Custom BioVisualizer Solution Enhances Preclinical Data Analysis

This case study showcases how Excelra delivered a preclinical data visualization platform to help a medical technology company analyze complex preclinical and transcriptomics datasets. By customizing the BioVisualizer platform and integrating scientific data management capabilities, Excelra enabled intuitive biomarker tracking, time-series analysis, and data-driven insights for immuno-oncology research.

Our client

The client is a US-based medical technology company specializing in advanced drug-delivery systems and cancer immunotherapy. With growing volumes of heterogeneous preclinical and transcriptomics data, the organization required scalable scientific informatics services to centralize, visualize, and analyze data across studies.

Client’s challenge

Ongoing preclinical studies generated large, diverse datasets that were difficult to analyze using traditional tools. The client lacked a centralized solution for interactive visualization, time-series biomarker analysis, and statistical exploration. In particular, longitudinal analysis was critical for understanding disease progression and therapeutic response, yet existing workflows were manual, fragmented, and inefficient—limiting the value of their preclinical insights.

Client’s goals

The client aimed to implement a preclinical data visualization platform that could integrate multiple datasets, enable real-time statistical analysis, and support bulk transcriptomics workflows. Key goals included intuitive biomarker tracking over time, PCA-based data exploration, and secure, scalable data management aligned with modern scientific data management practices.

Our approach

Excelra customized its BioVisualizer platform through an iterative, feedback-driven approach. Working closely with the client’s scientific teams, we adapted visualization modules, workflows, and branding to match specific analysis needs. Interactive filtering allowed users to select samples by experimental group, time point, and quality parameters, aligning with best practices in data visualization in life sciences.

The solution incorporated advanced statistical tools such as Student’s t-test, ANOVA, Mann-Whitney U test, and PCA, along with differential gene expression analysis for bulk transcriptomics. Secure data storage and integration were enabled through Excelra Cloud Solution, ensuring scalability and compliance for sensitive preclinical datasets.

Our solution

Interactive data exploration

with sample selection by criteria (experimental groups, time points…) and filtering of low-quality data points via parameters that could be dynamically updated.

Visualization modules

offering a range of plot types, such as box plots, bar charts, heatmaps, and PCA plots. A particular focus was to add a time series visualization module for the analysis of clinical data over time.

Statistical analysis

including statistical tests like Student’s t-test, ANOVA, and Mann-Whitney U test.

Data management

ensuring scalable and secure data storage through Excelra’s Cloud Solution.

Data integration

with a fully configurable selection of datasets to include and their linkage to sample and subject metadata.User

interface and branding

customized interface to match the client’s brand and preferences.
The platform’s modular design aligns with Excelra’s broader informatics and analytics offerings and can be extended to additional workflows such as single-cell analysis or multi-omics integration.

Result

The solution significantly simplified preclinical data management and analysis, reducing manual effort and accelerating insight generation. Real-time statistical testing and intuitive visualizations improved biomarker interpretation, while secure cloud-based infrastructure ensured reliable data access. The client achieved measurable time and resource savings, supporting faster R&D cycles in cancer immunotherapy programs.