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SandboxAQ Collaborates with The Michael J. Fox Foundation to Speed Identification of New Therapies

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Collaboration with KU Leuven, [led by global leader Peter Vangheluwe, PhD, a longstanding partner of The Michael J. Fox Foundation] will leverage Large Quantitative Models (LQMs) and other advanced AI technologies to design and rapidly screen potential new drug compounds

PALO ALTO, Calif., Oct. 29, 2024 /PRNewswire/ — SandboxAQ announced today that The Michael J. Fox Foundation for Parkinson’s Research (MJFF) has selected the company’s AI platform to accelerate the identification of compounds that activate a gene linked to Parkinson’s disease (PD). SandboxAQ’s team of computational chemists and machine learning experts will collaborate with the Vangheluwe lab and CD3 at Belgium-based KU Leuven to identify activators for ATP10B. Peter Vangheluwe is a global leader in lysosomal transporters that are implicated in Parkinson’s disease, such as ATP13A2 and ATP10B. As a long-standing MJFF partner, the Vangheluwe lab has helped to better understand the underlying mechanisms of ATP13A2 and ATP10B dysfunction in Parkinson’s disease and pioneered drug discovery efforts on ATP13A2.

ATP10B is a novel candidate risk gene for PD encoding a sphingolipid-transporting ATPase involved in neuronal lipid homeostasis. As a member of the P4-ATPase family, it flips glucosylceramide across the lysosomal membrane, maintaining essential cellular functions. Despite its potential as a therapeutic target, drug discovery efforts face challenges due to ATP10B’s multiunit structural complexity, poor expression and difficult handling and limited understanding of its large-scale reorganization during a complex functional cycle. Targeting ATP10B requires novel approaches to identify small molecule modulators capable of restoring its function.

“Leveraging innovative technology in Parkinson’s research and fostering a collaboration with leading experts] is one of the many ways MJFF works to enable a diverse pipeline of treatments for people with Parkinson’s disease,” said Michelle Durborow, head of research operations, MJFF. “We look forward to this collaboration with SandboxAQ and KU Leuven to unlock novel treatments for PD.”

SandboxAQ’s Large Quantitative Models (LQMs) integrate active learning with physics-based scoring functions to create detailed protein profiles and complex interaction matrices. This approach enables rapid in silico high-throughput screening of millions of available compounds to identify potential modulators of ATP10B’s function. Leveraging their expertise in challenging protein targets, SandboxAQ will also support assay development and optimization, generate actionable hypotheses for ATP10B activation and advance early-stage drug discovery efforts on a remarkably complex target with major implications in neurodegenerative diseases.

“SandboxAQ’s Large Quantitative Models and AI simulation techniques have proven their ability to rapidly identify ligands and design novel molecules for other challenging neurodegenerative diseases such as Alzheimer’s,” said Nadia Harhen, GM of AI Simulation at SandboxAQ. “KU Leuven hosts one of the world’s foremost research labs for Parkinson’s disease, and we’re eager to apply our Large Quantitative Models to their existing efforts, accelerating new breakthrough treatments for PD.” 

KU Leuven researchers, in collaboration with the Centre for Drug Design and Discovery (CD3) of KU Leuven, have taken the first steps to unlock the ATP10B protein for small molecule drug discovery since first describing the gene in 2020. Despite significant advances in understanding the biology of ATP10B, the protein has proven difficult to study. Also, there is little real-world data available related to this specific class of lipid flippases that researchers can use to identify the most effective compounds. SandboxAQ’s Quantitative AI simulations can generate accurate data that enable a more efficient search of the vast chemical space to find and develop compounds with the correct profile.

“The ability to simulate a drug compound’s effects on ATB10B and analyze its mode of action will greatly accelerate our groundbreaking research, helping us achieve with AI technology what lab experimentation alone could not,” said Peter Vangheluwe, professor and head of the Laboratory of Cellular Transport Systems at KU Leuven. “SandboxAQ’s technology has opened the door to a new way of designing novel molecules from the vast chemistry space and testing our hypotheses with unprecedented speed and accuracy, delivering previously unknowable insights that will guide our research.”

About SandboxAQ
SandboxAQ is a B2B company delivering AI solutions that address some of the world’s greatest challenges. The company’s Large Quantitative Models (LQMs) deliver critical advances in life sciences, financial services, navigation, cyber and other sectors. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors including T. Rowe Price, Eric Schmidt, Breyer Capital, Guggenheim Partners, Marc Benioff, Thomas Tull, Section32, and others. For more information, visit http://www.sandboxaq.com.

About KU Leuven
KU Leuven boasts a rich tradition of education and research spanning six centuries. Recognized with the European HR Excellence in Research Award, the university’s commitment to fundamental research remains unwavering. Simultaneously, KU Leuven stays attuned to contemporary cultural, economic, and industrial developments, as well as the needs and expectations of the community.

As Belgium’s largest university in terms of research funding and expenditure, KU Leuven is a proud charter member of LERU. The university excels in both fundamental and applied research across all academic disciplines, maintaining a strong international orientation. In the Times Higher Education 2023 ranking, KU Leuven was ranked as the 14th best European university. Additionally, for four consecutive years, it has been recognized as the most innovative university in Europe by Reuters’ Top 100 of the World’s Most Innovative Institutions.

The Lab of Cellular Transport Systems (LCTS), led by Prof. Dr. Peter Vangheluwe, is dedicated to advancing our understanding of cellular transport mechanisms. The lab focuses on the unique molecular properties of P-type ATPases and their crucial roles in health and disease. Through cutting-edge research, LCTS aims to uncover the physiological functions of these transport systems, contributing to the development of novel therapeutic strategies for various diseases.

The Centre for Drug Design and Discovery (CD3) is a pioneering drug discovery centre and investment fund. KU Leuven Research & Development and the European Investment Fund created CD3 in 2006 to drive the translation of innovative basic research to the clinic. With a focus on the discovery and development of new medicines, CD3 supports academic research groups and small companies by providing expert drug discovery capabilities and financial resources. The center has successfully launched multiple investment funds, including a €70 million fund (CD3 IV) in 2023 to expand its scope and impact.

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Chef Robotics Physical AI Models Can Now Automate Baked Goods Packing

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SAN FRANCISCO, April 29, 2026 /PRNewswire/ — Chef Robotics, a leader in physical AI for the food industry, today announced that Chef robots can now automate tray assembly for baked goods packing. The application places baked products, such as burger buns, chocolate chip cookies, biscotti, butter cookies, biscuits, fortune cookies, granola bars, rusks, and shortbreads into trays and packaging containers before sealing.

Watch Chef robots in action.

Baked goods packing has historically been difficult to automate for high-mix production. Each item behaves differently on the production line—a granola bar compresses under the wrong grip, while a biscotti or rusk can crack if placed at the wrong angle. Surface textures range from glazed and smooth to crumbly and irregular, and strict presentation requirements leave little room for error. This variability has made it challenging for automation systems to reliably handle baked goods at production speeds, leaving food manufacturers dependent on manual labor and traditional bakery equipment.

To address this, Chef built its baked goods packing application on its existing piece-picking capability, which uses Chef’s AI-powered computer vision and physical AI models trained across diverse real-world production environments. This allows Chef robots to assess each item’s position, shape, and orientation in real time and determine how to pick the items from the pan and place them quickly and precisely without damaging them.

The baked goods packing application supports four distinct placement capabilities.

First, Chef’s vision system detects the angle at which each item sits in the pan and reorients it after picking, placing it on the tray at the exact angle required, regardless of its original position, enabling retail-ready presentation for SKUs that require precise angular placement.

Second, Chef robots can place multiple baked goods into the same packaging container in a single automated pass, completing full tray assembly without manual intervention.

Third, for packaging containers with multiple small compartments, Chef robots can precisely place items into each designated section, including multiple items in the same compartment, using Chef’s AI vision model to detect compartment positions and orientations in real time.

Fourth, Chef’s vision system identifies the exact center of each tray and places every item at a predefined offset from that center, ensuring a uniform, consistent arrangement across every pack regardless of how trays arrive on the conveyor.

For food manufacturers evaluating bakery systems and baked goods packaging automation, the application offers higher throughput, reduced labor dependency, and consistent presentation across shifts. The capability runs on Chef’s existing robotic hardware and software, allowing manufacturers to deploy it without requiring any changes to their production lines.

Chef’s baked goods packing application is available in the U.S., Canada, Germany, and the UK and is included as part of Chef’s robotics-as-a-service (RaaS) pricing model.

About Chef Robotics
Chef is the first company to have commercialized a scalable AI-driven food robotics solution. With over 104 million servings made in production, Chef leverages ChefOS, an AI platform for food manipulation, to offer a Robotics-as-a-Service solution that helps industry-leading food companies increase production volume and meet demand. Headquartered in San Francisco, CA, Chef aims to empower humans to do what humans do best by accelerating the advent of intelligent machines. Visit https://chefrobotics.ai to learn more.

View original content:https://www.prnewswire.com/news-releases/chef-robotics-physical-ai-models-can-now-automate-baked-goods-packing-302756923.html

SOURCE Chef Robotics

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Chef Robotics Physical AI Models Can Now Automate Baked Goods Packing

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SAN FRANCISCO, April 29, 2026 /PRNewswire/ — Chef Robotics, a leader in physical AI for the food industry, today announced that Chef robots can now automate tray assembly for baked goods packing. The application places baked products, such as burger buns, chocolate chip cookies, biscotti, butter cookies, biscuits, fortune cookies, granola bars, rusks, and shortbreads into trays and packaging containers before sealing.

Watch Chef robots in action.

Baked goods packing has historically been difficult to automate for high-mix production. Each item behaves differently on the production line—a granola bar compresses under the wrong grip, while a biscotti or rusk can crack if placed at the wrong angle. Surface textures range from glazed and smooth to crumbly and irregular, and strict presentation requirements leave little room for error. This variability has made it challenging for automation systems to reliably handle baked goods at production speeds, leaving food manufacturers dependent on manual labor and traditional bakery equipment.

To address this, Chef built its baked goods packing application on its existing piece-picking capability, which uses Chef’s AI-powered computer vision and physical AI models trained across diverse real-world production environments. This allows Chef robots to assess each item’s position, shape, and orientation in real time and determine how to pick the items from the pan and place them quickly and precisely without damaging them.

The baked goods packing application supports four distinct placement capabilities.

First, Chef’s vision system detects the angle at which each item sits in the pan and reorients it after picking, placing it on the tray at the exact angle required, regardless of its original position, enabling retail-ready presentation for SKUs that require precise angular placement.

Second, Chef robots can place multiple baked goods into the same packaging container in a single automated pass, completing full tray assembly without manual intervention.

Third, for packaging containers with multiple small compartments, Chef robots can precisely place items into each designated section, including multiple items in the same compartment, using Chef’s AI vision model to detect compartment positions and orientations in real time.

Fourth, Chef’s vision system identifies the exact center of each tray and places every item at a predefined offset from that center, ensuring a uniform, consistent arrangement across every pack regardless of how trays arrive on the conveyor.

For food manufacturers evaluating bakery systems and baked goods packaging automation, the application offers higher throughput, reduced labor dependency, and consistent presentation across shifts. The capability runs on Chef’s existing robotic hardware and software, allowing manufacturers to deploy it without requiring any changes to their production lines.

Chef’s baked goods packing application is available in the U.S., Canada, Germany, and the UK and is included as part of Chef’s robotics-as-a-service (RaaS) pricing model.

About Chef Robotics
Chef is the first company to have commercialized a scalable AI-driven food robotics solution. With over 104 million servings made in production, Chef leverages ChefOS, an AI platform for food manipulation, to offer a Robotics-as-a-Service solution that helps industry-leading food companies increase production volume and meet demand. Headquartered in San Francisco, CA, Chef aims to empower humans to do what humans do best by accelerating the advent of intelligent machines. Visit https://chefrobotics.ai to learn more.

View original content:https://www.prnewswire.com/news-releases/chef-robotics-physical-ai-models-can-now-automate-baked-goods-packing-302756923.html

SOURCE Chef Robotics

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Air Products to Expand Industrial Gas Supply for Samsung Electronics’ Next-Generation Semiconductor Fab in South Korea

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New investment underscores the company’s long-term commitment to Korea and its leading role in the global semiconductor industry 

LEHIGH VALLEY, Pa., April 29, 2026 /PRNewswire/ — Air Products (NYSE:APD), a world-leading industrial gases company and serving Samsung globally, today announced it has been selected by Samsung to supply industrial gases for its new advanced semiconductor fab in Pyeongtaek, Gyeonggi Province, South Korea.

Under the agreement, Air Products will build, own and operate multiple state-of-the-art production facilities and a bulk specialty gas supply system to supply nitrogen, oxygen, argon, and hydrogen for Samsung’s new semiconductor fab. The new facilities are expected to come onstream in multiple phases from 2028 through 2030.

Air Products has a long track record of executing multiple phase expansions in Pyeongtaek to support Samsung’s growing manufacturing needs. This latest project represents Air Products’ largest investment to date in the semiconductor industry and will establish Pyeongtaek as the company’s single largest operations site globally supporting the electronics industry. 

“Air Products is honored to be selected once again by Samsung and to have their continued confidence as a trusted partner supporting their strategic growth plans,” said SR Kim, President, Air Products Korea. “This significant investment reinforces Air Products’ role as a leading global supplier to the semiconductor industry and underscores our long-standing commitment to supporting our strategic customers with safety, reliability, efficiency and excellent service.”

Air Products has served the global electronics industry for more than 40 years, supplying industrial gases safely and reliably to many of the world’s leading technology companies. The company has operated in Korea for more than 50 years and has established a strong position in electronics and manufacturing sectors.

About Air Products

Air Products (NYSE: APD) is a world-leading industrial gases company in operation for over 85 years focused on serving energy, environmental, and emerging markets and generating a cleaner future. The Company supplies essential industrial gases, related equipment and applications expertise to customers in dozens of industries, including refining, chemicals, metals, electronics, manufacturing, medical and food. As the leading global supplier of hydrogen, Air Products also develops, engineers, builds, owns and operates some of the world’s largest clean hydrogen projects, supporting the transition to low- and zero-carbon energy in the industrial and heavy-duty transportation sectors. Through its sale of equipment businesses, the Company also provides turbomachinery, membrane systems and cryogenic containers globally.

Air Products had fiscal 2025 sales of $12 billion from operations in approximately 50 countries. For more information, visit airproducts.com or follow us on LinkedInXFacebook or Instagram.

This release contains “forward-looking statements” within the safe harbor provisions of the Private Securities Litigation Reform Act of 1995. These forward-looking statements are based on management’s expectations and assumptions as of the date of this release and are not guarantees of future performance. While forward-looking statements are made in good faith and based on assumptions, expectations and projections that management believes are reasonable based on currently available information, actual performance and financial results may differ materially from projections and estimates expressed in the forward-looking statements because of many factors, including the risk factors described in our Annual Report on Form 10-K for the fiscal year ended September 30, 2025 and other factors disclosed in our filings with the Securities and Exchange Commission. Except as required by law, we disclaim any obligation or undertaking to update or revise any forward-looking statements contained herein to reflect any change in the assumptions, beliefs or expectations or any change in events, conditions or circumstances upon which any such forward-looking statements are based.

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SOURCE Air Products

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