CASE STUDY

Optimizing Immunotherapy Clinical Trial Data

Data types in this case study: RNA-Seq, Digital Pathology, H&E, IHC, Clinical

Case Study Highlight

Our client faced two key challenges: (1) quickly accessing their clinical trial data for report generation, and (2) conducting the complex analyses required for their generated data (including IHC images, Bulk RNAseq, etc.). Sonrai Cloud provided efficient and predominantly automated data management. This enabled their team to swiftly analyze data and produce reports in real-time as the trial advanced.

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The Company

Our client, a prominent US-based oncology drug development company, employs over 200 specialists dedicated to creating patient-centric therapies. They are at the forefront of redefining drug development standards, with a strong emphasis on the accuracy, integrity, and precision of clinical trial data, essential for informed decision-making, risk minimization, and optimal resource utilization.

The Challenge

In preparation for Phase II trials, our client-focused on maximizing and optimizing the data extracted from each patient, recognizing the high costs and critical importance of these trials. The hurdles outlined below highlighted the necessity for a strategic, data-driven approach to propel their oncology drug development program forward effectively.

  • Maximizing Data Quality and Quantity: With the high cost of running Phase II trials, the client aimed to maximize data extraction from patients, whether blood or tissue samples. They wanted to ensure the most optimal use of these samples for meaningful insights.
  • Efficient Data Collection and Management: The client struggled with inefficiencies in handling contract research organization (CRO) readouts, often requiring manual interventions for data amendments. Manual data processing is prone to human errors. The lack of a data management tool compromised data integrity, leading to unreliable trial results.
  • Clinical Trial Report Generation: The client wished to swiftly generate comprehensive reports on trial progress, necessitating an efficient system for collating and analyzing patient samples and data to provide timely updates and insights.
  • FDA Clinical Reporting: A key challenge for our client was enhancing the presentation of clinical trial results for FDA reporting, necessitating a system that could accurately compile, analyze, and clearly communicate complex data in compliance with stringent FDA standards.
  • Addressing Research and Clinical Inefficiencies: The client struggled with inefficient data collection and processing, highlighting the need for an improved data structure and management.
  • Identifying Predictive Biomarkers: The client wanted to identify subpopulations within the clinical trial data that show a better response to the drug, necessitating the use of predictive biomarkers to accurately stratify patients and optimize treatment efficacy.

The Difference Sonrai Makes

Every organization is unique, and generic solutions fall short in addressing their distinct challenges. Sonrai is purpose-built to tackle the complexities of precision medicine, offering tailor-made solutions that align with your specific needs.

Discover Predictive Biomarkers 52% Faster

Sonrai’s AI technology supports rapid biomarker identification, empowering our partner to predict optimal therapy responses through an innovative toolkit.

57% Acceleration in MoA Studies

See how Sonrai unified diverse data sources to rapidly understand complex molecular pathways, helping identify predictive biomarkers and drug mechanisms of action.

14% Reduction in Preclinical Phase

Discover how Sonrai helps pharmaceutical companies overcome challenges in Invivo Drug Efficacy with AI-powered analytics.

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"Utilizing Sonrai's AI data management platform transformed the way we handle our clinical trial data; we've managed to get more insights out of patient samples, accelerating our research and identification of predictive biomarkers. Sonrai was instrumental in helping us achieve more reliable and accurate outcomes."

The Strategy

Realizing the limitations of their existing systems and the benefits of incorporating advanced AI-driven analytics and data management, the client sought a solution that aligned with their objectives and challenges. Their decision to work with Sonrai was driven by the need for advanced data management and analytics capabilities, coupled with Sonrai’s proven expertise in AI and precision medicine.

  • Maximizing Data Quality and Quantity: Sonrai Discovery efficiently manages and analyzes patient data, maximizing the utility of each sample. Its advanced data integration capabilities ensure that all relevant information, whether from blood or tissue samples, is accurately captured and utilized for in-depth analysis.

  • Efficient Data Management and Clinical Collaboration: Sonrai Discovery streamlines the management of CRO readouts and clinical data by automating the data handling process. This reduces the need for manual intervention, minimizing the risk of errors in data entry and enhancing collaboration efficiency.

  • Overcoming Data Collection and Management Challenges: Sonrai’s precision medicine data management tools are designed to mitigate risks like sample mislabeling and inaccurate data entry. By providing a robust framework for accurate data collection and management, they ensure the integrity and reliability of trial data.

  • Clinical Trial Report Generation: Sonrai Discovery can quickly generate comprehensive reports on the progress of clinical trials. It collates and analyzes patient data efficiently, providing timely insights and updates essential for ongoing trial assessment.

  • Streamlining FDA Clinical Reporting: Sonrai Discovery can compile, analyze, and present complex clinical trial data in a clear, comprehensible, and regulatory-compliant manner. This facilitates the FDA approval process by ensuring all submissions meet the required standards.

  • Developing Predictive Biomarkers: To identify responsive patient subpopulations, Sonrai Discovery can leverage its capabilities in predictive biomarker development. It uses sophisticated analytics to stratify patients based on their response to the drug, thereby optimizing treatment efficacy and personalizing therapy approaches.

The video below is an example of some of the analysis possible from immunotherapy clinical trials. Note: The data shown is not our clients data, this is publicly available clinical trial data that was analysed on our platform by our data science team.

Results

The client observed marked improvements in decision-making, risk reduction, and operational efficiency, laying a robust foundation for the subsequent phases of drug development.

  • Enhanced Data Quality and Utilization: The client reported an improvement in data quality and increased utilization from each patient sample. Using Sonrai Discovery’s advanced integration capabilities, they could accurately capture and analyze critical data from various samples, leading to more profound and actionable insights.
  • Streamlined Data Management and Collaboration: Automating data handling processes significantly streamlined the management of CRO readouts and clinical data. This reduction in manual interventions led to fewer errors and enhanced efficiency in collaboration, resulting in smoother trial operations.
  • Reliable Data Collection and Maintenance of Integrity: The client overcame major data collection challenges. With Sonrai’s robust framework, issues like sample mislabeling and inaccurate data entry were significantly reduced, ensuring the integrity and reliability of trial data.
  • Efficient Clinical Trial Reporting: Sonrai Discovery enabled the client to generate comprehensive and timely reports on the trial’s progress. This efficiency in reporting improved the assessment and decision-making processes for the trials.
  • Effective Stratification with Predictive Biomarkers: The client effectively used predictive biomarkers to identify patient subpopulations that showed enhanced responses to the drug. This stratification optimized treatment efficacy and marked significant progress in personalized therapy approaches.

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