Region Hovedstaden Program
Erhvervsforsker Area
Ikke defineret Investment
Percentage
58.65 Invested
1.1 mill. Budget
1.8 mill. Partners
Technical University of Denmark, ELOS MEDTECH PINOL A/S People
ELOS MEDTECH PINOL A/S
Read more about the project
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| Surgical Pakke Robot | 2019 - 2020 | Innobooster
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Surgical Pakke Robot
Period
2019 - 2020
Region
Region Hovedstaden Program
Innobooster Area
Biotek, Medico og Sundhed Investment
Percentage
33 Invested
127.050 Budget
385.000 Partners
Caretag Aps People
CARETAG ApS
Read more about the project
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| SusBrane Towards Zero-harmful Discharge: Sustainable Industrial Laundry Wastewater Treatment by Advanced Membrane Technologies | 2023 - 2027 | Grand Solutions
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SusBrane Towards Zero-harmful Discharge: Sustainable Industrial Laundry Wastewater Treatment by Advanced Membrane Technologies
Period
2023 - 2027
Region
Program
Grand Solutions Area
Ikke defineret Investment
Percentage
68.93 Invested
13.8 mill. Budget
20.1 mill. 35% of the total annual emissions of micro-/nano-plastics (MNPs) into the environment comes from the washing of synthetic textiles. This, as well as the fact that contaminants of emerging concerns (CECs) from garments can be absorbed by MNPs, makes the discharge of MNPs from industrial laundry wastewater an environmental problem. It can lead to aquatic pollution through inadequately treated wastewater and terrestrial contamination due to the use of wastewater sludge in agriculture. It results in chronic exposure as MNPs work their way up through the food chain, ending up in human food products. As society moves toward a circular economy, by increasing the use of multi-use garments, there is an urgent need to remove the MNPs from industrial laundry wastewater before discharge into the sewage. However, the current industrial laundries are not capable of removing MNPs. An estimated 90% of industrial laundry wastewater discharges to sewage without adequate treatment, raising risks for the natural environment and human health.
SusBrane consortium delivers a solution to this problem by capturing MNPs in a membrane filtration system followed by degradation of nano-plastics (NPs) and CECs in a catalytic reactor. The implementation will enable the industrial laundries to achieve zero-harmful discharge, reduce consumption of freshwater by 90% and energy by 20%, enabling significant cost reduction (Return on Investment = 55%), circular economy solutions and CO2 reductions.
Partners
Technical University of Denmark, LiqTech Ceramics A/S, Central vaskeriet, University of Extremadura, JENSEN INDUSTRIAL GROUP A/S, Ecolab ApS People
Read more about the project
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| SusProPass: Enabling Sustainable Production of UPM3 Circulation Pumps via Process Passports | 2023 - 2026 | Industrial Researcher
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SusProPass: Enabling Sustainable Production of UPM3 Circulation Pumps via Process Passports
Period
2023 - 2026
Region
Program
Erhvervsforsker Area
Ikke defineret Investment
Percentage
51.62 Invested
1.0 mill. Budget
2.0 mill. Projektet sigter mod at udvikle konceptet med processpas, der kan bidrage til at forbedre beregning af Grundfos’ produktionsmiljøpåvirkninger og øge troværdigheden af deres bæredygtighedsrapportering. Projektets resultater vil implementere processpas til produktionen af Grundfos UPM3-pumper og demonstrere at, de kan forbedre nøjagtigheden af produktions-CO2-beregning med op til 25% og muliggøre identifikation af processoptimeringsmuligheder der kan øge materialforbrugseffektiviteten med 5-8%.
Partners
Aarhus University, GRUNDFOS A/S People
Read more about the project
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| Sustainable aluminium busbars for electrical vehicles | 2024 - 2027 | Industrial Researcher
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Sustainable aluminium busbars for electrical vehicles
Period
2024 - 2027
Region
Program
Erhvervsforsker Area
Ikke defineret Investment
Percentage
62.98 Invested
1.1 mill. Budget
1.7 mill. Målet med det foreslåede erhvervs-PhD-projekt er at udvikle avancerede bæredygtige aluminium (Al) busbar løsninger til højspændings (HV) strømdistribution i elektriske køretøjer (EV'er). Dette mål vil blive opnået gennem en kombination af dybtgående højopløsnings mikrostrukturell karakterisering af nyudviklede Al-busbarlegeringer og applikationsspecifik testing ved realistiske EV-strømfordelingsforhold. En ny Al busbarlegering, der rummer minimum 40 vægt% genanvendt Al vil blive udviklet.
Partners
Technical University of Denmark, HYDRO PRECISION TUBING TØNDER A/S People
Read more about the project
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| Sustainable and democratic IoT development | 2023 - 2024 | Innofounder
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Sustainable and democratic IoT development
Period
2023 - 2024
Region
Program
Innofounder Area
Ikke defineret Investment
Percentage
100 Invested
430.000 Budget
430.000 Microsoft estimates today that 30% of all IoT implementations fail. As IoT technology is a key factor in becoming more sustainable, optimised and data-driven, it is very important that we find a more stable solution. IoT implementations seem easy and simple from the outside, but that is far from the truth. The production and development of each type of IoT device is different and thus entails its own IoT project with its own design, test and deployment phase. The current solution is therefore to pay hundreds of thousands for a proof-of-concept product, that might not work or scale well with the business.
Iotbee is creating an innovative electronic IoT device, where hundreds of different types of sensors can be connected. We combine that with a streamlined and fully automatic design tool for all types of sensors, so that companies can create their own IoT products and start projects independently without large costs for consultants and where the prototype phase is shortened from 1 - 2 years to 1 - 2 weeks. The company will be able to utilise their data from day 1, making the barrier to IoT insanely low.
Partners
Acembee ApS People
Read more about the project
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