Ed Griffen

7 Followers

12 SlideShares 7 Followers

12 SlideShares 7 Followers

Highly experienced, energetic, creative medicinal chemist. • Delivered design successes against potency, selectivity & pharmacokinetic issues with a particular strength in lead generation. • Expert practitioner of data-driven, hypothesis based design. • Experience of working in very wide range of target classes in Oncology, Infection and CNS/Pain. • Lead chemist on 10 projects over 17 years. • Experienced at international working with Swedish, North-American, Indian and Chinese colleagues. Skilled in: • Ligand-based, structure-based and fragment-based design. • Screening design and work up (full HTS, directed screens & libraries, phenotypic screening). • Innovator in computational medi...

medicinal chemistry mmpa toxicology ai interpretable ai drug discovery big data qsar admet medchemica machine learning pharmacokinetics computational chemistry cheminformatics potency toxophore ibsa sar matched molecular pairs dmpk pharmacophore pharmcophore

Aktivität
Info

Extracting actionable knowledge from large scale in vitro pharmacology data

Vor 7 Jahren • 221 Aufrufe

Extracting medicinal chemistry knowledge by a secured Matched Molecular Pair Analysis platform: standardization of SMIRKS enables knowledge exchange

Vor 6 Jahren • 861 Aufrufe

Learning Medicinal Chemistry ADMET rules UKQSAR Sept 2017

Vor 6 Jahren • 661 Aufrufe

SCI What can Big Data do for Chemistry 2017 MedChemica

Vor 6 Jahren • 874 Aufrufe

Explainable AI in Drug Hunting

Vor 4 Jahren • 342 Aufrufe

Emerging Challenges for Artificial Intelligence in Medicinal Chemistry

Vor 4 Jahren • 259 Aufrufe

Pharmacophore extraction from Matched Molecular Pair Analysis

Vor 7 Jahren • 723 Aufrufe

MedChemica Large scale analysis and sharing of Medicinal chemistry Knowledge poster

Vor 7 Jahren • 371 Aufrufe

RSC Hatfield 2018 Kinase meeting : potency patents MMPA approaches

Vor 4 Jahren • 236 Aufrufe

Griffen MedChemica Virtual Tox Panel

Vor 4 Jahren • 338 Aufrufe

Accelerating lead optimisation with active learning by exploiting MMPA based ADMET knowledge with regression forest potency models

Vor 4 Jahren • 185 Aufrufe

MedChemica Levinthal Lecture at Openeye CUP XX 2020

Vor 4 Jahren • 390 Aufrufe

Highly experienced, energetic, creative medicinal chemist. • Delivered design successes against potency, selectivity & pharmacokinetic issues with a particular strength in lead generation. • Expert practitioner of data-driven, hypothesis based design. • Experience of working in very wide range of target classes in Oncology, Infection and CNS/Pain. • Lead chemist on 10 projects over 17 years. • Experienced at international working with Swedish, North-American, Indian and Chinese colleagues. Skilled in: • Ligand-based, structure-based and fragment-based design. • Screening design and work up (full HTS, directed screens & libraries, phenotypic screening). • Innovator in computational medi...

medicinal chemistry mmpa toxicology ai interpretable ai drug discovery big data qsar admet medchemica machine learning pharmacokinetics computational chemistry cheminformatics potency toxophore ibsa sar matched molecular pairs dmpk pharmacophore pharmcophore