A new collaboration with Alphabet's Wing will only deliver sandwiches. It demonstrates the tricky parts of taking to the sky. Starting today, eager customers of the US pizza restaurant chain Papa Johns living in one corner of southern North Carolina will have the opportunity to receive their food from the sky, thanks to a new collaboration with Alphabet's drone company, Wing . But Papa Johns' signature pizzas won't be on offer. Instead, drone-loving North Carolinians will have to choose between three kinds of sandwiches, a newer product for the fast-food chain: Philly cheesesteak, chicken bacon ranch, or steak and mushroom varieties.

WIRE)-- Simulations Plus, Inc. (Nasdaq: SLP), a leading provider of modeling and simulation software and services for pharmaceutical safety and efficacy, today announced it has entered a new collaboration with a large pharmaceutical company to extend the industry's top-rated machine learning models for the prediction of ionization constants (pKa) in the ADMET Predictor platform. In this collaboration, the partner company will contribute tens of thousands of proprietary pKa measurements. The team at Simulations Plus will aim to leverage the expansive databases to improve the accuracy of predictions, and extend the chemical coverage space, using its novel machine learning and atomic descriptor calculation methods. Dr. Robert Fraczkiewicz, Research Fellow and project lead, said: "The ionization of molecules in water impacts nearly all properties driving the absorption, distribution, metabolism, and elimination processes which occur in vivo and determine whether a molecule can be turned into a drug. We identified early the importance of accurately, and rapidly, predicting this information using machine learning approaches and were fortunate to benefit from government grants and other collaborations over the years to develop novel 2D pKa models which have consistently outperformed other software and are on par with the accuracy of the best computationally intensive ab initio methods. This new partnership will enhance our current approaches and further distinguish ADMET Predictor as the preeminent property prediction platform in the drug discovery space. We value the trust and confidence our partner has in the people and technologies at Simulations Plus, and our team is looking forward to working with them to achieve our mutual goals."

Today Roche announced a new collaboration with Bristol Myers Squibb that will use cutting edge digital methods to bring significant improvements in standardization and interpretation of tissue-based assays. This new partnership will leverage Roche's established partnership with PathAI. Through this new collaboration, Roche will integrate a novel PathAI-developed algorithm for biomarker analysis into their digital pathology workflow software. The AI-powered algorithm will be used by Bristol Myers Squibb to analyze clinical trial samples and generate biomarker data. These pathology imaging tools will enable very precise diagnoses that will lead to personalized treatment options for patients with solid tumors.

A HI-TECH firm that is a stalwart of East Lancashire Chamber of Commerce is sharing in £3million of Euro cash to boost artificial intelligence.

With about one billion proton–proton collisions per second at the Large Hadron Collider (LHC), the LHC experiments need to sift quickly through the wealth of data to choose which collisions to analyse. To cope with an even higher number of collisions per second in the future, scientists are investigating computing methods such as machine-learning techniques. A new collaboration is now looking at how these techniques deployed on chips known as field-programmable gate arrays (FPGAs) could apply to autonomous driving, so that the fast decision-making used for particle collisions could help prevent collisions on the road. FPGAs have been used at CERN for many years and for many applications. Unlike the central processing unit of a laptop, these chips follow simple instructions and process many parallel tasks at once.

With about one billion proton–proton collisions per second at the Large Hadron Collider (LHC), the LHC experiments need to sift quickly through the wealth of data to choose which collisions to analyse. To cope with an even higher number of collisions per second in the future, scientists are investigating computing methods such as machine-learning techniques. A new collaboration is now looking at how these techniques deployed on chips known as field-programmable gate arrays (FPGAs) could apply to autonomous driving, so that the fast decision-making used for particle collisions could help prevent collisions on the road. FPGAs have been used at CERN for many years and for many applications. Unlike the central processing unit of a laptop, these chips follow simple instructions and process many parallel tasks at once.

Linglong Kong (mathematical and statistical sciences) is the co-lead of a new collaboration of 18 researchers across North America working together to improve the way neuroimaging data is analyzed. In the hands of the right reader, it may prove to be a very important one--such as the likelihood of a particular patient developing a neurological disorder like dementia or responding positively to a new treatment for depression or ADHD. Recent rapid innovations in technology have enabled the unprecedented collection of complex neuroimaging data to measure different perspectives on brain structures and functions. This information-rich data offers incredible potential to investigate neurological and psychiatric diseases, trace neural network changes of various disorders and understand the inner workings of the human brain--helping lay the foundation for a future with more precise, patient-specific medical treatment options. Some of the more complicated problems involve integrating complementary sources of information--such as those that arise from studies that collect data using multiple neuroimaging modalities simultaneously, or studies that aim to combine brain imaging with genomics.