Unifying Recipe Management | Automation.com

Unifying Recipe Management

April 302012
Unifying Recipe Management
Automation.com Exclusive - Part 2 from Pharmaceutical Automation Roundtable (PAR) 2011
April 2012
By Bill Lydon, Editor
This article on Unifying Recipe Management is the second article in a series covering the recent annual Pharmaceutical Automation Roundtable (PAR). The individual PAR group members have a wealth of practical knowledge and knowhow to share with other participants, truly learning from each other.
I had the privilege of attending the Pharmaceutical Automation Roundtable as an observer in November 2011. This PAR was hosted by Johnson & Johnson in Spring House, PA, with Dave Stauffer, Terry Murphy, and Joel Hanson of Johnson & Johnson participating.
Lead automation engineers from various parts of the world attended the invitation-only, two-day event. This is the most knowledgeable group of automation professionals gathered in one place at any one time focused on discussing automation issues.  A range of companies participated including Abbott, Amgen, Biogen Idec, BMS, Genentech, Genzyme, Glaxo, Imclone, Johnson & Johnson, Eli Lilly, Lonza, NNE Pharmaplan, Novo Nordisk, Pfizer, and Sanofi-Aventis.
The PAR was founded about 15 years ago by Dave Adler and John Krenzke, both with Eli Lilly and Company at the time, as a means of benchmarking and sharing best practices for automation groups among peer pharmaceutical companies. The group specifically does not discuss confidential or proprietary information, cost or price of products, price or other terms of supply contracts, or plans to do business or not do business with specific suppliers, contractors, or other companies.
Recipe Management
There was an excellent presentation on an implementation of a unified recipe management approach and then a lively discussion about this topic. The presentation described the overall goal and vision to increase manufacturing productivity and accomplish zero day production releases. Batch information would immediately available via electronic records and eliminate delays. The “big hairy goals” in the project are to have system-independent recipe design that drives Electronic Laboratory Notebook (ELN), Manufacturing Execution Systems (MES) and Laboratory Execution Systems (LES).
In addition, this approach creates a depository of digital nuggets of proven knowledge and experience that can readily be reused to create new recipes and procedures. Adhering to ISA88 and ISA95 functional standards are the foundation for this approach. ISA95 (ANSI/ISA-95) is the international standard for the integration of enterprise and control systems that defines standard data models and terminology for equipment, material and personnel. ISA88 (IEC 61512-1) is the international standard for defining batch production processes.
Recipe implementation objectives include design, configuration and commissioning electronic recipes for R&D, analytical labs and manufacturing to ensure real-time availability of process and analytical data from recipes. Accomplishing this starts with adoption and implementation of ISA95 and ISA88 standards to achieve a uniformity of models, structure and data for lab through production. The components of recipes are decomposed into basic components including parameters, operations, actions, and processes. These are used to create a knowledge depository providing building blocks that can be used by designers to create new recipes. These basic building blocks need to be defined well only once, thus avoiding duplication and providing versatile and easily maintained building blocks for replication and reuse.
The goal is a single recipe warehouse for both development and manufacturing. A challenge to creating common master batch records is the disparate sources of information and systems that exist in various forms. Recognizing that the diversity in systems exist in various groups and many formats, a software approach was shown that extracts required data from that various systems already in place including LIMS, MES, Automation, control systems, etc. It was emphasized that data is extracted in the easiest way that each system can provide it (i.e. exported spreadsheet, comma delimited file, etc.). The data with context is then cleaned and normalized for data warehouse storage, providing a single common data model for all data regardless of the data's source. This is designed to have the least burden on the systems that are the source for the information. It was noted that the architecture deployed uses established data warehousing and business intelligence techniques that integrate data from multiple source systems.
The following are comments from PAR participants from the discussion after the presentation that I thought were worth noting:
“One of our sites embraced S88 and on a new product they reduced cycle times by 40%.”
“A deficiency in S88 and S95 is that they do not have good models of analytical methods that are important for drug development.”
“This is part of our BI (Business Intelligence) initiative…”
“The transformations for different equipment takes a lot of manual work.” (Editor’s note: This is because the source systems have multiple data structures sometimes without associated product or process context. There are no standards.)
“We are building our own solution since there is not one off-the-shelf.” (Editor’s note: This was a fairly common issue.)
“If the data triggers do not exist in the controllers they needed to be added. These triggers or context need to be specified for new equipment and systems.”
Thought & Observations
The recipe information is sitting out in multiple systems and various members of the PAR group are finding ways to leverage this data. The presenters illustrated a way to do this using standard business intelligence and knowledge warehouse tools for Business Intelligence. Broadly defined, Business Intelligence is a set of methodologies, processes, architectures, and technologies that transform raw data into meaningful and useful information to enable more effective strategic, tactical, and operational insights and decision-making.  A core concept is accepting the data from the various systems (examples: DCS, LIMS, Historians, SCADA) in the simplest way possible and depositing it into a relational database. This becomes the resource for various users to create analysis and reports. The concepts being implemented are really central to good structured design methodology that uses top-down functional decomposition to simplify and systemize to create more flexible and higher quality systems.
Automation vendors typically think of providing “their” integrated system but do not have to live with the integration of multiple systems. The need for greater efficiency and flexibility is requiring these users to integrate at a higher level in a way that deals with the diversity of systems installed at multiple plants.
Your thoughts and comments are welcomed.
Links to other articles in this series:
Part 2: Unifying Recipe Management (You are currently reading this article)
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