Venelin Mitov1, Ghaith Aljayyoussi2,4, Peter Webborn3, Daniel Lill1, Aline Fuchs2, Nathalie Gobeau2, Stephen Brand2
1IntiQuan AG - A ProductLifeGroup Company, 2Medicines for Malaria Venture, 3Independent DMPK consultant, 4Liverpool School of Tropical Medicine
Objectives: The MMVSola web application aims to streamline the drug development process for antimalarial treatments by providing a comparative analysis of candidate compounds based on their physicochemical properties and a common experimental and modelling framework [1,2]. MMVSola was created to assist teams in Lead Optimisation to optimize compounds, ensuring they meet dose criteria for treatment efficacy and chemoprevention without the need for specialist PK/PD simulation scientists, and reducing the necessity for numerous SCID mice experiments. The tool helps to pinpoint optimization parameters and choose the most promising candidate from a series. Methods: MMVSola integrates data from various preclinical experiments and uses PK/PD modeling and simulation of drug concentration and parasitaemia over time to generate comparative dose predictions. It predicts human pharmacokinetics (PK) and pharmacodynamics (PD) using in-vitro experiments, including hepatocyte and microsome intrinsic clearance assay data, preclinical PK assessment from animals, and parasitaemia growth inhibition in-vitro assays. MMVSola was developed in a collaboration between MMV and IntiQuan AG, using the R-packages MMVshiny, IQRtools, and MMVmalaria. MMVshiny orchestrates the high-level user interface, the specification of input parameters, and rule-based imputation of default values for missing inputs. IQRtools and MMVmalaria are the backbone of MMV’s PK/PD modeling and simulation framework. These packages are available under open source licenses [3,4]. Results: For several compounds, MMVSola’s predictions of minimum inhibitory and maximum parasiticidal concentrations have been validated against measurements in humans [5]. The application has demonstrated high utility in comparing pharmacokinetic profiles and dosing regimens of multiple candidate compounds, significantly reducing the time and resources needed for late lead selection. The tool allows for the fewest possible initial inputs to generate a prediction thanks to smartly chosen default values and rules for imputing missing inputs. Through an interactive interface the user can manipulate or tune specific properties of the molecule and see the immediate effects on predicted PK/PD parameters and dose. Users can enter inputs for one compound manually or upload an Excel excerpt file from a ScienceCloud database for multiple compounds at a time [6]. The app keeps track of which parameters were informed from the ScienceCloud input file or entered manually and generates an Excel report for later use. Conclusions: MMVSola represents a significant advancement in the field of antimalarial drug development. Its ability to provide actionable insights early in the development process makes it an invaluable resource for researchers and pharmaceutical companies. By leveraging preclinical data in an efficient way, MMVSola contributes to the global effort to combat malaria. Keywords: MMVSola, antimalarial drug development, pharmacokinetics, pharmacodynamics, dose prediction, mathematical modeling, Medicines for Malaria Venture
[1] https://mmvsola.org [2] https://www.mmv.org/newsroom/news-resources-search/mmv-awards-dr-stephen-brand-led-team-developing-innovative-dose [3] https://iqrtools.intiquan.com [4] https://github.com/MMVverse [5] Ghaith Aljayyoussi, et al. 2022. MMVSola: an open tool for early PK and antimalarial dose predictions. Poster presentation for Keystone Malaria Symposium, Breckenridge, Colorado, April 2022. [6] https://www.mmv.org/newsroom/news-resources-search/optimizing-data-management-streamline-antimalarial-research
Reference: PAGE 33 (2025) Abstr 11578 [www.page-meeting.org/?abstract=11578]
Poster: Methodology - Other topics