AI and machine learning are powering a step-change in the time and cost of discovery from hit to lead and on to candidate molecule. Computational visualization for multi-parameter optimization shows which chemical changes maximize biological impact and how these affect other molecular properties, while accurate binding affinity calculations help you to zero-in on the variant with the best chance of success.
“As a global computational chemistry team within a contract research organisation (CRO), we aimed to improve the consistency, scalability, and scientific rigor of our molecular modelling workflows across a wide range of client projects. Cresset supported a smooth transition from a previously used commercial tool and helped address key limitations around accessibility and deployment at scale. A differentiated licensing model has enabled broad access across chemistry and biology teams while reserving advanced capabilities for computational chemistry specialists. This approach has helped balance accessibility, scientific depth, and efficient use of resources, enabling wider engagement without compromising rigor. The Cresset team have been highly responsive and knowledgeable, working closely with us to support adoption across a global user base. Training was organised according to user needs, with regular office hours providing an open forum for questions and ongoing support.
Overall, Cresset has become a valuable part of our computational chemistry toolkit, strengthening consistency, productivity, and confidence in decision-making across our organisation.”
Nicola Porta, Senior Scientist, Evotec
We are pleased to be working with Cresset’s software. This provides us with intuitive molecule design, a powerful ability to understand SAR and design plus a fresh way for generating novel and diverse structures for our projects.
Dr Kristian Birchall, Medical Research Council Technology, UK
We really like the powerful combination of excellent software tools and molecular design expertise which we get from working with Cresset.
Dr Graham Sibley, Head of Chemistry, F2G, UK
We wanted to use computational methods to suggest alternative substructures which could replace part of one of our key leads. We’d looked at other tools previously, without success, then turned to the Spark™ field-based approach. We looked at the top 50 hits from Spark and selected a subset to synthesise. Whilst the synthesised compounds exhibited a broad range of activities, we were delighted to observe that a number turned out to be nanomolar hits – with several even more potent than the original lead. One of these compounds is now our key lead against this target and further analogue synthesis is underway. Spark has certainly helped direct us towards some novel and very useful SAR on this occasion.
Laurent Rigoreau, Group Leader Medicinal Chemistry, Cancer Research Technology Discovery Laboratories
Cresset Discovery’s computational experience and high standard of scientific support is ideally suited to help drive the next stage of this project.
Dr Richard Boyce, Senior Director of Research, PhoreMost
The protein interaction potential capability [in Flare] highlighted common features across the family of targets of interest that we had not been able to visualize before. We used this information to drive ligand design into a direction we have not explored before.
Dr Martin Quibell, MAQU Chemistry Consulting, UK
