ManufacturingThe relentless pursuit of value from the vast amount of data we collect is a challenge that all pro-active enterprises face.  In fact, we know this ability is critical to ensuring the ongoing quality of product and process.

The stakes however are being raised even further for pharmaceutical manufacturing firms as the Office of Pharmaceutical Quality (OPQ) at FDA continues to move toward establishing standardized quantitative metrics whose reporting will soon be required in an effort to assess the state of Quality for manufacturing facilities and U.S. marketed products across the industry.

The key to continuous improvement is understanding what our data is telling us about current operations and what it allows us to forecast and pre-emptively manage for the future.  

The challenge of course, is in addressing the numerous sources of data calling for our attention and applying the necessary discernment to address the most relevant stuff.  That is, getting at the most useful view of the information in a timely way that allows us to pick the signal out of the noise.  This would include functionalities that enable us to drill through the layers of information available, visualize the data, filter it as relevant, and analyze for our targeted purposes.  Specifically, one might expect the use of site- and product-specific analytics along with interactive graphs and statistical modeling will be necessary tools.

Pharmaceutical firms however are increasingly faced with the challenge of managing manufacturing networks and quality systems that are the result of multiple legacy systems coming together via the M&A cycle, and gaps inevitably need to be filled.  Supply chain complexity and silos of specialization have also created unique challenges for all life science firms to stay on top of quality across the enterprise.  Common types of data are often contained in multiple sources or not adequately captured at all.  The proliferation of outsourcing has only further complicated the ability to ensure consistency across operations and visualize the one true version of the truth we seek.  Understandably, it can often be difficult to even know where to start. 

For sure, the successful solutions are going to require a robust architecture and involvement from key stakeholders to ensure their various intended applications and purposes are accounted for.

Quality Metrics

Quality.Metrics.Pharmaceutial..jpgThe FDAs partnership with ISPE and recent Guidance on Quality Metrics for the Pharmaceutical industry will eventually force the hand of those firms governed under CDER and CBER regulations, and perhaps this is just the initiative we need to get our housekeeping in order. 

While the Pilot study and Guidance appear to be triangulating toward a common core set of Quality Metrics for reporting purposes such as lot acceptance and complaints rates, most manufacturers realize that there are a significant number of additional manufacturing and commitment-related metrics that bear monitoring relative to their specific operations and products.  They also realize that now is the time to prepare for the eventual regulatory requirements and take advantage of the comprehensive look at Quality Systems to determine what KPIs are truly indicative and plan to manage them going forward.  Doing so promises not only a reduced regulatory burden as the FDA transitions to a risk-based inspection system, but also increased efficiencies in terms of limiting re-work and supply chain interruptions. Integrating data collection and management systems enables quality leaders and their teams with the power of strategic visualization, streamlined processes for reporting and timely decision-making.

To set themselves up for success, pharmaceutical manufacturers need to:

  • Identify key process indicators and decision points.
  • Ensure adequate capture and integrity of mission critical data.
  • Integrate information feeds to a common system.
  • Enable easy and customizable visualization.
  • Ensure compatibility and scalability of the platform.
  • Develop procedures to maintain the system and react quickly to detected problems.
  • Enable electronic data sharing and reporting.
Mapping Strategic Decisions

Although there is no one best way to accomplish all of this, best practices have certainly begun to emerge and lessons learned from similar-scale initiatives can certainly be applied.  A functional mapping of strategic decisions to capabilities needs to take place early in the process and the ultimate solutions must be tailored to the unique demands of your products and supply chain.  Although initial configuration of the system is sure to require an investment of resources from multiple areas (QA, QC, IT, Regulatory, etc.), the benefits promise to be far-reaching.

Beyond meeting the minimal compliance requirements to collect and share relevant data, the right approach to integrating and managing data can also enable higher levels of performance by identifying signals in near-real-time and recognizing trends of concern to avoid future problems. Visualization of key manufacturing insights allows both rapid response to detected problems and predictive power to promote continuous improvement and mitigate both risk and unnecessary cost.

Quality.Metrics.Pharmaceuticals.Paragon.jpgSignificant Benefits

Return on investment is expected to take the form of reduced manual and redundant process steps, human error, and long-term costs of the Quality Assurance program.  Additional - and significant - benefits include improved compliance posture in meeting multi-national surveillance and reporting requirements as well as establishing a framework for a healthy and aware Quality Culture that figures to pay dividends for years to come.

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