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NHG Centre for Medical Technologies & Innovations (CMTi) and National Health Innovation Centre Singapore (NHIC) Joint MedTech Grant Call

nhg logoTo encourage innovation in healthcare, the NHG Centre for Medical Technologies and Innovations (CMTi) and NHIC rolled out the NHG CMTi-NHIC Joint MedTech Grant, which provides internal seed funding for the development of innovative MedTech solutions. This grant aims to fund the early stage development of technological solutions that are commercially viable to resolve unmet needs in healthcare. Potential areas for MedTech innovation include, but are not limited to, medical devices, diagnostics, and digital applications.

The Centre for Medical Technologies and Innovations (CMTi) is NHG’s primary engine that drives innovation through the translation of ideas into implementable products, bridging the gap between unmet clinical needs, MedTech development, and innovative healthcare solutions. CMTi continuously looks out for opportunities to foster meaningful partnerships and builds its strategic innovation ecosystem with both local and international partners spanning across industry, academia, research and government sectors. From assessing problem statements and use cases, to building and supporting the navigation to resources, strategizing the right collaborative approach with our partners, and finally solution adoption and healthcare implementation, CMTi is fully equipped with a productization strategy for efficient business model execution.

Innovation teams may leverage on the potential outcomes of this seed funding to seek further competitive funding at the national level and advance the development of their MedTech solutions to bring them to implementation.


Application Eligibility
  • The main applicant (i.e. PI) should hold a primary appointment in and be salaried by an NHG institution.
  • Co-I(s) should hold at least an adjunct position in a local public institution.
  • Individuals from overseas institutions or private companies can only participate as Collaborators.


Funding Information

The successful application will be awarded a funding of maximum S$100,000 for a duration of one (1) year.

This grant could be used to support manpower, equipment and other operating expenses required for the development of the proposed MedTech solutions. Up to 50% of the total approved budget could go to the institution(s) of Co-I(s). Collaborator(s) are not entitled to receive directly any portion of the grant. Overheads or indirect research costs will not be supported.


Funded Projects
Host Institution Principal Investigator (PI) Project Title
2019 (Awarded in 2020)
TTSH Dr How Kwang Yeong SERA, Surgical Enhanced Recovery Assistant (Mobile App Development for ERAS patients)
NSC Prof Steven Thng Developing the Handheld Confocal Raman for in-vivo study of skin biochemistry: A prospective clinical study on effects of moisturisers on skin biochemistry
NSC Dr Tey Hong Liang Alleviation of procedure-related pain using a non-invasive vibratory device
NSC Dr Tan Siyun, Lucinda Artificial Intelligence-incorporated automated attachable Dermatoscopy for Bedside Algorithmic Diagnosis of Melanoma
TTSH Dr Aung Myint Oo Pilot project of a modular assembled, multiple surgical procedures training simulator
NSC Lim Ziying Vanessa Formulation of a safe and effective silver-containing antimicrobial moisturiser for concurrent emollient and prolonged anti-septic effects
TTSH Danson Yeo Prediction of body composition using 3D optical imaging and machine learning in an Asian Population
NSC Tan Yingrou Automation of Tissue Optical Clearing Processes
KTPH Hah Yan Yee Application of artificial intelligence in detection of red reflex for the grading of cataracts
NSC Tey Hong Liang Anti-inflammatory moisturizer cream containing oligonucleotide for management of atopic eczema
KTPH Wei Shan Applying Virtural Reality in Cognitive rehabilitation for stroke survivors
NSC Cheng Hui Mei 3D-printed Rapidly Administrable Microneedle Patch for Acne Scar Treatment
TTSH Trevor Binedell 3D knitted prosthetic socket with integrated liner
TTSH Leong Khai Phang Rapid and Accurate Genomic Data Interpretation for Personalized Medicine
TTSH Fan Bingwen Eugene Algorithm for diagnosis of peripheral blood films via deep learning and computer vision.


For more information about this grant, please visit this link and contact your Host Institution’s Research Office:

Ms Evangeline Ng
DID: 6496 6984
Email: This email address is being protected from spambots. You need JavaScript enabled to view it.