John-Claude Saltiel, MBA’s Post

The quantification of viral loads in patients is essential for planning treatment plans and formulating isolation protocols to prevent further spread of the virus. However, the small size (~ nm) and low refractive index of viral particles often make this challenging. In a new study, researchers from #GIST have now developed DeepGT, a novel synergistic biosensing platform that combines Gires-Tournois (GT) nanophotonic biosensor with deep learning algorithms trained on large datasets. It accurately and rapidly detects the stage of infection, ranging from asymptomatic to severe, even at extremely low viral concentrations. Read more in Nano Today: https://ow.ly/i95B50PWWRz #GIST #Korea #ResearchNews #ArtificialIntelligence #diagnostics #virus #QuantitativeBiosensing #biosensors #Biosensor #DeepGT #DeepLearning #BrightFieldMicroscopy #nanophotonics #COVID19 #SARSCov2

Before specialised pathogen AI algorithms, scientists had to rely on memory to identify potential virus mutations. Now, an algorithm has automated the process, allowing health experts to reconstruct the virus’s evolutionary history. This is a game-changer in the fight against COVID-19 and future viruses helping experts determine whether a new sequence is a truly independent mutation or a combination of existing variants. #covid #ai #vaccine #health #mit

More fun with AI and splicing: Here we design a screen for Huntington's disease using LJSplice2.x to identify targets for steric blocking ASOs to favor normal over pathogenic transcripts. The pathogenic transcript results in a polyadenylated exon 1-intron 1 transcript with the polyA ~680 bases into intron 1. Exon 1 is considered a strong splice site. Here we tile around cis-regulatory elements predicted to weaken mutant while favoring non-mutant HTT splicing. #huntingtonsdisease #oligonucleotides #lajollalabs

What a great week w/ Ascidian Therapeutics team in Baltimore at American Society of Gene & Cell Therapy’s 7,700 strong Annual Meeting. The field is moving fast. Some reflections: 1️⃣ Location location location 🗺 Novel neuro-penetrant capsids are long-time stars of the ASGCT show. Progress in neuro in Baltimore was substantial, but other tissue types also appear tractable to engineered AAVs. Increased emphasis on manufacturability of these novel variants means we are much more likely to see drugs into bodies over the next 1-2 years. Highly encouraging for genetic diseases originating outside the liver. 2️⃣ Overheard: “ASGCT is turning into my JPM.” ☕ 🤝 Partnering discussions were copious (in an otherwise exceptionally well run meeting, the early closing time of the only cafe was a constant comment … ) Expect to see increasing cargo - capsid collaborations as novel delivery and novel cargos find each other to tackle specific biology. 3️⃣ RNA > DNA Novel RNA editing payloads, like what Ascidian is working on, and also other approaches, are moving into clinic quickly. Being easier to package is one key advantage because … see 1️⃣ 🗺. Wall Street may be noticing. RNA editors have outperformed even the hot DNA editing IPOs YTD by a wide margin. 📈 4️⃣ Big Pharma bringing the “R” back to R&D 🔬 ASGCT (like similar meetings) is often where academic and biotech investigators share Research ... Big Pharma comes in for Development. But in Baltimore, Big Pharma research (Sanofi most visibly) shared a high volume of great work on capsid engineering, viral immunology, and good ol’ fashioned CMC. 🏭 5️⃣ What hasn’t changed? Transformative efficacy. Gene therapy & gene editing is hard at every level (research, development, manufacturing, and commercialization). Yet we keep at it, because of the potential for stunning efficacy, demonstrated this week by data from Akouos/Eli Lilly and Company, Decibel Therapeutics/Regeneron, and others who enabled profoundly deaf children to hear for the first time. ⚜ I’m already looking forward to next year in New Orleans. Come along. ⚜ 

Check this recent post from Kate Baker!

ARTIFICIAL INTELLIGENCE CAN PREVENT EPIDEMICS AND OUTBREAKS The use of AI in epidemic control is enhancing its various facets, including predicting outbreaks and speeding treatments. Read more: https://lnkd.in/dVuV9UCB

Predicting the Unseen: AI Model Aims to Stop Viruses Before They Jump Species Predicting the Unseen: AI Model Aims to Stop Viruses Before They Jump Species The recent COVID-19 pandemic served as a stark reminder of the devastating potential of zoonotic diseases, viruses that leap from animals to humans. With increasing human-animal interactions and environmental changes, the risk of future pandemics remains high. Now, researchers at the University of Gothenburg offer a glimmer of hope with a groundbreaking AI model that delves into the intricate world of sugars to predict which viruses pose the greatest threat. This innovative model, unlike its predecessors, focuses not on the viruses themselves, but on the sugary molecules […] For more, please visit the link https://lnkd.in/gRKuQ3cg

Got invited by Kudos to showcase my recently published research on Machine Learning and Tuberculosis. Discover more about it and my perspectives in the link below! #MachineLearning #TuberculosisResearch #DataScience #HealthTech #ResearchInsights #PublicHealth

Predicting the Unseen: AI Model Aims to Stop Viruses Before They Jump Species Predicting the Unseen: AI Model Aims to Stop Viruses Before They Jump Species The recent COVID-19 pandemic served as a stark reminder of the devastating potential of zoonotic diseases, viruses that leap from animals to humans. With increasing human-animal interactions and environmental changes, the risk of future pandemics remains high. Now, researchers at the University of Gothenburg offer a glimmer of hope with a groundbreaking AI model that delves into the intricate world of sugars to predict which viruses pose the greatest threat. This innovative model, unlike its predecessors, focuses not on the viruses themselves, but on the sugary molecules […] For more, please visit the link https://lnkd.in/gRKuQ3cg

The Echocardiographic Evaluation of the Right Heart: Current and Future Advances. So much progress over the years in understanding and assessing the Right Heart in health and disease, with even more to come from AI, integrated phenotyping, and POCUS to broaden access to disease detection and outcome prediction. Thanks to Christian O'Donnell, Pablo Sanchez, Bettia Celestin, and Francois Haddad!! Online in Current Cardiology Reports - https://rdcu.be/dsCfy