Robert Foster, Lhasa Limited - Qepler Summits And Conferences

Robert Foster

Senior Scientist
Lhasa Limited
United Kingdom
Lhasa Limited is a not-for-profit organisation and educational charity that facilitates collaborative data sharing projects in the pharmaceutical, cosmetics and chemistry-related industries.

Rob completed his masters in Chemistry in 2009 at the University of Sheffield before staying on to complete a PhD in organic chemistry, investigating novel synthetic routes towards pyrazoles using sydnones in cycloaddition reactions, under the supervision of Professor Joseph Harrity.

Having completed his PhD in 2012, Rob spent the next 4 years working for a contract research organisation undertaking various custom and contract synthesis projects for the pharmaceutical and agrochemical sectors. A move away from the laboratory in 2016 brought Rob to Lhasa where he has been involved in the scientific research and development of various Lhasa products.

Initially Rob deciphered metabolism data for predictions of metabolic fate in Meteor and forced degradation pathways for Zeneth, before moving onto developing alerts for multiple toxicity endpoints in Derek and writing AOPs for carcinogenicity in Kaptis. Since 2020, Rob has predominantly focused on the development of genotoxicity solutions at Lhasa in his current role as lead scientist for Sarah (Lhasa’s statistical-based tool for mutagenicity predictions) and Lhasa’s ICH M7 solution.

Related Sessions:

3rd Annual Genotoxic Impurities
in Pharmaceuticals Summit 2023

Genotoxic Impurities in Pharmaceuticals strategies & new methodologies: analysis, in silico & regulations.
  • 09 Mar 2023
  • Virtual,
  • Pharma
Day 2: Friday, 10 March 2023
CASE STUDY: Development of in silico systems for expert review under ICH M7 guideline: increasing efficiency through automated arguments
  • Software can provide solutions for all aspects of an ICH M7 workflow
  • Expert review is valuable for resolving predictions from 2 (Q)SAR models
  • Common arguments used in expert review for recurring prediction scenarios have been published
  • Implementation of a semi-automated expert review feature into in silico tools can increase efficiency and consistency of expert review
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