Past Projects – Lean Launchpad Singapore
Nus enterprise website

Past Projects


  • 2019


    Principal Investigator: Prof Subramanian S. Venkatraman
    Team Members: Chaw Su Yin, Zhao Yida, Dr Annanya Shetty

    Globally, 200 million patients suffer from peripheral arterial disease (PAD) in which narrowed arteries restrict blood supply to the limbs and lead to amputations if left untreated. The current intervention involves reopening the blocked vessel followed by a Drug-Coated Balloon (DCB), which reduces inflammation to prevent re-narrowing. However, the low drug transfer rate with DCBs results in 60% of patients undergoing re-interventions every 3 years, coupled with the risk of drug-flaking related complications.
    Nanolimus is a novel nanocarrier which enables sustained release of Sirolimus that: i) achieves long-term control of inflammation and reduces the surgical re-intervention rate by half; ii) addresses long-term toxicity issues with Paclitaxel, the current drug used in DCBs, and iii) can be used with an injection system for localised drug delivery with minimum drug loss. Nanolimus will positively impact PAD treatment by reducing the frequency of re-interventions and lowering the safety risks and cost burden.

  • 2019
    Good Moood

    NUS, Dept of Pharmacology

    Principal Investigator: Assoc Prof Dawe Gavin Stewart
    Team Members: Dr Heng Hui Li, Dr Jasinda Lee Hanqing

    According to the Global Organisation for Stress, 75% of adults experience moderate to high level stress and 48% say stress has a negative impact on their personal and professional life. Without proper management, stress can exert a stunningly toxic toll on the body, brain, mind and soul, leading to depression, anxiety, meltdowns and panic attacks.
    Our research has identified a natural active ingredient from milk with anti-anxiety and anti-depressant like properties. This active ingredient has been scientifically proven to have various beneficial effects on brain function, such as improving focus, alertness, mood, learning and memory. It helps better management of stress-induced cognitive deficit problems.
    We are looking to commercialise Good Moood as a novel brain health supplement for consumers to better face and overcome day-to day challenges! Good Moood can be packaged into capsule or as powder, and can be used to complement a wide range of food and beverages such as milk and yoghurt.

  • 2019


    Principal Investigator: Dr Mark Chong
    Team Members: Alex Goh, Khong Wai Kit

    RelievIO is developing a proprietary technology that is able to provide a rapid, comfortable way to decompress small bowel intestinal obstruction (SBIO) to reduce hospital stays and to rapidly select patients for adhesiolysis (a complex and difficult surgery).
    Our technology consists of an integrated system that can automate suction and insufflation through our novel customised enteric tube. The combination of the integrated system and the novel tube generate what is termed as a “positive displacement technique” ensuring safe and efficient decompression of the bowel.
    We envisioned that our technology will be able to reduce length of stay by 50% for the treatment of SBIO and this will help reduce the healthcare burden and improve patient comfort.

  • 2019
    Perfusable Knit


    Principal Investigator: Asst Prof Michinao Hashimoto
    Team Members: Dr Atsushi Takano, Lee Cheng Pau, Tong Thi Kim Thu

    The perfusable knit (PK) is a knitted platform that can store, transfer, and release liquid materials contained inside. The liquid materials are in a part of the knitted structures, and thus enable us to carry, use and release them in and with textiles. Our technology allows fabricating meter-scale perfusable textiles using structural yarn (e.g. acrylic) in combination with elastomeric tube using industrial knitting machines.
    One of the possible use case of PK is the development of a flexible temperature control module. For example, the quality control of pharmaceuticals requires strict temperature control for thermosensitive drugs during transportation. PK enables developing miniaturised temperature-control sleeves and offers a solution to this problem.

  • 2019
    Capsule AI

    NUS, ECE

    Principal Investigator: Prof Guo Yong Xin
    Team Members: Dr Guo Yingkai, Dr Shweta Pradip Jadhav, Qiu Kunpeng, Zhang Yongxin, Zhang Yuyan

    We developed a smart, efficient and easy-to-use diagnosis decision system based on AI deep learning technology for capsule endoscopy in response to increasing demand for capsule endoscopic image diagnosis in the world.
    Through deep learning technology and internet accessibility, hospitals and medical institutions in Singapore can now provide a sharable, large-scale, cross-regional professional medical service for the world.
    For the doctor(End-User), it significantly reduces the time of reading images, reduces the probability of misdiagnosis, and improves the level of diagnosis and treatment. For the patient(Beneficiary), it effectively reduces the time of treatment and enjoy high-level medical care in high level hospitals or medical institution in Singapore. Finally, for the Hospital(Customer), it will enhance Singapore’s hospital service capabilities and tools for high-level Singapore medical institutions to export medical services.

  • 2019

    NUS, ChBE

    Principal Investigator: Assoc Prof Lanry Yung Lin-Yue
    Team Members: Dr Ang Yan Shan, Dr Norman Teo Zhi Wei, Dr Wu Shuang

    BioDetectIF aims to accelerate drug discovery via our proximity assay which enables the direct measurement of drug-target interactions in translatable systems. Drug discovery is a time consuming (> 10 years) and expensive (billions of dollars) process. Yet on average, only one in every 5,000 compounds selected for pre-clinical development is successfully developed as an approved drug. This figure can be improved if the compound selection decisions were supported by sound proof-of-mechanism evidence. Here, we offer a no-wash solution-phase assay which provides reliable and direct insight into drug-target binding within 30 minutes even for in vivo models. Compared to the existing protein melting method and cell-based assay, our assay is cost-effective, rapid and much simpler without the need for complicated vector design or controlled sample heating. Furthermore, it can be easily integrated into existing automation workflow based on microplate reader and high content screening systems.