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Deep 6

Deep6 accelerates clinical trial recruitment with Spark NLP

Read the full case study

INDUSTRY: Life Science

Introduction: Deep6 AI uses cutting edge data and engineering techniques to find more, better-matching patients for clinical trial in minutes, not months.

Challenge: “Recruiting patients for clinical trials is a major challenge in drug development. Finding patients requires an in-depth understanding of their medical histories and current health statuses while the majority of patient data is unstructured and spread across physician notes, pathology, imaging, genomic, and other reports. For this reason, clinical trial recruitment is a slow and manual process. Too few people participate in clinical trials, and the consequences are enormous:

  • 10.8 average months of delay per trial 10.8
  • 86% of trials suffer delays
  • 50% of trial sites fail
  • 993 Human lives lost on 1 blockbuster drug
  • 2.9B Revenue lost on 1 blockbuster drug
  • 5x Drug price increase”

Solution: Deep 6 uses the Spark natural language processing (NLP) platform to apply state-of-the-art deep learning to accurately extract the relevant clinical facts from unstructured text. These facts are then used in subsequent data science pipelines in constructing patients’ medical histories.

50%less errors than spaCy makes on NER
80xfaster training than spaCy on one machine
Zerocode changes to switch between local and cluster models
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