For 37 hours this June the entirety of the 250,000 processor SuperMUC supercomputer (one of the largest computers in the world, located in the Leibniz Rechenzentrum, Leibniz Supercomputing Centre, LRZ, near Munich, Germany) was dedicated to simulations investigating how candidate drugs work in a range of disease cases.

The study was designed by a team at UCL, as part of a long term project to use computer simulations to inform personalised medicine – customizing treatment regimens for specific patients – and drug design.

The use of the full capacity of the machine for a single study was unprecedented, and a one day workshop was organized on December 13th to celebrate its successful execution bringing together the scientists involved with researchers and staff at LRZ who helped to make it possible.

The team responsible for the simulations (Agastya Bhati, Srdan Jovanovic and David Wright), along with group leader Peter Coveney, presented results produced by the study.

These included a recently published [1] improved methodology for computing the strength of drug binding, as well as differences observed between candidate drugs and illustrating the influence of the two most common mutations responsible for acquired resistance to major anti-breast cancer drugs (such as Tamoxifen and Raloxifene).

The workshop also discussed future collaborations, including the use of Big Data approaches in simulation analysis and continuing the groups collaborations within the EU funded CompBioMed project.

At the end of the workshop both UCL and LRZ team members toasted the achievement.

[1] “Rapid, accurate, precise and reliable relative free energy prediction using ensemble based thermodynamic integration”, A. P. Bhati, S. Wan, D. W. Wright, and P. V. Coveney, J. Chem. Theory Comput., Available Online (2016), DOI: 10.1021/acs.jctc.6b00979