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About Us

Established in 2014, GemVCare is founded on the idea that our community needs a far better approach to tackle the big and complex epidemic that is diabetes. We believe we’ve found the answer in personalized assessment.


Everyone is different, so is our health. Applying a personalized approach means we can provide more data and information to medical professionals to advise you on making decisions of diabetes prevention, diagnosis, treatment and care based on a precise understanding of your genetic profile.  This is achieved through rigorous assessments of your individual gene and biomarker profile, as well as other drivers and risk factors. This approach could help improve outcomes in diabetes.




Supported by the Innovation and Technology Commission’s “Technology Start-up Support Scheme for Universities”(TSSSU) 



Selected to be an incubatee at the Hong Kong Science Park


BOC(HK) FITMI Achievement Award 2015: "Technology Start Up" Award - Merit Award 



​Testing services officially launched


Selected to be in SPRINTER program organized by HKSTP, HSBC and HKBAN



Hong Kong ICT Award 2018: ICT Startup (Social Impact) Gold Award


Established GemVCare (Shenzhen) Limited in Shenzhen, China


The 49th International Exhibition of Inventions Geneva Award: Silver Award

Our Core Technology

Central to our personlized care model are the genetic markers used to harness the genetic profiles of our clients, as well as the core technology deployed to find these markers.

Our founder is amongst the first researchers in the world to discover diabetes genes specific for Asian people. The discoveries were made over two decades of clinical research and validation for a wide range of genetic discoveries related to diabetes.


Our state-of-the-art technologies used to make the above discoveries possible – namely next generation sequencing, proprietary algorithm and other advanced molecular techniques – have become the backbone of our unique testing capabilities combining IT & biology. GemVCare is glad to be able to adapt these technologies for the use of the wider public through technology transfer from the Chinese University of Hong Kong.


The genetic findings born from these technologies, when analyzed together with other health parameters and the big data we have collected over the years, give rise to many meaningful data –  such as the risks of developing diabetes and its complications and other major chronic diseases  – that could provide valuable information to medical practitioners in making diabetes treatments and management decisions or recommendations. This approach has since become a new strategy recommended by different professional bodies in the prevention and management of diabetes.

*Patented technology means patents and pending applications licensed from the Chinese University of Hong Kong relating to®, DForesee®, DProtect® and Monogenic Diabetes Panel.



  1. Ahmad A, Lim LL, Morieri ML, Tam CH, Cheng F, Chikowore T, Dudenhöffer-Pfeifer M, Fitipaldi H, Huang C, Kanbour S, Sarkar S, Koivula RW, Motala AA, Tye SC, Yu G, Zhang Y, Provenzano M, Sherifali D, de Souza RJ, Tobias DK; ADA/EASD PMDI; Gomez MF, Ma RCW, Mathioudakis N. Precision prognostics for cardiovascular disease in Type 2 diabetes: a systematic review and meta-analysis. Commun Med (Lond). 2024 Jan 22;4(1):11. doi: 10.1038/s43856-023-00429-z. PMID: 38253823; PMCID: PMC10803333.

  2. Tobias DK, Merino J, Ahmad A, et al. Second international consensus report on gaps and opportunities for the clinical translation of precision diabetes medicine. Nat Med. 2023 Oct;29(10):2438-2457. doi: 10.1038/s41591-023-02502-5. Epub 2023 Oct 5. PMID: 37794253; PMCID: PMC10735053.

  3. Leslie RD, Ma RCW, Franks PW, Nadeau KJ, Pearson ER, Redondo MJ. Understanding diabetes heterogeneity: key steps towards precision medicine in diabetes. Lancet Diabetes Endocrinol. 2023 Nov;11(11):848-860. doi: 10.1016/S2213-8587(23)00159-6. Epub 2023 Oct 4. PMID: 37804855.

  4. Franks PW, Cefalu WT, Dennis J, Florez JC, Mathieu C, Morton RW, Ridderstråle M, Sillesen HH, Stehouwer CDA. Precision medicine for cardiometabolic disease: a framework for clinical translation. Lancet Diabetes Endocrinol. 2023 Nov;11(11):822-835. doi: 10.1016/S2213-8587(23)00165-1. Epub 2023 Oct 4. PMID: 37804856.

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