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Tim Hunkapiller, PhD., Partner


Dr. Tim Hunkapiller has been a pioneering presence in computational biotechnology since its infancy 30 years ago and is co-inventor of the largest selling analytical research instrument in the world: the Perkin Elmer/Applied Biosystems DNA sequencer. Through his Seattle, Washington-based company DiscoveryBiosciences, he provides technical consulting and commercialization services to both established and upcoming biotech companies. Given his partnerships with Microsoft, IBM, the Applera group of companies, among others, and his expertise in genetics, immunology and bioinformatics, Dr. Hunkapiller is in a unique position to help client companies thrive in the converging fields of biotech, medicine and IT and become more competitive and commercially successful.

Dr. Hunkapiller earned a PhD from California Institute of Technology and was Research Assistant Professor in the Department of Molecular Biotechnology at the University of Washington until 1998. As a scientist, Dr. Hunkapiller's research focus included molecular immunology, evolution, computational genetics and comparative genomics. He is considered a leading expert on the genetics, genomic organization and functional diversity of the immune system. For the last 20 years, he has also been involved in bioinformatics, algorithm and database development and experimental process optimization.

While at Caltech, Dr. Hunkapiller originated the model for the automated, fluorescent DNA sequencer. The manifestation of this idea in products such as the ABI 3700tm and the MD Megabasetm sequencers catalyzed and enabled the completion of the first drafts of the Human Genome and helped to revolutionize the field of genomics. He continues to work with Applied Biosystems today on improving the throughput and quality of data from these instruments and their associated chemistry.

Dr. Hunkapiller has been Advisor to a number of biotechnology companies as well as technology companies servicing the biotechnology and pharmaceutical industry. These efforts range from helping with SNP association studies for target discovery in breast cancer to the application of novel computer technologies in intelligently searching very large, unstructured text sources to improve intellectual property analysis.


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