DEVELOPER TOOLS

Computational biology tools are regarded as key to improving the productivity of the drug discovery process and introducing the efficiency of high-level computations to biology, which has hitherto been largely unaffected by the 'in-silico' revolution. However, while there have been occasional successes, a lot more rigorous validation and case studies are required to increase the penetration levels of computational biology tools in the drug discovery industry. "Although many teething technical problems and lack of quality data are currently restraining uptake, the expected shift of ongoing research efforts from the academic to the commercial arena in the near future will definitely support greater use of these tools in the drug discovery process," remarks Frost & Sullivan Drug Discovery Technologies Analyst, Raghavendra Chitta. While generating a deluge of information, the high-throughput genomics wave has simultaneously created a problem of varying data formats and data incompatibility. Here, computational biology is emerging as the ultimate means of effectively integrating data and enabling accurate comparison of the information derived from discrete data sets. In addition, predictive models based on the systems approach of computational biology tools have enhanced their value for drug discovery purposes. The increased yield of compounds triggered by high-throughput systems coupled with the urgent need to increase drug productivity is placing a premium on the use of computational biology tools by drug discovery firms. The technology will allow for enhanced portfolio management and more effective utilisation of limited financial resources while yielding substantial cost and time savings. "The rewards of a drug discovery program with a tightly integrated in-silico simulation system are astounding, with the ability to prioritise, validate and eliminate targets at a very early stage in drug discovery," notes Mr. Chitta. "The elimination of false leads at an early stage rather than at the clinical trial stage can offer savings amounting to nearly US$200-US$300 million." Currently at an early adopter stage, the world computational biology market is mostly populated by entrepreneurial start-ups. This US$60.0 million market is projected to grow at a compound annual growth rate (CAGR) of 43.5 per cent from 2004-2011 to reach US$751.8 million. Of the four primary segments - pathway modelling and simulation, tissue modelling and simulation, cellular modelling and simulation as well as disease modelling and simulation - it is the latter, which will have the highest growth potential. Currently representing just under half of overall market revenues, disease modelling and simulation will register an impressive CAGR of 54.5 per cent from 2004-2011. Seen as more of a follower rather than a leader when it comes to the adoption and innovation of new technologies, Europe, with 25 per cent of overall market revenues, currently trails the United States that generates nearly 65 per cent of revenues with Asia (dominated by Japan) accounting for the remainder. However, Europe is making strong strides with a host of new initiatives including the EMI-CD project at the Max Planck Institute for Molecular Genetics as well as the European Union-supported COMBIO and EUSYSBIO projects. Even as the market marches forward, challenges remain. For instance, pharmaceutical companies have been cautionary in their approach towards computational biology tools, preferring that all in-silico technologies be validated thoroughly before implementing them. This is likely to prove an extremely expensive proposition for smaller computational biology companies. To some extent, drug discovery companies' conservative approach towards computational biology tools can be attributed to their disappointing experience with the 'gene to drug' concept. The losses sustained due to investments in this failed concept have made drug companies understandably cautious of novel post-genomic tools. "In addressing this issue, companies need to work on generating success stories by developing an in-house compound and taking it till the commercial phase," advises Mr. Chitta. "Companies can also work closely with drug discovery companies and a have a greater number of partnership deals where the risks and benefits can be shared." Already, the increasing number of royalty and milestone payment agreements between computational biology tools vendors and drug discovery companies as well as strategic partnerships bode well for the faster adoption of these tools into drug discovery. If you are interested in a virtual brochure, which provides manufacturers, end-users, and other industry participants an overview of the latest analysis of the Strategic Analysis of the World Computational Biology Markets (F351-55), then send an e-mail to Radhika Menon Theodore, Corporate Communications, at rmtheodore@frost.com with the following information: your full name, company name, title, telephone number, fax number and e-mail address. Upon receipt of the above information, an overview will be sent to you via e-mail. Strategic Analysis of the World Computational Biology Markets