Thailand LAB INTERNATIONAL 2025: A global hub for science and innovation
Thailand LAB INTERNATIONAL 2025 returns as Asia’s leading platform for the scientific, laboratory, and analytical industries. This year, the event broadens its scope, bringing together global innovators, thought leaders, and cutting-edge technologies. From breakthroughs in life sciences to the latest analytical instruments, the event continues to be a hub for collaboration and knowledge exchange.
In a strategic move to strengthen its international presence, Bio Asia Pacifi c - held in Bangkok since 2020 - has rebranded as BioAP INTERNATIONAL. This transformation refl ects its commitment to serving the rapidly evolving life sciences and biotechnology sectors beyond the Asia Pacifi c region, embracing a truly global vision.
The shift to BioAP INTERNATIONAL is part of an ongoing effort to
connect industry leaders, researchers, and innovators worldwide. By expanding its network, the event aims to foster collaboration, accelerate innovation, and drive growth across the life sciences and biotechnology sectors. This rebranding underscores its mission to bridge continents, facilitating the exchange of ideas and solutions at the forefront of scientifi c advancement.
Attendees can expect a world-class exhibition featuring high-impact conferences, live demonstrations, and unparalleled networking opportunities. Thailand LAB INTERNATIONAL 2025 is more than an event - it’s where the future of science takes shape. Join in and be part of Asia’s most dynamic laboratory community.
Save the date: 3–5 September 2025, BITEC, Bangkok, Thailand. More information online:
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Strategic partnership to expand OOC solutions distribution in Japan
Machine learning enhances polymer production efficiency
Machine learning is helping optimise polymer manufacturing by reducing the reliance on expensive and time-consuming experimentation. Polymers, such as plastics, are essential in a wide range of applications, from packaging and automotive to medical devices and optic fi bres. Their properties are determined by their monomers - the chemical building blocks that form a polymer. However, controlling the chemical behaviour of monomers during production is a complex challenge.
A team led by Professor Mikiya Fujii at Japan’s Nara Institute of Science and Technology has demonstrated the potential of machine learning to optimise this process. Using mathematical modelling, the researchers were able to streamline the polymerisation process and identify optimal manufacturing conditions. Their fi ndings were published in Science and
Ryosuke Ogihara, CEO/President, Primetech Corporation.
Dr Paul Brooks, CEO, CN Bio. Corporation.
CN Bio, a leading provider of Organ-on-a-Chip (OOC) systems designed to enhance drug discovery and development workfl ows, has announced a strategic partnership with Primetech Corporation, a Japanese distributor of life sciences research equipment. This agreement establishes a direct distribution channel for CN Bio’s OOC solutions in Japan, providing customers with localised support and technical expertise.
Driven by shifting global regulations and an increasing push for new approach methodologies (NAMs), the demand for OOC solutions in Japan is accelerating. The country’s OOC market is forecast to reach $28.2 million by 2030, growing at a compound annual growth rate (CAGR) of 30.7%. Pharmaceutical and biotech companies are increasingly adopting OOC technologies to improve preclinical drug development, which reduces failure rates and accelerates the discovery of new therapeutics. The partnership with Primetech will allow CN Bio to meet the growing market demand by expanding its reach within the Asia-Pacifi c region.
CN Bio’s PhysioMimix® OOC systems accurately replicate human physiology in the lab, providing more reliable predictions of drug responses. These advanced in vitro models help reduce reliance on animal testing while offering critical insights into drug bioavailability, toxicology, and disease modelling. With these systems, researchers can better assess the effi cacy and safety of drug candidates early in the development process, minimising costly late-stage failures.
Ryosuke Ogihara, CEO of Primetech Corporation, commented: “We are excited to begin our partnership with CN Bio to offer their innovative
microphysiological systems and reagents.
These cutting-edge solutions have the potential to signifi cantly accelerate the drug discovery process, and we are confi dent they will drive research effi ciency and success for our customers.”
Dr Paul Brooks, CEO of CN Bio, added: “Partnering with Primetech is a key step in our global growth strategy. It allows us to expand our distribution network in Japan, providing direct support and addressing the increasing demand for our OOC solutions. This agreement underscores our commitment to delivering world-class OOC technologies and transforming drug discovery globally.”
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Technology of Advanced Materials: Methods.
To train the machine learning model, the team developed a polymerisation process that quickly generated experimental data. They focused on producing a styrene-methyl methacrylate co-polymer, synthesised by mixing the monomers in a solvent with an initiator and heating the mixture in a water bath.
The researchers employed fl ow synthesis, a technique that mixes and heats solutions in a continuous fl ow. This method offers better mixing, effi cient heating, and precise control of variables like heating time and fl ow rate, making it ideal for data collection.
The machine learning model analysed fi ve critical variables: initiator concentration, solvent-to-monomer ratio, styrene proportion, reaction temperature, and time in the water bath. The goal was to achieve a fi nal product with 50% styrene content.
Surprisingly, the model required only fi ve calculation cycles to determine optimal conditions, which included a lower reaction temperature, extended time in the water bath, and reduced monomer concentration in the solvent. The researchers were particularly intrigued by the impact of solvent concentration, which proved as signifi cant as monomer proportions.
“Our results demonstrate that machine learning not only can explicitly reveal what humans may have implicitly taken for granted but can also provide new insights that weren’t recognized before,” Professor Mikiya Fujii said. “The use of machine learning in chemistry could open the door for smarter, greener manufacturing processes with reduced waste and energy consumption.”
More information online:
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The flow synthesis reactor with two bottles containing a monomer, initiator and solvent mixed using a micromixer. The synthesis is controlled with AI-based design of experimental conditions such as the temperature and a flow rate. Credit: Nara Institute of Science and Technology
The research was published in Science and Technology of Advanced Materials (STAM)
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Collaboration targets multi-specific biologics for solid tumour treatment
BioMed X, an independent biomedical research institute based in Heidelberg, Germany, has announced a new collaboration with Daiichi Sankyo, a global pharmaceutical company headquartered in Japan. This partnership aims to drive the development of bi- and multi-specifi c biologics for innovative cancer therapies targeting solid tumours.
The collaboration, titled New Strategies for Targeting Solid Tumors with Multi-Specifi c Biologics (MTT), will take place at BioMed X’s Heidelberg facility. The project is focused on developing next- generation biologics, such as bi- and tri-specifi c antibodies, that can target multiple sites within the tumour microenvironment. These therapies aim to overcome the limitations of traditional treatments by leveraging synergistic effects of different antitumor signalling pathways and mechanisms.
The MTT initiative will address key research challenges, including Developing novel therapeutic concepts for bi- and multi-specifi c biologics targeting new extracellular or intracellular combinations for solid tumours; Identifying and validating promising target combinations through in vitro and in vivo research; Creating advanced in vitro assay systems to assess the functionality of new target combinations.
As part of this collaboration, BioMed X and Daiichi Sankyo are calling
for research proposals from global scientists to contribute to this groundbreaking project. Researchers are encouraged to submit original proposals, particularly those with preliminary experimental data or utilizing cutting-edge machine learning tools. The project invites proposals focused on solid tumour indications, but excludes classical immune cell engagers, combination therapies, and modalities outside peptides or proteins, such as small molecules, nucleic acids, or gene therapies.
The selected research group will join seven other teams at BioMed X’s Heidelberg Institute, collaborating in a dynamic environment aimed at advancing cancer therapy. Interested researchers can submit their proposals through the BioMed X Career Space by 9 March 2025.
Christian Tidona, Founder and Managing Director of BioMed X, stated: “Partnering with Daiichi Sankyo on this project allows us to expand our oncology research and focus on next-generation biologics that could transform cancer treatment. This collaboration is a testament to our commitment to pioneering innovative therapeutic approaches.”
More information online:
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