Despite the need for new innovative therapies, the rate of novel drug development has remained level with about 35-40 new approvals each year (see figure below). One crucial factor restricting the rate of new drug discovery is the limited set of therapeutic gene targets. There are approximately 1,500 approved therapeutic compounds, but they target only about 300 gene products. Most new compounds in testing are directed toward these same known targets.
However, the potential number of drug targets is at least an order of magnitude greater. DrugBank associates over 4,000 targets with the 7,500 compounds in its database, and GeneCards catalogues over 10,000 genes that have data indicating they “cause, predispose, or protect from diseases.” Why does the current pharmacopeia only exploit less than 10 percent of the potentially targetable gene products then?
The problem is that there is still too much unknown about how most gene products actually work. A tremendous amount of genetic information has been amassed and deposited into online databases. Data about how, under certain conditions in some systems, transcription of certain genes increase or decrease, proteins that interact, and genes that are mutated more frequently in certain systems. Almost all of this data, however, is simply correlative. These massive databases simply do not contain the key information required to really understand how genes produce biology. No amount of deep and thorough analysis of the massive amount of information currently stocked away can illuminate how most genes function because there is a critical dearth of information indicating which genes actually drive the biology.
This lack of information about which genes are responsible for biological responses and disease progression stems from the difficulty in obtaining this data experimentally. Data is needed that causally links gene products to phenotypic changes. This requires assays that assess how the perturbation of certain genes changes the responses or characteristics of cells in a model system, and there are few experimental approaches to generate this sort of data efficiently.
Some techniques, such as genomic recombination technologies like transcription activator-like effector nucleases (TALENs) and zinc-finger nucleases (ZFNs), can provide the needed data by disrupting or otherwise altering genetic targets in a precise manner. However, functional analysis tools must be able to assay the roles of large numbers of genes simultaneously. Collecting data on this scale requires parallel measurements in genome-wide functional assays, which is difficult with these gene manipulation techniques.
There are really only two technologies that currently form the basis of techniques for broad-based genetic screens that assess the functions of large numbers of genes in a single assay: RNA interference (RNAi) and CRISPR knockout screens.
Although RNAi and CRISPR loss-of-function screening approaches are effective, their potential to elucidate gene function remains somewhat limited. One limitation is that either approach only looks at the effects produced by the disruption of a single gene within the system. In reality, though, it is rare that one gene produces one trait. Most phenotypes are caused by multiple interacting genes. While loss-of-function screens can be designed to look for interacting genes, such as Bassik, et al. has shown, paired gene screens can only be run on a limited set of a few hundred genes, so efficient combinatorial assessments of interacting genes across the genome is really out of reach at the moment.
Also, disruption of gene function by knockdown or knockout provides only a limited range of functional assays. Genes may also be activated or otherwise functionally modulated to produce biological responses. Although RNAi can only be used for loss-of-function screens, CRISPR has shown some potential in screening for the activation or gain of genetic function. There is the potential, then, for the development of more sophisticated CRISPR-based screens that assay for genetic changes activating new pathways or bringing about novel biological transformations that may well elucidate disease development.
Thus, while RNAi and CRISPR loss-of-function screens provide one of the few effective approaches currently available for genome-wide functional screening, they are not sufficient to meet the daunting challenge of understanding how genes produce biology. Progress in identifying novel therapeutic targets will continue at a glacial pace until more advanced techniques are developed to address the challenge of teasing out the complex genetic networks that drive and control cellular responses and processes.
New Drug Approvals and R&D Expenditures on Annual Basis. The number of new drugs with novel mechanisms approved each year by the FDA (left axis) as compared with the annual expenditures reported by pharmaceutical companies in the 2014 Biopharmaceutical Research Industry Profile published by PhRMA (http://www.phrma.org/profiles-reports).
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