Presentations

• Using AI to Derive Valuable Insights from Drug Discovery Data
  Segall MD
  EFMC International Symposium on Medicinal Chemistry, 4-8 Sept 2022
• Predicting Reactivity to Drug Metabolism: Beyond CYPs
  Öeren M
  ACS Fall, 21-25 August 2022, National Meeting and Expo
• Guiding Anti malarial Optimisation using Deep Learning Imputation
  Segall MD
  ACS Fall, 21-25 August 2022, National Meeting and Expo
• Accessible AI for Small Molecule Discovery Research
  Mansley TE
  SLAS 2022 International Conference and Exhibition
• Imputation Versus Prediction and Applications in Drug Discovery
  Segall MD
  AI in Chemistry, 28-29 September 2020, Virtual Conference
• Practical Application of Deep learning to Drug Discovery Project Data
  Segall MD
  Alpine Medicinal Chemistry Conference, 30 January – 3 February 2020, St. Anton, Austria
• Practical Applications of Deep Learning to Imputation of Drug Discovery Data
  Irwin B
  AI3SD Network+ Conference, Winchester, UK, 2019
• Mechanism and Prediction of UGT Metabolism
  Öeren M
  ACS National Meeting and Expo 2019, San Diego, USA
• Predicting pK_a Using a Combination of Quantum and Machine Learning Methods
  Segall MD
  12th International ISSX Meeting, Oregon, USA, 2019
• N- and S-Oxidation Model of the Flavin-containing MonoOxygenases
  Walton P
  American Chemical Society National Meeting and Exposition 2019, Orlando, USA
• A Single Deep Learning Model for Confident Imputation of Heterogeneous Drug Discovery Endpoints
  Segall MD
  Gordon Research Conference 2019, Mount Snow, USA
• A Novel Scoring Profile for the Design of Antibacterials Active Against Gram-Negative Bacteria
  Montefiore B
  2nd SCI/RSC Symposium on Antimicrobial Drug Discovery, 2018
• Imputation of Protein Activity Data Using Deep Learning
  Segall MD
  “Streamlining Drug Discovery” Symposia and Exposition, Cambridge MA, USA
• Hydrogen Bonding: Ab Initio Accuracy From Fast Interatomic Gaussian Approximation Potentials
  Öeren M
  ACS Fall 2018 National Meeting and Exposition, Boston, USA
• Capturing and Applying Knowledge to Guide Compound Optimisation
  Champness E
  “Streamlining Drug Discovery” Symposia and Exposition, Shanghai, China; Tokyo, Japan
• Intuitive Workflow to Enumerate and Explore Large Virtual Libraries
  Cooke A
  ACS Spring 2018 National Meeting and Exposition, USA
• Capturing and Applying Knowledge to Guide Compound Optimisation
  Segall MD
  ACS Spring 2018 National Meeting and Exposition, USA
• Translating Methods from Pharma to Fragrances and Flavours
  Mansley TE
  ACS Spring 2018 National Meeting and Exposition, USA
• Integrated Cheminformatics to Guide Drug Discovery
  Champness ED
  ACS Fall 2017 National Meeting and Exposition, Washington DC, USA
• Improved quantum mechanical model of P450-mediated aromatic oxidation
  Leth R
  ACS Fall 2017 National Meeting and Exposition, Washington DC, USA
• Overcoming Psychological Barriers to Good Decision-Making in Drug Discovery
  Segall MD
  UK QSAR and Cheminformatics Group Spring 2017 Meeting, 26th April 2017, Jealot’s Hill, UK
• Combining quantum and QSAR methods for prediction of acid dissociation constants
  Hosseini-Gerami L
  ACS Spring 2017 National Meeting and Exposition, 2nd-6th April 2017, San Francisco, USA
• Confidently Targeting High Quality Hits from High-Throughput Screening
  Segall MD
  ACS Spring 2017 National Meeting and Exposition, 2nd-6th April 2017, San Francisco, USA
• Data visualization: Saying it all in a bite-sized chunk
  Champness EJ
  ACS Spring 2017 National Meeting and Exposition, 2nd-6th April 2017, San Francisco, USA
• Seamless integration of 3D structure-based design and 2D structure-activity relationships to guide medicinal chemistry
  Segall MD
  3rd Drug Discovery Re-Invented Conference, 21st-24th February 2017, Cancun, Mexico
• Predicting interactions of compounds and metabolites with toxicity-associated targets
  Hunt P
  ACS Fall 2016 National Meeting and Exposition, 21st-25th August 2016, Philadelphia, USA
• Which P450: Predicting which cytochrome P450 isoforms are involved in the metabolism of a xenobiotic
  Leth R
  The UK-QSAR Spring 2016 Joint meeting with Physchem Forum, 15th-16th March 2016, Stevenage, UK
• Closing the loop between synthesis and design: Helping chemists to use all the information in compound optimization
  Mansley TE
  ACS Spring 2016 National Meeting and Exposition, 13th-17th March 2016, San Diego, USA
• Bridging the dimensions: Seamless integration of 3D structure-based design and 2D structure-activity relationships to guide medicinal chemistry
  Segall MD
  ACS Spring 2016 National Meeting and Exposition, 13th-17th March 2016, San Diego, USA
• Sometimes the mountain has to move…but you cannot let it realise it’s happening
  Champness EJ
  ACS Spring 2016 National Meeting and Exposition, 13th-17th March 2016, San Diego, USA
• Which P450: Predicting which cytochrome P450 isoforms are involved in the metabolism of a xenobiotic
  Hunt P
  ACS Spring 2016 National Meeting and Exposition, 13th-17th March 2016, San Diego, USA
• Gaussian processes: We demand rigorously defined areas of uncertainty and doubt
  Champness EJ
  ACS Spring 2016 National Meeting and Exposition, 13th-17th March 2016, San Diego, USA
• Data visualization: New directions or just familiar routes?
  Chamness EJ
  ACS Fall 2015 National Meeting & Exposition, 16-20 August, 2015, Boston, USA
• Modeling ABC transporters as potential DILI targets
  Segall MD
  ACS Fall 2015 National Meeting & Exposition, 16-20 August, 2015, Boston, USA
• Quantum mechanical models of P450 metabolism to guide optimization of metabolic stability
  Segall MD
  ACS Spring 2015 National Meeting & Exposition, 22-26 March, 2015, Denver, USA
• Similarity to SAR -Interactive navigation of similarity relationships to guide optimization
  Segall MD
  ACS Spring 2015 National Meeting & Exposition, 22-26 March, 2015, Denver, USA
• Quantum mechanical models of P450 metabolism to guide optimization of metabolic stability
  Segall MD
  Drug Discovery USA 2015 – Advances in Drug Discovery and Design, 9-11 February, 2015, Baltimore, USA
• Addressing Toxicity Risk When Designing and Selecting Compounds in Early Drug Discovery
  Champness EJ
  Congress of Medichem, 18-20 November 2014, Suzhou, China
• Viewing Structured Compound Data in an Unstructured Way
  Champness EJ
  International Drug Discovery Science & Technology, 18-20 November 2014, Suzhou, China
• The challenges of making decisions using uncertain data
  Champness EJ, , Segall MD
• Improving the Chance of Success Where an Outcome Can’t be Predicted
  Segall MD
  ACS Fall 2014 National Meeting & Exposition, 10-14 August, 2014, San Francisco, USA
• Predictive Application of Bioisostere Transformations to Identify Novel High Quality Compound Ideas
  Champness EJ
  ACS Spring 2014 National Meeting & Exposition, 16-20 March, 2014, Dallas, USA
• Addressing Toxicity Risks with Designing and Selecting Compounds in Early Drug Discovery
  Segall MD
  Fusion Enabling Future Pharma, 9-12 July, 2014, Chicago, USA
• Advances in Multi-Parameter Optimisation: Targeting the ‘best’ profile for your project’s objectives
  Champness EJ
  ACS Spring 2014 National Meeting & Exposition, 16-20 March, 2014, Dallas, USA
• Addressing Toxicity Risk when Designing and Selecting Compounds in Early Drug Discovery
  Champness EJ
  ACS Spring 2014 National Meeting & Exposition, 16-20 March, 2014, Dallas, USA
• (Quantitative) Structure-Activity Relationships: Guiding compound design and selection
  Segall MD
  OpenEye CUP XIV, 5-5 March, 2014, Santa Fe, USA
• Finding and Applying Rules for Successful Drug Discovery
  Champness EJ
  BIT’s 4th Annual International Congress of Medichem – 2013, 13-16 November, 2013, Haikou, China
• Multi-parameter Optimization in Drug Discovery: Quickly targeting compounds with a good balance of properties
  Segall MD
  Select Biosciences, ADME and Toxicology 2013, 30-31 May, 2013, New Delhi, India
• Finding and Applying Rules for Successful Drug Discovery
  Segall MD
  GTC 7th Annual Drug Design and Medicinal Chemistry, 8-10 May 2013, Boston, USA
• How to strike the right balance of chemical and biological properties for your compound in discovery?
  Segall MD
  Scinovo, Unlocking the Value of Drug Candidates, 23 April 2013, Stevenage, UK
• Finding Multi-parameter Rules for Successful Optimization
  Segall MD, Yusof I, Champness EJ
  ACS National Spring Meeting 2013, New Orleans, LA, USA
• Exploring the chemical space of screening results
  Champness EJ, Segall MD, Leeding C, Chisholm J, Yusof I, Martinez H, Foster N
  ACS National Spring Meeting 2013, New Orleans, LA, USA
• Multi-parameter Optimisation in Drug Discovery: Quickly Targeting Compounds with a Good Balance of Properties
  Segall MD
  BIT IDDST 2012, Nanjing, China
• Relative Drug Likelihood: Going beyond drug-likeness
  Segall MD, Yusof I
  ACS National Fall Meeting 2012, Philadelphia, PA, USA
• MPO for the masses: Practical application of multi-parameter optimisation to guide compound design and selection
  Champness EJ, Segall MD
  ACS National Fall Meeting 2012, Philadelphia, PA, USA
• Comprehensive comparison of automatically generated QSAR models of target potency
  Segall MD, Gola J (Insylix), Lariviere D, Champness EJ, Leeding C, Yusof I, Chisholm J
  ACS National Spring Meeting 2012, San Diego, CA, USA
• Can we really do computer-aided drug design?
  Segall MD
  ACS National Spring Meeting 2012, San Diego, CA, USA
• Psychology of Drug Discovery: Overcoming barriers to good decision-making
  Segal, MD
  Zing Medicinal Chemistry Conference, Lanzarote, 2012
• Overcoming psychological barriers to good decision-making in drug discovery
  Segall, MD
  Keystone Symposium, Addressing the Challenges of Drug Discovery 2011, Tahoe City, CA, USA
• Multi-parameter Optimisation in Drug Discovery: Quickly targeting compounds with a good balance of properties
  Segall, MD
  Elrig Drug Discovery 2011, September 2011, Manchester, UK
• Guided Application of Med Chem Rules to Generate ‘Good’ Ideas
  Segall, MD
  ACS Spring Meeting, March 2011, Anaheim, CA, USA
• Making Priors a Priority
  Segall, MD
  ACS Spring Meeting, March 2011, Anaheim, CA, USA
• Automatically Finding Drug Discovery ‘Rules of Thumb’
  Tatsunori Hashimoto, Matthew Segall and Ed Champness
  Euro QSAR, September 2010, Rhodes, Greece
• Exploring Project Spaces to Quickly Identify High Quality Compounds
  Champness EJ, Segall MD
  MipTec, September 2010, Basel, Switzerland
• Finding drug discovery “rules of thumb” with bump hunting
  Hashimoto T, Segall MD
  ACS Fall Meeting, August 2010, Boston, MA, USA
• Psychological barriers to good decision-making: How addressing cognitive biases could improve drug discovery
  Segall MD, Chadwick A
  ACS Spring meeting, March 2010, San Francisco, CA, USA
• Visual analyses for guiding compound selection and design
  Champness EJ
  ACS Spring meeting, March 2010, San Francisco, CA, USA
• Guiding the Decision-Making Process to Identify High Quality Compounds
  Segall MD, Champness E, Obrezanova O, Leeding C
  ISSX North American meeting, October 2009, Baltimore, USA
• Enabling Interactive Multi-Objective Optimization for Drug Discovery Scientists
  Champness EJ
  BeLive IT, October 2009, Brussels, Belgium
• Drug discovery – Why gamble when you can count cards?
  Champness EJ
  Bio-IT World Europe, October 2009, Hannover, Germany
• BioInformatics and Drug Discovery-“StarDrop” Drug Discovery Platform
  Segall MD
  Tennessee Biotechnology Association, September 2009, Nashville, TN, USA
• Automated QSAR Modeling to Guide Drug Design
  Obrezanova O, Segall MD
  ACS National Meeting, Spring 2009, Salt Lake City, UT, USA
• Automated QSAR Modeling to Guide Drug Design
  Obrezanova O, Segall MD, Gola JMR, Champness EJ
  Zing Computational Chemistry Meeting, March 2009, Antigua
• Automatic QSAR Modeling of Blood-Brain Barrier Penetration by Gaussian Processes Method
  Obrezanova O, Gola JMR, Champness EJ, Segall MD
  eCheminfo Latest Advances in Drug Discovery Informatics, October 2008, Philadelphia, PA, USA
• Multiparameter Optimisation: Achieving Balance with Confidence
  Segall MD
  MipTec, October 2008, Basel, Switzerland
• ADMET Optimization and in Silico Drug Discovery
  Segall MD
  IBM Life Sciences Modeling & Simulation Summit, September 2008, Amagi Homestead, Japan
• Turning uncertain, multivariate data into effective decisions
  Segall MD
  AAPS Drug Discovery Strategies and Critical Issues for Clinical Candidate Selection, May 2008, South San Francisco
• From Drug Discovery to Drug Design: Uncertain models to certain success?
  Segall MD
  ADMET Europe, February 2008, Stockholm, Sweden
• From Drug Discovery to Drug Design: Uncertain models to certain success?
  Segall MD
  ACS Western Regional Meeting, October 2007, San Diego, CA, USA
• Gaussian Processes: A method for automatic QSAR and ADME modelling
  Obrezanova O, Gola J, Segall M
  ACS Fall Meeting, August 2007, Boston, MA, USA
• Predictive ADME Models in Drug Discovery: Can You Trust Them? Can You Afford Not To?
  Beresford A
  Med Chem USA, October 2007, Boston, MA, USA
• Gaussian Processes: A method for automatic QSAR and ADME modelling
  Obrezanova O, Gola J, Segall M
  UK QSAR, October 2007, Stevenage, UK
• Automatic Model Generation.
  Gola JMR, Obrezanova O
  4th Joint Sheffield Conference on Chemoinformatics, June 2007, Sheffield, UK
• The Journey from Drug Discovery to Drug Design: How far have we travelled?
  Segall MD
  SMI in Silico ADMET, May 2007, London, UK
• Opening the “black box”: Interpreting in silico models to guide compound design.
  Champness E
  ACS Spring Meeting, March 2007, Chicago, IL, USA
• Why are we Still Doing Drug Discovery?
  Segall MD
  ACS Spring Meeting, March 2007, Chicago, IL, USA
• ADME Screening: High Throughput vs High Intelligence.
  Beresford AP
  Med Chem Europe, February 2007, Barcelona, Spain