The objective of this Phase I proposal is to demonstrate the feasibility of an innovative Cloud Information Management Bundle system, CLIMB, that will increase efficiency and improve capabilities in animal model data management. Current data management systems for animal model research have limitations. For example, paper-based recording systems used by technicians are error prone, time consuming, or focused on storing data and retrieving it at a later time, without attention to cumulative data relationships that can be used to identify important trends or risks. Moreover, researchers often miss windows of opportunity to take action on time-sensitive events because the investigators are in meetings or traveling. To overcome these limitations, RockStep Solutions LLC, a private enterprise spinoff of the Jackson Laboratory (JAX), has designed a system that integrates real-time communication capabilities, cameras, bar-code readers, and touch screens of mobile devices with cloud computing, relational database management systems, and innovative algorithms to create an efficient data management ecosystem in which laboratory technicians and geographically-separated research investigators can manage their experiments in real-time as a cohesive team. The core of the CLIMB system is based on extending and integrating the complementary capabilities of two existing systems developed by JAX: JaxLIMS (a Laboratory Information Management System developed for the NIH Knockout Mouse Program) and JAX Colony Management System (JCMS, a system for managing mouse or rat research colonies and supporting basic animal husbandry tracking, sample tracking, and phenotype/ experimental data collection.) In this feasibility study, we propose three interconnected specific aims:
AIM 1) implement the data model core in the cloud and develop prototype user interfaces, AIM 2) develop the core infrastructure, methods, and algorithms for the data monitoring and messaging system, and AIM 3) deploy and test, a functional wireframe version of CLIMB in a JAX research laboratory. The outcome of Phase I is a deployed system that will allow us to test the system in a real lab setting to gather metrics and feedback from actual users. Accomplishment of our aims will demonstrate the feasibility of the proposed CLIMB system technology and set the stage for further development in which we will build up a production scale system with full functionality (Phase II) and for market entry (Phase III). The CLIMB system will be developed initially for biomedical research that uses rodents as the platform for discovery; however, the design is extensible to many other model organisms and general laboratory workflows. The extensible design will enable expansion of the product market into other biomedical research areas as part of the future commercialization plan. IMPACT: This colony management technology is very powerful and offers several advantages: 1) enables real- time communication utilizing familiar tools among a group of animal technicians and scientific team members; 2) reduces the risk of experimental setback; and 3) improves the efficiency of complex experiments.
The NIH Invests approximately $12 billion each year in animal model research that is central to both understanding basic biological processes and for developing applications directly related to improving human health. More cost-effective husbandry and colony management techniques, equipment, and new approaches to improve laboratory animal welfare and assure efficient and appropriate research use (e.g., through cost savings and reduced animal burden) are high priorities for NIH. RockStep Solutions proposes to meet this need by integrating existing and emergent software and communication technologies to create a novel solution, Cloud Information Management Bundle (CLIMB'), for research animal data management. CLIMB extracts immediate value of data in animal research laboratories and extends the database into a multimedia communication network, thus enabling science that would be impractical to conduct with traditional methods.
