application and data modernization

Meet Our Customer

Founded in 2009, Nurix Therapeutics is a clinical-stage, science-focused company committed to bringing novel, first-in-class therapies to patients who do not have adequate treatment options. Nurix develops small molecule drugs that are designed to modulate protein levels in cells as a new therapeutic approach for a broad range of diseases.

Challenge

When Nurix first approached NorthBay Solutions, the company was wrestling with a rigid, legacy on-premises Oracle infrastructure that was holding them back.

The database was used to collect and analyze participant data, and at 1.2 terabytes and counting, the licensing fees and maintenance costs had become unmanageable.

Application and data modernization would enable Nurix to not only reduce the high fixed-costs associated with Oracle, but also be able to scale usage and fees up and down along with the data processing requirements.

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Challenge

When Nurix first approached NorthBay Solutions, the company was wrestling with a rigid, legacy on-premises Oracle infrastructure that was holding them back.

The database was used to collect and analyze participant data, and at 1.2 terabytes and counting, the licensing fees and maintenance costs had become unmanageable.

Application and data modernization would enable Nurix to not only reduce the high fixed-costs associated with Oracle, but also be able to scale usage and fees up and down along with the data processing requirements.

Implication

Unless Nurix modernized their infrastructure, they would continue to wrestle with high costs and lengthy data processing cycles, which would inhibit them from moving forward with the multiple rounds of complex, simultaneous clinical trials required to develop breakthrough therapies.

Vision

As a pioneer in novel therapeutics, Nurix is relentlessly committed to the highest level of scientific inquiry. An agile IT infrastructure would enable them to conduct more clinical trials, process data analytics more quickly, and launch new drugs to help patient’s lives.

Solution

Migrating from a proprietary Oracle database to the cloud would give Nurix massive scalability at a manageable cost — if they could be convinced to do so. A long-time user, Nurix was initially skeptical about migrating their Oracle database. Also, their existing technology partner lacked extensive cloud transformation experience, and thus recommended that Nurix reach out to NorthBay Solutions.

The team at NorthBay Solutions proposed decommissioning their on-premises Oracle database and deploying a solution on AWS Aurora PostgreSQL. Knowing that Nurix would require proof that the AWS Aurora PostgreSQL solution would meet their technical requirements and time to learn how to operate it in production, NorthBay Solutions first conducted an extensive analysis of the current environment, then developed a reference architecture for the AWS Aurora PostgreSQL database.

Next, they migrated and tested all recent dataset and historical data, and conducted multiple mini-Proofs of Concept (POCs) along the way to validate that it was functioning as expected. Once all 1.2 TB of data had been migrated, they validated it via row-by-row comparison of the source (Oracle) and destination (Aurora PostgreSQL) databases. Finally, NorthBay Solutions developed an operational procedures runbook for managing the solution in production.

Benefits

As a result of partnering with NorthBay for the AWS database migration, Nurix was able to:

  • Reduce analytics processing times from days to hours in order to run more simultaneous clinical trials
  • Gain the agility required to scale resources along with processing needs at a manageable cost.
  • Shift from a rigid upfront Capex model to a more flexible, consumption-based Opex model.
  • Take advantage of funding available through the AWS DB Freedom program to offset implementation costs.

What’s Next

Following the success of the migration project, the NorthBay team is now working with Nurix to develop a roadmap and vision for modernizing applications and adopting machine learning solutions