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UID:19445-1670922000-1670925600@www.siliconvalleyacs.org
SUMMARY:Optimizing Pharmaceutical Powder Characterization: 5 Key Techniques
DESCRIPTION:Brian Rodenhausen\, Ph.D.\, Anton Paar\n Co-sponsored by C&EN Webinars and Anton Paar\n10am-11am\, Online via Zoom\, Free\, Registration required\n\nMany parameters\, both internal and external\, influence the behavior of pharmaceutical powders. Understanding why and how is the first step in optimizing your process for developing novel pharmaceutical powders.\n\nThis webinar will focus on 5 key techniques for characterizing pharmaceutical powders including methods for analyzing surface area\, particle size\, density\, and flow. Anton Paar Lead Scientist Brian Rodenhausen\, Ph.D. will walk you through each of these techniques\, explaining both the application as well as key developments in the technology and instrumentation.\n\nAfter the webinar\, you will have a better understanding of how powder characteristics combine with environmental elements to impact your powders during all stages – from synthesis to formulation to tablet production.\n\nKey Learning Objectives:\n\nHow to improve the accuracy and consistency of solid dosage forms\nHow humidity and temperature changes affect pharmaceutical powders\nHow accurate density measurements speed up the tableting process\n\nWho Should Attend:\n\nLaboratory Managers\nResearch Scientists\nFormulations Scientists\nQC/QA Engineers
URL:https://www.siliconvalleyacs.org/event/optimizing-pharmaceutical-powder-characterization-5-key-techniques/
LOCATION:Virtual
CATEGORIES:C&EN Webinar
ATTACH;FMTTYPE=image/jpeg:https://www.siliconvalleyacs.org/wp-content/uploads/2022/12/CEN-webinars.jpg
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DTSTART;TZID=America/Los_Angeles:20220126T160000
DTEND;TZID=America/Los_Angeles:20220126T170000
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CREATED:20220107T225541Z
LAST-MODIFIED:20220107T225541Z
UID:18054-1643212800-1643216400@www.siliconvalleyacs.org
SUMMARY:Creating Structured R&D Data for Artificial Intelligence
DESCRIPTION:Will Tashman\, Uncountable and Melissa O-Meara\, C&EN Media Group\nSponsored by C&EN Webinars\n8-9am\, Online via Zoom\, Free\, Registration required\n\nOverview: The most challenging barrier for R&D teams to make use of machine learning and artificial intelligence is not using the best technique\, but having access to clean\, structured data. Current data systems often fall short\, with inputs and outputs not connected\, ambiguity in naming\, and under-specification of results. As a result\, machine learning wins are isolated to teams working on specialized projects. \nWatch this webinar to learn the framework for a modern\, structured\, data management system. When a traditional ELN or LIMS is used\, teams often still work in spreadsheets\, making it impossible for the entire company to benefit from their learnings. A modern system will move scientists out of spreadsheets\, and create a set of data that the entire company can benefit from.\n\n\nKey Learning Objectives: \n\nHow modern data management systems differ from legacy LIMS and ELN systems\nWhy structured data\, and not proprietary algorithms\, leads to success at innovative companies making use of machine learning.\nThe prerequisites for making machine learning work across an organization\n\n\nWho Should Attend:\n\n\nR&D Executives looking to speed up their teams workflow\nTeam Leaders\nLab Managers
URL:https://www.siliconvalleyacs.org/event/creating-structured-rd-data-for-artificial-intelligence/
LOCATION:Virtual
CATEGORIES:C&EN Webinar
ATTACH;FMTTYPE=image/jpeg:https://www.siliconvalleyacs.org/wp-content/uploads/2022/01/Creating_Structured_RD_Data_CEN-Webinar.jpg
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