Using a desk-side 3D printer, dentists can now build a permanent crown material in just 15 minutes while also accurately replicating the patient’s natural tooth colour without the use of additional colouring. This solution saves dentists and patients a significant amount of time when compared to the weeks the process would have previously taken.
A*STAR’s Institute of Materials Research and Engineering (IMRE) contributed technical expertise and experience to the project, creating a specially formulated resin with excellent strength, rigidity, and biocompatibility that mimics tooth enamel.
The agency has licenced a method for producing a three-dimensional object layer-by-layer using a computer-generated design, thereby accelerating the research and development period, and accelerating the commercialisation of the material.
A dental crown is one of the most common dental procedures used to restore or repair teeth, but it is still a time-consuming procedure. Singapore is attempting to shorten appointment times by using innovative 3D-printed dental crowns.
Patients must visit the dentist at least twice when getting a dental crown. The first visit consists of preparing the tooth and taking an impression of the permanent crown’s construction. The impression is then sent to a third-party dental laboratory to be made into a crown. This procedure can take two to three weeks, which is inconvenient for the patient. Multiple appointments also take up dentists’ time, which could be better spent treating more patients.
As a result, it is not surprising that the dental industry sees 3D-printed dental crowns as a viable solution. Instead of waiting for the laboratory, dentists could print the crown in their clinic, and patients could be fitted with their new crown in a single appointment.
Although 3D printing technology is mature, creating a material that meets healthcare regulatory standards remains difficult. The material must also be strong enough to withstand wear and tear while remaining biocompatible.
The solution consisted of two parts: first, 3D printing technology, and second, developing the right material to print the crowns with. As it is intended to last for several years, the crown material must match actual tooth enamel strength and have high biocompatibility. It must also meet some regulatory requirements.
It has been difficult to develop a material that meets all the criteria for a permanent dental crown in the market, however, A*STAR intends to develop new and unique dental needs, as well as other dental products. More than 20 customers in Singapore use the technology’s 3D printed dental crown solution, as do international customers in China, Hong Kong, Macau, and Malaysia.
OpenGov recently reported that researchers from the Faculty of Dentistry at the University of Hong Kong (HKU) and the Department of Computer Science of Chu Hai College of Higher Education, collaborated to develop a new approach using artificial intelligence to automate the design of individualised dentures, to enhance the treatment efficiency and improve patient experience.
The AI technology used in the process was based on 3D Generative Adversarial Network (3D-GAN) algorithm and tested on 175 participants recruited at HKU. The study shows that AI technology could reconstruct the shape of a natural healthy tooth and automate the process of false teeth design with high accuracy.
Meanwhile, the Health Sciences Authority (HSA) of Singapore has collaborated with four other international regulatory agencies as part of the Access Consortium to expedite the approval of a new therapeutic product for the treatment of two eye diseases that are among the leading causes of irreversible vision loss.
Through the “New Active Substance Work Sharing Initiative” (NASWSI) of the Access Consortium, a five-way product evaluation was conducted for the first time. This multi-agency programme aims to expedite patients’ access to innovative medications and treatments by improving the regulatory review process and reducing duplication of efforts on the part of both regulators and pharmaceutical companies.
The Access Consortium is a group of like-minded international health product regulators. With the introduction of its newest consortium member, the UK MHRA, in January 2021, it was renamed the previous Australia-Canada Singapore-Switzerland Consortium (ACSS). The new name reflects the group’s primary goal of providing patients in member countries with timely access to high-quality, safe, and effective therapeutic products.
A multidisciplinary team of Massachusetts Institute of Technology (MIT) researchers led by Iddo Drori, a lecturer in the MIT Department of Electrical Engineering and Computer Science (EECS), has used a neural network model to solve university-level math problems at a human level in a matter of seconds.
“It will help students improve, and it will help teachers create new content, and it could help increase the level of difficulty in some courses. It also allows us to build a graph of questions and courses, which helps us understand the relationship between courses and their pre-requisites, not just by historically contemplating them, but based on data,” Iddo explained, also an adjunct associate professor at Columbia University’s Department of Computer Science.
Additionally, the model automatically explains solutions and rapidly generates new math problems for university-level courses. When the researchers presented these machine-generated questions to university students, the students were unable to distinguish whether the questions were created by a human or an algorithm.
This approach might be used to simplify the creation of course content, which would be particularly beneficial for big residential courses and massive open online courses (MOOCs) with thousands of students. The technology might also be used as an automated tutor that demonstrates to students how to solve basic math problems.
In the past, researchers employed a neural network, such as GPT-3, that was merely pretrained on the text like it was shown millions of examples of text to learn the patterns of natural language. This time, they employed a neural network that was trained on the text and “tuned” on code.
A machine learning model can perform better by using this network, known as Codex, which is effectively an additional pre-training procedure.
The model was exposed to millions of code examples from internet repositories. As the training data for this model contained millions of natural language words and millions of lines of code, it learns the relationships between text and code.
The machine-generated questions were evaluated by showing them to university students. The researchers assigned students 10 problems from each undergraduate math course in random order; five questions were prepared by people and the remaining five were generated by a computer.
Students were unable to discern whether the machine-generated questions were produced by an algorithm or a human, and they scored the difficulty level and course-appropriateness of questions generated by humans and machines similarly.
Researchers emphasised that this effort is not meant to take the place of actual teachers. They claim that although automation has reached 80 per cent accuracy, it will never reach 100 per cent. Every time someone figures something out, someone else will pose a more challenging problem.
Simply this work opens the door for people to begin using machine learning to answer ever-harder questions, and academics are optimistic that it will have a significant impact on higher education.
The team has expanded the work to handle math proofs because of the approach’s effectiveness, although there are several limits they intend to address. Due to computational complexity, the model is currently unable to answer questions with a visual component or resolve computationally intractable issues.
The model is being scaled up to hundreds of courses in addition to these obstacles. They will produce more data with those hundreds of courses, which they may use to improve automation and offer perceptions into course design and curricula.
The Science and Technology Academic and Research-Based Openly Operated Kiosks or STARBOOKS of the Department of Science and Technology (DOST) have arrived on the island of San Miguel in Tabaco, Albay, providing easy access to S&T learning.
STARBOOKS is the country’s first digital science library, created by the Science and Technology Information Institute (DOST-STII). It is a stand-alone information source intended for those who have limited or no access to S&T information resources.
The project’s goal is to provide Science, Technology, and Innovation (ST&I) content to geographically isolated schools and communities across the country. STARBOOKS contains many digitized S&T resources in various formats such as text and video or audio organised in specially designed “pods” with an easy-to-use interface.
STARBOOKS, as SMNHS teacher John Darnell Balbastro put it, is “one way of elevating the scientific and technological literacy” of their students. Its wide range of digitised S&T resources in various formats will “intensify the curiosity among our young learners,” and its offline access will address the lack of S&T learning resources in San Miguel.
Through this programme, DOST Region V, in collaboration with its dedicated Provincial S&T Centres and implementers, will continue to promote and empower S&T knowledge and education.
Meanwhile, Jamaica Pangasinan, Senior Science Research Specialist at the Space Mission Control and Operations Division (SMCOD) of the Philippine Space Agency (PhilSA), said that she was impressed by the level of environmental and social awareness of the incoming senior high school students, which was shown in their work at the “LIFT OFF: PhilSA Space Science Camp 2022.”
She said that the mission goals showed how eager the students were to solve the problems and threats facing the environment right now.
Fourteen science high schools from the 16 divisions of Metro Manila chosen by the Department of Education (DepEd) to attend the camp presented their space missions. Each team had five (5) minutes to talk about their satellite’s mission, its most important technical features, and why it was important.
The students came up with a wide range of missions, from observing Earth to keeping an eye on space junk to sending probes to other planets.
Only two missions were better than the rest. These are the Monitoring Illegal Mining Activities in Remote Areas (MIMA) by Bianca Louise B. Cruz and Oscar A. Araja II of the City of Mandaluyong Science High School, and the Venus Seismic Activity Monitoring Satellite (V-SAMS) by Peter James Lyon and Ysabela Juliana Bernardo of the Caloocan City Science High School.
The students who work on MIMA said that the goal of their satellite mission is to protect the environment and make sure that mining laws and rules are followed better in the country. Based on their plan, MIMA would be a Synthetic Aperture Radar (SAR) satellite that could see through clouds to spot changes in areas where mining could be happening. It would take pictures with the help of optical imagers.
The goal of V-SAMS, on the other hand, would be to learn more about Venus, which is like Earth’s twin, and especially about its earthquakes. To do this, V-SAMS would use infrared imaging to track the surface temperature of Venus’s volcanoes, figure out which ones will erupt, and find other volcanoes that are still active on the planet.
It would also have an interferometric SAR (InSAR) to look for changes on Venus’s surface and signs of earthquakes. V-SAMS would also have an optical payload that would let it take high-resolution pictures.
The National Environment Agency (NEA) and the Singapore Land Authority (SLA) have signed a Memorandum of Understanding (MOU) to develop the use of Global Navigation Satellite System (GNSS) data from SLA’s Singapore Satellite Reference Network (SiReNT) to help NEA better monitor island-wide atmospheric moisture. The goal of the five-year partnership is to help Singapore with weather monitoring by giving it more data and making it easier to do exploratory studies for weather forecasting.
“The collaboration between NEA and SLA highlights our commitment to achieve synergies and tap on enablers across the public sector. This partnership provides a platform for NEA to utilise SLA’s expertise in GNSS data collection and processing, enabling NEA to explore non-traditional methods to enhance our weather monitoring and forecasting capabilities,” says Luke Goh, CEO, NEA.
On the other hand, Colin Low, CEO of SLA, said that SLA’s partnership with NEA is a part of its ongoing efforts to collaborate with parties from the public and commercial sectors to open up new applications for SiReNT and its other geospatial products.
The SLA believed combining the knowledge of multiple parties might lead to more innovation and the discovery of workable solutions that could be advantageous to Singapore and the industries.
Colin continued by saying that they are eager to collaborate with NEA to research the unique uses of SiReNT data for improved weather monitoring and research projects on weather forecasting and climate change. The many experiences that were gathered and shared during this partnership will serve as a foundation for upcoming developments in this area.
The production of accurate weather forecasts, climate monitoring, and timely warnings of dangerous weather events all depend on meteorological measurements. The Meteorological Service Singapore (MSS) routinely gathers a variety of observational data from ground-based and aircraft sensors, such as temperature, wind, and moisture.
To measure these weather components at various altitudes of the atmosphere, sensors linked to a weather balloon are routinely launched twice a day at MSS’ Upper Air Observatory (UAO). To enhance the sounding data from the weather balloon, MSS erected a GNSS reference station at UAO in 2019.
This station will provide continuous estimates of moisture in an atmospheric column known as the integrated precipitable water vapour.
In accordance with the MOU, SiReNT will incorporate MSS’s GNSS station, giving MSS access to continuous, almost real-time atmospheric moisture readings for the entire island. By supplying greater resolution and more frequent observation data, this non-conventional moisture data will complement MSS’s current observation network data and enable research into possible uses for weather forecasting.
The partnership will also help SLA’s SiReNT station network, which now consists of nine reference stations dispersed throughout Singapore, grow. The network will grow to 12 stations with more data receivable with the installation of NEA’s GNSS base receiver station at UAO that will be integrated into SiReNT and two anticipated additional coastal SiReNT reference stations. The SiReNT system can create precise positioning data with an accuracy of up to 3 cm and correct positional inaccuracies in GNSS signals.
The SiReNT technology fosters innovation across a range of sectors, including autonomous driving, logistics and automation in the building industry, and monitoring of changes in Singapore’s land height and sea level.
The addition of stations by the end of 2022 will further increase the stability of the services and applications SiReNT now supports in several important industries. It can also be used in novel ways for scientific research on climate change.
Michael G. Regino, President and CEO of SSS, announced that self-employed, volunteer, non-working spouses, and land-based Overseas Filipino Workers can pay their contributions through the online method of their choice. This was done in cooperation with the different financial and private sectors.
“We encourage our members and employers to pay their contributions using our online channels as through these payment facilities, they no longer must go to our branches. These can be accessed at the safety and convenience of their homes or offices,” says Michael.
Individual members may furthermore use the websites and mobile apps of other SSS-accredited collecting partners, such as most banks in the public and commercial sectors of the nation. However, both commercial and domestic employers have access to online payment methods.
SSS is a publicly funded social insurance programme that the Philippine government requires to provide coverage to all wage earners in the private, public, and unorganised sectors.
The agency is mandated to set up, develop, promote, and perfect a sound, tax-free social security system that fits the needs of everyone in the Philippines. This system should encourage social justice through savings and protect members and their beneficiaries from the risks of disability, illness, maternity, old age, death, and other things that could cause a loss of income or a financial burden.
OpenGov Asia earlier reported that digitalising SSS pension fund services remain one of the top priorities in the Philippines and that more online services will be added to its digital channels.
More than 30 member services and more than 20 employer services are currently easily accessible on the SSS website. Transactions for membership, contributions, loan granting and repayment, and benefit distributions are only a few examples of the services offered. Other SSS internet platforms also extend some of these features.
Further, almost all new online services are made available via the agency’s website, which serves as its main online platform. However, more work is being done to make the services on this portal accessible to smartphone users via the SSS Mobile App.
The agency is slowly making it mandatory for its programme to be done online. Those who don’t have their own way to do business online can use the e-Centres in branches.
In the meantime, the Department of Education (DepEd) worked with the Young Southeast Asian Leaders Initiative (YSEALI) and exchanged alumni to improve education about climate change through an online programme called Climate Changemakers.
The National Educators Academy of the Philippines (NEAP) has recognised Climate Changemakers as the first climate change training course as part of the Department’s Professional Development Priorities.
Through online training and other digital education initiatives, the programme aims to make teachers better able to teach climate change skills, integrate climate change skills, and act on climate change in the country.
The ten-week online course, which used synchronous and asynchronous modalities to address common misconceptions about climate change, was successfully completed by 400 instructors. Additionally, it gave teachers a place to consider their own learning, exchange difficulties and effective methods.
The Young Southeast Asian Leaders Initiative Professional Fellows Program (YSEALI PFP) is a two-way exchange programme run by the U.S. Department of State. Its goal is to help young leaders from different countries in Asia and the United States to get to know each other better and strengthen economic relationships.
Data is information that has been organised in a way that makes it simple to move or process. It is a piece of information that has been converted into binary digital form for computers and modern methods of information transmission.
Connected data, on the other hand, is a method of displaying, using, and preserving relationships between data elements. Graph technology aids in uncovering links in data that conventional approaches are unable to uncover or analyse.
Different sectors have invested in big data technologies because of the promise of valuable business insights. As a result, various industries express a need for connected data, particularly when it comes to connecting people such as employees or customers to products, business processes and other Internet-enabled devices (IoT).
In an exclusive interview with Mohit Sagar, CEO and Editor-in-Chief of OpenGov Asia, Chandra Rangan, Chief Marketing Officer of Neo4j shared his knowledge on how a connected data strategy becomes of paramount importance in building a smart nation.
Connected data enables businesses
A great example of the power of graph technology, and a very common use case for Neo4j, is its use in the financial sector to uncover fraud. Finding fraud is all about trying to make connections and understand relationships, Chandra elaborates. A graph-based system could detect if fraud is taking place in one location and determine if the same scenario has occurred in other locations.
“How does one make sense of this? Essentially, you are traversing a network of interconnected data using the relationships between that data. Then you begin to see patterns develop and these patterns provide you with answers so that you can conclude whether there is fraud.”
What is of great concern is that fraud is occurring with much greater frequency and with a higher success rate nowadays. The key to stopping and mitigating the impact is time. Instead of detecting a fraud that occurred hours or days ago,
“What if the organisation could detect it almost immediately and in real-time as it occurs?” asks Chandra. “Graph offers this kind of response and is why it’s a great example of value!”
Supply chain and management are other excellent examples of RoI. One of Neo4j’s clients, which operates arguably the largest rail network in the United States and North America created a digital twin of the entire rail network and all the goods. With graph technology across their network, they can now do all kinds of interesting optimisation much faster, leading to better, more efficient outcomes for their entire system.
The pandemic has taught the world about the value and fragility of supply chains. Systems across the globe are being reimagined as the world’s economy realise the need to become more digital and strategic. More supply sources, data, data sharing, customer demands, and increased complexity necessitate modern, purpose-built solutions.
Apart from all the new expectations and requirements for modern supply chains, systems need to and are becoming more interconnected because of new technologies.
Maintaining consistent profitability is difficult for firms with a high proportion of assets. Executives must oversee intricate worldwide supply chains, extensive asset inventories and field operations that dispatch workers to dangerous or inaccessible places.
With this, organisations need a platform that connects their workforces and makes them more capable, productive and efficient. A platform that provides enterprises with real-time visibility and connectivity, while also assuring efficiency, safety, and compliance.
Modern technologies are required to improve interconnectivity, maximise the value of data, automate essential procedures, and optimise the organisation’s most vital workflows.
Modern data applications require a connected platform
“When we programme, when we create applications, we think in what we are calling a graph. This is the most intuitive approach that you can have,” says Chandra.
Any application development begins with understanding the types of questions people want to solve and then mapping it to a wide range of outcomes that they want to achieve. These are typically mapped in what is known as an entity relationship diagram.
Individuals’ increased reliance on systems that work in a way that makes sense to them and supports them has increased criticality. And frequently, when these systems fail, Neo4j makes sense of complexity and simplifies what needs to be done, resulting in a significant acceleration.
As the world becomes more collaborative, integrated, and networked, nations must respond more quickly to changes in their business environment brought on by the digital era; otherwise, they risk falling behind or entering survival mode.
The proliferation of new technologies, platforms, and devices, as well as the evolving nature of work, are compelling businesses to recognise the significance of leveraging the most recent technology to achieve greater operational efficiencies and business agility.
A graph platform connects individuals to what they require, and when and when they require it. It augments their existing process by facilitating the effective recording and management of personnel data. Neo4j Graph Data Science assists data scientists in finding connections in huge data to resolve important business issues and enhance predictions.
Businesses employ insights from graph data science to discover activities that point to fraud, find entities or people who are similar, enhance customer happiness through improved suggestions, and streamline supply chains. The dedicated workspace combines intake, analysis, and management for simple model improvement without workflow reconstruction.
As a result, people are more engaged, productive, and efficient with connected data. Nations can bridge information and communication gaps between executive teams, field technicians, plant operators, warehouse operators and maintenance engineers. Increasing agility and productivity offers obvious commercial benefits.
In short, organisations easily integrate their whole industrial workforce to increase operational excellence and decrease plant downtime, hence maximising revenues. This methodology is based on a collaborative platform direction.
Contextualising data increases its value
According to Chandra, data is a representation of the world in which people live, and people use data to represent this world. As a result, the world is becoming more connected, and people no longer live in silos and continue to be associated in society.
“If you think about data as the representation of the world that we live in, it is connected data and we can deal with all the complexities that we need to deal with when we try to make sense out of it,” explains Chandra.
Closer to home, connected data is crucial to Singapore’s development as a smart nation. “Connected data is at the centre of each of those conversations around developing the nation. When you think of Singapore as a connected ecosystem and when you think about citizens, services, logistics, contract tracing, and supply chain.”
Chandra believes that the attributes have saved the connection between data and people, which is why connections are important. Once people understand those connections, it becomes much easier and much faster to derive the insights that are required.
Without connected data, organisations lack key information needed to gain a deeper understanding of their customers, build a complete network topology, deliver relevant recommendations in real-time, or gain the visibility needed to prevent fraud.
Thus, “knowing your customer is understanding connected data.” With the right tools, data may be a real-time, demand-driven asset that a financial institution can utilise to reinvent ineffective processes and procedures and change how it interacts with and comprehends its consumers.
“Me as a person – who I am, my name, where I live – these are all properties of who I am. But what really makes me me, are the relationships I have built over time. And so, the notion that almost every problem has data that you can really make sense of with graphs is the larger “Aha” moment,” Chandra ends.
Legacy systems are still in use pieces of hardware or software that are out of date. These systems frequently have problems and are incompatible with more modern ones. Although they can be used in the manner intended by their creators, they cannot be improved.
It is the backbone of many excellent organisations, since they utilise software, apps, and IT solutions that are crucial to the general operation of the business but are obsolete and, in some cases, no longer supported by the original software vendor or developer.
While running legacy systems may not appear to be a big deal, they do present a unique set of challenges and potential issues that organisations would be remiss to ignore.
Thus, obsolete legacy systems are at best a nuisance and, at worst, can undermine an organisation’s entire IT security strategy, severely impeding productivity. Furthermore, the longer a company waits to modernise a legacy system, the more difficult the transition becomes.
However, system modernisation is always a prerequisite for digital transformation. Most firms will be unable to fully grasp the benefits of new technologies and solutions without it.
Due to the rapid development of technology, businesses must maintain compatibility with legacy systems that impede the implementation of contemporary technologies.
With this, the Centre for Strategic Infocomm Technologies (CSIT) employs technology to facilitate and advance Singapore’s national security. Due to the environment’s highly secret nature, it must be air-gapped.
This means that development and deployment are conducted in networks that are not connected to the internet. Consequently, all platforms had to be installed on-premises.
Despite not being able to utilise internet-connected services, CSIT has a Cloud Infrastructure and Services section that offers developers the necessary infrastructure to concentrate on software development.
Further, a monolith system is a big application consisting of code built by several developers over many years. Frequently, the code is inadequately maintained. Some of these developers may have left the development team or the organisation, leaving knowledge gaps.
Due to a lack of expertise and the difficulty of modifying a system that is constantly in use in production, refactoring the code is comparable to replacing the tyres on a moving car.
Having a legacy system result in greater maintenance and support costs and decreased efficiency. Since the monolith system was still essential, CSIT opted to adopt a more manageable strategy by decomposing it into smaller services using the microservices methodology.
Microservices, on the other hand, are software programmes that execute a business function as part of a larger system yet are separate services. These services are intended to be lightweight and straightforward to implement.
Microservices have the following advantages: each service is independently scalable; services have smaller code bases that make them easier to maintain and test; and problems are isolated to a single service, allowing for faster troubleshooting.
In addition, there are two main microservice architectures to consider when implementing the microservices approach. Each has advantages and disadvantages that correspond to specific use cases as Orchestration, as the name suggests, necessitates an orchestrator actively controlling the work of each service, whereas Choreography takes a less stringent method by allowing each service to carry out its work freely.
Microservices architecture may not be appropriate for all projects and choosing an architecture should be based on the needs of the project; therefore, CSIT advised to expect new problems to arise and be prepared to adapt to them.
A partner company of Hong Kong Science and Technology Parks Corporation (HKSTP) that specialises in end-to-end artificial intelligence (AI)-driven drug discovery, announced that the company’s Hong Kong team has identified multiple potential therapeutic targets for the fatal and incurable amyotrophic lateral sclerosis (ALS), using its proprietary biology AI platform, PandaOmics™. The research was in collaboration with Answer ALS, the largest and most comprehensive ALS research project ever. The findings were published in the June 28 issue of Frontiers in Aging Neuroscience.
The team of researchers leveraged massive datasets to find genes relevant to disease, which could serve as potential targets for new therapeutics. The target discovery engine helped analyse the expression profiles of central nervous system (CNS) samples from public datasets, and direct iPSC-derived motor neurons (diMN) from Answer ALS.
The study resulted in the identification of 17 high-confidence and 11 novel therapeutic targets from CNS and diMN samples. These targets were further validated in the c9ALS Drosophila model, mimicking the most common genetic cause of ALS, of which 18 targets (64%) have been validated to have functional correlations to ALS. Notably, eight unreported genes, including KCNB2, KCNS3, ADRA2B, NR3C1, P2RY14, PPP3CB, PTPRC, and RARA, strongly rescued neurodegeneration through their suppression. All the potential therapeutic targets were disclosed in the paper and at ALS.AI.
The Director, Robert Packard Center for ALS Research and Answer ALS stated that he is excited to see the Answer ALS data being used to identify possible ALS disease-causing pathways and candidate drugs. The work done by the HKSTP partner company is how this unprecedented program was envisioned to help change the course of ALS.
A Professor at Tsinghua University and Founder of 4B Technologies stated that from AI-powered target discovery based on massive datasets to biological validation by multiple model systems (fly, mouse, human iPS cells), to rapid clinical testing through investigator-initiated trials (IIT), this represents a new trend that may dramatically reduce the costs and duration and more importantly the success rate of developing medicines, especially for neurodegenerative diseases.
The Co-CEO and CSO of an end-to-end AI-driven drug discovery firm stated that this demonstrates the power of their biology AI platform, PandaOmics, in target discovery. It is impressive that around 70% of targets identified by AI were validated in a preclinical animal model.
The team is now working with collaborators to progress some targets toward clinical trials for ALS, while also further expanding the utilisation of the drug discovery engine to identify new targets for other disease areas including oncology, immunology, and fibrosis.
The Head of the Institute for Translational Research at HKSTP noted, “We are thrilled to witness Insilico Medicine Hong Kong team’s breakthrough in the application of AI-powered drug discovery and development in ALS.”
The global study led by multidisciplinary experts in ALS and AI has revealed new aspects of our understanding of the disease and opens a new window of opportunities for developing potentially new treatment options, demonstrating the importance of a collaborative approach and the potential of AI with deep insights in addressing clinical unmet needs, she said.
She added that HKSTP will continue to build a thriving I&T ecosystem for accelerating and commercialising innovative solutions and nurturing local and global I&T talent.
The HKSTP partner firm has been conducting research on ALS target discovery and drug repurposing with other interested parties using PandaOmics™ since 2016. This study further validates the drug discovery engine as an AI tool capable of identifying therapeutic targets with potential roles in ALS neurodegeneration and creating new avenues for drug discovery and a better understanding of this rare and fatal neuromuscular disease.