target identification and validation

Data types in this case study: Clinical, Proteomics

Case Study Highlights

This case study explores how we helped our pharma client overcome challenges in identifying therapeutic targets by extensively searching and analyzing public proteomic databases, curating tailored datasets, and ensuring the reproducibility of findings. This streamlined the target identification process and allowed the client to focus on the most promising candidates without requiring technical expertise.

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Cost per Target Validation Reduction

Advanced data integration and automated workflows improved data analysis and minimized human error. Combined with precision algorithms, this efficiency decreased the need for costly repeat experiments, lowering overall operational costs.

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Over 24 months

In reduced project timelines, decreased labor needs, and fewer repeat experiments. These savings and faster time-to-market for drug development substantially increased the return on investment.

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Target Validation Acceleration

Sonrai Discovery doubled the speed of target validation by using advanced data analytics and automated workflows that streamlined the target ID and validation processes, reducing the timeline and expediting the drug development cycle.

XGBoost shows ML-based discovery, bar chart shows human target expression by response to current treatments, and in vivo analysis allows for rapid target validation using RECIST criteria

"Working with Sonrai was an important step for our target identification process. Their comprehensive search and analysis of proteomic databases uncovered specific evidence that supported the clinical relevance of our target. We are now better equipped to focus our efforts on potential therapeutic breakthroughs."

The Client

A leading global pharmaceutical company at the forefront of healthcare innovation encountered target identification and validation challenges for specific proteins in primary tumours. Additionally, the company was actively exploring additional targets with significant therapeutic potential for their alpha particles.

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.

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14% Reduction in Preclinical Phase

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"Sonrai's curated datasets based on our specific requirements made a significant impact on our target identification process. Their dedication to narrowing down target datasets enabled us to focus on the most promising candidates, saving us valuable time and resources."

Pharma Company Challenges

  • Data Handling Issues: Manual data analysis from high-throughput screenings and genomic studies was time-consuming and error-prone.
  • Lengthy Processes: The target identification and validation phases were excessively long, taking up to 12 and 25 months.
  • Accuracy Concerns: Existing methods had a higher rate of false positives and negatives in target identification, which could lead to costly misdirection in research efforts.
  • Obtaining Quantitative Proteomic Data: The company faced difficulties in obtaining accurate and reliable proteomic data to identify differentially expressed proteins in primary tumors. This data is crucial for understanding the molecular basis of diseases and potential drug targets.
  • Target Identification: Identifying specific evidence for a target of interest proved to be a complex task. The company needed to discern which proteins showed potential for targeted therapeutic interventions.
  • Exploration of Additional Targets: The company sought to explore additional protein targets with even greater differential expression in primary tumours. This process required comprehensive analysis and validation of potential targets to ensure their therapeutic relevance.

Before collaborating with Sonrai, our client faced significant challenges due to manual high-throughput screenings and genomic analyses, burdened by isolated and non-automated lab infrastructures that made data processing slow and prone to errors.

Lab Techniques and Methodologies:

  • High-throughput screening (HTS)
  • Genomic and transcriptomic analysis
  • Proteomics using mass spectrometry
  • Bioinformatics for data analysis
  • CRISPR-Cas9 and siRNA-based gene editing
  • PK/PD studies
  • Biomarker development
  • In vivo models and patient-derived xenografts (PDX)

Lab Infrastructure:

  • Automated HTS systems and plate readers 
  • PET/SPECT scanners
  • NGS platforms and mass spectrometers
  • CRISPR kits and systems
  • Bioinformatics Languages (Python, R)
  • Cell culture systems
  • PK/PD modeling software
  • ELISA kits and ddPCR systems
  • In vivo imaging systems

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The Strategy

The team at Sonrai was excited to help the client overcome these challenges and meet its objectives. Our team adopted a robust strategy to address the challenges faced by the pharma company:

  • Advanced Data Integration: Sonrai reduced the data preprocessing and analysis time from three months to four weeks, utilising powerful bioinformatics tools and automated systems.
  • Automated Workflows: The introduction of automation significantly reduced human error and increased the throughput of experimental data, boosting the efficiency of the target identification process.
  • Precision and Reproducibility: Enhanced algorithms improved target identification accuracy, and reproducibility was confirmed in 100% of cases, ensuring reliable results across experiments.
  • Target Validation: Sonrai’s target validation strategy leverages AI-driven precision medicine technology to integrate and analyze diverse multi-omics data, enhancing the speed and accuracy of identifying and validating potential therapeutic targets.
  • Comprehensive Search and Analysis: Sonrai extensively searched and analyzed public proteomic databases to gather relevant data on differentially expressed proteins in primary tumours. This enabled the identification of potential therapeutic targets.
  • Curated Datasets: Sonrai curated datasets tailored to the client’s requirements, streamlining the target identification process. The company could focus on the most promising candidates by narrowing the target datasets.
  • Reproducibility of Findings: To ensure the reliability and accuracy of the findings, Sonrai performed a meticulous re-analysis of the proteomic data. This step involved validating the results against the original work done by the pharma team.
  • Data Transformation: Sonrai facilitated the seamless integration of the client’s data into the Sonrai Discovery platform. By transforming the data into a user-friendly format, the pharma company could explore and utilize the data without needing technical expertise.
"The collaboration with Sonrai has been transformative for our drug development efforts. Their ability to handle complex proteomic data and deliver quantitatively confirmed results is commendable. We're excited to explore new targets with Sonrai by our side."


Sonrai's analysis successfully confirmed the up-regulation of the protein of interest specifically in prostate cancer tissues, providing essential quantitative validation for its potential as a therapeutic target. With these promising results, the company is also evaluating the role of this protein across various cancer types, supporting its long-term strategy to develop pan-cancer treatments.

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Target ID & Validation
21 month Acceleration

The target identification phase was reduced from 12 months to just 5 months, and the target validation phase was shortened from 25 months to 11 months.

cost efficiency (1)
Cost Savings

Operational costs were significantly reduced, reducing the timeline from 37 months to 16 months, saving the company over $1.5 million.

Precision Icon
Clinically Relevant Targets
Improved by 31%

Increasing the effectiveness of therapies in early-stage clinical trials. This enhancement was pivotal in advancing the client’s drug development pipeline and quickly bringing effective treatments to market.

Client Satisfaction Rating

Reflecting the substantial impact of Sonrai’s contributions on its operations and outcomes.

Quantitative Validation and Statistical Significance

Quantitatively Confirmed

Sonrai’s analysis confirmed the up-regulation of the protein of interest in prostate cancer tissue. This quantitative validation provided crucial evidence for its potential as a drug target.

Significant Findings
Statistically Significant Findings

Through rigorous analysis, Sonrai established statistically significant up-regulation of the protein in recurrent prostate cancer patients compared to non-recurrent patients. This data pointed to the target’s clinical relevance and therapeutic potential.

Hollistic Data Overview
Robust Evidence for Target

The comprehensive evidence provided by Sonrai’s analysis offered robust support for the clinical relevance of the validated target. This evidence bolstered the company’s confidence in pursuing further research and development efforts.

R and D Team
Empowered R&D for Exploration

Armed with these promising results, the pharma company gained the confidence to proceed with their research and development endeavors involving the newly identified targets. Sonrai’s insights opened doors for innovative explorations in drug development and precision medicine.

What’s Next?

“Building on the success in oncology, we plan to expand Sonrai’s technology across disease program indications, aiming to cut target validation times across these key areas by 2026.”

  • Expansion into Predictive Biomarker Discovery: Building on the successful partnership, Sonrai Discovery will aid the client delve deeper into predictive biomarker discovery. By using Sonrai’s advanced machine learning algorithms and integrating multi-modal data, the client is better placed to identify high-value biomarkers that optimize patient stratification and tailor therapies, leading to improved patient outcomes and more efficient clinical trials. 


  • Mechanism of Action (MoA) Studies: Sonrai will assist the client in uncovering intricate molecular pathways and optimize drug designs through accelerated MoA studies. Leveraging Sonrai’s AI-powered analysis could help the client understand how drugs interact at molecular levels, which is crucial for developing more effective therapeutic interventions.


  • Enhanced Data Integration for Real-Time Analysis and Decision Making: Sonrai can offer more sophisticated solutions for real-time data integration and analysis. This would enable the client to streamline the target validation process further and adapt quickly to new research data as it becomes available, thereby enhancing decision-making and accelerating the cycle from experimentation to validation and eventual clinical application.

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