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Good Reads: Half of FDA GMP Warning Letters Tied to Batch Failures

2012-05-24T15:25:07Z

Opportunities abound for the adoption of best practices and better process intelligence in pharma manufacturing. A recent eye-opening analysis in In-Pharma Technologist revealed that in 2011 nearly half of all FDA Good Manufacturing Practices (GMP) warning letters sent contained references to the companies’ “…failure to thoroughly investigate batch failure.” The article also highlighted the warnings companies received for failure to establish or follow written policies and procedures.

Companies that establish best practices such as those found in a QbD framework not only decrease regulatory warnings and costly investigations but also reap many business benefits: faster time to market, lower cost of goods, more efficient tech transfer and scale up and many more. Learn more about how companies have embraced a process intelligence culture in our customer case studies.

-- Bob Di Scipio

Process Intelligence Outlook: Getting Products to Market Faster

2012-05-10T15:37:10Z

If you attended last week’s Interphex Conference you may have noticed that the word “Process” showed up in many session titles. Process Understanding, Process Validation, Process Improvement and Process Intelligence appear to be moving from buzzwords to substantive, resourced initiatives in biopharma manufacturing.

Factors such as patent expirations, downward price pressure (from generics and legislators) and unpredictable clinical results have put pressure on process development and manufacturing operations to accelerate the commercialization of approved products with higher quality and better margins. Many life sciences companies are realizing that investments in manufacturing technologies, the adoption of a Process Intelligence culture and initiatives such as QbD and PAT can help them achieve their objectives. In a recent PharmTech Talk article, Patricia van Arnum discusses the state of pharmaceutical manufacturing based on her recent Interphex experience:

“Driven by quality-by-design principles, companies are seeking ways to enhance their process understanding and build better control strategies based on that understanding in their manufacturing processes. Strategies for risk assessment and risk mitigation have been an important theme among the conference sessions as well as the tools, such as process analytical technology (PAT), which can be used to better that understanding.”

Biopharma companies are using IT tools such as Aegis’ Discoverant to help meet the afore-mentioned goals. As Gartner recently noted in its recent report on Cool vendors in Manufacturing Operations:

“Unlike conventional statistical analysis tools that require staged data, Discoverant employs an underlying data model and device connectors to provide users with a central point of access to disparate sources of process and product data…For life science companies, it helps enable a more efficient technology transfer and process scale-up.”

Learn more about the Discoverant data aggregation, analytics and reporting platform in Aegis’ presentation, A Process Development and Manufacturing Intelligence Platform to Enable Process Understanding, Continuous Quality Verification (CQV) & Real Time Release.

-- Bob Di Scipio

Process Intelligence Outlook: New Process Validation Guidance Fuels Need for QbD

2012-05-03T15:11:05Z

It’s been more than a year since the FDA issued its new guidance, “Process Validation: General Principles and Practices,” which describes process validation in three stages–Process Design, Process Qualification and Continued Process Verification. The guidance helps pave the way for companies struggling to implement a Quality by Design (QbD) framework, providing the necessary justification. As stated in a recent PharmPro article: “To support a final quality assurance approach to manufacturing, it is the information and knowledge gained from pharmaceutical development studies and process characterization studies that lead to an effective quality control strategy, based on scientific understanding.”

This guidance represents a dramatic shift from the practice of demonstrating process validation with “three batches” to a much more programmatic, scientific-based approach to establish process understanding and apply it to greatly enhance product predictability and reduce risks. The article shares a useful framework to help guide companies through the transition to a QbD approach.

Companies that adopt QbD and implement best practices for data analysis to achieve a culture of process understanding will reap greater rewards, including:

Reduced batch failures
Lower final product testing and release costs and reduced operating costs from fewer deviations and investigations
Reduced raw material and finished product inventory costs
Faster tech transfer and regulatory approval of new products and process changes
Fewer and shorter regulatory inspections of manufacturing sites

-- Justin Neway

We're Hiring - Analytics Intern

2012-05-02T14:02:48Z

Aegis is looking for a talented, enthusiastic intern to join our Consulting Team as a full-time intern or contractor from June 1, 2012 to Dec. 31, 2012. The Analytics Intern will assist with implementing process monitoring systems, statistical investigation and provide general analytic consulting support using Aegis’ Discoverant software. This individual will work collaboratively with Aegis’ Consulting Team, under the supervision of a Senior Analytics Specialist, and may provide an entry-level individual with the unique opportunity to gain applied analytic experience in the life sciences industry.

Click here for full job description.

Good Reads: FierceBiotech’s Future of BioPharma Manufacturing report

2012-04-26T17:57:05Z

Process and automation. These two themes jumped out at me when I read a recent report from FierceBiotech titled “The Future of BioPharma Manufacturing.” It highlights pharma’s slow pace of adopting practices and technologies that help “…control quality, save money and increase efficiency,” then notes areas of achievement and opportunity. The report points to semiconductor manufacturing as an example of an industry that has embraced process modeling and data analysis for manufacturing improvements and suggests pharma companies can follow suit:

“Ideally, companies can combine process modeling with other software and equipment that monitors processes in real time and offers ongoing advice about when and how to intervene to ensure quality output.”

The report also discusses the problem with paper – and I would add “spreadsheet madness” – which impairs quality control due to human error and a slow, reactive response time. With automation tools and practices in place business users reduce risk, save time, boost productivity – and avoid costly mistakes – through real-time process understanding. McKinsey & Co. notes: “Advanced real-time process automation technology – combining computer software, hardware, and machine controls – will help to deliver greater manufacturing flexibility, improved yields and better quality.”

Companies that embrace a process intelligence culture focused on people, process and automation represent the future of biopharma manufacturing characterized by risk reduction, leaner supply chains, science-based decision making and, ultimately, greater profitability.

-- Justin Neway

Good Reads: CMOs Innovate to Differentiate

2012-04-19T19:22:46Z

One trend I’ve noticed in meeting with customers that was validated in an article in this month’s issue of Life Science Leader is that innovation has bubbled up to become a key driver in the selection criteria for CROs and CMOs. In a Q1 2012 survey by Nice Insight, innovation, defined as “the ability to improve in-house capabilities with customized solutions,” was added to the list of partner selection criteria, joining quality, reliability, productivity, regulatory track record and affordability.

The article goes on to explain that CMOs are applying innovation in numerous ways—from breakthrough science, to better business practices and problem solving. For example, they are using technology tools for collaborative process intelligence and data sharing with sponsor organizations and to gain process understanding to improve their own businesses as a key differentiator.

-- Geri Studebaker

Aegis News: Discoverant Applauded in Gartner “Cool Vendors” Report

2012-04-16T15:17:37Z

This week Aegis was profiled in Gartner’s “Cool Vendors in Manufacturing Operations, 2012” report. According to Gartner authors Leif Ericksen and Simon Jacobson, the five companies named in the report exemplify innovative solutions addressing high priority manufacturing operations issues, such as product quality and safety.

The report discusses a rising trend in IT investments that help with collaboration and decision making. In reference to Discoverant specifically the report states:

“Unlike conventional statistical analysis tools that require staged data, Discoverant employs an underlying data model and device connectors to provide users with a central point of access to disparate sources of process and product data…For life science companies, it helps enable a more efficient technology transfer and process scale-up.”

- Bob Di Scipio

Good Reads: Process Mapping as a Starting Point for Better Understanding

2012-04-05T19:18:58Z

In Contract Pharma’s, “Process Mapping: Why we need a “robust” process mapping system,” the author discusses the importance of a mapping system with the following attributes:

“Robustness: The process can be replicated by different people, with different backgrounds, under different conditions, to yield the same results. This is important to preserve the process knowledge and ensure it is not affected by personal bias or from any other particular condition.

“Efficiency: This can be described in terms of how good the communication is between stakeholders despite different backgrounds, and the ability to coordinate efforts according to the complexity of the system and the pre-defined level of information required.

“Maintainability: This is the property that a process map must possess, as the process may change. This easily happens when we start to map a process during the development phase. Accommodating change without losing information, redoing work or being forced to perform further analysis are all important when completing the process map.”

The article compares available process mapping tools, favoring the IDEF-0 technique which, according to the author, provides the most robust, systematic approach that moves companies from subjective- to objective-based decision making.

He notes, “…mapping is a critical activity when we have to analyze a process in order to gain a better process understanding.”

-- Justin Neway

Process Intelligence Outlook: An Evolution of Business Intelligence

2012-03-28T15:03:37Z

I’ve run across a few blog posts over the years that discuss the differences between process intelligence and business intelligence (BI). In Gartner’s “Process Intelligence and Business Intelligence: Do They Share More than a Word?” Jim Sinur shared: “I believe that process context and near real time adjustment adds new dimensions that BI has not considered, but I believe that PI and BI share some common components and behavior.”

I believe process intelligence is a key evolutionary complement to BI and Manufacturing Intelligence (MI), providing access to real-time data for all areas of business including Operations and Manufacturing. So what makes process intelligence different and how do life sciences manufacturing organizations instill a process intelligence culture?

I like this definition from Software AG’s Matt Green: “PI is a fundamentally different approach to intelligence gathering and utilization. Built from the ground up with the end user in mind, PI is a collection of tools that interact seamlessly with each other to give the user the functionality they need when they need it.”

Process intelligence answers the question “why did it happen?” in addition to BI’s “what happened?” At the crux of a Process Intelligence culture is how well organizations bring together people, processes and technology to provide data-driven decision making. Forward thinking life sciences companies are incorporating solutions like Discoverant to provide user-centric access (e.g., Manufacturing, Quality, Tech Transfer) to different types of data found in traditional IT, OT and BI systems for continuous process understanding across geographically dispersed manufacturing networks.

Watch for more to come on best practices for creating a Process Intelligence culture…

-- Joe Rothman

Good Reads: Costs of Poor Quality Quickly Add Up

2012-03-23T14:47:43Z

A recent article in PharmaManufacturing discusses the obvious and more subtle costs of poor quality for pharma manufacturers, including regulatory fines, tarnished corporate reputations, bad batches and wasted raw materials, to name a few.

The article also highlights some eye-opening statistics from survey results presented at recent ICH conferences:

Of those who responded, 12% had incurred regulatory costs due to GMP deficiencies.
62% did not calculate the cost of poor quality at their production sites; only 11% had had such programs in place for five years or more.
53% used manual methods to collect, analyze and publish data, with 29% using ERP and 6% using control charts.
Roughly 92% did not evaluate the cost of improving quality against the potential cost of failure.
Only 14% had conducted ROI analyses of their PAT programs.

On a positive note, the survey found that “Those companies that use IT to collect, analyze and report on poor quality costs tend to perform better than those who don’t.” Companies that embark upon QbD initiatives have a better understanding of their manufacturing processes and are better equipped to proactively make business decisions based on science and data.

-- Justin Neway