ASIA News

The latest upgrade makes it easier for people to control who sees and accesses their health information.  

On March 9, the Innovation and Technology Commission (ITC) in Hong Kong launched a special call under the Public Sector Trial Scheme for projects to support product development and application of technologies for the prevention and control of COVID-19.  WHAT’S IT ABOUT The special round aims to fund trials of R&D outcomes in the local public sector relating to detection, diagnosis or surveillance of the COVID-19 virus, or reduction of the risks of infection and its spread. According to its official release, the R&D outcomes should be immediately ready for trials by government departments or the relevant public organizations to bring about benefits for the community in fighting the epidemic in the near future. The target funding recipients are local R&D centers, universities and other designated public research institutes, as well as all technology companies conducting R&D activities in Hong Kong. The funding ceiling for each project is HKD $2M in general, and a higher ceiling for individual projects may be considered if necessary and justified. Applications will be accepted from now until April 10, and more details are available here.  THE LARGER TREND Last week, Singapore-born, Boston-based digital therapeutics startup Biofourmis announced that its technology is being utilized in a remote monitoring and disease surveillance program in Hong Kong involving patients with diagnosed or suspect cases of COVID-19. The program is being administered by the University of Hong Kong.  Elsewhere in APAC, governments or public agencies are collaborating with healthtech startups to tackle the management and/or diagnosis of COVID-19. Singapore’s national HIT agency, IHiS, has worked with local healthcare AI startup Kronikare to pilot iThermo – an AI-powered temperature screening solution that screens and identifies those having or showing symptoms of fever, HealthcareITNews reported. Singapore-based Veredus Laboratories worked with the Home Team Science and Technology Agency (HTX), a statutory board under the Ministry of Home Affairs, to develop its VereCoV Detection Kit, a portable Lab-on-Chip application capable of detecting the 2019 Novel Coronavirus (COVID-19) in a single test, according to MobiHealthNews report. ON THE RECORD “The aim of the call is not only to promote the realization and commercialization of local R&D outcomes, but also to encourage the public sector to use technologies for tackling the COVID-19 epidemic in Hong Kong, thereby bearing dual significance,” said an ITC spokesman in a statement. 

iThermo reduces the need for manual temperature screening, and provides prompts where secondary checks can be carried out for feverish persons identified by the solution.

A new study, conducted by Korean academic hospitals and Lunit, a medical AI company specializing in developing AI solutions for radiology and oncology, demonstrated the benefits of AI-aided breast cancer detection from mammography images. The study was published online on 6 February 2020, in Lancet Digital Health and features large-scale data of over 170,000 mammogram examinations from five institutions across South Korea, USA, and the UK, consisting of Asian and Caucasian female breast images. TOP FINDINGS One of the major findings showed that AI, in comparison to the radiologists, displayed better sensitivity in detecting cancer with mass (90% vs 78%) and distortion or asymmetry (90% vs 50%). The AI was better in the detection of T1 cancers, which is categorized as early-stage invasive cancer. AI detected 91% of T1 cancers and 87% of node-negative cancers, whereas the radiologist reader group detected 74% for both. Another finding was a significant improvement in the performance of radiologists, before and after using AI. According to the study, the AI alone showed 88.8% sensitivity in breast cancer detection, whereas radiologists alone showed 75.3%. When radiologists were aided by AI, the accuracy increased by 9.5% to 84.8%. An important factor in diagnosing mammograms is breast density and dense breast tissues, mostly from the Asian population, make it harder to interpret as dense tissue is more likely to mask cancers in mammograms. According to the study’s findings, the diagnostic performance of AI was less affected by breast density, whereas radiologists' performance was prone to density, showing higher sensitivity for fatty breasts at 79.2% compared to dense breasts at 73.8%. When aided by AI, the radiologists’ sensitivity when interpreting dense breasts increased by 11%. THE LARGER TREND Findings from a study published in Nature indicated that Google’s AI model spotted breast cancer in de-identified screening mammograms with greater accuracy, with fewer false positives and false negatives than experts, HealthCareITNews reported. Lunit recently raised a $26M Series C funding from Korean and Chinese investors, which the company said was its biggest funding round, according to a DealStreetAsia report in January.  ON THE RECORD “It is an unprecedented quantity of data with accurate ground truth--especially the 36,000 cancer cases, which is seven times larger than the usual number of datasets from resembling studies conducted previously,” said Hyo-Eun Kim, the first author of the study and Chief Product Officer at Lunit.  Prof. Eun-Kyung Kim, the corresponding author of the study and a breast radiologist at Yonsei University Severance Hospital, said: “One of the biggest problems in detecting malignant lesions from mammography images is that to reduce false negatives—missed cases—radiologists tend to increase recalls, casting a wider safety net, which brings an increased number of unnecessary biopsies.” “It requires extensive experience to correctly interpret breast images, and our study showed that AI can help find more breast cancer with lesser recalls, also detecting cancers in its early stage of development.” 

Japanese giant Sumitomo Dainippon Pharma and Oxford-headquartered AI-driven drug discovery company Exscientia yesterday announced that they have created a new compound which is in the process of entering human clinical trials in Japan. This is the first time a new precision engineered drug generated by AI is entering Phase 1 human clinical trials. The trial aims to measure the efficacy of the drug for patients with obsessive-compulsive disorder (OCD).  WHY IT MATTERS According to Exscientia, developing a single drug is around $1.75B and discovery makes up a third of that cost. This entire project was five times faster than typical discovery – it took 12 months, vs. the typical five years, with the candidate compound found within 350 synthesized compounds vs. the typical 2500 compounds.  WHAT HAPPENED The drug, which is named DSP-1181, was created through the joint research by Sumitomo Dainippon Pharma and Exscientia. The former provided its experience and knowledge in monoamine GPCR drug discovery and the latter applied its Centaur Chemist AI platform for drug discovery. THE LARGER TREND MIT's School of Engineering and Takeda Pharmaceuticals Company are also working together to drive innovation and application of AI applications for healthcare and drug development, HealthcareITNews recently reported. Last December, French AI startup Iktos and skin-health focused pharmaceutical company Almirall announced a research collaboration in AI for new drug design.  ON THE RECORD "We are very excited with the results of the joint research that resulted in the development of candidate compounds in a very short time. Exscientia's sophisticated AI drug discovery technologies combined with our company’s deep experience in monoamine GPCR drug discovery, allowed us to work synergistically, delivering a highly successful outcome. We will continue to work hard to make this clinical study a success so that it may deliver new benefits to patients as soon as possible," said Toru Kimura, Board of Directors, Senior Executive Officer and Senior Executive Research Director of Sumitomo Dainippon Pharma in a statement.  Andrew Hopkins, CEO of Exscientia, said: "We believe that this entry of DSP-1181, created using AI, into clinical studies is a key milestone in drug discovery. This project’s rapid success was through strong alignment of the integrated knowledge and experiences in chemistry and pharmacology on monoamine GPCR drug discovery at Sumitomo Dainippon Pharma with our AI technologies. We are proud that our AI drug discovery platform Centaur Chemist has contributed to generate DSP-1181 and look forward to its progression as a treatment for obsessive-compulsive disorder."

These services include digital diagnostic pathology, access to proton therapy information, teaching surgery, an AI-enabled care for in-patients and an autonomous robot for operating rooms.

Better health information systems that allow every Thai to access their personal health information, including diabetes risk and screening records, could contribute to reducing unmet need.

“This is a big step forward in personalizing cancer treatment and ensuring better patient outcomes,” said Professor Lim Chwee Teck, Mechanobiology Institute, NUS Biomedical Engineering.

“Our goal is to make all of a patient’s health record available in our clinical portal so that when a clinician brings up a patient’s record, they can have all the information they need,” said S. Wissmann, director of information management, Mater.

The new SERI-NTU Advanced Ocular Engineering (STANCE) Laboratory is a collaboration between NTU, SNEC and SERI.