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DTSTAMP:20230831T095755Z
LOCATION:Schwarzhorn
DTSTART;TZID=Europe/Stockholm:20230628T110000
DTEND;TZID=Europe/Stockholm:20230628T130000
UID:submissions.pasc-conference.org_PASC23_sess139@linklings.com
SUMMARY:MS5D - Novel Cloud-Based High Performance Computing and Artificial
  Intelligence Approaches to Emerging Computational Problems in Drug Design
  and Material Science
DESCRIPTION:Minisymposium\n\nThe cloud is providing increasing value in th
 e pharma and material science domains. It enables access to a broad range 
 of HPC and AI services and eliminates the need to lock-in a particular har
 dware choice for a long period of time, especially when the physical locat
 ion of the hardware resources becomes less important provided certain secu
 rity, compliance and cost requirements are met. In order to take full adva
 ntage of the wide range of heterogeneous architectures available, it is cr
 itical to continuously optimize and adapt algorithms and approaches to the
  changing computational landscape. In our minisymposium we will showcase f
 our examples of innovative approaches to HPC and AI from the fields of dru
 g design and material science. We demonstrate a computing-as-a-service app
 roach to the unattended, system-agnostic thermodynamic stability predictio
 n of the amorphous drug system and a web-based platform that gives experim
 entalists access to computational workflows directly from their laboratory
  workstation. Finally, we will present an automated workflow for reaction 
 network exploration with the hierarchical AI-driven approach using the exa
 mple of a catalyst for the asymmetric reduction of ketones and a crystal s
 tructure prediction study performed entirely in the cloud.\n\nHigh-Through
 put Ab Initio Reaction Mechanism Exploration in the Cloud with Automated M
 ulti-Reference Validation\n\nUnderstanding the kinetics of a chemical reac
 tion in silico involves mapping out a network of all relevant paths across
  a complex potential energy surface. The complexity of the reaction networ
 k calls for a hierarchy of computational methods: from cheap semi-empirica
 l methods for the initial broad e...\n\n\nLeopold Talirz (Microsoft Resear
 ch), Jan P. Unsleber (ETH Zurich), Hongbin Liu (Microsoft Research), and T
 homas Weymuth and Markus Reiher (ETH Zurich)\n---------------------\nDisco
 vering New Materials with the AiiDAlab Platform: A View into the Daily Rou
 tine of Coupling Experiments with HPC\n\nAtomistic simulations are a cruci
 al tool in materials science for explaining experimental observations, pre
 dicting materials properties and identifying new materials for synthesis. 
 However, the communication loop between computational experts and experime
 ntalists can be lengthy, delaying progress. T...\n\n\nCarlo Antonio Pigned
 oli (Empa, NCCR MARVEL)\n---------------------\nSystem-Agnostic Prediction
  of Pharmaceutical Placebo Stability via Cloud Computing and Experimental 
 Validation\n\nWe present a cloud computing application aimed at the unatte
 nded, high-throughput prediction of thermodynamic stability of amorphous p
 harmaceutical delivery systems. To that end, we discuss the system-agnosti
 c solubility prediction of Vitamin E TPGS and Tween 80 surfactants in Copo
 vidone. Underlying...\n\n\nGeorgios Antipas (Molecular Modelling Laborator
 y); Samuel Kyeremateng, Regina Reul, and Kristin Voges (AbbVie Deutschland
  GmbH); Nikolaos Ntallis, Aybüke Gülkaya, and Konstantinos Karalis (Molecu
 lar Modelling Laboratory); and Lukasz Miroslaw (Microsoft)\n--------------
 -------\nCrystal Structure Prediction on Cloud Based HPC Resources\n\nThe 
 presentation will cover crystal polymorphism as its understanding is imper
 ative within the pharmaceutical industry. Since changes in molecular packi
 ng can result in large differences in targeted properties applicable to bo
 th performance and safety. First-principles crystal structure prediction g
 ...\n\n\nGrahame R. Woollam (Novartis)\n\nDomain: Chemistry and Materials\
 n\nSession Chair: Lukasz Miroslaw (Microsoft)
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