3D Cellular Imaging in Pre-clinical Drug Development
The pre-clinical drug development workflow includes toxicity evaluation at iteratively higher biological levels: cellular, tissue, organ, and whole organism. The ability to model and image at each of these levels is a powerful tool for molecule evaluation and development.
Ex vivo 3D cellular modeling and imaging is a valuable early step in a candidate molecule’s toxicity evaluation. This discussion focuses on ex vivo 3-dimensional (3D) cellular modeling and imaging. In vivo small animal modeling and imaging is considered in the companion discussion available here.
Capabilities and Benefits
Individual cells within a 3D cell culture provide data regarding a molecule’s sub-cellular effects on general cell functions, such as cell growth rate. 3D cell culture is also used to evaluate toxicity for specific cell types, providing data on tissue and organ functions.
A 3D cell culture allows the cells to grow and the culture to expand in all directions, thereby mimicking a natural microarchitecture. This type of culture provides insight into a molecule’s impact on cell-to-cell interactions in a way that is more physiologically relevant than a 2D monolayer culture. High-resolution imaging of the 3D culture provides valuable information on a molecule’s impact on tissue structure and integrity.
Having relevant, robust, and predictive cellular toxicity data such as this early in the drug development process helps reduce downstream costs by avoiding inadequate toxicity testing that can lead to clinical testing failure.
Needs and Challenges
It can be difficult to obtain high-quality, detailed images of thick cell cultures. One challenge that, when met, helps optimize imaging is the formation of consistently round spheroids that are not attached to the plate or tube. This enables high-resolution imaging of small targeted areas to gather data on subcellular and intercellular processes. Consistent spheroid cultures also reduce the amount of extraneous data that requires processing.
Robust, predictive datasets are needed to make reliable decisions regarding toxicity and downstream workflow steps. Fast imaging time is needed to realize high sample throughput for a more robust dataset. An integrated, automated workflow that is easy to use and modify is also conducive to the generation of robust, targeted datasets.
Another challenge is understanding the implications of using homogeneous animal cell models to predict outcomes in human clinical trials. Again, a robust dataset is needed along with advanced data analysis software to accurately translate cellular toxicity data for downstream use.
Download our whitepaper to learn more about the key issues, implications, and recommended strategies for drug toxicity evaluation using 3D cellular models and in vivo small animal models.