Atomicas

Use of 𝗡𝗼-𝗖𝗼𝗱𝗲 𝗔𝗜 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺𝘀 in Drug Discovery In today's fast-paced drug discovery landscape, No-Code AI platforms are revolutionizing the way scientists and researchers approach complex tasks. These platforms enable drug hunters to streamline workflows, accelerate data analysis, and generate actionable insights without the need for programming expertise. At 𝗔𝘁𝗼𝗺𝗶𝗰𝗮𝘀 𝗔𝗜 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝘀, we specialize in creating interactive, affordable, and customizable web applications tailored for the unique challenges of drug discovery. Whether you're aiming to enhance ADME/T predictions, automate, or optimize lead identification, and optimization studies, our solutions empower your team to achieve breakthroughs faster. 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗶𝗻𝗴 𝘁𝗵𝗲 𝘄𝗮𝘆 𝗱𝗿𝘂𝗴 𝗱𝗶𝘀𝗰𝗼𝘃𝗲𝗿𝘆 𝗵𝗮𝗽𝗽𝗲𝗻𝘀 – 𝗼𝗻𝗲 𝗮𝗽𝗽 𝗮𝘁 𝗮 𝘁𝗶𝗺𝗲! Are you looking for the 𝗽𝗲𝗿𝗳𝗲𝗰𝘁 𝗽𝗮𝗿𝘁𝗻𝗲𝗿 𝘁𝗼 𝗱𝗲𝘃𝗲𝗹𝗼𝗽 𝗰𝘂𝘁𝘁𝗶𝗻𝗴-𝗲𝗱𝗴𝗲 𝘁𝗼𝗼𝗹𝘀 𝗳𝗼𝗿 𝘆𝗼𝘂𝗿 𝗱𝗿𝘂𝗴 𝗱𝗶𝘀𝗰𝗼𝘃𝗲𝗿𝘆 𝗻𝗲𝗲𝗱𝘀?  We'd love to learn more about your requirements. Let's innovate together! 📩 Reach us at suneel@theatomicas.io #DrugDiscovery #MedicinalChemistry #ComputationalChemistry #AISolutions #Collaboration

#DataBuster0.2.1 has been released and is now available for download via PIP. Databuster is an open-source repository designed to provide deeper insights into your small molecule dataset, including chirality, duplicates, peptide-like and macrocycle-like structures, and PAINS alerts. It helps users preprocess, filter, and select an optimized dataset for machine learning modeling. Access to #Databuster WebApp: https://lnkd.in/eE-DvxCt We are currently working on manuscript, complete code will released along with the manuscript. Looking for similar NO-CODE, user-friendly web app for your internal drug discovery projects? Reach out to us at suneel@theatomicas.io. We’d love to learn about your project and explore collaboration opportunities! #ADMEDatasets #DrugDiscovery #SmallMolecules #MedicinalChemistry #WebApp #ATOMICAS

The U.S. Food and Drug Administration (FDA) has issued its inaugural draft guidance on the utilization of artificial intelligence (AI) in drug and biological product development. This initiative signifies a pivotal move toward integrating AI into regulatory decision-making concerning product safety, efficacy, and quality. he guidance introduces a risk-based framework to evaluate AI model credibility within specific contexts of use (COU), reflecting the FDA's dedication to promoting innovation while upholding stringent safety and effectiveness standards. Key Highlights: Risk-Based Framework: The guidance outlines a framework for assessing AI model credibility, beginning with a clear definition of the question or decision the AI model addresses, the COU, and the associated AI model risk. Evaluating AI model risk is crucial, as the credibility assessment activities should align with the level of risk and be tailored to the specific COU. Early Engagement: The FDA encourages sponsors and stakeholders, including technology and biotech companies and AI tool developers, to engage with the agency early in the development process. This proactive approach aims to ensure the appropriateness of AI applications and to identify potential challenges related to AI use in specific COUs promptly. Experience-Driven Framework: This guidance builds upon the FDA's extensive experience, having reviewed over 500 regulatory submissions incorporating AI components since 2016.It also incorporates insights from public workshops, industry and academic experts, and over 800 comments from more than 65 organizations on the 2023 AI in drug development discussion paper. The FDA is seeking public comments on this draft guidance within 90 days. Sponsors and interested parties are strongly encouraged to provide feedback. To read the full draft guidance and submit comments, please visit the FDA's official website. This development aligns with broader regulatory trends in the United States concerning AI. The regulation of artificial intelligence is an emerging issue, with various jurisdictions globally developing public sector policies and laws to promote and regulate AI. FDA's initiative represents a significant step in ensuring that AI technologies in drug development are both innovative and adhere to the highest standards of safety and efficacy. https://lnkd.in/eC29Mmj9 #FDA #AIinDrugDiscovery

Welcome back from the holidays! We're thrilled to share the latest updates on our developments. Have you had a chance to explore CHEMLAB, our self-learning platform for Cheminformatics coding and AI/ML-driven drug discovery? Here is the link: https://lnkd.in/eWXAtnPt Here's a quick demo showcasing its capabilities and features. We'd love to hear your thoughts and suggestions on the preview course—your feedback will help us refine and enhance the platform for an even better learning experience. Take a look, and let us know what you think! #Cheminformatics #Learnings #AIDrivenDrugDiscovery #NewUpdates #ComingSoon #ATOMICAS

Its Live. You can register and start beginners course in cheminformatics. Please note : Don't forget 'Mark as Completed' once you're done with the particular topic, it tracks your progress and help you to issue the certificate as well! #HappyLearnings

Day 2: 🔬 Introducing 𝗗𝗮𝘁𝗮𝗕𝘂𝘀𝘁𝗲𝗿: 𝗔𝗻 𝗢𝗽𝗲𝗻-𝗦𝗼𝘂𝗿𝗰𝗲 𝗣𝗮𝗰𝗸𝗮𝗴𝗲 𝘁𝗼 𝗗𝗲𝗲𝗽-𝗗𝗶𝘃𝗲 𝗶𝗻𝘁𝗼 𝗦𝗺𝗮𝗹𝗹 𝗠𝗼𝗹𝗲𝗰𝘂𝗹𝗲 𝗗𝗮𝘁𝗮𝘀𝗲𝘁𝘀. Working with chemical datasets from open sources? How well do you know their quality and consistency To Install : pip install databuster 𝗗𝗮𝘁𝗮𝗕𝘂𝘀𝘁𝗲𝗿 is an open-source tool designed for: 1. Dataset Integrity Checks: Detect duplicates, tautomers, salts, and inconsistencies. 2. Advanced Analysis: Compute properties and validate datasets with cheminformatics tools. 3. Preprocessing for Modeling: Streamline tasks to prepare clean, reliable datasets. 💡 Explore 𝗗𝗮𝘁𝗮𝗕𝘂𝘀𝘁𝗲𝗿 on GitHub to ensure high-quality data for better modeling and analysis. Collaborate, contribute, and transform your workflows! https://lnkd.in/eQp49Uf8 #OpenSource #Cheminformatics #DataQuality #DrugDiscovery #MedicinalChemistry #ATOMICAS_Day2 #ComputationalChemistry

🚀 Exciting Announcement: Launching CHEMLAB! 🌟 Day 1: We are thrilled to announce the 𝗹𝗮𝘂𝗻𝗰𝗵 𝗼𝗳 𝗖𝗛𝗘𝗠𝗟𝗔𝗕 (preview) – 𝗮𝗻 𝗼𝗻𝗹𝗶𝗻𝗲, 𝘀𝗲𝗹𝗳-𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗽𝗹𝗮𝘁𝗳𝗼𝗿𝗺 designed to empower students, researchers, and professionals with the latest in cheminformatics and AI/ML. Are you looking to 𝗺𝗮𝘀𝘁𝗲𝗿 𝘆𝗼𝘂𝗿 𝘀𝗸𝗶𝗹𝗹𝘀 𝗶𝗻 𝗰𝗵𝗲𝗺𝗶𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗰𝘀 𝗮𝗻𝗱 𝗔𝗜/𝗠𝗟? and take your expertise to the next level?.  📅 Beginners course (𝗣𝗿𝗲𝘃𝗶𝗲𝘄 𝘃𝗲𝗿𝘀𝗶𝗼𝗻) 𝗻𝗼𝘄 𝗮𝘃𝗮𝗶𝗹𝗮𝗯𝗹𝗲! 𝗡𝗲𝘄 𝗥𝗲𝗴𝗶𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻𝘀 𝗮𝗿𝗲 𝗮𝗰𝗰𝗲𝗽𝘁𝗲𝗱 𝗳𝗿𝗼𝗺 𝘁𝗼𝗺𝗼𝗿𝗿𝗼𝘄. 🌟 Why CHEMLAB?  ✅ Comprehensive courses tailored for AI/ML in drug discovery  ✅ Step-by-step learning with theory, hands-on tutorials, and quizzes  ✅ Perfect for beginners and advanced learners alike  ✅ Get Certified  ✅ Industry-ready training to prepare the next generation of AI/ML scientists 👉 Join us on this journey to revolutionize learning in cheminformatics and AI/ML! 💡 #Cheminformatics #AIinDrugDiscovery #MachineLearning #CHEMLAB #Education #DrugDiscovery #SelfLearning #AI #ML #OnlineLearning

#AtomicasInnovation #6DaysOfATOMICAS #AIForDrugDiscovery #MedicinalChemistry #ZoomingInto2025

Our CEO, Dr. Suneel Kumar BVS, will be delivering a guest lecture on "Formulation AI: A Novel Web-Based Platform for Drug Formulation Using AI" on January 9, 2025, as part of the 5-day Faculty Development Program (FDP) organized by the School of Pharmacy, Kaziranga University. Refer comments section for registration link. Looking forward to interacting with you!. #Formulations #DrugDiscovery #WebSolutions #UpcomingEvents #CEOTalks

🚀 "𝗠𝗮𝘀𝘁𝗲𝗿 𝗖𝗵𝗲𝗺𝗶𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗰𝘀. 𝗖𝗼𝗱𝗲 𝗠𝗼𝗹𝗲𝗰𝘂𝗹𝗲𝘀. 𝗨𝗻𝗹𝗼𝗰𝗸 𝗔𝗜 𝗗𝗿𝘂𝗴 𝗗𝗶𝘀𝗰𝗼𝘃𝗲𝗿𝘆." - Introducing 𝗖𝗛𝗘𝗠𝗟𝗔𝗕®, a focused online learning platform designed for cheminformatics and AI-driven drug discovery. Whether you're a student, researcher, or industry professional, CHEMLAB® helps you: ✅ Build a solid foundation in cheminformatics ✅ Gain hands-on experience with ready-to-use coding snippets ✅ Learn systematically with interactive content, quizzes Launching Tomorrow. Stay tuned this space for more updates. 🔗 Join us at CHEMLAB® and empower your learning today!  #Cheminformatics #AIDrugDiscovery #LearningPlatform #AI #DrugDiscovery #MolecularModeling #SkillDevelopment #LifelongLearning