For a small Biotech company, having all of their research data in a cleaned, validated and ready-to-use format is a critical part of their IP strategy. This organization counts a variety of chemical companies amongst its client base, and keeping their proprietary data secure yet complete and easy to disseminate is key to the value they provide their clients. Indeed, it’s key to the value of their company as a whole.
As their research teams generate new data, it’s captured by the Snthesis platform where it is aggregated, connected and harmonized before being exported into their in-house data science infrastructure in a clean and validated format. This approach frees their data science team to focus on delivering valuable insight instead of focusing on aggregating and validating data. The resulting flow of information is driven to reporting tools and dashboards for their closely-engaged Management and Sr. Leadership.
Using Snthesis has allowed them to evolve their experimental data pipelines without any outside assistance and gives them complete agency to add new classes of data or new data points as needed. Most importantly, the Snthesis platform allows them to quickly create new datasets and compile both recent and historical research data in support of the requirements of new clients. This reduction in time-to-value fosters a nimble and agile approach to growth in the biotech space.
The assays they have developed to assess whether a given sample is viable for a given purpose is part of their IP. Being able to aggregate, connect and harmonize all of the data generated by an assay or series of assays over time (including sample provenance and context of creation) is crucial in proving the validity of individual assays and the overall assay pipeline to potential partners and clients. In turn, being able to do that is crucial in proving the value of the organization to potential investors.
In some cases it’s not just “what you know”. It’s being able to quickly combine different assay results and surface them in a validated, secure and flexible environment so you can easily prove and share what you know.
For a small Biotech company, having all of their research data in a cleaned, validated and ready-to-use format is a critical part of their IP strategy. This organization counts a variety of chemical companies amongst its client base, and keeping their proprietary data secure yet complete and easy to disseminate is key to the value they provide their clients. Indeed, it’s key to the value of their company as a whole.
As their research teams generate new data, it’s captured by the Snthesis platform where it is aggregated, connected and harmonized before being exported into their in-house data science infrastructure in a clean and validated format. This approach frees their data science team to focus on delivering valuable insight instead of focusing on aggregating and validating data. The resulting flow of information is driven to reporting tools and dashboards for their closely-engaged Management and Sr. Leadership.
Using Snthesis has allowed them to evolve their experimental data pipelines without any outside assistance and gives them complete agency to add new classes of data or new data points as needed. Most importantly, the Snthesis platform allows them to quickly create new datasets and compile both recent and historical research data in support of the requirements of new clients. This reduction in time-to-value fosters a nimble and agile approach to growth in the biotech space.
The assays they have developed to assess whether a given sample is viable for a given purpose is part of their IP. Being able to aggregate, connect and harmonize all of the data generated by an assay or series of assays over time (including sample provenance and context of creation) is crucial in proving the validity of individual assays and the overall assay pipeline to potential partners and clients. In turn, being able to do that is crucial in proving the value of the organization to potential investors.
In some cases it’s not just “what you know”. It’s being able to quickly combine different assay results and surface them in a validated, secure and flexible environment so you can easily prove and share what you know.
