MerSci helps companies in BioPharma industry to rapidly integrate data from pre-clinical and clinical research systems, experimental sources, sensor networks, and external providers to address challenging analytics problems in areas such as Genomics, Transcriptomics, Proteomics, Metabomics, and System Biology, by leveraging statistical and machine learning models that generate actionable insights.
A major biotech research institute specialized in Proteomics, faced several challenges in establishing an effective linkage between their data acquisition channels from experiments and the core customizable analytics engine.
MerSci developed a customized platform to automate and scale the analytics pipeline by real-time ingestion of the streamed data from experiments into the analytics engine.
It provides a vast set of insights through various analysis techniques ranging from statistical analyses such as feature interaction analysis, sequential data modeling, and design of experiments to machine learning-based solutions such as anomaly detection and cluster analysis.
The developed solution played a major role in supporting basic and clinical research needs. It provided an integrated environment to perform end-to-end development of various analyses on real-time streaming data.
Leveraging cutting-edge technologies such as GPU-accelerated analytics, the time for solution prototyping was reduced significantly which resulted in a substantial efficiency gain.
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