Proteins have long been recognized as critical molecules for diagnosis, tracking and treatment of disease. With the increasing understanding of the role that proteins play in every aspect of our lives, our environment, our health and our safety, the identification and understanding of how the hundreds of thousands of different proteins interact, what they indicate and how they operate is critical. Proteins drive many disease mechanisms, and play a central role within drug discovery, disease diagnostics and a host of related fields.
However, the accurate detection and measurement of multiple proteins continues to be an arduous, expensive and time-consuming process, with three technical limitations of existing state-of-the-art platforms holding back the true potential of multiple protein detection and measurement. These limitations are:
- Limited detection range: Proteins of are present within most samples at very different concentrations; from sub pg/mL levels to mg/mL levels, spanning over 8 logs of concentration range. Existing systems are unable to screen across such a wide range of protein concentrations in one test, requiring complex, costly, and time-consuming repeat experiments and repeated use of precious samples.
- Limited biological relevance: Rather than developing assays (tests) around biological needs, the limited detection range of existing state-of-the-art platforms means multiplexed protein assays are typically confined to a selection of proteins known to be present in samples at similar concentration ranges. This severely restricts the ‘biological relevance’ of many assays. Ideally, proteins could be selected from across the full proteome range to form a biologically relevant multiplexed test, e.g. selections from each of the yellow highlighted areas in the below figure.
- Limited data accuracy: Existing micro-array based protein measurement platforms typically deliver a single data point per assay, as illustrated in the figure below. Such data can be difficult to quantify, and often suffers from a lack of consistency and reproducibility, with high levels of ‘false’ signals caused by non-specific protein-to-protein interactions, bringing assay/test results into question. Ideally, a platform would provide users with a greater depth of information on each assay so that a more accurate and reliable assessment of the assay results can be made.
Longitudinal Assay Screening (LAS), first developed by Inanovate in 2010, directly addresses these three limitations, delivering a new and powerful solution to the detection and measurement of multiple proteins.