A multiscale model to minimise animal usage in Leishmaniasis drug development

Leishmaniasis is an important 'poverty related neglected disease', impacting on the health of hundreds of millions of people worldwide. The severe scarring associated with cutaneous leishmaniasis often results in long lasting social stigma, whereas visceral leishmaniasis (VL) is responsible for over 40,000 deaths each year. No vaccines exist for human leishmaniasis, though therapeutic vaccines are in clinical trial. The limited treatment options each have significant side effects or ethical limitations on use. Although over 3 million compounds have been screened in vitro against Leishmania in drug discovery projects, approaches in drug development for leishmaniasis have changed little in the past quarter century and whilst animal models have undoubtedly played a role in getting current drugs to the clinic, the financial and ethical costs of animal research and a greater appreciation of its limitations continues to stifle progress.

Here, a consortium of academic institutions (York, LSHTM, Glasgow) and SMEs (SimOmics, Cybula, Pharmidex) are proposing to develop a novel multiscale computational model of VL coupled to a user friendly simulation interface that will, through improved predictive models, i) predict more effective combined therapies using existing and / or repurposed drugs, ii) support the development of new drugs through lead optimisation, iii) identify new immuno-therapeutic approaches and iv) predict the impact of confounding factors affecting efficacy (e.g co-infection & malnutrition). The technology will serve to dramatically increase the capacity for evaluating existing drugs, generate new knowledge on drug immune interactions and provide a driving force for innovative drug discovery while replacing, reducing and refining the use of animals in drug development for this important infectious disease. Given similarities between the leishmaniases and other intracellular pathogens (e.g. TB), and the modular nature of the technology developed, the research will provide a framework for building a platform of computational tools to assist in drug development for a wide range of human and veterinary infectious diseases.

Full details about this CRACK IT Challenge can be found on the CRACK IT website.

Timmis J, Alden K, Andrews P, Clark E, Nellis A, Naylor B, Coles M and Kaye P (2017). Building confidence in quantitative systems pharmacology models: An engineer's guide to exploring the rationale in model design and development. CPT Pharmacometrics and Systems Pharmacology, Volume 6, Issue 3, Pages 156-157, doi:10.1002/psp4.12157.