Throughout its 125-year history, the client has grown into one of the world’s largest biotech companies, as well as a leading provider of in-vitro diagnostics and a global supplier of transformative innovative solutions across major disease areas.
The Challenge
Drug discovery is a complicated process. It requires high precision to analyze big data sourced from various instruments, smart wearables, or across labs – all of which pile up as operational inefficiencies that can cause delays and cost escalations.
The client ran its lab workflow on legacy systems requiring high manual intervention. This was time-consuming and hindered scale-up. A single experiment took a fortnight and 20 scientists; the client could only run 80 weekly experiments. Rerunning these experiments was a costly proposition.
The client commissioned Persistent to help it automate the lab workflow, enabling its scientists to visualize the experiment and see its real-time status to draw timely insights that could lead to faster turnaround at lowered costs.
The Solution
Persistent’s team of Google experts, 5 onshore and 20 offshore, created a platform that automated the client’s lab workflow, helped its scientists visualize the process, and analyzed data in real-time.
Our team leveraged some of Google Cloud Platform’s (GCP) best-in-class solutions, starting with GCP Foundation to quickly set up an enterprise-ready foundation on Google Cloud, including billing and identity management with Google SSO for authentication. We established a secure protocol to connect source and ingestion to GCP and automated data fetching from sequencer pipelines. We leveraged GCP’s Cloud Storage to store unstructured raw data and plugged-in compute engines for on-demand data processing.
The Outcome
The real-time processing of data and automated workflow helped the client:
- Slash experimental costs by 60%.
- Scale-up experiments by 125 times, from 80 per week to 10,000.
- Improve turnaround time with reduced manual errors.
