MMVSola : the science of predicting compound power

Dr Stephen Brand

In 2020, MMV developed the innovative, free, user-friendly application ‘MMVSola’.

MMVSola combines information on the chemical, physical and biological properties of a compound to predict the human dosage required to clear all malaria parasites from a patient. It uses state-of-the-art mathematical modelling to consolidate data from different preclinical experiments, seamlessly translating the results into predictions on the clinical activity of different drug candidates in humans. This means that, for the first time, an accessible application can be used to predict dosing and treatment durations for potential antimalarial candidates as early as the discovery phase. This helps identify the best possible candidates and design better and more informative clinical trials.

It also removes the need for animal efficacy studies, saving crucial resources, reducing animal usage and expediting drug development timelines. MMVSola will also help standardize malaria drug discovery data so that laboratories can collaborate more effectively. MMVSola is a powerful and innovative tool, which can be used to select drug candidates and transform early drug development.

In this interview, Dr Stephan Brand discusses the MMVSola project.

1. Could you briefly introduce us to MMVSola?

MMVSola is a free, web-based tool based on a well-established methodology developed by MMV and launched in 2020. It performs human exposure and dose predictions for antimalarial compounds using preclinical data. We have specific dose and parasite-reduction criteria for our clinical candidates – aiming for a single-dose combination treatment of less than a gram to cure a typical adult. MMVSola allows teams to confirm compounds are in line with these criteria from the early discovery stages and, if not, identifies which of the compound properties are best to focus optimization on.

Beyond malaria drug discovery, MMVSola’s human pharmacokinetic prediction capability can be freely used for drug discovery in any other therapeutic areas.

2. What are the main advantages of MMVSola?

The tool allows researchers to take early (and limited) data and perform a preliminary estimation of the efficacious dose in humans by the discovery teams without the need for an expert. As predictions are made using in vitro and limited animal data, MMVSola can be used early, before investing in expensive and time-consuming experiments. It also identifies key compound properties for further development during the lead optimization phase, including potency, metabolism and protein binding. By using this tool for all our discovery projects, we also aim to standardize the comparison of compounds across projects.

3. Where does the name MMVSola come from and who did you partner with to develop it?

MMVSola was named to commemorate Suresh Solapure, who tragically passed away recently and was an early champion of using pharmacokinetic1 / pharmacodynamic2 modelling to predict dosage at MMV. He also contributed to the discovery and development of one of our key candidates. For the pharmacokinetic aspects of the tool, we partnered with Peter Webborn (an independent pharmacokinetic consultant) to develop our predictions of human exposure using a well-established and robust methodology. For pharmacodynamic modelling and tool construction, we worked with Ghaith Aljayoussi (Liverpool School of Tropical Medicine, UK), who also developed the in vitro methodology, which replaces animal efficacy studies. Key members of the MMV modelling team were Nathalie Gobeau, Aline Fuchs and Mohammed Cherkaoui, who supported Ghaith and validated the methodology.

4. Now that you and your team have developed this tool, what are the next projects in the pipeline?

We will now focus on further developing the tool and creating new capabilities. We are aiming to use real-world pharmacokinetic/pharmacodynamic population data to enable predictions for ACPR28 and, importantly, to predict a dose in children and a dose for prophylaxis. We are also providing continuous support to users of the tool and working towards publishing this work.


1. Duration of activity of the drug in the body.

2. The biochemical and physiological effects of drugs in the body.