Genomic and proteomic tools are thought to be the key in increasing the efficiency of drug discovery and development, which not only faces a problem of being a time-consuming process but a lack of standardisation has led to a reproducibility issue.
In addition, since genetic variations elicit varied drug responses in different people, understanding the impact single nucleotide polymorphisms (SNPs) also becomes complicated.
Current research activities aim at going beyond the realm of human genome sequencing to expand the list of identified proteins and genes. This, ultimately, is expected to help in improved understanding of disease mechanisms and the development of corresponding therapeutics.
"These target validation bottlenecks need to be eased with faster, easier-to-use analytical systems, for example, those that can measure biomarkers as surrogate endpoints," says technical insights research analyst Katherine Austin from Frost & Sullivan.
The report, entitled "Drug Discovery-European Advances in Genomics and Proteomics," said that pharmacogenomics studies, which are used to predict an individual patient's response to a specific drug, is an area that researchers need to identify and analyse sequence differences, or polymorphisms and their involvement in drug response.
The complexity of the human proteome will prove a considerable obstacle in terms of resolution and purification of protein mixtures. The report recommends the development of sophisticated techniques to separate the proteins that exist in varied forms corresponding to the functional needs of a cell.
Emerging technologies such as microarrays, automation and robotics are taking genomics and proteomics research to new heights. Indeed, a UK-based initiative using terahertz radiation or T-rays is set to reveal new information about molecular structure and protein interactions through spectroscopy.
"Weeks, if not months, were initially required to elucidate the expression of a single gene," said Dr Austin. "Now, tens and thousands of genes can be studied in a single afternoon."
Several new computer-modelling approaches such as molecular dynamics (MD), ligand docking (LD), pharmacophore modelling (PM), homology modelling (HM) and enzyme-substrate modelling (ESM) are gaining in popularity. Previously time-consuming and skill-intensive assays and preparations can now be achieved thousands of samples at a time and within a few hours.
Since conventional technologies such as 2D gel electrophoresis pose certain limitations, the development of new technologies such as isotope coded affinity tags, 2D chromatographic separation, terahertz pulsed imaging (TPI) and terahertz pulsed spectroscopy (TPS) and protein arrays are also gaining in prominence.
Proteomics and genomics are also achieving prominence in the area of molecular diagnostics. The hope is, that in incorporating this technology, scientists will be able to treat diseases according to specific genetic markers and select medications and dosages that are optimised for individual patients.
SNP-based DNA fingerprinting (a subsector of molecular diagnostics) is already being widely deployed in forensics, wildlife and conservation studies and for establishing paternity. In the future, improved automation, high throughput, scalability and reliability aspects are expected to expand the reach of molecular diagnostics.
The report also describes how molecular test kits, which employ pharmacogenomics, are set to allow physicians to screen patients for potentially life-threatening reactions and side effects before prescribing a particular drug.
"These developments mark the advent of the age of personalised medicine in which the physician will no longer prescribe a drug on the 'one size fits all' basis and would instead customise it to the patient's individual profile," said Dr Austin.
Researchers in Europe have already developed a DNA chip to analyse the effect of genetic variations on the way patients metabolise as many as 25 per cent of all prescription drugs. This chip may also enable pharmaceutical companies to select the appropriate patients for clinical trials.
Ultimately, by using a genetic test to include patients most likely to respond favourably to a drug and exclude those prone to negative reactions, a pharmaceutical