In a Research and Markets report, Technology Transfer Strategies – A Guide to Maximizing Returns Within the Pharmaceutical and Biopharmaceutical Industries, the authors note:
The efficient and effective transfer of new technologies is widely recognized as being a key component of gaining competitive advantage for corporations, industry and for individual nations. The rapidly changing commercial environment of the pharmaceutical industry requires that individual companies take advantage of their comparative advantages to maintain and gain competitive advantage.
I highlight this because Emerson’s Chris Amstutz, director of the Life Science industry consulting team, shared with me a whitepaper, Making Technology Transfer Painless. This whitepaper, as well as a Life Science Leader magazine article on this subject, Trimming Technology Transfer with Automated Solutions, was written by Emerson’s Michalle Adkins and Robert Dvorak.
The challenge beyond the product development work is the collection, organization, and transfer of masses of information required to define and produce the product, satisfy regulatory reporting requirements, and obtain the required licenses.
Moving the potential molecular or biological entity through the various stages from research and development (R&D) through testing, licensing, and commercialization requires an ever-increasing amount of data—written protocols, aggregated production data, and manual reports.
The article highlights a Tufts University study summarized in a 2009 Standard and Poor’s Industry Surveys – Biotechnology, which found that:
…it can take as long as 15 years and as much as $1.2 billion to move a drug from pre-clinical development to biopharmaceutical product market launch. Even excluding the financial drain of drug development failures and associated time expended, the cost remains at $559 million per biologic.
In the R&D to Clinical transition step, promising candidates are submitted to the appropriate regulatory agency, and production is established to support phase I, phase II, and phase III clinical trials. Toxicities and pharmacokinetics require models for determining dosage, buffers, and coatings. The associated documentation produced and process data from the production process to support this transitional step is enormous.
In the clinical to commercial step transition, after regulatory approvals have been granted, the production process must scale up from pre-clinical to more good manufacturing practice (GMP)-compliant clinical manufacturing. Data is accumulated along the way from laboratory notebooks containing the sample data and new test methods. The whitepaper notes:
…scientists and engineers are working to define experiments to be conducted, collect and correlate data, assure batch context of data, define the process, and optimize process parameters. Alterations made during process runs must also be documented, understood, and managed as part of the total process history.
After the production campaign, supporting the clinical phase is complete:
…manufacturing data including processing parameters, in-process and release testing results, recipe or batch record information, and materials information are summarized in a report. This along with the actual clinical trial data is used for product licensing applications.
Now if this sounds like a lot, we’ve only now entered the transfer to commercial manufacturing. Technology transfer is an iterative process moving information from development to manufacturing. As Michalle and Robert highlight in the article, it involves:
…disseminating known information about the product and the anticipated process, collecting and analyzing test results, defining and executing experimental batches and campaigns, gathering process data, and providing summaries. Inputs consist of what is known about the product and the process at the time — data from prior similar products, research data from lab notebooks, characterization studies, batch instructions, set points, experimental data, and a campaign plan. Outputs consist of executed batch records, processing data, and test results, generally in the form of written reports — often hundreds of pages long. These huge, often repetitive, documents must be reviewed and understood in total.
Accumulating and organizing the mass of data throughout the process is critical in the efficient and effective transfer process. The whitepaper highlights how applications such as Optimal Industrial Automation’s SynTQ which connects with analyzers, data analysis tools, and control systems, combined with Syncade operations management software which tracks production data, recipes, and changes to organize the information required. Chris and his consultant team provide the expertise to help pharmaceutical and biotech manufacturers improve this knowledge management process and standardize on a common set of tools to streamline and simplify the technology transfer process.