Acceleration in the cancer target identification timeline
Improvement in prediction for cancer-specific protein targets
Through improved differentiation between cancer-specific and normal tissue protein expression
A leading biopharma company developing novel cancer therapeutics needed to accelerate target discovery without compromising scientific rigor. The work required an analytics platform capable of processing massive-scale genomics datasets, identifying and prioritizing potential cancer targets, and distinguishing cancer-specific protein expressions from normal tissue, the precondition for reducing toxicity in downstream therapeutics.
The company's existing tooling could not standardize data across the varied experimental platforms its researchers depended on, and visualization of complex genomic relationships remained manual and slow. The result was a target discovery pipeline that was scientifically credible but operationally constrained.
OneSix designed and built an advanced genomics analytics platform engineered for the scale and specificity of cancer target discovery. The platform applies machine learning models to large-scale cancer genome datasets, with algorithms that identify and prioritize gene expressions and dedicated prediction engines that distinguish cancer-specific from normal tissue protein targets.
Meta-analysis capabilities standardize data across varied experimental platforms, allowing researchers to compare and combine findings that previously sat in incompatible formats. Visualization tools surface complex genomic relationships in forms researchers can interrogate, shortening the path from data to hypothesis.
In production, the platform delivered a 3X acceleration in the target identification timeline and an 85% improvement in prediction for cancer-specific protein targets. By improving the differentiation between cancer-specific and normal tissue, the platform also helps researchers identify candidate targets with lower toxicity risk, a material advantage in the development of novel cancer therapeutics.
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