Medvolt’s Post

I spent yesterday afternoon completing Thermo Fisher Scientific‘s #massspectrometry simulation on Forage and thoroughly enjoyed it! In the simulation I: • Explored the applications of mass spectrometry in various fields, including sports, to understand its wide-ranging uses. • Gained a comprehensive understanding of the process of #dopingtesting using mass spectrometry, including the stages involved. • Accessed additional resources to deepen knowledge about mass spectrometry, broadening the understanding of its applications. • Discovered the fundamental principles behind mass spectrometry, including #ionisation and ion manipulation, enabling a solid grasp of its underlying concepts. This simulation helped broaden my knowledge of the machines I use in my everyday work life and I’d reccomend it to those who are interested in toxicology or biochemistry. Check out the simulation here: https://lnkd.in/gNj8zCHT #science #toxicology

Read our new article on #toxicology #AI and #XAI Toxic Alerts of Endocrine Disruption Revealed by Explainable Artificial Intelligence | Environment & Health https://lnkd.in/dHUFX2wY

Thrilled to see this article being featured and to have worked alongside the amazing team at Ignota Labs on it. This work discusses the difficulty in addressing safety issues within drug discovery, whilst highlighting how in silico tools can be used to turn safety issues around. I encourage anyone curious about how AI, cheminformatics and bioinformatics can be used to tackle toxicity within drug discovery to read the article using the link below. #DigitalDiscovery #drugsafety #cheminformatics #AI

Great Article from Ignota Labs ! Read about SOTA in tox and mechanistic modelling and hypothesis generation — the next stage of ML for real world toxicity prediction!

This week, Ignota Labs’ article has been featured by #DigitalDiscovery. Masarone, Beckwith, Lane, Hosseini-Gerami et al. explore the state of the art in toxicology prediction for drug discovery, across a variety of modelling techniques and novel data sources such as organ-on-a-chip studies. Discovering drugs that show therapeutic potential is hard and expensive. But finding drugs which do not have severe side effects is even harder. Safety concerns such as toxicity halt 56% of projects, but despite this, safety assessment is often neglected until the late stages of the discovery timeline. Our AI platform SAFEPATH brings safety to the forefront, combining cheminformatics, bioinformatics, and multimodal data analysis to explain why and how safety issues occur, delivering actionable insights to refine or repurpose drug candidates. To understand the novel data sources utilised in SAFEPATH, read the Perspective article here: https://lnkd.in/eQjn8zNf. #drugdiscovery #AI #drugturnaround #toxicity #drugsafety

Explore the future of toxicology in the "Tox Hack: Unleashing the Power of AI and Machine Learning" symposium, led by Claire Neilan and Peyton M.. Learn how AI and machine learning are reshaping toxicology assessments, accelerating drug discovery, and improving safety through innovative data-driven approaches. Don't miss the opportunity to dive into real-world applications of AI in toxicology! Link for registration to the Annual meeting: https://lnkd.in/ek5UQRza

Machine learning (ML) is rapidly transforming the field of toxicology, offering exciting opportunities for improving risk assessment and safety evaluation in chemical substances. In this review, Lusine T., AI Analyst & Advanced Spectroscopy Scientist at API and Arno Siraki, Biochemical Toxicologist and Professor at the University of Alberta, explored the fundamental concepts of ML, highlighted key algorithms, and introduced a practical workflow guiding successful application of ML models in toxicology. We’re thrilled to share this insightful review, which not only sheds light on the transformative potential of ML in toxicology but also provides a clear roadmap for researchers and practitioners looking to integrate these technologies into their work. We look forward to fostering more collaboration with our academic partners, as we work together to accelerate drug discovery and development in the life sciences! 🔬🧬 Read the full review here 👉 https://lnkd.in/g52djQEp #MachineLearning #Toxicology #AIInToxicology #lifesciences

🙋♂️Excited to share my colleague's latest blog on how genAI is transforming traditional chemical risk assessment methods. At Evalueserve, we're at the forefront of this innovation, using AI to streamline data integration, enhance report generation, and improve predictive toxicology. 👀 Efficient chemical identification and grouping, streamlined literature reviews, and summarized safety data for precise, actionable insights is needed in Hazard and Risk Assessment. Our customised and tested Generative AI not only boosts the accuracy and efficiency of risk assessments but also sets new industry standards, ensuring public safety and regulatory compliance. Let's connect and explore how this cutting-edge technology can revolutionize your product safety and risk assessments! 👉 Read more here: https://lnkd.in/g8X9dFFZ

Looking forward to tomorrow's keynote presentation by Thomas Hartung on Probabilistic Risk Assessment Using Artificial Intelligence. In the meantime, today, during the poster session, I will be happy to meet the participants of #ESTIV2024 at poster number 29. We will discuss a question that you have been interested in for a long time, but you were shy to ask about - the regulatory acceptance of #AI for chemical risk assessment. European Society of Toxicology in Vitro ESTIV

Is SEND sparking a controversy within nonclinical research by accelerating the development of Virtual Control Groups? Read my experiences of the debate at this year's Society of Toxicology meeting #send #cdisc