Academic Research Institution

Vanderbilt University

Automating Research Lab Workflows

Siciliano Lab at Vanderbilt University transformed its in vivo animal study management by adopting Scispot’s Unified Platform. Previously hindered by manual spreadsheet tracking, scattered data, and inefficient analysis, the lab leveraged Labspaces, Labflows, and Labsheets to centralize and standardize workflows. Sample Manager’s barcode integration ensured accurate animal and reagent tracking, while Zapier automated metadata updates. Scispot’s Jupyter Hub and AI dashboard revolutionized data analysis, delivering nuanced insights for behavior studies, pharmacology, and analytical chemistry. This shift reduced errors, saved costs, and improved data continuity, enabling the lab to focus on groundbreaking addiction research with enhanced efficiency and productivity.

The Challenge: Inefficient Animal Colony and Data Management

Siciliano Lab at Vanderbilt University’s Department of Pharmacology and Center for Addiction Research faced significant challenges in managing in vivo animal studies. Manual data logging in spreadsheets and scattered data across multiple systems led to siloed knowledge, time-consuming searches, and errors in tracking animal colony details, such as cage assignments and experimental protocols. These inefficiencies slowed research progress, increased costs due to unattended animals, and complicated data analysis for their diverse workflows involving behavior studies, pharmacology, analytical chemistry, and optical tools.

  • Manual tracking of animal study data in spreadsheets
  • Scattered data across systems, causing siloed knowledge
  • Errors in animal colony management, leading to unnecessary costs
  • Time-consuming data searches and inefficient analysis processes

The Need: Streamlined Animal Colony Management and Data Analysis

The lab required a centralized, user-friendly platform to automate animal colony management, streamline experimental workflows, and enhance data analysis. They needed a solution to track animals and reagents, integrate with existing tools, and provide insights through automated analysis, all while supporting their complex, multidisciplinary research without extensive technical expertise.

  • Automated animal colony management with cage and project tracking
  • Centralized data access to eliminate silos and improve continuity
  • Integration with lab tools and automated data analysis capabilities
  • User-friendly, no-code platform for diverse research workflows

The Solution: Scispot’s Unified Platform with Advanced Analytics

Scispot’s Unified Platform transformed Siciliano Lab’s operations by centralizing animal colony management and research workflows. Labspaces and Labflows organized animal study protocols, while Labsheets standardized data capture for in vivo experiments, including cage assignments and project associations. Sample Manager’s barcode integration enabled precise animal and reagent tracking, reducing errors and preventing double ordering. Zapier triggers automated metadata workflows, streamlining updates and notifications. Additionally, Scispot’s Jupyter Hub automated data analysis, and the AI-powered dashboard provided actionable insights, enhancing research outcomes across behavior studies, pharmacology, and analytical chemistry.

  • Labspaces and Labflows for structured animal study organization
  • Labsheets for standardized in vivo data capture
  • Sample Manager with barcode scanning for accurate animal and reagent tracking
  • Jupyter Hub and AI dashboard for automated data analysis and insights

The Outcome: Enhanced Efficiency and Research Productivity

Scispot’s implementation led to significant improvements in Siciliano Lab’s operations. The platform reduced manual errors, saved costs by optimizing animal and reagent usage, and freed up staff time for core research. The centralized system improved data continuity despite personnel turnover, while the global search function and AI-driven analytics accelerated insights from complex datasets. These advancements enabled the lab to manage multiple in vivo experiments efficiently and advance their addiction research.

  • Reduced errors and costs through automated animal colony management
  • Freed up staff time by centralizing data and streamlining workflows
  • Improved data continuity and accessibility with global search
  • Enhanced research insights via Jupyter Hub and AI dashboard

Scispot has elevated our lab’s efficiency. We can now simultaneously manage multiple in vivo experiments, coordinate animal study schedules, and conduct complex animal tracking protocols

~ Cody Siciliano, Asst Professor at the Center for Addiction Research

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