TECH OFFERS

Collagen is a structural protein prevalent in the connective tissues of all organisms, and is the building block of biomaterial that is essential in wound healing and tissue regeneration. Through a patented extraction method, a novel Type I Amphibian collagen has been valorised from discarded skins, an agrifood waste stream and processed into a medical grade collagen biomaterial. The extracted pristine native amphibian collagen possesses unique properties, combining attributes associated with aquatic and land-based collagen sources, giving the extracted collagen more versatility than conventional sources of collagen. The Type I Amphibian collagen possesses a higher biocompatibility and water solubility as compared to mammalian sources of collagen, with a better thermostability profile, than marine sources of collagen. The technology provider has demonstrated the medical application of this extracted collagen by developing a range of specialised wound dressings, specifically designed for the management of chronic wounds. These dressing will significantly improve clinical outcomes and increase the rate of chronic wound closure.  The technology provider is looking for partnerships or collaborations to transform this pristine collagen into medical products. Additionally, with a pristine collagen extract, hydrolysing them into smaller fragments (collagen peptides) that can be customised to the needs of the partnership or collaboration, for the medical/cosmeceutical/nutraceutical industry.  A unique pristine Type 1 collagen of amphibian origin, in its native triple helix form. Relatively high denaturation temperature of ~43°C, to withstand the average human body temperature of 37°C, thus retaining its functionality better in human body as compared to marine collagen. Can serve as a matrix or carrier for bioactives such as anti-microbials or anti-inflammatory drugs or compounds that confer additional specific therapeutic benefits. Reduced risk of adverse reactions or rejection compared to traditional biomolecules, thereby increasing clinical safety. Can be easily chemically cross-linked to form a microporous scaffold that facilitates tissue regeneration and accelerates the rate of re-epithelialization. Proven to inhibit/deactivate matrix metalloproteinase (MMPs), producing an optimal healing environment for the wound. Exists as Nano Fibres that are 20–25 nm in diameter with a length of 200–400 nm, enhancing cell-material interactions and better supporting fundamental cellular processes. Highly absorbable and thus able to remove wound exudate, allowing for a reduction in inflammation and oedema at the wound site.  Amphibian collagen can be used widely for biomedical applications, nutraceutical products, as well as cosmetics. Well known for its biocompatibility in human tissue, collagen is widely used in clinical practice for accelerated wound healing, post debridement. The main clinical usage of this technology allows collagen to act as support matrices for the repair of matrix-rich tissues that have been damaged and replacing scaffolds for tissue filling.  In the cosmetic front, collagen is extremely suitable for the care of dry, UV-exposed, and environmentally stressed skin as well as ageing skin. It is one of the main constituents of cosmetic formulations due to its moisturising, regenerating, and film-forming properties. However, the technology provider is also keen to collaborate with partners to explore beyond the applications stated above. With increasing consumer awareness of skincare and beauty products, the collagen market is expected to have a continued upward trend. Due to a greater emphasis being placed on developing products that are environmentally friendly and sustainable, the approach of upcycling amphibian skins that would otherwise be discarded as waste, will be embraced by the consumer fraternity. The global collagen market was valued at USD 9.66 billion in 2022 and is expected to expand to USD 19.98 billion in 2030 at a CAGR of 9.36 % during the forecast period of 2023-2030. Though intense competition, with many established brands and new entrants in the extraction of collagen, this technology is unique in the resources used – amphibians. There is no commercial available amphibian collagen in the market and the technology provider is the first to have demonstrated the use of this in wound dressing and cosmetics. Amphibian collagen is expected to be widely embraced as there are no religious restrictions, unlike other traditional sources of collagen.  A medical grade collagen with intact native triple helix structure. A special mechano-chemical method of extraction that form a sustainable waste valorisation process. Maintains unique properties of both aquatic and land-based collagen, unlike current sources of collagen. Nano-collagen fibres that are of 175-187% thinner than those of mammalian collagen. Is easily processed into gelatin and easily hydrolysed to form collagen peptides. Collaborations can be medical or cosmetic related. White labeling options available. All products conform to ISO10993 and can be ETO sterilized. Amphibian Collagen, Wound Healing, Cosmetic, Environmental Sustainability, Biocompatibility Personal Care, Cosmetics & Hair, Healthcare, Medical Devices, Pharmaceuticals & Therapeutics, Waste Management & Recycling, Food & Agriculture Waste Management

Despite the remarkable achievements of large language models (LLMs) in various tasks, there remains a linguistic bias that favors high-resource languages, such as English, often at the expense of low-resource and regional languages. To address this imbalance, we introduce SeaLLMs, an innovative series of language models that specifically focuses on Southeast Asian(SEA) languages. SeaLLMs are built upon the Llama-2 model and further advanced through continued pre-training with an extended vocabulary, specialized instruction and alignment tuning to better capture the intricacies of regional languages. This allows them to respect and reflect local cultural norms, customs, stylistic preferences, and legal considerations. Highlights: The models' attunement to local norms and legal stipulations—validated by human evaluations—establishes SeaLLMs as not only a technical breakthrough but also a socially responsiveinnovation. SeaLLM-13b models exhibit superior performance across a wide spectrum of linguistic tasks and assistant-style instruction-following capabilities relative to comparable open-source models. SeaLLMs outperform mainstream commercialized models for some tasks in non-Latin languages spoken in the region, meanwhile, SeaLLMs are efficient, faster, and cost-effective compared to commercialized models. The SeaLLMs went supervised finetuning (SFT) and specialized self-preferencing alignment usinga mix of public instruction data and a small number of queries used by SEA language native speakers in natural settings, which adapt to the local cultural norms, customs, styles and laws inthese areas. SeaLLM-13b models exhibit superior performance across a wide spectrum of linguistic tasks and assistant-style instruction-following capabilities relative to comparable open source models. Moreover, they also outperform other mainstream commercialized models in tasks involving very low-resource non-Latin languages spoken in the region, such as Thai, Khmer, Lao,and Burmese. Training Process Our pre-training data consists of more balanced mix of unlabeled free-text data across all SEA languages. We conduct pre-training in multiple stages. Each stage serves a different specific objective and involves dynamic control of (unsupervised and supervised) data mixture, as well as data specification and categorization. We also employ novel sequence construction and masking techniques during these stages.Our supervised finetuning (SFT) data consists of many categories. The largest and most dominantof them are public and open-source. As the aforementioned are English only, we employed several established automatic techniques to gather more instruction data for SEA languages through synthetic means. For a small number of SFT data, we engaged native speakers to vet, verify and modify SFT responses so that they adapt to the local cultural customs, norms, and laws. We also adopted safety tuning with data for each of these SEA countries, which helps to address many culturally and legally sensitive topics more appropriately - such tuning data tend to be ignored, or may even appear in conflict with the safety-tuning data of other mainstream models. Therefore, we believe that our models are more local-friendly and abide by local rules to a higher degree. We conduct SFT with a relatively balanced mix of SFT data from different categories. We make use of the system prompt during training, as we found it helps induce a prior which conditions the model to a behavioral distribution that focuses on safety and usefulness.   Through rigorous pre-training enhancements and culturally tailored fine-tuning processes,SeaLLMs have demonstrated exceptional proficiency in language understanding and generation tasks, challenging the performance of dominant commercial players in SEA languages, especially non-Latin ones. The models’ attunement to local norms and legal stipulations—validated by human evaluations—establishes SeaLLMs as not only a technical breakthrough but a socially responsive innovation, poised to democratize access to high-quality AI language tools across linguistically diverse regions. This work lays a foundation for further research into language models that respect and uphold the rich tapestry of human languages and cultures, ultimately driving the AI community towards a more inclusive future. One of the most reliable ways to compare chatbot models is peer comparison. With the help ofnative speakers, we built an instruction test set, called Sea-bench that focuses on various aspects expected in a user-facing chatbot, namely: (1) task-solving (e.g. translation & comprehension), (2)math-reasoning (e.g., math and logical reasoning questions), (3) general-instruction (e.g.,instructions in general domains), (4) natural-questions (e.g., questions about local context often written informally), and (5) safety- related questions. The test set also covers all languages that we are concerned with. AI model candidates' responses to the test set's instructions may be judged and compared by human evaluators or more powerful large and commercialized AI models to derive a reliable performance metric. Through this process, we demonstrate that our SeaLLM-13b model is able to perform on-par or supasses other open-source or private state-of-the-art models across many linguistic and writing tasks. Infocomm, Artificial Intelligence

As rapid global warming accelerates, the need for increased sustainability efforts has become a critical societal challenge. While individual lifestyle changes can contribute, their impact remains limited without broader systemic shifts. This places significant pressure on industries, particularly the fashion & textiles sector, a major contributor to climate change responsible for 10% of global greenhouse gas emissions. Decarbonising this industry is therefore crucial to achieving a sustainable future. This technology enables textiles and fabrics to remove carbon dioxide (CO2) from air. The patent-pending material functionalises textiles to capture CO2 present in air which is sequestered into a harmless mineral during the laundering process. The resultant mineral which is environmentally safe is then washed away, leaving the textile recharged to remove CO2 once more. With this technology, decarbonisation of the textiles industry can be achieved through the decentralised action of consumers utlising functionalised carbon removing products. The technology owner is interested in working with interested companies in the fashion industry value chain to test-bed this new material for carbon removing apparel and fabrics. The technology is formulated and provided in a liquid formulation, to be a drop-in process where it is embedded in textiles during the “finishing stage” (last step) of a textile mill. Some features of the carbon removing technology include: Continual recharging of functionalised textiles through normal laundering process Forms a stable and environmentally friendly mineral upon sequestration of CO2 by regular detergent Lasts at least 10 washing cycles Can be embedded with standard finishing equipment (particularly at the padding and stenting steps) Currently optimised for cellulose based textiles but proof of concept has demonstrated polyester, polyamide, wool and blends thereof This technology has been designed for textiles – both for apparel and functional fabrics. It can also be considered for non-woven materials as well as for other applications such as coatings. Facing immense pressure to reduce its environmental impact, the fashion and textiles industry, a major contributor to global warming, seeks sustainable solutions that don't disrupt its fast-paced production. With an addressable global market of US$227 billion for textiles, this innovative technology offers a solution to textile manufacturers to reduce the industry’s carbon footprint. This empowers consumers to become active participants in combating climate change, simply by choosing clothes made with this technology. Offers a proprietary, environmentally safe carbon removal solution for textile industry Continual usage of the functionalised textiles – textiles are rechargagle to remove CO2 multiple times Does not require the adoption of new machinery or processes for its implementation carbon dioxide removal, textile, additive, carbon removal, fabric, decarbonisation, fashion, clothing, materials, mineral, functionalisation, sustainable, sustainability, apparel Materials, Nano Materials, Chemicals, Inorganic, Additives, Sustainability, Low Carbon Economy

The technology presented is an Artificial Intelligence (AI) model developed to extract essential information from scanned medical certificates. The trained model can extract pertinent details from medical certificates issued locally in Singapore and can help companies streamline their medical leave management  process by automating the approval of medical leave requests. The extracted details can also help in seamless integration with a company's existing workflow. The technology enables prompt and precise handling of leave requests and thus reduces administrative workload, processing time and errors introduced due to manual entry. The trained AI model recognizes terms and entities from scanned medical certificates. This includes but is not limited to - Clinic name Clinic address Clinic telephone number Patient name Start date of medical leave End date of medical leave Duration of medical leave The Name Entity Recognizer (NER) model is trained based on an open-source library and can be integrated with the existing workflow or system to automate the extraction of information for approval or recording purposes. The model, in its current state, is trained on a diverse dataset of medical certificates issued in Singapore and is suitable for application in systems providing Document Management and Human Resource solutions. The application of the model will particularly be useful for - Companies looking to automate their medical leave processing or application workflow. Insurance providers. Vendors specialising in Document Management, HR software solution, Payroll, and Attendance solutions.  The model can be integrated into their existing solution to value add in the processing of medicate certificates. The model is implemented using Natural Language Processing and deals with the domain of Named Entity Recognition. It has been trained using a diverse dataset of medical certificates issued in Singapore and is able to recognize entries of interest automatically from a scanned copy of the document. The model is able to take in the variation of formats, prints and naming of the entries and provide a recognizable input to the software systems making use of it. Medical Leave, Documentation Management, Named Entity Model, Human Resource Software, Medical Leave Automation Infocomm, Artificial Intelligence

This biotechnology pertains to a modular cloud-based bioprocessing system designed to streamline and enhance the cultivation and analysis of biological cultures. Addressing the complexities and constraints of traditional bioprocessing, this technology simplifies operations, making advanced bioprocessing tools accessible to a broader range of users. It has shown its versatility across various segments including educational institutions, research labs, biotech and bio-manufacturing companies and even within the food service industry, providing an efficient, flexible, affordable and scalable solution for growing biological cultures. The system comprises a base bioreactor unit with multiple add-on modules, including a multitude of environmental sensors, linear peristaltic pumps, compressed gas flow regulators, and novel stirrers & boosters. It is also controlled by a propietary cloud-based software, which provides a number of benefits for device management. This allows the user to access the bioreactor from anywhere, monitor experiments in real-time, and receive alerts for any errors. The modularity provides flexibility in the co-development of various bio-manufacturing applications, especially in streamlining production.      This technology is applicable in industries ranging from bio-medical to bio-pharma to food tech to environment tech. It serves as a foundation for products like vaccines, metabolites, cultured meats, fermented foods, biofuels, adjuvants, microbial inoculants, etc. It is especially relevant for R&D departments and educational programs focused on biotechnology and life sciences. The technology surpasses current market offerings with its modular design, ease of use, flexibility and affordability, enabling users to customize their setup according to their needs without extensive training or investment, thus democratizing advanced bioprocessing. Bioprocessing, Modular Bioreactor, Cell Culture, Microbial Cultivation, Synthetic Biology Culture, Scalable Biotechnology, Biotech Education, Advanced Biomanufacturing, Cultivated Meats, Alternative Proteins, Bio-Medical, Bio-Pharma, Fermentation, Precision Fermentation, Traditional Fermentation Foods, Processes

Near-infrared (NIR) light, part of the electromagnetic spectrum just beyond visible light, has various applications, particularly in vital sensing and food analysis. However, existing technologies for generating NIR light present certain limitations. Traditional halogen lamps can emit a continuous spectrum from visible to NIR wavelengths but pose challenges such as considerable heat generation, short lifetime, and difficulties in light distribution control. As a modern alternative, near-infrared LED arrays offer advantages such as no heat radiation and long lifespan. However, they are not suitable for applications requiring a wide wavelength range due to a lack of continuous output across the entire NIR spectrum. The wavelength intensity variation of NIR-LED arrays also affected the consistency of sensing and analysis. To overcome these challenges, the technology owner has developed a unique NIR phosphor as a heat-free light source with a wide spectrum range, enabling degradation-free analysis. Especially in food analysis, prolonged exposure to a halogen lamp may damage food. In addition, the long lifetime of this NIR source reduced the need for frequent replacements, leading to cost savings. Moreover, it can irradiate broadband NIR light from a single source, enabling easy light distribution control and wavelength axis alignment and reducing wavelength intensity variation within the irradiation plane. These advantages ensure consistency and accuracy in sensing and analytical applications. The technology owner is seeking R&D collaborations with industrial partners interested in integrating this advanced NIR light source into their applications. Compared to conventional near-infrared LED light sources, this NIR light source has a broader spectrum width, making it more suitable for spectroscopic measurements, especially those using multiple wavelengths. Key features of this technology are: Wideband spectrum: 450nm to 1000nm (over 1000nm is under development) Output: approximately 3W per module Adjustable spectral shape and light distribution angle to meet different needs Easy light focusing control and uniform wavelength intensity on the irradiation surfaces Long product life: 40,000 hours (LED chip guaranteed time), 40 times longer than typical lifespan of halogen lamps Minimal accuracy loss due to temperature changes: output drops by 8% only when the temperature increases from 25°C to 75°C, compared to a 27% drop of other products This unique near-infrared light source can be widely applied to night vision, non-contact vital sensing, food analysis, medical diagnosis, agricultural analysis, and other fields. Potential applications include (but are not limited to): Night vision: surveillance camera, traffic monitoring system, etc. Non-contact vital sensing: health monitoring (heart rate, oxygen saturation), self-health care, etc. NIR spectroscopy: foreign matter inspection, fruit and vegetable analysis, internal quality check, fresh food quality control, etc. Fluorescence imaging: endoscope, fundus camera, etc. Wide wavelength range and adjustable spectral shape No heat generation: enable degradation-free analysis Long product life: reduce maintenance frequency and costs Enhance the consistency and accuracy of sensing and analysis near-infrared spectroscopy, vital sensing, night vision, Light source Electronics, Lasers, Optics & Photonics, Healthcare, Diagnostics, Foods, Quality & Safety

Paper packaging is a versatile material used for a wide range of products. Its widespread adoption is due to its renewable and relatively low-cost resource along with environmental benefits such as recyclability and biodegradability. While paper packaging offers several advantages, some drawbacks of the material include porosity and the lack of barrier properties against moisture, oil, and grease. To overcome these limitations, conventional coatings such as polyethylene (PE) or polyfluoroalkyl substances (PFAS) have been employed to impart the required barrier protection. However, during the paper recycling process, it is difficult to repulp the coated paper due to several factors and results in reduced recyclability of such packaging materials. The technology on offer is a water-based coating formulation that can be applied onto paper packaging surfaces to act as a barrier against grease, liquid water, and water vapour. The coating imparts barrier protection functionalities, improving the paper’s resistance to grease, liquid water, and water vapor significantly. Use of bio-sourced constituents in the coating also improves product sustainability. As the coating’s constituents are repulpable, recyclability of the paper packaging can be achieved. With increasing awareness of reducing packaging waste, the deployment of this technology will offer companies a recyclable paper packaging with notable barrier properties. The technology owner is seeking for R&D co-development, test bedding and IP out licensing opportunities of this technology with interested companies. The water-based barrier coating technology has the following features: Consists of bio-sourced constituents to improve product sustainability Enables repulping of coated paper, largely improving recyclability of such packaging materials Improved barrier to water vapour transmission (WVTR) - WVTR value as low as 100 g/m2.day (based on ASTM E96) Improved liquid water resistance - Cobb60 value as low as 10 g/m2 (based on TAPPI T441) Improved grease resistance - a KIT rating as high as 12 (based on TAPPI T559) Easily applied by standard coating equipment Potential applications include (but are not limited to): Paper-based food packaging Paper boards, bags, and shipping sacks Products requiring enhanced barrier paper packaging Improves paper-based product recyclability while improving barrier properties of the paper Utilisation of bio-sourced constituents in coating formulation increases product sustainability Offers an alternative to PE and PFAS coated paper that are difficult to repulp coating, barrier, packaging, paper, water-based, recycling, recyclable, pulp, sustainability, sustainable, circular economy Chemicals, Coatings & Paints, Foods, Packaging & Storage, Organic, Bio-based, Sustainability, Circular Economy

There is a high demand for invitro diagnosis (IVD) test kits for various diseases in ASEAN and this technology is suited to provide product support to commercialise IVD test kits especially for public health problems faced in ASEAN. Produced under ISO13485 certified production, the IVD tests have high sensitivity and specificity, especially supporting the specific types of local ASEAN microorganisms detection. The technology services have supported the production of test kits for infectious disease for specific conditions such as Covid-19 and Leptospirosis. There are varieties of detection platforms which has been used in clinical laboratory system in hospital and clinic in remote areas. However, to improve the quality of produced IVD test kits,  standarised production process under the ISO13485 requirements are provided. Until now, the IVD test technologies that the technology provider can support include: Lateral flow-based assay test kit Immunological-based diagnostic test kits Biomolecular detection for IVD By providing standardised production facility, the technology provider is able to service the following potential applications:  Produce the highest risk class of IVD test kits that professionals require and can be widely used in Clinical Laboratory Analysis or Medical Technology Units for laboratory diagnosis services in hospitals. Produce IVD test kits for home use such as Point of Care Testing kits which offers personal care with easy-to-read and yourself analysis. Test kits needed for the veterinary and food-supporting industries. Supported under the Center of Excellent in Medical Innovative Development and Accelerating Support for Commercialization (MIDAS Center), the Technology Acelerator specifically designed to empower resarchers in advancing their medical IVD test kits. The technology provider focuses on taking research and innovation to IVD product development, ensuring all kits meet the international standards and can gain FDA approval worldwide. IVD kits, ISO13485, Manufacturing, Invitro diagnostics, infectious diseases Healthcare, Diagnostics, Medical Devices

Alzheimer’s disease (AD) is a neurodegenerative disease that mainly affects individuals above the age of 65. However, most patients are diagnosed only when significant symptoms appear, by which time severe brain pathology and neuronal cell death have already occurred, resulting in significant brain atrophy. Consequently, the optimal treatment window is often missed, leading to a fatal outcome. The technology is a simple, non-invasive, and accurate diagnostic solution for Alzheimer’s disease (AD), which can distinguish patients with AD from healthy people and evaluate disease status from a single drop of blood, with more than 96% accuracy. By combining proprietary machine learning algorithms for data analysis, this cutting-edge technology can be applied towards developing a clinical tool for population-scale screening, early diagnosis, staging and monitoring of the disease. The technology consists of the following main parts: With the advancement of ultrasensitive and high-throughput blood-based protein measurement technology (i.e. proximity extension assay), a simple and reliable blood test has been developed for AD diagnosis, by detecting a customized panel of novel plasma protein biomarkers. The test can detect AD 5-10 years before clinical symptoms manifest. Based on a proprietary self-developed algorithm, this system can differentiate among the early, intermediate, and late stages of AD, and can also be used to monitor the progression of the disease over time. Early diagnosis of Alzheimer’s disease Large-scale screening of Alzheimer’s disease Disease staging and progressing monitoring for Alzheimer’s disease, which can facilitate personalized intervention The global Alzheimer's Disease Diagnostics and Therapeutics Market is expected to reach USD 21.7 billion by 2030, at a CAGR of 5.5% during the forecast period 2021 to 2030. The market for Alzheimer's disease diagnostics and therapies was influenced by the outbreak of the COVID-19 pandemic when it first appeared. The increasing use of biomarkers in Alzheimer's diagnosis and the development of new drugs are the primary factors driving the expansion of the Alzheimer's disease diagnostics and therapeutics market. Another important factor is the rising incidence of Alzheimer's disease worldwide. The uniqueness of this technology includes several key features: Advanced data analytic tools and machine learning algorithms have been employed to achieve accurate and early detection of AD at 5-10 years before symptoms appear (accuracy above 96%). Notably, the disease-modifying drug Lecanemab has recently been approved for treatment of early AD patients by the Food and Drug Administration in USA. Accurate early detection of AD will help patients initiate medications and intervention in a timely and effective manner. This technology employs a multi-dimensional analysis approach to evaluate the status of different human body systems related to AD, including the immune, metabolic, neural, and vascular systems. This provides a more comprehensive assessment of an individual’s AD upon disease progression, enabling personalized analyses and suggestions tailored to each individual’s unique circumstances. This technology offers risk prediction by classifying individuals into different levels of AD risk, enabling targeted control and management of disease risks. Lastly, this technology facilitates close monitoring through regular testing, ensuring that AD risk or disease progression is closely tracked. By combining these features, the technology offers a holistic approach to early detection, risk assessment, and management of AD. alzheimers disease, biomarker, blood based biomarker, AD detection, early diagnosis Healthcare, Diagnostics, Pharmaceuticals & Therapeutics