Challenge
A therapeutics company struggled to use public omics datasets to guide critical portfolio decisions, such as identifying patient population sizes for different targets, evaluating opportunities for indication expansion to determine where their therapy might be most effective, and selecting the most appropriate cell lines for in vitro or PDX experiments. The datasets were scattered across different sources, formats, and structures, making it difficult to extract useful insights. Computational biologists spent hours answering specific scientific questions due to the inefficiencies of the dataset formats, causing delays and missed opportunities to accelerate drug discovery progress.
Action
Diamond Age created a fully customized solution tailored to the company’s needs. We pulled omics data from five public and proprietary sources, relying heavily on custom R code to tailor the process to fit the specifics of each dataset. Beyond simply reformatting, this required deep biological knowledge to re-analyze the data, derive new metrics, and apply advanced methods to ensure the data’s utility. Some key features of the solution include:
- Enabling clients to define exact formats, curated datasets, and specify the information available, ensuring full transparency and confidence in the data.
- Standardizing data into a user-friendly format while giving clients full control over its use, free from restrictive APIs or recurring license fees (beyond data access licenses).
- Supporting system evolution by updating datasets with new metrics and features as the client discovers additional use cases or relevant insights.
These steps transformed the raw information into a standardized, user-friendly format, making it easy to query. This enabled the company to seamlessly analyze and explore their data in a way that met their unique needs, leveraging insights that a basic data analyst or data engineer without a biological background would be unable to achieve. Moreover, the low ongoing costs relative to licensing off-the-shelf platforms or hiring an internal team make the solution a sustainable choice. By owning the system, the company maintains control over it, ensuring it can evolve alongside their needs and discoveries.
Result
The streamlined system transformed the company’s ability to analyze omics data. Tasks that once took hours to query now take minutes, empowering both computational and non-computational biologists to explore terabytes of data with ease. The solution enables a wide range of applications, including:
- stratifying patient populations,
- validating and identifying new targets and indications for therapies,
- selecting optimal cell lines for experiments, and
- conducting exploratory discovery to uncover new opportunities.
The company used this solution to make critical decisions, such as which targets and indications to pursue and which cell lines to select for experiments. It has also provided valuable insights into disease mechanisms, which has supported decision-making efforts. By dramatically reducing query time and increasing accessibility, the company has strengthened its decision-making processes and improved its operational efficiency.
Do you have a question about how to streamline your omics data analysis? Please contact us at contact@diamondage.com or visit https://diamondage.com/contact/.