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Discover new technologies by our partners

TechInnovation 2023 showcases more than 100 latest technologies and innovations in sustainability, health and well-being and AI in healthcare from our partners in Hong Kong SAR, Korea, Japan, Singapore, Slovakia, and Thailand. Enterprises interested in these technology offers can register at to meet these technology providers and arrange for your 1-1 business meeting.

Novel Photosensitizer Compounds for Photodynamic Therapy (PDT)
Photodynamic therapy (PDT) is a highly targeted treatment modality activated through light-based photooxidation process where a photosensitizer (PS) molecule upon illumination by visible or near infrared light, produces Reactive Oxygen Species (ROS) that invokes cellular death. This technology surfaced two newly discovered synthetically modified Eosin Y analogue compounds, E3B and E5B as organic PS for targeting Gram-positive bacteria, in particular Methicillin-Resistant Staphyloccocus aureus (MRSA), without non-specific killing of normal mammalian cells. Microbial infectious diseases caused by multidrug resistant pathogens are a constant severe threat to global public health. PDT is a form of antibiotic-free phototherapy to efficaciously treat microbial infections with advantages in spatiotemporal controllability, non-invasiveness, minimal off-targets and side effects, and broad antimicrobial spectrum. However, the promise of PDT in antibacterial intervention has not been fully fulfilled particularly using conventional organic PS due to restricted structural availability. Herein, we disclosed organic PS compounds, E3B and E5B, with high intracellular ROS-generation capabilities under white light irradiation at very low light dose without suffering photobleaching of traditional PSs to combat antimicrobial resistance as a promising antibacterial PDT for translation to clinical trials. The technology owner is seeking collaboration with biotech, clinical stage biotech and pharmaceutical companies to develop and commercialize new antimicrobial PDT agents superior to currently marketed organic PSs. The technology has been validated till in vivo specificity and stability studies. There are opportunities in R&D collaboration to demonstrate the interactions and characterization of the novel E3B and E5B PS with metabolites in controlled functional assays of microbial communities.
Cost Effective Hybrid Additive and Subtractive Manufacturing Laser based System
In manufacturing there are many instances where there is a need for low production runs of parts. These could be for parts of an equipment, tools, small volume runs for trials or customised parts. However, traditional manufacturing techniques are usually not cost-effective for such low volume runs, while current additive manufacturing suffers from low strength, long print times and poor surface finish needing post-processing. Additionally, for techniques using powder and filaments, considerations have to be given to the storage due to oxidation, degradation, flammability and toxicity of these precursor materials. The tech owner has developed a hybrid manufacturing technique that involves both additive and subtractive manufacturing methods. Instead of powder or filaments, sheets and foils are used as precursor materials, thereby alleviating cost, safety and performance concerns that were outlined. A laser is used to cut and fuse the different layers of the build.   Numerous tests conducted by the team have consistently yielded parts that are dense and displayed high strength. The system is able to work with different materials, including highly reflective ones such as, aluminium, copper. Parts using carbon fibres, composition materials, ceramics, etc have also been successfully printed. Based on initial estimates, this technique offers up to 80% cost advantage over powder bed systems. The tech owner is seeking partners to collaborate in test bedding the system for manufacturing of complex, customized and/or high strength / high thermal conductivity parts for applications in the healthcare, semiconductor, aerospace, automotive, telecoms or marine & offshore sectors.
Novel Ingestible Capsule X-ray Dosimeter for Real-Time Radiotherapy Monitoring
In radiotherapy for patients with gastrointestinal (GI) cancer, real-time, continuous monitoring of X-ray radiation in the GI track can greatly improve the precision of the treatment. This proposed technology consists of a swallowable X-ray dosimeter capsule for real-time monitoring of absolute absorbed radiation dose and changes in pH and temperature in the GI tract. Using a neural network-based regression model and a luminescence of nanoscintillators fiber, the capsule is able to estimate radiation dose from radioluminescence and afterglow intensity and temperature. Initial preclinical study in a rabbit model showed that the dosimeter was approximately five times more accurate than standard methods for dose determination. Hence, these swallowable dosimeters may help to improve radiotherapy and understand how radiotherapy affects tumour pH and temperature. The technology owner is seeking for collaborations and out-licensing with medical institutions and medical device companies for clinical testing and further research identifying the capsule's position and posture after ingestion, developing a robust positioning system.
Boron Nitride Composites For Thermal Management
Thermal management is an essential part of the design of high power density electronics. As the power density of electronic devices increases, so does the amount of heat they generate, and this heat must be dissipated effectively to prevent the devices from overheating and failing. This technology offers a method to produce high thermal conductivity boron nitride (BN) composites that aim to improve thermal management in high power density electronics, leading to more efficient, more compact, and safer electronic systems. BN composites are a group of materials made by combining boron nitride with another material, such as a polymer, metal, or ceramic. A key advantage of such composites is that they exhibit higher thermal conductivity than any commercially available material that is electrically insulating. The resultant BN composites are also low in weight, easily shaped, exhibit good mechanical properties, and offer the unique capability of designing the path by which the heat will be conducted. These properties fulfil the demanding requirements for electronic packaging in emerging markets like Internet of Things and embedded systems, autonomous vehicles, high speed computers, satellites to name a few. The technology owner is seeking for co-development and out-licensing opportunities with semiconductor and device-assembling companies that require high thermal conductivity materials.
Universal Robotic Gripping: Variable-Stiffness Gripper Enabled by Jamming Transition
Recent advances in soft robotics revolutionize the way robots interact with the environment, empowering robots to undertake complex tasks using soft and compliant grippers. Compared to traditional rigid structures. Soft grippers have excellent adaptability for a variety of objects and tasks. However, the existing gripper systems faces some challenges, such as handling delicate, wet, and slippery items, risk of damaging valuable items, and high production cost. Based on pneumatic jamming of 3D-printed fabrics, the technology owner has developed a variable-stiffness soft pneumatic gripper that can apply small forces for pinching and pick-up heavy objects via stiffening. The invented grippers are soft and adaptive to handle dedicate items with various shapes and weights, minimizing the damaging risk of items during gripping process. In addition, such gripper with adjustable stiffness could handle heavy and bulky items by increasing its gripping strength. These benefits make the gripper more versatile and adaptable to various applications in agriculture, food processing, packaging, manufacturing, and human-robot interaction (HRI). The technology owner is seeking to do R&D collaboration, IP licensing, and test-bedding with industrial partners intending to integrate variable-stiffness gripper in their applications. 
Microfluidic Immunoassay Device for Blood Analysis
A microfluidic chip-based mechanism has been developed as a Point-of-Care Testing (POCT) device to replace Lateral Flow Assays (LFA) for fast and convenient blood analysis. The microchip system utilises the principle of immunoassays but with high accuracy and compatibility to different signalling tags, providing a quantitative readout. Conventional immunoassays involve multistep procedure and long process time. While LFAs are fast and convenient, they are qualitative. The device demonstrated a one-step assay that can achieve equal or higher sensitivities than standard methods within significantly shorter total processing time. In a microfluidic device, the sample flows in precisely defined microchannels, which allow better control of fluid behaviour and higher consistency in testing results compared to LFA in which the sample flows by wicking through the porous paper-based material. This technology resides in the assembly of components and materials to immobilise antibodies or antigens onto the chip which can be easily scaled for commercial production. The technology owner is seeking collaborations with manufacturers of IVD devices or Medtech companies to out-license the technology and expand the range of antibodies targets for the microchip.
Building Explainable, Verifiable, Compact & Private AI Solutions For Critical Applications
The technology consists in a new type of neural networks, providing explainable, verifiable, compact and private AI solutions. Explainability: the technology provides precise global explanations and the exact rules learned by the AI model, even with large datasets. We transform clients' raw data and/or models into meaningful results through high-quality visual analytics, empowering them to enhance the model based on these explanations. Formal Verification: the technology allows the client to formally verify certain properties of the model, such as its robustness to adversarial attacks, its fairness according to certain features, etc.
A Suite Of AI Tools To Detect And Monitor Neurological Diseases From CT Scans
Neurological diseases are the second leading cause of death. CT scans have been used as the primary modality to diagnose brain abnormalities such as Intracranial Haemorrhage (ICH) and neurodegeneration. Radiologists usually have to deal with an overwhelming scan backlog and writing radiology reports is a time consuming process. Manual segmentation of lesions is tedious and existing heuristics have been shown to overestimate lesion volumes. Clinicians are also wary of the ‘black box’ nature of deep learning models. Hence, an automated tool in the workflow could substantially improve clinical productivity and interpretability is crucial to build trust with clinical stakeholders. Our proposed technology is an AI solution that automates ICH detection and brain tissue segmentation on CT scans, producing accurate volumetric information to assist triaging. Our technology also comes with a set of tools to interact with the AI models and generate reports easily. Moreover, we strengthen our AI transparency with interpretable models. Our platform also focuses on model robustness tests to assure AI safety.  
Rapid Digital Twinning using robotised LiDAR cameras
Digitalisation is a global trend with digital twin technology increasingly adopted in various industrial segments including smart factories and plants, digital facility management and operation & maintenance, building and construction, etc. Rapid generation of digital twin of physically existing is desired. Conventionally, digital twin is mainly generated using design software which requires professional modellers to spend substantial design time pending on the complexity of the physical twin (to be constructed) and the manpower available. Building information modelling (BIM) is increasingly used as a representation for the digital twin. For existing environments, scan to BIM technology and authoring software products are used for the process of reconstructing of BIM models from LiDAR scanned point clouds. This manual process is typically time consuming, tedious and error prone. Often, meshed models are used for visualization purpose of the digital twin.