MMVSola aims to accelerate the selection of the best candidate drugs.
MMVSola is a free tool that predicts (i) clinical pharmacokinetics (in malaria as well as other diseases) and (ii) the dose required to clear all malaria parasites from an adult patient weighing 50 kg. The tool can be used to make clinical predictions as early as the discovery phase, saving crucial time and resources.
The origins of the tool
MMVSola was named to commemorate Suresh Solapure, a microbiologist and friend of MMV who tragically passed away in 2016. Suresh was an early champion of using pharmacokinetic and pharmacodynamic (PKPD) data modelling to predict drug dosage. This innovative tool was built in 2020 by Dr Ghaith Aljayyoussi (Liverpool School of Tropical Medicine) and Dr Pete Webborn (MMV consultant), with the support of MMV Discovery and Translational team members, and expert external advisors such as Dr Phil Lowe, Prof Malcolm Rowland, Prof Dennis Smith, Dr Anne Cooper and Dr Rob Riley. The tool was launched to MMV’s drug discovery teams in 2020 and is now being made available to the wider research community.
How it works
Validated, state-of-the art mathematical algorithms consolidate data from different preclinical experiments, seamlessly translating the results into predictions of both the drug candidate’s exposure and effect on parasite dynamics. Using these predicted terms, a clinical antimalarial dose is determined. In addition, the tool’s PK prediction function can be used in therapeutic areas outside of malaria as well. MMVSola can be used early, before investing in expensive and time-consuming experiments (though a minimum set of data are required). The greater the amount of data and the more advanced the compound, the greater the power of MMVSola in helping to discover and select the best possible candidates, and subsequently to design better and more informative clinical trials.
→ For more information on MMVSola, please visit the MMVSola webpage.