Seoul National University

A consortium led by South Korea's top universities, Yonsei University and Seoul National University, will embark on a national project promoting the early detection of autism spectrum disorder in the country. Backed by the National Center for Mental Health and the Ministry of Health and Welfare, the project received 9.2 billion won ($6.6 million) in government funding. According to a media release, the project aims to develop AI-powered digital and medical devices for screening autism, which are targeted for release by 2028. The devices will be run by algorithms based on data from a cohort of 1,200 infants and toddlers below 48 months. Additionally, applications for an innovative medical device designation from the Ministry of Food and Drug Safety will be pursued. WHY IT MATTERS A recent article noted an overall increase in cases of ASD among Korean children and adolescents from 2011 to 2021. It has been estimated that the prevalence of DSM-5-defined ASD is at 2.20% . This trend may necessitate calibrating strategies to enable timelier and more effective prevention and care of children with autism. However, current approaches in ASD diagnosis, according to the Yonsei-SNU-led consortium, are largely dependent on specialists' findings and subjective observations of guardians, which often render them inconsistent and short of objectivity. "The AI-based [ASD] screening assistive medical device to be developed through this project will be an opportunity to shift the paradigm of early autism diagnosis and treatment," explained Chun Geun-ah, professor at Yonsei University Severance Hospital and principal project investigator. "The consortium will establish a foundation to overcome the limitations of diagnosing [ASD] and lead to better treatment outcomes," Kim Boong-nyeon, SNU Hospital (SNUH) professor and co-principal investigator, also said. The consortium involves several major hospitals, such as Yonsei's Gangnam Severance Hospital, Ewha Womans University Hospital in Seoul and Mokdong, and Seoul St. Mary’s Hospital, and digital health companies, including HurayPositive and Adotcure. THE LARGER TREND In 2023, SNUH opened a living laboratory to collect data that will be used to develop algorithm-driven models for detecting and personalising the treatment of ASD. The lab, also supported by the NCMH, serves as a bedrock for new digital therapeutics and the discovery of autism biomarkers. AI has seen increasing applications in ASD screening and treatment. EarliTec Diagnostics in the United States is a major developer in this space. It received regulatory approval for its autism decision support tool in 2022. Meanwhile, in Japan, new research utilised eye-tracking technology to demonstrate how predictable movement stimuli can be potentially used as a behavioural marker for autism .

The use of biologics is rapidly increasing as new drugs are approved for label expansions. Monoclonal antibodies, multispecific antibodies, and antibody-drug conjugates (ADCs) are being implemented in an array of fields, including oncology, immunology, and neurology. As clinical demand for biologics increases, biopharmaceutical companies must ensure that they have the manufacturing capacity available to produce enough biologics. Creating adequate capacity for any therapeutic can be challenging, and the specialized technologies for manufacturing complex biologics require flexibility and agility in production processes. I will discuss how contract development and manufacturing organizations (CDMOs) ensure that biopharmaceutical companies have a partner with the speed, flexibility, and expertise necessary for successful drug development and manufacturing. Challenges of in-house capacity Fortune Business Insights estimates the global value for next generation biomanufacturing will be close to $40 billion by 2033. As the industry prepares for a period of growth, there is a desire to increase productivity and efficiency in biologics manufacturing. But as the biologics become more complicated, maintaining or increasing production efficiency becomes more difficult. Each class of biologics brings its own challenges, ranging from supply chain logistics to complex chemistry that must be consistent between batches. presented by Sponsored Post How PDPM Optimization Improves Facility Financial Performance Transitioning to PDPM models significantly shifted the healthcare industry. By replacing the RUG system, healthcare providers cut waste and more accurately reflect the care each patient received. By Medrina Additionally, new manufacturing facilities take time and money to build. The Pharmaceutical Research and Manufacturers of America (PhRMA) calculates that it typically costs $2 billion and five to ten years to finish constructing, staffing, and certifying a new manufacturing facility. If companies opt for in-house manufacturing, these extended construction times require biopharmaceutical companies to begin building plants while clinical trials for promising therapies are underway. With the success rate of phase III clinical trials averaging roughly 55 percent, in-house manufacturing can be a gamble. Furthermore, biopharmaceutical companies must also contend with the potential introduction of a competitor therapy, changes in regulatory guidelines, and shifts in geopolitics, which can all contribute to deviations from the predicted demand for a biologic. Unfortunately, due to the unique and modality-specific technologies required to produce advanced therapies, repurposing facilities to develop another therapy is not always feasible. The difficulty of repurposing plants could leave companies with an expensive and underutilized facility, one that runs the risk of being divested later down the line. Contract developers and manufacturers: necessary and beneficial partnerships CDMOs are a solution to these obstacles. Contract developers and manufacturers are specialized partners that ensure production capacity exists for the biopharmaceutical companies developing life-saving therapies. By focusing on high-quality and reliable manufacturing of biologics, CDMO partnerships allow the industry to pool the necessary risks of biopharmaceutical manufacturing. But CDMOs are not all created equal, and biopharmaceutical companies should carefully consider their options. presented by Sponsored Post Top-Rated Practice Management Solutions for Med Spas Every wellness clinic is only as successful as the capabilities of its software. Here's where you can find the top-rated practice management solutions for med spas. By PatientNow One of the biggest benefits a CDMO partnership can offer is speed in facility construction. The best CDMOs should be able to bring construction times for building high-tech manufacturing plants down to as low as two years (compared to the five-to ten-year industry average). While two-year construction times are only found among top-tier CDMOs, having industry-leading speed available is a massive boon, improving manufacturing capacity and responsiveness. By partnering with agile CDMOs, biopharmaceutical companies can feel confident that they will always have the capacity to meet patient demand, address drug shortages, and respond to dynamic markets. Flexibility within both the facilities and the broader organization is another defining characteristic of a high-value CDMO. As a specialized development and manufacturing partner, CDMOs adapt to changing demands in a way that in-house operations may not. The best CDMOs will design plants that allow for efficient manufacturing across a range of molecules, including complex and emerging therapies such as ADCs. Furthermore, CDMOs should be prepared to seamlessly transition between different products as market demand changes. Flexible facilities and comprehensive capabilities make for a strong partner to biopharmaceutical companies seeking efficient and adaptable development and manufacturing services. Of course, speed and flexibility must not be achieved at the expense of quality. Meeting or exceeding regulatory standards and maintaining high-quality production across batches are foundational for every CDMO. But operational excellence will be found in companies whose dedication to quality extends beyond the facility floor. CDMOs need skilled teams capable of handling not only facility construction and validation, but also vendor management, tech transfers, strong client communication, and more. CDMO partnerships should therefore be assessed both on the output quality of their plants and their ability to deliver high-quality results across the entire company. Expanding future capacity starts today Investing in the development and commercial manufacturing of a new therapy will carry some degree of risk. But the right CDMO will manage the risk. As the industry continues expanding the availability and efficacy of biologic treatments, the need for strong CDMO partnerships will continue to increase. The complex chemistry and specialized technologies involved in biologics production are arguably becoming more difficult to create in-house. But it is never too late, or too early, to start engaging with a CDMO partner to enhance the speed and flexibility of your biologics development and manufacturing. Jack ChoiJack Choi is the founder and CEO of Anatomage Inc., based in California. Anatomage is a digital healthcare platform that specializes in bringing accurate medical solutions to healthcare providers and inspiring the next generation of health professionals across the globe. Choi is also as a research scientist at the Precision Machinery Design Center in Seoul University and adjunct professor at the Industrial Engineering Department of Dongkuk University. Choi earned a B.S. in mechanical engineering from Seoul National University and an M.S. in mechanical engineering and Ph.D., Engineering from Carnegie Mellon UniversityThis post appears through the MedCity Influencers program. Anyone can publish their perspective on business and innovation in healthcare on MedCity News through MedCity Influencers. Click here to find out how.

Neo-1 is the first model to unify de novo molecular generation and atomic-level structure prediction in a single model, by generating latent representations of whole molecules instead of predicting atomic coordinates Neo-1 is generalizable across structural and sequence inputs, including partial inputs, and allows for arbitrary constraints with real-world empirical data, significantly reducing the search space needed to identify small molecule drug candidates, and thus dramatically improving the empirical value of computational drug discovery Optimized together with NVIDIA, Neo-1 enables design for high-value mechanisms of action, including molecular glues and other proximity-based therapeutics, directly addressing one of pharma’s biggest discovery bottlenecks, and is already in use across three large pharma and biotech partnerships with VantAI NEW YORK--(BUSINESS WIRE)--VantAI today unveiled Neo-1, the world’s most advanced atomistic foundation model and the first to unify de novo molecular generation with multimodal structure prediction, at NVIDIA GTC 2025. Neo-1 is a breakthrough model that enables all-atom de novo design across biomolecular space in addition to remarkable multimodal structure prediction capabilities Neo-1 is designed to make the systematic re-wiring of protein interactions possible, enabling drug developers to precision-engineer novel therapeutics, including molecular glues, bifunctional degraders, and other proximity-based modalities. For an expanded technical preview, click here. “Our vision is to make protein interactions programmable,” said Luca Naef, Co-Founder & CTO of VantAI who led the development of Neo-1. “This is only possible if we can precision-design the structure of novel biomolecules, including drug-like small molecules. Existing models allow us to decode the structures of molecules, but to make new medicines we need to be able to design them. Neo-1, for the first time, allows for this in a single unified model.” Neo-1 represents a novel approach for the field. While prior all-atom structure foundation models merely predict atomic coordinates, Neo-1 generates latent representations of molecules which can then be decoded into their three-dimensional structure. This methodology enables Neo-1 not only to predict the structure of protein-small molecule complexes to generate entirely new molecules tailor made to a given pocket. As a result, Neo-1 unlocks new opportunities in drug design, including for novel molecular glues and other emerging proximity modulation therapeutics—modalities in which VantAI is leading innovation. Critical advances underlying Neo-1 include: Multimodal inputs — accepts any combination of (partial) sequence, (partial) structure, and experimental data, such as NeoLink-derived restraints or almost any real-world empirical constraint Unified de novo molecule generation and structure prediction — enables atomic-resolution design and reconstruction of protein interfaces, critical for challenging mechanisms of action (MOAs) like molecular glues Massive-scale training — among the largest diffusion-based models in biology, trained on structural and synthetic datasets using hundreds of NVIDIA H100 GPUs Custom datasets and tools — incorporates PINDER & PLINDER (co-developed with NVIDIA) and synthetic data created using GPU-mmseqs2, a tool developed by NVIDIA and SNU, now planning on deploying it via NVIDIA’s recently announced MSA-Search NIM In particular, Neo-1 has been trained using VantAI’s proprietary NeoLink dataset. This access to a vast new type of data and broad programmability has yielded a model that is highly performative, enabling precise molecular design and reconstruction of protein interface structures at atomic resolution, joint capabilities that are critical for unlocking de novo design of challenging MOAs such as molecular glues. VantAI has leveraged this to generate active small molecules for previously undruggable targets in its pipeline in a time frame of weeks, instead of what has traditionally taken years. Michael Bronstein, Chief Scientist at VantAI and DeepMind Professor of AI at the University of Oxford noted, “Neo-1 unlocks the potential of VantAI’s high-throughput ‘black-box’ data platform, NeoLink. VantAI’s unique approach to data and AI will allow us to illuminate the geometric vocabulary of protein interaction at the full proteome scale, a step necessary to design next-generation therapeutics currently beyond reach. Being both one of the leading frontier AI labs in the bio space and having such a differentiated data source makes VantAI truly unique.” “Neo-1 is a breakthrough model that enables all-atom de novo design across biomolecular space in addition to remarkable multimodal structure prediction capabilities,” said Anthony Costa, Director of Digital Biology at NVIDIA. “Acceleration of Neo-1 on the NVIDIA platform is crucial to accelerate scientific advances in the hands of scientists using the model.” VantAI is currently deploying Neo-1 to select commercial and academic partners, including Janssen (J&J), Blueprint Medicines, and Bristol Myers Squibb, and looks forward to leveraging Neo-1 to accelerate key milestones across these successful discovery collaborations as well as for VantAI’s own internal pipeline. About VantAI VantAI is pioneering a transformative approach to drug discovery by illuminating the dynamic networks of protein interactions that drive biological function. Leveraging our groundbreaking NeoLink structural proteomics platform and next generation foundation models, we generate unprecedented interactomics data at scale, revealing how molecules connect, interact, and shape cellular behavior — in 3D. Alongside a robust and mechanistically differentiated internal pipeline, VantAI collaborates extensively with external partners to accelerate the delivery of innovative therapies. Our cross-disciplinary team of scientists and engineers is uniquely positioned to unlock novel therapeutic strategies that induce, modulate, or block protein interfaces—making previously undruggable targets accessible and providing powerful new ways to target diseases by rewiring cellular circuitry. For more information, visit www.vant.ai.