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Advancing Big Data in Pharmaceutical Manufacturing

Improve Productivity and Efficiency Through Predictive Analytics


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Overview

Almost every pharmaceutical company uses Hadoop in some capacity to unlock the value of its rich data sets. Combining structured and unstructured data in an enterprise data lake enables pharmaceutical companies to geta 360-degree view of machine-generated data, and provides the foundation for advanced analytics to uncover valuable insights that can increase manufacturing process efficiency.

Price and quality are key considerations in the purchasing decision of any product. Pharmaceuticals and medical equipment are no exception. The processes used in the manufacture of a drug or medical device has direct impact on product quality, yield and cost. This is why it is so important to continually maintain and improve production efficiencies.

The Pharmaceutical and Medical Device industries have the added dimension of the Federal Drug Administration (FDA). FDA regulations extend into the manufacturing process. Changes in the manufacturing process of an already approved drug or device cannot adversely affect quality, pass FDA scrutiny and maintain FDA approval.

Every annual percentage increase in manufacturing yield can equate to significant increase in line output. For this reason, Pivotal is working with partners and customers to address func- tional and performance bottlenecks that limit data analytics and insights on manufacturing line yield performance, while ensuring (and even improving) quality control.

Advancing Big Data in Pharmaceutical Manufacturing

Scale-out storage combined with massively parallel processing analytics and in-memory computing is required to glean and operationalize insights from large volumes of disparate machine data. The potential gains include:

  • Identifying the data’s combined and interrelated impact on yield
  • Analyzing related events to identify corrective and preventive actions
  • Building on existing yield gains by mining data down to the finest level

Pivotal provides the business intelligence and analytics capabilities needed for a highly-automated manufacturing environment.

The Enterprise Data Lake, Brought to Life By Pivotal

An enterprise data lake is a place where data from any source, in any format, can be preserved and mined for actionable insights. It enables deep analysis by data scientists as well as the creation of analytic models. Model output is saved and (most importantly) can be utilized to effect change in the operations of the factory, product and equipment maintenance, and more.

The physical composition of an enterprise data lake is commodity hardware clustered for massive scale with low cost storage of data. The power and promise of the enterprisel data lake is brought to life with technology from Pivotal and its strategic partner Hortonworks.

Hortonworks HDP for storing and accessing data from any source, in any format

Pivotal HDB for SQL access to data and deep analytic modeling

Apache MADlib (incubating) for processing analytic models natively in Pivotal HDB

Spring Cloud Data Flow for data ingestion, transformation, and enrichment

Pivotal GemFire for event stream analysis - take action to effect change

What does this mean for Manufacturing and the Manufacturing Process?

With Pivotal’s help, pharmaceutical and medical equipment manufacturers can gather data from:

  • Various databases (e.g. materials)
  • Live equipment on the factory floor (e.g. temperature)
  • Alarms and test results

The data can be continually integrated and fed into operational systems for:

  • Process monitoring and control
  • Quality assurance
  • Order fulfillment and shipping
  • Regularity compliance and submission

With the help of a Pivotal powered enterprise data lake, the manufacturing process operates at maximum efficiency; producing products of the highest quality and ensuring regulatory compliance.

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