Best Of Both Worlds: Genentech Accelerates Drug Research With MongoDB & Oracle

“Every day we can reduce the time it takes to introduce a new drug can have a big difference on our patients,” said Doug Garrett, Software Engineer at Genentech.

Genentech Research and Early Development (gRED) develops drugs for significant unmet medical needs. A critical component of this effort is the ability to provide investigators with new genetic strains of animals so as to understand the cause of diseases and to test new drugs.

As genetic testing has both increased and become more complex, Genentech has focused on redeveloping the Genetic Analysis Lab system to reduce the time needed to introduce new lab instruments.

MongoDB is at the heart of this initiative, which captures the variety of data generated by genetic tests and integrates it with Genentech's existing Oracle RDBMS environment. MongoDB’s flexible schema and ability to easily integrate with existing Oracle RDBMS has helped Genentech to reduce development from months to weeks or even days, significantly accelerating drug research. “Every day we can reduce the time it takes to introduce a new drug can have a big difference on our patients,” said Doug Garrett, Software Engineer at Genentech.

Previously, the Genentech team needed to change the schema every time they introduced a new lab instrument, which held up research by three to six months, and sometimes even longer. At the same time, the database was becoming more difficult to support and maintain.

The MongoDB redesign delivered immediate results. In just one example, adding a new genetic test instrument (a new loader) had zero impact on the database schema and allowed Genentech to continue with research after just three weeks, instead of the standard three to six-month delay.

MongoDB also makes it possible for Genentech to load more data than in the past, which fits in well with the “collect now, analyze later” model, something he noted MongoDB co-founder Dwight Merriman has often suggested.

Said Garrett: “Even if we don’t know if we need the data, the cost is practically zero and we can do it without any programming changes, so why not collect as much as we can?”


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