Virtual Assay: Drug safety and efficacy prediction software.

Case studies

The software

The Virtual Assay software provides a framework to run in silico drug trials in populations of human cardiac cell models for predictions of drug safety and efficacy.

Everyone is different

No two individuals respond to a drug in exactly the same way. Due to sometimes subtle variability at a physiological level, what works for one person may not work for another, even before taking into account any additional complicating factors. This is one of the most significant challenges faced by the pharmaceutical industry; clearly it is neither practical nor desirable to test a new drug on the entire population to ensure it is both safe and effective.

Drug Safety

Ensuring a drug does not have potentially harmful or unexpected side-effects requires a huge amount of rigorous testing before the drug can be approved for clinical use. Even then, unforeseen problems can occur due to patient population variation or exacerbation of other pre-existing diseases. For example, over half of the 40 drugs withdrawn from the market in the last 20 years were withdrawn for unanticipated cardiac effects such as drug-induced arrhythmia, or ‘long QT’ (a prolonged refractory period between ventricular depolarisation and repolarisation).

“Virtual” Screening

To overcome this, in silico human modelling at a cell physiology level is becoming increasingly important in both drug efficacy and safety pharmacology testing. Consequently, it is attracting significant attention from both the commercial sector and regulatory bodies such as the US FDA, UK MHRA, and the European MRA.

Calibrated model populations

Virtual Assay starts with well-understood human cellular biology models and modulates the variables to generate a range, or population, of models, which will respond differently to the same inputs. These populations are then calibrated against experimental data, retaining only those models in Calibrated Model Populations range with experimental observations. Once calibrated, these populations can be used to analyse the effects of different pharmaceutical agents on cellular response at the population level.

Key advantages

  • Human-based methodology
  • Tight coupling between modelling and specific experiments
  • Users can produce models constructed with their own experiments
  • Quantitative prediction of the effects of drugs on cellular function
  • Mechanistic explanation into the causes of drug effects by predicting the effects of drugs and providing an explanation as why and what are the main determinants of the effects
  • Takes into account inter-subject variability in the modelling and simulation
  • Consultancy services also available

Case Studies

You can find here some Case Studies using the Virtual Assay software.  



  • Virtual assay was the winner of the 2017  Safety Pharmacology Society Technological Innovation AwardElisa Passini presented "Virtual Assay: a User-Friendly Framework for In Silico Drug Trials in Populations of Human Cardiomyocyte Models” and received the prize at Safety Pharmacology Society meeting 2017. 
  • Blanca Rodriguez received the MPLS Impact award for the commercial impact on the research of the Computational Cardiovascular Science group on Pharmaceutical companies.
  • Oliver Britton was awarded the 2014 3Rs winner prize by The National Centre for the Replacement Refinement & Reduction of Animals in Research.
  • Oliver Britton was one of the four finalist in the 2014 UK ICT Pioneers awards for his research in Population of Models. Find below the video of the competition.


The software development for Virtual Assay has been supported by the EPSRC Impact Acceleration Account awarded to the University of Oxford and developed in collaboration with Oxford Computer Consultants.

This research is supported by the National Centre for the Replacement Refinement and Reduction of animals in research (NC3Rs). 




Human in silico drug trials demonstrate higher accuracy than animal models in predicting clinical pro-arrhythmic cardiotoxicity. 
E. Passini, O. J. Britton, H.R. Lu, J. Rohrbacher, A.N. Hermans, D.J. Gallacher, R.J.H Greig, A. Bueno-Orovio, B. Rodriguez. Frontiers in Physiology. doi:10.3389/fphys.2017.00668. 8:668. 2017.

Experimentally−calibrated population of models predicts and explains inter−subject variability in cardiac cellular electrophysiology
O. Britton‚ A. Bueno−Orovio‚ K. Van Ammel‚ HR. Lu‚ R. Towart‚ DJ. Gallacher and B. Rodriguez. Proceedings of the National Academy of Sciences.  110 (23): E2098-E2105. doi:10.1073/pnas.1304382110. 2013.


Licences are available now. This license is intended for academics carrying out research and not for use by consumers of commercial businesses.

For commercial use licences visit here

Contact information

For further information about the tool, or to arrange a collaboration, please contact us.