Unified Code & No-Code Discovery
A prominent US-based diagnostic company with satellite locations across Europe faced a significant challenge in its biomarker discovery and development process. The scarcity of bioinformaticians and the growing need for expedited access to analyses among research scientists was a critical issue. Despite possessing valuable data, they needed help harnessing it effectively for biomarker discovery.
The challenge stemmed from a resource-intensive workflow handled by a small team of bioinformaticians, which didn’t meet the urgent data analysis needs of research scientists. The departure of crucial bioinformaticians created irreplaceable gaps, further hindering progress. Researchers relied heavily on bioinformaticians to access and process data, working in isolation from each other. This lack of communication led to unclear methodologies and multiple data versions, resulting in slow and inefficient discovery and development processes.
- The bioinformaticians were overwhelmed by various ongoing projects, leaving them limited bandwidth to assist researchers in real time.
- While highly skilled in coding and data analysis, the bioinformaticians found it challenging to bridge the gap between their coding expertise and efficiently translating the researchers’ data analysis needs. While the researchers understood the biology, they needed help articulating their data analysis requirements in a way bioinformaticians could quickly grasp.
- The challenging nature of their work sometimes meant that bioinformaticians operated in silos. They only occasionally had the time or means to understand the needs and concerns of the research scientists fully.
- Research scientists needed quicker answers to their questions and the ability to perform initial data analysis independently. Relying on bioinformaticians resulted in delays.
- The bioinformaticians conducted their analyses on local machines. This approach created problems related to data version control, unclear and non-reproducible methodologies, and the isolation of analysis insights that only the performer understood.
- A centralized data management and analysis tool with great integration capabilities was needed to suit both the researchers’ and bioinformaticians’ requirements.
Sonrai Discovery unified the client’s diverse data sources. This code-free interface empowered researchers to explore vast datasets, construct cohorts, and perform analyses while integrated Jupyter Notebooks enhanced code-based analysis for bioinformaticians. This cohesive environment now fosters collaboration between bioinformaticians and research scientists, allowing both teams to explore and analyze data effectively and communicate in real-time.
- Sonrai Discovery empowered research scientists to perform initial data analysis within a no-code environment, significantly reducing their dependence on bioinformaticians.
- By integrating with Jupyter Notebooks, Sonrai enhanced the collaborative aspects of the data analysis process, ensuring that bioinformaticians and researchers could work together more efficiently.
Sonrai’s solution improved version control, minimizing discrepancies and ensuring that analyses were replicable and traceable.
- Sonrai’s capabilities facilitated the integration of diverse data modalities, creating a unified data source that enhanced the accuracy and efficiency of biomarker discovery.
This partnership moved our client closer to creating innovative and life-saving diagnostic solutions. A dual environment for diagnostic companies promotes inclusivity, efficiency, collaboration, and dynamic use of skills. It overcomes obstacles related to varying skill sets, interdisciplinary collaboration, and bottlenecks, accelerating decision-making. This approach optimizes the entire analytical process.
Efficient Biomarker Discovery
Research scientists can now efficiently discover and validate novel biomarkers without extensive coding skills, significantly accelerating the biomarker development process.
The partnership fostered seamless collaboration between bioinformaticians and research scientists. They could work together more effectively, with researchers conducting initial analyses and bioinformaticians fine-tuning algorithms as needed.
The combined use of Sonrai Discovery and Jupyter Notebook within Sonrai’s cloud environment allowed for rapid prototyping. The company could swiftly test new diagnostic algorithms using real-world data, leading to more accurate and effective results.
Custom Script Development
With the flexibility to develop custom quality scripts using Jupyter Notebooks within Sonrai’s environment, the diagnostic company improved data accuracy and ensured the reliability of their diagnostic tests.
Streamlined Regulatory Compliance
Our client achieved streamlined regulatory compliance, benefiting from Sonrai’s ISO 13485 accreditation. Sonrai’s ISO-accredited Quality Management System (QMS) ensured efficient documentation and audited their data processes, ensuring strict adherence to industry regulations.
Adherence to FAIR Data Principles
Sonrai’s capabilities align with the FAIR data principles by making data findable, accessible, interoperable, and reusable, ultimately enhancing diagnostic and biomedical application research and development processes.