Increasing Adoption of Computational Biology Tools in Drug Discovery Industry

LONDON , August 29/PRNewswire/ --     In a move aimed at augmenting shrinking product pipelines, the drug discovery industry is employing high-level computational biology tools. The industry also expects to reduce the duration of the drug discovery process, especially in toxicology and drug efficacy studies.

New analysis from Frost & Sullivan (www.biotech.frost.com), World Computational Biology Markets, reveals that revenues in these markets totalled USD 60.0 million in 2004 and can reach USD 751.8 million in 2011.

An increase in royalty and milestone payment agreements is strengthening strategic partnerships between computational biology tools vendors and drug discovery companies This, in turn, is nurturing the faster adoption of these tools in drug discovery.

The U.S. Food and Drug Administration's (FDA) pronouncement of in-silico biology (model-based drug development) as an important step in improving drug development knowledge management and decision making, has provided further support to this adoption. Besides using it, FDA scientists are also collaborating with others in the refinement of quantitative clinical trial modelling using simulation software to improve trial design and predict outcomes.

The advent of HTS and ultra HTS (uHTS) has created a huge number of drug candidates increasing the need for the drug discovery for computational tools to investigate ADME/TOX properties at a very early stage to arrive at decision of which of drug candidates can be pushed into clinical trials stage.

"Use of computational biology tools eliminates false leads at the early stages of drug discovery," says Frost & Sullivan Industry Analyst Raghavendra Chitta. "This helps cut down costs since the later stages are more expensive and time-consuming."

Nevertheless, adoption of these tools is still in its initial stage. As pharmaceutical companies that have invested heavily in computational tools after the Human Genome Project are yet to see any tangible returns, there exists a natural scepticism about their efficacy.

Therefore, computational biology companies have to quantify their productivity increments through wet lab experiments to substantiate their claims. The need of the hour for computational biology companies is to generate success stories by working on in-house compounds and taking them to their commercial phase.

For the increased uptake of computational biology tools it is essential to have qualified software developers trained in biology, chemistry, and the specific methods of modelling and simulation needed to interpret data to improve the research process. Many countries are setting up new academic programs tailored to meet this specific demand.

Companies also have to be prepared to deal with the technical inertia among biologists who consider it very difficult to implement the complex biological system using a series of differential equations and prefer instead to use traditional methods.

"Computational biology works by integrating data from various sources to model a biological process," says Chitta. "Although genomics has generated a huge deluge of information, it has also created a new problem of varying data formats incompatible with each other."

The increasing transfer of knowledge from the academic to commercial sector and the drive toward data standardization through the systems approach are likely to solve these challenges.

After the series of consolidation, which took place in the pharmaceutical industry, these companies are looking for a single large technological platform that can satisfy a multitude of their research needs. Computational biology companies need to pattern themselves to meet these requirements in order to utilize this opportunity.

World Computational Biology Markets is part of the Drug Discovery subscription. It evaluates pathway modelling tools, tissue modelling tools, cellular modelling, and disease modelling tools. Analyst interviews are available to the press.

(4/10/05)