Advancing In Vivo Drug Development

Use case highlights

The workflow below shows the management and analysis of in vivo data using Sonrai Discovery. The data was used to identify the most effective treatments for tumours and assess their safety profiles. Tumour samples were collected at different stages of the study, and both imaging (IHC) and omics (RNA sequencing) data were generated to explore the mechanisms of action of the therapy combinations.

Aligning efficacy studies with precision medicine

This use case shows a solution addressing operational inefficiencies in tumour volume analysis and data management, while also opening up new avenues in precision medicine. By aligning efficacy studies with precision medicine data, pharmaceutical companies are better equipped to develop more targeted therapies and support progress toward drug discovery.

Pharmaceutical companies in this phase encounter challenges such as inefficient tumour volume analysis, often hindered by basic tools like spreadsheets and standalone graphing software. Integrating diverse datasets from various Contract Research Organisations (CROs) adds further complexity, requiring accurate and consistent data management for early problem identification. There's also a need for efficient data cleaning and standardisation to reduce manual labour and errors, and high-quality reporting for internal decision-making and communication with external partners.

Step-by-step workflow for in vivo drug efficacy

Step 1: Data cleaning and formatting assessment

Sonrai Discovery eliminates the need for manual aggregation and reconciliation of data from multiple CROs — a process that traditionally consumes days or weeks and is prone to errors. Sonrai handles diverse data formats from various CROs by uploading data to the platform, identifying and resolving complexities and inconsistencies. This reduces the time and effort required for data harmonisation, letting pharmaceutical companies progress more quickly to data analysis and development activities.

Step 2: Enhanced data management

With the Sonrai Discovery pipeline in place, the frequency of incoming CRO data becomes less of a bottleneck. It integrates data as it arrives, on any schedule or in any batch, supporting consistent, automatic processing. This simplifies initial data handling and establishes a more error-resistant workflow.

Refining data management practices this way helps bolster the accuracy and consistency of tumour volume measurements — important for promptly identifying potential issues. Real-time data monitoring and analysis gives teams more immediate access to processed data, supporting swifter decision-making as issues arise, and helps manage more simultaneous projects or studies in parallel.

Step 3: Development of custom data processing tools

Working closely with users, Sonrai Discovery builds a custom workflow for tumour volume analysis, featuring automated data cleaning and standardisation — particularly relevant to automating these steps in tumour volume analysis specifically. This personalised approach reduces analysis turnaround time and adapts to project-specific needs.

Step 4: Advanced variables analysis

Sonrai Discovery enables comprehensive analysis of variables such as drug dosage, tumour growth, response data (e.g. RECIST criteria) and biomarker levels. This analysis provides a detailed view of the drug's impact, aiding in the nuanced understanding of treatment effects.

Step 5: Toxicity assessment

Using Sonrai's analytics, toxicity thresholds are established to inform dosing regimens, balancing efficacy and safety. Systematic monitoring of mouse weights offers data on drug side effects and efficacy. Data processing, visualisation and analysis of animal pharmacology and toxicology studies supported more efficient IND applications.

Step 6: Enhanced reporting capabilities

Sonrai Discovery enables the rapid generation of comprehensive reports, streamlining communication with internal teams and external partners and simplifying the presentation and sharing of critical findings.

Results

Through Sonrai's AI-powered analytics on in vivo imaging data from mouse models, the collaboration also achieved: