Triple W Japan, developer of urination predictor, wins $610K grant for clinical...

Triple W Japan, developer of urination predictor, wins $610K grant for clinical research

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Image credit: Triple W Japan

 

See the original story in Japanese.

Tokyo-based Triple W Japan, the Japanese startup developing developer of urination predictor device DFree, announced last week that it was selected by NEDO for the corporate alliance program for R&D-focused startups, and will receive a subsidy of up to 70 million yen (about $610K US). The target for the subsidy is joint research with large companies in relation to DFree’s small size and high performance, and since the expenses required for research will be paid up to the maximum amount, it is possible to obtain the full subsidy.

The contents of collaborative research with each of five major companies are as follows:

  • Accenture…Collaborative research on nursing care packages combining various sensors and nursing care record data, joint development of algorithms and software, support for overseas development centered on Europe, etc.
  • Itochu Chemical Frontier…Development of a high precision ultrasonic sensor, high accuracy coupled with algorithm development, etc.
  • Itochu Techno Solutions…Feasibility studies, joint development of software, etc.
  • Paramount Head…Improve accuracy through the combination with various sensors, joint solution development, etc.
  • Revamp…Feasibility study at nursing care facilities, sales support, etc.

Among these companies, Revamp also participated in the series A funding round that Triple W Japan conducted last July. Also, in February of last year, the company acquired a subsidy of up to 70 million yen from NEDO’s another R&D venture support project (commonly known as the STS grant project).

DFree’s mobile app for nursing care facilities
Image credit: Triple W Japan

Recently, Triple W Japan won Grand Prize at the “Japan Healthcare Business Contest” conducted by the Ministry of Economy, Trade and Industry on March 3rd. Interest from Europe is also high, and it seems that DFree was exhibited as a use case of Soracom, an IoT-focused mobile network service from Japan, which announced its advance into Europe at the Mobile World Congress held in Barcelona earlier this month. They are also scheduled to represent Japan in the Netherlands’ startup conference competition Get in the Ring (which timing-wise overlaps with Tech in Asia Singapore 2017…) from May 17th to the 19th.  Moreover, in Kawasaki city, DFree is certified as the Kawasaki Innovation Standard with the city subsidizing expenses for its use in nursing care facilities, which is expected to spur introduction.

Triple W Japan’s CEO Atsushi Nakanishi had the following to say about the future of DFree:

I’d like to work with Kawasaki city to see it implemented for in-home nursing care and rehabilitation. In particular, most patients who have suffered from a stroke undergo a rehabilitation process where they’re forced to wear a catheter after surgery (to compensate for difficulty urinating), which they then have removed and wear diapers, finally graduating from those, in order to fully rehabilitate into society. DFree would be useful in the process of removing the diaper.

Nakanishi continued:

DFree has already begun to be used in French nursing home care facilities, and we will promote trials for full-scale introduction. We’re also in the process of contracting with a German company. We are collaborating in Europe since the structure of nursing care is well established. Regarding areas where nursing care is not easy, I’d like to consider making rehabilitation models and home care support tools and packages. I’d like to partner with insurance companies.

At the beginning of the project, DFree had set a goal of predicting bowel movements, but recently seems to be shifting its focus to urination control. On this, Nakanishi said that the technological development of urination prediction is the priority because urination is more frequent than bowel movements, making it easier to develop data and algorithms; also, throughout the world there are more people who are in need of support for urination rather than defecation. It appears that once they have answered the demand for urination prediction, they will once again return to the development of a solution for defecation prediction.

Translated by Amanda Imasaka
Edited by Masaru IKeda