A unified AI framework for solubility prediction across organic solvents

Antony D. Vassileiou, Murray N. Robertson, Bruce G. Wareham, Mithushan Soundaranathan, Sara Ottoboni, Alastair J. Florence, Thoralf Hartwig, Blair F. Johnston

Research output: Contribution to conferencePoster

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Abstract

We report on the use of a single, unified dataset for machine learning (ML)-driven solubility prediction across the chemical space. This was a departure from the solvent-specific datasets more commonly used.
Original languageEnglish
Pages24-24
Number of pages1
Publication statusPublished - 16 May 2022
EventCMAC Annual Open Day 2022 - Glasgow, United Kingdom
Duration: 16 May 202218 May 2022

Conference

ConferenceCMAC Annual Open Day 2022
Country/TerritoryUnited Kingdom
CityGlasgow
Period16/05/2218/05/22

Keywords

  • machine learning
  • solubility predication
  • Conductor like Screening Model for Real Solvents (COSMO-RS)

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