Chaste: developing sustainable software for computational biology

Gaining a full understanding of complex living systems is essential to tackling some of the most pressing research questions of the 21st Century, from the processes of early development of an organism to the effects of ageing. This system-level behaviour arises from complex interactions between component processes at many levels of biological organisation. For example, the development of a complex functional multicellular organism from a single cell involves tightly regulated and coordinated cell behaviours coupled through short- and long-range biochemical and mechanical signals.

Recent advances in experimental techniques are resulting in a wealth of high-quality data and detailed, but isolated, descriptions of such complex biological systems. To truly comprehend this complexity, we need computational models, which can link observations to mechanisms in a quantitative, predictive, and experimentally verifiable way. The goal of this project is to produce high-quality software to support this, so that researchers can be sure that their computational models are generating the correct outputs reliably and reproducibly. Our software can then be used to guide the work of biologists in universities, research institutes and industry who are trying to understand how complex biological systems work.

We have already started working towards this goal by developing Chaste, an open-source software library for modelling the behaviour of collections of cells in biological tissues. This involves multiscale modelling - that is combining mathematical models for things that happen in fractions of a second to processes that take years, as well as things that are very small (on the level of individual proteins) to the large scale of the whole body. To fulfil this software's full potential for the benefit of the UK biology research community, we will enable a richer variety of computational models to be simulated using the software, allowing researchers to utilise new high-quality 3D experimental data. We will also upgrade our software to make use of the latest advances in computing and hardware, and introduce new ways that users can interact and interface with the software without expert programming knowledge. In this way, we will accelerate the use of robust, extensible software for using computational models to help understand and interpret complex biological systems.

Chaste is an open-source framework for the simulation of computational models in biology. Chaste provides modules for handling common scientific computing components, such as meshes and solvers for ordinary/partial differential equations, as well as agent-based and multiscale simulations. Re-use of these components avoids the need for researchers to 'reinvent the wheel' with each new project, accelerating the rate of progress in new applications by providing robust, well-documented and continuously tested libraries. Chaste comprises ~500k lines of C++ code and is freely available under a BSD license.

Since its inception in 2005, Chaste has been downloaded >5,000 times by academic and industrial research groups in >50 countries, and has facilitated a large number of leading scientific studies in areas including cardiac electrophysiology, drug safety assessment, cancer biology, and developmental biology.

Since 2015, Chaste has evolved from being developed primarily within a single institution to being multi-institutional, with multinational contributors. However, at a time when the need for robust software for computational approaches biology is urgent and there is an avalanche of high-quality experimental data requiring modelling to fully interpret, we lack dedicated software development funding to fully realise Chaste's potential uptake by the scientific community as a multiscale, multicellular modelling tool. To this end, we propose to hire research software engineers to complete the following objectives:

1. extend existing functionality for multiscale modelling of multicellular populations;
2. upgrade and future-proof our software development infrastructure;
3. improve the interoperability of our software platform;
4. lower barriers to usage and increase community engagement.

The resulting computational tool and associated infrastructure and training resources will be made freely available and will drive forward computational modelling in biology.