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DTSTART;TZID=UTC:20260926T110000
DTEND;TZID=UTC:20260926T120000
DTSTAMP:20261005T100841
CREATED:20260617T070853Z
LAST-MODIFIED:20261002T051058Z
UID:6017-1790420400-1790424000@assetonline.org
SUMMARY:Artificial Intelligence (AI) in Modern Pharmacy: Molecules to Medicines
DESCRIPTION:AI in Pharmacy Flier_US\nREGISTER Here \n ASSET Bioinformatics Workshop 2026 \n(Open to All) \nArtificial Intelligence (AI) in Modern Pharmacy: Molecules to Medicines \nModerator: Dr. Sumaya Sanober\, Ph.D.\nDepartment of Computer Science\nOld Dominion University\nNorfolk\, VA\, USA \nInstructor: Maseera Siddiqui\, MS\nDepartment of Pharmacy\nJawaharlal Nehru Technical University\nHyderabad\, TG\, India \n                                         Online Program | Every Saturday | September 26 to November 7\, 2026 \n                                         11:00 AM to 12:00 PM (EST)  |  8:30 PM to. 9:30 PM (IST) \n\nASSET presents “Artificial Intelligence (AI) in Modern Pharmacy: Molecules to Models”\, a six-session course offered under the ASSET Bioinformatics Workshop 2026 series. Running every Saturday from September 26 to November 7\, 2026\, this program is designed for high school students\, university students\, and professionals seeking to learn how AI is transforming pharmacy and pharmacology through computational drug discovery\, precision medicine\, molecular modeling\, predictive pharmacokinetics\, automated dispensing\, and data-driven therapeutics while exploring STEM and healthcare-related careers. All AI- and pharmacy-loving individuals are welcome.\n\nAbout ASSET Crash Course on AI in Modern Pharmacy: From Molecules to Models\nASSET provides an intensive\, forward-looking curriculum designed to bridge computational data science and pharmaceutical care. Over six structured sessions\, participants explore how artificial intelligence is transforming every phase of the discipline from deep-learning algorithms for molecular docking\, quantitative structure-activity relationship (QSAR) modeling\, and accelerated drug discovery\, to predictive pharmacokinetics\, automated dispensing\, and clinical decision support. The program bridges high-level theory with real-world healthcare applications\, empowering students\, researchers\, and clinicians to navigate next-generation pharmacology. The training culminates in an interactive 7th session: The ASSET AI Pharmacy Quiz Challenge\, a high-stakes\, competitive showcase designed to test your mastery\, reinforce core competencies\, and award recognition and e-certificates to the top performers leading the digital pharmacy revolution. \nYou can review a past seminar session hosted by the team via the ASSET ONLINE AI Workshop to get a feel for their presentation style and event format. \n\nLearning Outcomes\nBy the end of this course\, students will be able to:\n\n1. Understand core pharmacy AI tools\n2. Model computational drug discovery workflows.\n3. Predict clinical trial outcomes.\n4. Optimize smart drug manufacturing.\n5. Improve clinical medication safety.\n6. Navigate AI ethics responsibly. \nMaseera Siddiqui Slides_AI in Pharmacy-Class I_26Sep26\n\nClass 1 (Week 1) – September 26\, 2026\nUnderstanding AI: Foundations for Pharmacy\nTopics:\n> AI basics\n> Types of pharmaceutical data\n> Where AI fits across the drug life cycle\n> Generative AI\n> Machine learning vs Deep learning\n> Natural Language Processing\n> Computer Vision\n\nMaseera Siddiqui Slides_AI in Pharmacy-Class 2_3Oct26\n\nClass 2 (Week 2) –  October 3\, 2026\nFrom Molecule to Medicine: AI in Drug Discovery\nTopics:\n> Target Identification\n> Virtual Screening\n> Quantitative Structure–Activity Relationship (QSAR)\n> Molecular Docking\n> Protein Structure Prediction\n> ADMET\n> Predictive Toxicology\n> Workflow: Disease →Target→ Compound Library→ AI screening→ Molecular Docking→ ADMET Prediction→\n—>Lead Candidate\n\nClass 3 (Week 3) – October 10\, 2026\nAI in Clinical Trials and Precision Medicine\n> Preclinical Prediction\n> Biomarker Discovery\n> Virtual Animal Models to Test Compound Safety\n> Patient Stratification\n> Trial Recruitment\n> Treatment-Response Prediction\n> Pharmacogenomics \nClass 4 (Week 4) – October 17\, 2026\nSmart Pharma: AI in Formulation\, Manufacturing and Quality \n> Formulation Optimisation\n> Process Analytical Technology\n> Smart Manufacturing\n> Computer Vision\n> Predictive Maintenance\n> Batch-quality prediction\n> Supply-chain Applications \n\nClass 5 (Week 5) – October 24\, 2026\nAI in Clinical Pharmacy and Pharmacovigilance \n> Prescription Screening\n> Drug Interactions\n> Dose Optimization\n> Medication Errors\n> ADR detection\n> Safety-signal identification\n> Natural Language Processing\n> Clinical Decision Support \nClass 6 (Week 6) October 31\, 2026\nThe AI-Enabled Pharmacist: Generative AI\, Ethics and the Future \n> ChatGPT\n> AI-assisted research\n> Medical writing\n> Validation\, bias\, privacy\n> Validation gaps between prediction and real world biological outcomes\n> Regulatory Expectations\n> Responsible AI and Future Pharmacy Careers \n\n7th Session (Week 7) November 7\, 2026\nKnowledge Check (ASSET Test)\nRecap of the Artificial Intelligence (AI) in Modern Pharmacy (AIPA) Course &\nAIPA Quiz*\n(Winners\n$50  (1st)\n$40 ( 2nd)\n$30 (3rd)\n$25 (4th)\n$20 (5th)\n$10 (6th to 10th)\nand a Certificate of Completion from ASSET\nNote: To qualify for “AIPA ASSET Quiz”\, students must attend all six (6) sessions needs to be ASSET Annual Member.\nFor ASSET Membership click here ——>>> USA – India\n\n\nGuest Speakers\nTo Be Decided (USA)\nTo Be decided (UAE))\nTo Be Decided (India)\n\nWorkshop Pre-requisite:\n          * should have background knowledge in STEM\, specifically in chemistry.\n* Provide your complete information (Full Name\, School & Country). If not\, you will NOT be eligible for the Prize Money\nand Certificate.
URL:https://assetonline.org/event/artificial-intelligence-ai-in-modern-agriculture-the-future-of-the-smart-farming-bioinformatics-workshop-2026/
LOCATION:Online\, Norfolk\, VA\, MA\, United States
ORGANIZER;CN="ASSET":MAILTO:info@assetonline.org
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