AT A GLANCE Joined Glaxo in 1983 and most recently served as divisional director of the molecular sciences division of Glaxo Wellcome. Serves as an expert advisor for the UK’s Biotechnology and Biological Sciences Research Council and several universities on structural biology. Interests include film, music/opera, cricket, and football.
QWhere will bioinformatics be in two years? Five years?
AThe focus thus far has been in sequence analysis and comparative genomics, but going forward the emphasis is clearly moving to analysis of protein data, patterns of gene and protein expression, and biological pathway mapping by analysis of coordinated patterns of expression and protein interaction.
A key area is data integration and automated expert analysis the ability to simultaneously query many different large-scale data sets and make in silico prediction as to protein-protein interactions, biological pathways and networks, ADME/tox profiles, and disease models in whole organisms.
The automation in these analyses is critical as there are numerous algorithms that need to be strung together and applied on a massive scale. Fidelity and robust software engineering combined with a data warehouse concept are key elements so that the information derived from data does not lose its relevance over time.
QWhat are the biggest challenges the bioinformatics sector faces?
ABioinformatics is currently viewed as a source of in silico data that is used in preparation for going into the wet lab. This will remain true, but the balance has shifted dramatically, at least if you buy in to concepts of using all available genomic/proteomic/pharmacology data, not just a tiny slice for essentially traditional work. A major challenge is to convince non-bioinformaticians that in silico predictive methods are highly valid, of high value, and can significantly impact the rate of attrition in target selection and the lead optimization process.
QWhat do you see as the most important task for bioinformatics to address beyond genome sequencing?
AIntegration of large sets of disparate types of biological data and subsequent automated analysis to generate sharply focused hypotheses for lab work that are based on a holistic view of the proteome.
QWho are your current customers? Which additional customer group do you aim to capture?
ACurrent Biopendium customers are Pfizer and Genentech. We are also looking to establish collaborative target and drug discovery partnerships with the aim of moving down the value chain toward a product pipeline.
QWith what companies do you have partnerships?
AWe currently have collaborative agreements with Arrow Therapeutics in the field of antibacterials, and expect to be announcing a further major collaboration in the near future.
QWhat non-existing technology is number one on your customers wish list?
AThe ability to accurately pick the most biologically valid, druggable targets from a sea of possibilities and to match targets to narrow segments of chemical space for lead ID and optimization basically, to reduce gene-to-drug attrition and ineffectiveness.
QHow large is your bioinformatics staff?
AWe currently have a staff of 60 people split between bioinformatics and software engineering.
QDo you expect to see more M&A activity in the sector? Please explain.
AI expect that straight bioinformatics players will have to acquire other platforms (functional genomics, proteomics, chemoinformatics ) to move toward target validation and drug discovery. Bioinformatics platform companies impact at too early a stage in the discovery process to be very high value in the long term, and those companies that are essentially software tool providers have a limited market size.
QWhat made you decide to enter a career in bioinformatics?
AI didnt, my background is experimental protein structure/function and drug discovery. I moved toward informatics as I see it as the driver for efficient discovery of drugs against unprecedented targets.