Most gene expression studies have been performed on “bulk” tissue samples, consisting of millions of cells of various types and functions mixed together. Although such research is extremely useful for comparing general characteristics of tissues – for example, before and after therapeutic drug treatment – they are limited in their ability to inform on the characteristics and responses of different cell types within the tissue. More recently, advances in techniques for single-cell RNA sequencing have made it possible to profile gene expression in individual cells on a large scale, opening up the possibility to explore the heterogeneity of expression within and across cell types. This exciting technology is now being applied to almost every tissue in the human body, with some experiments generating expression profiles for more than 100,000 cells at a time. However, several roadblocks still stand in the way of making full use of this information, including issues related to missing data and scaling up existing bioinformatics analytical tools. Here, I will discuss some of the ways single-cell RNA-sequencing is being used to improve drug discovery and development, as well as some of the challenges we currently face. I’ll also highlight a new approach I am developing to help overcome some of these challenges.
