Fiona H. Marshall’s Post

We must passionately invest in nurturing the very essence of what makes us human—our creativity, empathy, and critical thinking. The motivation behind initiatives like the Prize for Computational Protein Design itself serves as a poignant warning, highlighting the extraordinary pace and impact of AI's evolution. This underscores the critical importance of reimagining our education system to equip the next generation with the skills and values needed to navigate and shape an AI-driven future. By embracing this transformative approach, we can safeguard the irreplaceable qualities that define us and inspire our youth to excel in harmony with emerging technologies. However, if we continue to teach the same things repeatedly, we will merely be faking progress, failing to genuinely prepare our children for the challenges and opportunities of an AI-driven future. It is essential to innovate our educational practices to ensure that our curriculum truly equips the next generation with the skills and mindset needed to thrive alongside advancing technology.

It's so exciting! 😁 😁 😁 This year truly marks the inaugural year of the AI Nobel Prize! With our MegaR technology platform, we can easily obtain structural information on GPCR, ligand-free/antagonist complexes, which is very beneficial for AIDD of GPCR drugs. This method has already been applied to targets like CCR8 and GPR75. We welcome pharmaceutical companies and biotech firms to collaborate with us! Fiona H. Marshall #GPCR #AI #AIDD #Drug Discovery

This represents a significant milestone and a clear recognition of #AI's astounding potential in analyzing biomedical data and generating new insights. It's heartening to witness the convergence of teams with diverse methodologies. In my view, this is merely the beginning; there is a lot more on the horizon, achievable through the integration of computational methods with biomedical expertise. Interdisciplinary teams are crucial for tackling complex health challenges. Congrats to Demis Hassabis, John Jumper, David Baker, and my alma mater, University of Washington. Good to see Isomorphic Labs taking this potential to the next level! #AI #interdisciplinaryscience #datascience #biomedical

I believe that AI is changing the future of healthcare, which shows us that it will revolutionise how we deal with human health challenges moving forward.

AlphaFold3 Unveils Molecular Secrets, Revolutionizing Drug Discovery and Biology Research Google and DeepMind's AlphaFold3, an AI model, predicts the structure and interactions of all life's molecules with unprecedented accuracy, improving upon existing methods by at least 50%. This advancement is expected to transform biological understanding and accelerate drug discovery. Isomorphic Labs is already applying AlphaFold3 to real-world drug design challenges, while the AlphaFold server provides free access to its capabilities for non-commercial research, democratizing access to predictive molecular modeling. #AlphaFold3 #AIinBiology #DrugDiscoveryRevolution #MolecularModeling #DeepMindInnovation #PredictiveBiology #StructuralBiology #AIforScience #BiotechBreakthrough #GenomicsAdvancement #AIinDrugDesign #OpenAccessResearch (Source: YouTube Video-ID hKcZIbWpNE4)

Please join the IMAG/MSM WG on Multiscale Modeling and Viral Pandemics and GLIMPRINT, Thursday, March 7th at 3 pm Eastern Time (ET) for: Belinda Akpa, University of Tennessee Every model has its place: combining systems, data-driven, and generative models for therapeutic design Drug discovery is a molecular search task with a challenging objective: modify the function of a complex biological system to interrupt disease processes. Conventionally, it is a costly, high failure-rate process – with molecular candidates clearing preclinical safety and efficacy hurdles only to fail upon delivery to humans. This happens partly because early screens in the discovery pipeline fall short of capturing the ultimate therapeutic value of new molecular candidates. For a molecule to become a successful drug, it should: (1) bind to a desired target protein; (2) be deliverable from a desired site of administration (oral, intravenous, etc.) to the physiological site of activity, with sufficient concentration for a sufficient duration of time; and (3) promote the desired pharmacological effect without causing unwanted toxicity. The chemical space that meets one of these objectives likely requires compromises in another, as binding, delivery, and activity depend on coupled and dynamic biophysical and biochemical interactions. To help improve the success rate of drug discovery, we should ideally look at design through the lens of human physiology. In this presentation, I will discuss our work on integrating mechanistic systems models with data-driven machine learning and generative AI models to empower physiology-informed design of potential therapeutics. For more information see: https://lnkd.in/g2gQt22C Register at: https://lnkd.in/env6WVM #MSMViral, #GLIMPRINT, #UTenn, #OakRidge, #DrugDiscovery, #Pharma, #MachineLearning, #AI, #MolecularDynamics, #Physiology, #Medicine, #TherapyDevelopment, #MathematicalBiology, #SystemsBiology, #Technology, #Software, #ComputationalBiology, #IUB, #Modeling, #eScience, #Multiscale, #HPC, #Simulations, #ComplexSystems, #Integration, #SpatialModels, #Bioinformatics

Revolutionizing biology with AI! 🌟 AlphaFold 3, by Google DeepMind, is here to change how we understand life's molecules. With precision never seen before, it's not just science—it's our future! 🔬💡 #AlphaFold3 #DeepMind #RevolutionaryAI #FutureOfScience #BiologyInnovation #AlphaFold3 #Deepmind #scientificbreakthrough #proteinfolding #biologicalresearch #techforgood #aiinscience #google #meta #sonnyarcot #arcotgroup AlphaFold 3, DeepMind AI, Protein structure prediction, Scientific research technology, Molecular biology, Non-commercial research access, Innovations in science

AlphaFold 3 is a game-changer in biology! 🌟 Developed by Google Google DeepMind, this revolutionary AI model can predict the structure of proteins and other molecules with unprecedented accuracy, surpassing its predecessors by over 50%. 📈🔬 Scientists worldwide can now access the new AlphaFold server for non-commercial research, unlocking rapid discoveries in biology, drug development, and molecular structure understanding. 🌍🚀 #alphafold3 #airesearch #proteinstructure #molecularbiology #drugdiscovery #googledeepmind #sonnyarcot #arcotgroup #google #meta

Chroma’s Evolution: Reflections from Co-Founder Jay Reichman In 1991, six passionate individuals founded Chroma Technology with a goal to revolutionize optical filters. From humble beginnings to a global leader in optical filter technology, our unwavering commitment to innovation and quality has defined our work. Jay Reichman, one of the original co-founders and current chair, reflects on a pivotal early achievement: “One of our early successes was the development of multicolor filters and mirrors for a technique called fluorescence in situ hybridization, otherwise known as FISH. It's a type of imaging analysis where they can image specific genes within chromosomes, which was pretty important for a lot of the early genomics genetic research.” Over the years, Chroma has continuously evolved. Reichman shares, "We've stayed at the forefront of microscopy techniques, working with Nobel laureates. But we've also ventured into machine vision, expanding our capabilities into the shortwave infrared region." From pioneering fluorescence filters to expanding into diverse markets such as machine vision and shortwave infrared, our journey has been driven by continuous innovation and a dedication to excellence. As a certified B Corporation and a 100% employee-owned company, our collaborative culture empowers us to build a better world for our employee-owners, customers, and the broader community. Read more about Chroma’s history and Jay’s insights here: https://lnkd.in/e9whFb5T

Want to listen to alum and newly-minted Nobel Prize winner, John Jumper, speak about AlphaFold, the revolutionary protein structure-predicting program? 🧬 💻 Head to this article to listen to his full talk during our inaugural Apex Lecture 👉