The future promises a paradigm shift in scientific collaboration
The lab of the future promises to be both physical and virtual. Adjacent technologies such as augmented display, motion control, and automatic identification are sparking new strategies for scientific collaboration across disciplines, geographies, and organizations. These rapidly evolving tools are poised to play a key role in establishing advanced social networking models designed to support the unique needs of laboratory professionals. As scientific social networking evolves, data and real-time activities will merge as collaborative partners see and experience laboratory events simultaneously, regardless of their geographic location.
Contemporary laboratory management technologies connect scientific innovation processes and information with other product lifecycle systems to facilitate collaboration internally and across external research networks. This helps create enterprise-wide intelligence that accelerates product development, reduces cycle times for commercialization, and improves insight into process and product quality.
These solutions have vastly improved the productivity, performance, and predictability of scientific work in laboratories for life science organizations. And the best is yet to come as new concepts for applying emerging technologies pave the way for the lab of the future.
Evolution of the social network
Outside the lab, people use social networks to communicate, share experiences, and gather helpful information such as rankings and reviews about products and services. But those public mechanisms are not a suitable option for scientific collaboration. The needs are similar, but they must be positioned in a different way. A vacationer may upload a photo from a smartphone to a social network with a single click. But information can’t safely be shared that way in a laboratory setting.
Researchers in science-driven companies must make certain that their intellectual property (IP) is not compromised during the collaboration process. Accordingly, a laboratory collaboration platform must provide basic security. In addition, it must ensure that conversations, actions, measurements, test results, and accompanying metadata are preserved as part of the experimental record.
Established models for social networking can help us envision a secure platform for scientific collaboration. A new vocabulary and process, designed for the unique requirements of scientific experimentation, would enable partners to substantiate data, processes, and outcomes similar to “liking” and “ranking” on conventional social networking platforms. And that’s just the beginning of what is waiting on the horizon.
Establishing the proper foundation
Adjacent technologies offer potential for deep, multidimensional collaboration methods that yield rich data with virtually no interruption of workflow. Such a collaboration platform must be based on a foundation that ensures data security, IP protection, and standardization. Standard processes are critical for establishing efficient lab environments, fostering communication among teams, and facilitating externalization for various parts of the development and manufacturing process.
Creating standardized processes, methodologies, and data sets can help organizations move forward by providing a consistent and secure way for people in separate domains to communicate with each other. Standardized processes also help professionals across the enterprise understand prior activities by preserving the context associated with the data via process metadata. A better understanding of data yields knowledge that can be shared internally and with partners.
These best practices need to be applied consistently across the product lifecycle continuum, from initial research to commercialized products. Doing so will create a foundational platform for supporting emerging adjacent technologies that have the potential to spawn new paradigms for scientific collaboration.
Ranking is a valuable feature of conventional social networking platforms that could be applied to the scientific social network. Similar to ranking hotels or restaurants on a scale from one to five stars, scientists would rate laboratory analytical techniques or lab equipment. Hotel ratings on social networks are based on parameters such as the quality of the beds, cleanliness, service, and whether the facility has a swimming pool. An analytical method could be ranked based on parameters like reproducibility, ease of use, inventory usage, material usage, and target results.
A lab worker could make a determination about whether to run a certain test or use a piece of equipment by consulting the rankings for that technique or equipment on the social network. If a scientist requisitions a new device, he or she could see how peers are using that device. Sharing this type of socially enriched metadata via a secure platform could speed innovation and improve productivity in tomorrow’s laboratory environments.
Sharing ideas using contemporary methods such as texting, chat rooms, ratings, and discussion forums promises to enrich scientific collaboration. When adjacent technologies are applied to the laboratory, social interaction may become even more valuable, deep, and intuitive.
Imagine a laboratory where everything and everyone had a unique identification that could be automatically read by the information system. Automatic identification of people, equipment, and materials integrated with motion control technology would enable information systems to sense hand motions and record what is performed without lab personnel needing to enter data.
If lab benches had video teleconferencing capabilities, geographically dispersed teams of scientists could work together as if they were in the same room. Augmented reality (AR) glasses could enhance teleconferencing by providing detailed information about anything scientists looked at while guiding them through the steps in a process without interrupting the workflow. Partners anywhere in the world could see everything the scientist sees along with the accompanying metadata.
The technologies to support such a lab all exist today and are not expensive. In the lab of the future, a foundational platform based on data security, IP protection, and standardization will work in harmony with these rapidly advancing physical devices. Let’s take a closer look at some of the adjacent technologies that could make this advanced collaboration platform possible.
Biorhythmic bracelets show great potential as a way to automatically identify people in a lab. A biorhythmic bracelet that is Bluetooth-enabled and has proximity capability can identify a person by his or her unique biorhythmic pattern, determine where a person is in the lab, and automatically communicate that information with the system and with partners via the scientific social network.
The way materials and equipment are identified continues to evolve. Quick-response (QR) codes improve readability and storage capacity over standard UPC bar codes. Radio-frequency identification (RFID) tags enable systems to automatically identify objects and their location. Near-field communication (NFC) technology enables devices to communicate with each other.
Integrating these identification mechanisms with laboratory management systems could automate and streamline lab activities. If someone stands in front of a bench and begins weighing material on a balance, the system will know who is performing the operation, identify the materials involved, confirm that the person has the appropriate level of training and clearance, and record the outcome. All of that information can be shared with authorized partners.
Using identification technologies in conjunction with a motion control system would be especially valuable. Motion-sensing input devices gained popularity in the consumer world by enabling people to interact with video games by using physical gestures. Early motion controllers utilized gyroscopes to detect gestures. This technology has continued to evolve and become more advanced. Recent models have servo-based video-sensing capabilities that can identify individual users by their facial features and other physical characteristics. They can also detect minute actions, such as the movement of a fingertip.
Motion controllers can be trained to understand what lab personnel are doing. Just as with motion-controlled gaming, the system can recognize specific motions and gestures. When a technician weighs a sample, the system would recognize the action, automatically record the results, and share them with collaborators via the social network. These automated activities would allow scientists to collaborate intuitively, without adding extra thought to the process or interrupting the workflow.
Augmented reality (AR) supplements a person’s view of a physical environment, with additional information supplied by computer-generated input. AR technology can be integrated into a head-mounted display, eyeglasses, safety goggles, or contact lenses. When wearing an augmented display, a scientist can simply look at a piece of equipment or a vial of material to instantly obtain information about it. Partners on the social network would simultaneously see what the scientist sees.
When AR technology is integrated with automatic identification and motion control, it could intelligently guide scientists through the steps in a process by displaying red or green lights that tell users when their actions are correct. A lab technician can tell the AR device to record video and verbal descriptions of work as it is performed. The system will automatically store all of this information in an electronic lab notebook and share it with the secure social network. Partners around the world can see what the technician sees via the augmented display.
Make it so
New models for social collaboration in the laboratory have the potential to help companies derive more value from their data, eliminate inefficiencies, attain a more complete understanding of their processes, and drive innovation as peers connect in the moment.
The physical devices that will enable this heightened level of interactivity are progressing rapidly, enabling futuristic lab capabilities. However, automatic identification mechanisms, motion control systems, augmented reality, and real-time video conferencing will only be useful if they are integrated with a platform that is based on a secure foundation.
Information systems must have a standardized way to identify, connect, and communicate with people, instruments, and materials. The foundation provides common administrative capabilities for resources, workflows, data, recipes, and methods. It also ensures data security, IP protection, and the preservation of context associated with data via process metadata.
Establishing a baseline foundation of standardized processes will enable science-driven companies to apply emerging adjacent technologies to shift the paradigm for how scientists work together. These capabilities exist today. As companies invest in technology, they should look for solutions that support emerging models for scientific social networking.
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