A Biotech Facility Transformed

In less than two years, Boehringer Ingelheim increased productivity fourfold at its newly acquired process development and manufacturing facility in Fremont, Ca.

By Ralf Otto and Frank Steinbach, Boehringer Ingelheim

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In March 2011, Boehringer Ingelheim (BI) acquired an existing biotech manufacturing facility in Fremont, Ca. The decision to purchase the site was driven by three strategic objectives: to secure process development and production capacity for BI’s own range of biomolecules, to extend its global biotech contract manufacturing business, and to give BI a significant presence in the San Francisco Bay area, the largest biotechnology hub in the world.

At the time of acquisition, achieving those objectives looked like a daunting challenge. The site was producing a single commercial product, but BI needed the capability to make dozens of different molecules and to meet the needs of every stage of the development process from toxicology studies and the early clinical phase onward. If the facility were to enter the highly competitive contract manufacturing space, it would also need to dramatically increase its productivity and drive out cost. Quality needed to be on a very high level, both to satisfy regulators and to ensure that products were produced right first time even in a multi product set-up.

Site Vision
Using the strategic objectives as a starting point, and benchmarking Fremont against the best in the world, the site leadership team developed an ambitious vision for the facility. They started with targets for just five key performance indicators: productivity, on time delivery, right first time, ramp-up to multiproduct capability and a measure of staff mindsets. If the metrics were straightforward, however, the targets certainly were not.

For the leadership team, the transformation effort wasn’t just about meeting business objectives. The team wanted Fremont to become a shining star in the BI portfolio and the targets reflected that aim, including a threefold improvement in productivity, for example, and a 50% reduction in production deviations. The time frame was challenging, too: BI aimed to hit its targets within 18 months, while simultaneously making the changes needed to integrate the site into the systems and processes of the wider BI organization, as well as phasing out all infrastructure provided by the previous owner.

To achieve what BI had to do in the time available, the site leadership team designed the transformation effort in two phases. The first phase would deliver a rapid and significant improvement in both performance and staff mindsets, by making the most important, but sometimes painful, changes to the way the plant was operated and managed. The second phase would be about sustaining continuous improvements over the long term, and building world-leading capabilities at the site. 

Critically, companies in the BI network assigned some of their most important biotech development and manufacturing projects to the site, and the site was also successful in quickly acquiring external contract development and manufacturing deals. The steep learning curve in operational execution and positive client feedback from these projects helped the site to gain confidence in its vision and ambitious targets. 

Fast, Phased Change
For the initial phase of the transformation, the site established a steering committee to drive the change process. They knew that whatever changes were made at Fremont would need to be aligned with the wider BI organization, so that committee included representatives from the Global Operations, Quality and Process Sciences functions. The change effort began with a detailed diagnostic of the site. Working with a group of external advisors and biotech experts from within BI, the leadership team spent two weeks examining every aspect of the plant’s operations in order to find opportunities to eliminate waste and improve performance. The diagnostic team’s deep understanding of the unique challenges of biotech production helped them produce hundreds of improvement ideas in that time, with many suggestions also coming from their own staff.

Operating Improvements
About 200 of the ideas identified in the diagnostic process were “quick wins,” changes that cost little to implement, but could deliver substantial improvements on the ground. For example, BI replaced complex pipe jumpers comprising more than 17 components with a much simpler, three-component design. The new design meant reconfiguring connections, which went from a three-hour, two-person job, to a task that took a single operator less than half an hour. Similarly, the introduction of automated small parts washers meant that instead of requiring four people to manually clean components between batches, operationally the facility needed only one.

Making these changes quickly didn’t just give them immediate performance improvements, it also sent a powerful signal to everyone in the plant that BI was serious about the change process, and that the organization was ready to listen to their ideas and invest to put them into action. 

After ‘wave zero’ of rapid improvements, BI started implementing the hundreds of detailed changes that would take the plant to where the company needed it to be. Those changes took place in three subsequent waves of about two months each. Each of these waves was designed to be broader in scope and the number of participating staff than the last. The team started by looking for improvement opportunities within individual functions, before moving on to examine cross-functional interactions, and finally to improvements in the way the plant interacted with its customers and the global BI organization.

The changes made during these phases were profound. A key focus, for example, was in reducing the cycle time to deliver a complete batch of product. By adopting a more aggressive approach to batch scheduling, improving the training of production staff, reducing unnecessary waiting time between steps and by implementing some key technical changes, like the introduction of faster in-process sampling technologies, BI found opportunities to reduce overall cycle time in downstream processing from 23 days to less than a week.

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