Digitally connected, standardized tools and processes with common data structures across the value chain can reduce cycle-times and simplify technology transfer. Generally speaking, technology transfer is the intersection between business, science, engineering, law, and government.

Steve Hayward
Product Marketing for Informatics Solutions, Dassault Systèmes BIOVIA

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. 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Over the last few decades, replacement of outdated paper-based data management systems has been identified as a means to accelerate this process. Most organizations are in their first or second “paperless” initiative, working to simplify workflows, standardize data, and better preserve and reuse knowledge. 

“Going paperless” or “going digital” is a strategic initiative that offers demonstrable operational benefits along the entire research-development-manufacturing continuum. While the implementation of electronic systems has reduced cycle times and compliance risk, issues remain with departmentally siloed systems and with non-standardized data across the product development process.

The result is poor data mining, growing inefficiencies, and hindered collaboration among the different domains. To satisfy the requirement of more efficient data and technology transfer, standardization of data and technology transfer across the entire product lifecycle is needed.

Technology transfer will occur between research, the different areas of development, quality assurance and quality control, manufacturing, and commercialization. This includes the transfer of parameters, data, methods, and documentation. (Credit: Dassault Systèmes BIOVIA)

An Electronic Lab Notebook (ELN) is often a key component to any such solution for the lab, because it addresses numerous pain points across industries: Collecting data efficiently and contemporaneously; standardizing the data that is collected; enabling collaboration and data re-use; and protecting intellectual property.

An ELN helps to preserve the digital thread of information throughout an organization, from research, to development, and to manufacturing, transforming the concept of technology transfer.

Collaborate More Effectively

Capturing experiments and data within a unified ELN doesn’t just remove paper from the lab; it provides access to historical data, allowing scientists to build on their colleagues’ work and expertise by easily searching for prior experiments and data to supplement their own experiments. As a result, teams can leverage common procedures and make incremental changes to optimize variations based on changing specifications, regional suppliers, and manufacturing capabilities—as opposed to designing each method or recipe from scratch.

At the manager level, the ELN makes it possible to quickly review the progress of projects and the division of labor in collaborative experiments and assign new tasks based on a clear understanding of lab priorities and utilization. Additionally, standardized experimental taxonomies, ontologies, and data formats give scientists a common language for communicating and interpreting data from across the organization and wider partner ecosystem.

This unified environment minimizes unused “dark data” and needlessly repeated experiments, streamlining the R&D network so that scientists can develop new products faster than ever before.

Turn Data into Information and Knowledge

The difference between raw data and useful information often comes down to context. To turn data into information, you must be able to access that data, aggregate it from multiple sources, and put it in a context that facilitates analysis.

 Moving from information to insight and knowledge requires interpreting information in context, assessing actions and collaborating with colleagues who build knowledge as a team. If everyone in the organization has access to the same knowledge base, everything works more efficiently and sound decision-making is simplified.

Information and context should flow from end to end through various systems, leveraging real-time data and process metadata from instruments, methods and supplies so knowledge is available at every decision point. Scientists can drill down into contextual data so they can better manage knowledge and meet compliance requirements. An ELN helps scientists to effectively manage knowledge, simplifying analysis, reporting and decision-making by making data contextually accessible.

Preserve Knowledge

When scientists capture all laboratory data digitally, they can more easily manage and access it at any point in the laboratory workflow. As data is transformed into knowledge, it can be preserved and shared through the entire innovation and product development lifecycle—from product ideation through downstream processes.

Information isn’t isolated in detached systems or paper records; instead, it is accessible to the right people on demand. If senior staff members leave, they don’t take knowledge with them and leave behind a hole in the knowledge base; even the least experienced researchers can leverage their expertise.

By electronically capturing and accessing data from early design and optimization experiments through commercialization, science-based companies can examine and optimize their own process and product quality. Well-managed laboratory data tends to be high quality and accessible data that fosters a culture of data-driven analytics and smart decision-making.

An ELN acts as a central repository for much of the data generated and shared within a lab setting. From planning and executing tasks, to recording the data, and compiling reports, an ELN enables collaboration and preserves knowledge. (Credit: Dassault Systèmes BIOVIA)
Transform Tech Transfer

By replacing paper-based and/or fragmented electronic systems along the product development lifecycle, an electronic environment helps streamline both data access and technology transfer. By standardizing data capture and data formats, an ELN provides the basis for a consistent thread of data connecting different domains. Utilizing a single common data structure and format following the ISA-88 and ISA-95 standards further enables efficient tech transfer.

By integrating business rules and quality standards within their digital strategies, companies can ensure that information complies with necessary standards and regulations as it moves across the development continuum. When data is aggregated and compiled to move from one domain to another, protocols can be implemented to automatically compile only specific information as required by SOPs; all other information is preserved for future reference if necessary.

A single digital solution centered around an ELN enables flexible data mining in early R&D as well as the compilation of more structured outputs and documents required for later reporting and regulatory submissions.

With an ELN as part of a larger digital strategy, companies can adopt an informatics approach that effectively connects innovation and commercialization stages with high-fidelity data that retains contextual information as projects move from R&D to manufacturing. A modern, scientifically-aware framework provided by an ELN captures and harmonizes data at its inception, preserving the information and knowledge for use throughout the end-to-end product lifecycle.

By bridging gaps between research, development, quality, and manufacturing in an intelligent manner, an ELN enables successful technology transfer across new product development and production operations, enhancing productivity, improving collaboration, and driving faster and better decisions that ultimately accelerate products to the market.

About the Author
Steve Hayward is a Ph.D. in Chemical Engineering, with a background in laboratory informatics, chemical modeling, and environmental analysis. Originally from Toronto, Canada, he currently leads product marketing efforts for informatics solutions at Dassault Systèmes BIOVIA in San Diego.

This article also can be found in the INTERPHEX 2018 Show Daily: Wednesday, April 18

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