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Merck Optimises Manufacturing With Big Data Analytics

2/04/2014 by


Pharmaceutical firm uses Hadoop to crunch huge amounts of data so it can develop vaccines faster. One of eight profiles of InformationWeek Elite 100 Business Innovation Award winners.

Producing pharmaceuticals of any kind is an expensive, highly regulated endeavor, but producing vaccines is particularly challenging.

Vaccines often contain attenuated viruses, meaning they’re altered so they give you immunity but not the actual disease, and thus they have to be handled under precise conditions during every step in the manufacturing process. Components might have to be stored at exactly -8 degrees for a year or more, and with even a slight variance from regulator-approved manufacturing processes, the materials have to be discarded.

“It might take three parts to get one part, and what we drop or discard amounts to hundreds of millions of dollars in lost revenue,” says George Llado, VP of information technology at Merck & Co.

In the summer of 2012, Llado was seeing higher-than-usual discard rates on certain vaccines. Llado’s team was looking into the causes of the low vaccine yield rates, but the usual investigative approach involved time-consuming spreadsheet-based analyses of data collected throughout the manufacturing process. Sources include process-historian systems on the shop floor that tag and track each batch. Maintenance systems detail plant equipment service dates and calibration settings. Building-management systems capture air pressure, temperature, and other readings in multiple locations at each plant, sampling by the minute.

Aligning all this data from disparate systems and spotting abnormalities took months using the spreadsheet-based approach, and storage and memory limits meant researchers could only look at a batch or two at a time. Jerry Megaro, Merck’s director of manufacturing advanced analytics and innovation, was determined to find a better way.

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