by Daniela Jansen
Life Science
The Importance of an Integrated Informatics Solution for Life Science Organizations and Keys to Successful Deployment
T
he exorbitant cost of bringing a new pharmaceutical product to market in the U.S. is well documented, with estimates as high as 12 years and $11 billion.1,2
There are many factors that drive
this cost, including rework due to a lack of access to information from previous experiments, loss of intellectual property (IP), and data mining inefficiency. The goal in drug development is to be the “first to file” for approval of a new drug in order to maximize return on investment (ROI) and increase profit potential, all while producing a high-quality product and remaining regulatory compliant.
For a drug development program to be successful, product and pro- cess knowledge should be managed along the entire product lifecycle. Knowledge management is a systematic approach to acquiring, analyzing, storing, and disseminating information related to a product, its compo- nents, and the manufacturing processes used to develop it. Sources of knowledge include prior knowledge, innovation, pharmaceutical de- velopment studies, manufacturing experience, continual improvement, change management activities, process validation studies, and technol- ogy transfer activities.3
Generally speaking, technology transfer is the intersection between business, science, engineering, law, and government.4
Within drug
development, it pertains to moving data, information, and knowledge across the various domains, including research and development (R&D), manufacturing, and commercialization so that new products can be made available to the public (Figure 1). Technology transfer becomes even more important when any activities like research, development, and/or manufacturing are outsourced to third-party contract organizations.
Over the last few decades, replacement of outdated paper-based data management systems has been identified as a means to accelerate this process. While the implementation of electronic systems led to reduced cycle times and compliance risk, issues remain with systems existing in departmental silos and nonstandardization of data across the drug development continuum. The result is poor data mining, inefficiencies, and hindered collaboration among the different domains. To satisfy the requirement of drug development companies for efficient data and tech- nology transfer, standardization of data and technology transfer across the entire pharmaceutical product lifecycle is needed.
A system that spans multiple domains also needs to be able to satisfy different needs and purposes. For example, scientists require an electronic environment for process management and compliance that supports both flexible authoring as well as more structured execution. In manufacturing, access to data generated in development allows companies to investigate
Figure 1 – Technology transfer will occur between research, the different areas of development, quality assurance and quality control, manufac- turing, and commercialization. This includes parameters, data, methods, and documentation.
and adjust the parameters of a formula in order to make improvements that can optimize factors like product purity, yield, and cost of production.
Successful deployment of an integrated informatics solution can address issues with ineffective data and technology transfer.
Three keys to successful deployment
1. Establish a single application platform Traditionally, the transfer of methods between development and quality control (QC) areas in drug development required companies to physically relocate the development team to the actual production site for extended periods to ensure complete and accurate technology transfer. This process creates an enormous burden for organizations, not to mention the poten- tial for information to be lost or incorrectly incorporated.
Life science companies have sought to enable and optimize the manage- ment of both R&D information and manufacturing QC and batch record data. Fragmented systems have been used in an attempt to bridge the gap between instruments used in the laboratory and data management systems. Customized interfaces of these types of systems require custom- coding and heavy information technology (IT) support, resulting in a high cost of ownership and risk of validation and compliance violations.
A unified scientific informatics platform, however, bridges the gap between instruments used in the lab such as electronic laboratory
AMERICAN LABORATORY • 21 • JUNE/JULY 2014
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