| I am a consultant geriatrician with an active clinical practice, caring for frail older adults with complex age-related conditions. Patients are at the heart of all I do, and my clinical work continually drives my research, which focuses on improving care through earlier detection, accurate prognostication, and personalised interventions. To address current gaps in identifying latent disease and physiological decline, I have developed expertise in data science and machine learning, building clinical classifiers and risk models, such as biological ageing clocks (LinAge and LinAge2), to assess physiological resilience across the life course. I currently lead the validation of the LinAge2 clinical ageing clock and its derivatives across multiple Singapore cohorts, including SG70, LIFELONG and others, to ensure broad population applicability. To support clinical translation, I collaborate with Singapore-based healthtech provider NOVI Health, which is integrating LinAge2 into its healthy longevity programme to track responses to lifestyle, dietary, and pharmacological interventions. I also co-lead the Singapore Chinese Health Study and its SG70 sub-study, co-lead medical technology innovation at Ng Teng Fong General Hospital through its Digital Think Tank, and lead the LIFELONG study within the National University Health System (NUHS). LIFELONG aims to validate, refine, and deploy clinically actionable ageing clocks, such as the LinAge family, through the NUHS Endeavour AI / Discovery AI platform. Together, these efforts support the development of evidence-based strategies for healthy longevity in clinical practice. |
| • 2025 - NUHS Commendation Award (FY2024) (for research excellence) • 2025 - Singapore Health Quality Service Awards - Gold Award • 2025 - NUS YLL SOM CSDU Academic Fellowship • 2024 - Singapore Health Quality Service Awards - Silver Award • 2024 - SGH Service Quality Award - Service with a Heart Award • 2022 - NMRC Research Training Fellowship • 2022 - SGH Service Quality Award - Service with a Heart Award |
| 1. Fong S, Denisov KA, Nefedova AA, Kennedy BK, and Gruber J. LinAge2: Providing actionable insights and benchmarking with epigenetic clocks. npj Aging 2025; 11(29): 1-7. 2. Yusri K1, Kumar S1, Fong S, Gruber J, and Sorrentino V. Towards Healthy Longevity: Comprehensive Insights from Molecular Targets and Biomarkers to Biological Clocks. International Journal of Molecular Sciences 2024; 25(12): 6793. 1Both authors contributed equally to this work. 3. Fong S, Pabis K, Latumalea D, Dugersuren N, Unfried M, Tolwinski N, Kennedy B, and Gruber J. Principal component-based clinical aging clocks identify signatures of healthy aging and targets for clinical intervention. Nature Aging 2024; 4(8): 1137-1152. 4. Theik DO, Fong S, Ang AGC. Sealed perforation of jejunoileal diverticulitis: a case report. Asian Journal of Gerontology & Geriatrics 2022; 17(1). 5. Teo E, Lim JSY, Fong S, Larbi A, Wright G, Tolwinski N, and Gruber J. A high throughput drug screening paradigm using transgenic Caenorhabditis elegans model of Alzheimer’s disease. Translational Medicine of Aging 2020; 4: 11-21. 6. Teo E, Fong S, Tolwinski N, and Gruber J. Drug synergy as a strategy for compression of morbidity in a Caenorhabditis elegans model of Alzheimer’s disease. GeroScience 2020; 42(3): 849. 7. Teo E, Ravi S, Barardo D, Kim H-S, Fong S, Cazenave-Gassiot A, Tan TY, Ching J, Kovalik J-P, Wenk MR, Gunawan R, Moore PK, Halliwell B, Tolwinski N, and Gruber J. Metabolic stress is a primary pathogenic event in transgenic Caenorhabditis elegans expressing neuronal human amyloid beta. Elife 2019; 8: e50069. 8. Fong S, Ng LF, Ng LT, Moore PK, Halliwell B, and Gruber J. Identification of a previously undetected metabolic defect in the Complex II Caenorhabditis elegans mev-1 mutant strain using respiratory control analysis. Biogerontology 2017; 18(2): 189-200. 9. Fong S1, Teo JWE1, Ng LF, Chen C, Lakshmanan LN, Tsoi SY, Moore PK, Inoue T, Halliwell, B, and Gruber J. Energy crisis precedes global metabolic failure in a novel Caenorhabditis elegans Alzheimer Disease model. Scientific reports 2016; 6(1): 1-9. 1Both authors contributed equally to this work. 10. Gruber J, Chen C, Fong S, Ng LF, Teo JWE, and Halliwell B. Caenorhabditis elegans: What we can and cannot learn from aging worms. Antioxidants & redox signaling 2015; 23(3): 256-279. |
| • Royal College of Physicians, United Kingdom |
