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Context
Challenge
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Contribution
Impact
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Life Sciences

AI-Driven Extraction of Consent Data for a Fortune 500

Overview
Context
Challenge
Testimonial
Contribution
Impact
Why It Matters?
Overflow
Overview & Metadata

AI-Driven Extraction of Consent Data for a Fortune 500 Life Sciences Company

Developed an AI-powered system to extract structured consent information from medical documents, enabling compliant use of millions of patient samples for research.
Client Context
Client Context

A Fortune 500 life sciences organisation required a scalable way to extract structured information from informed consent forms (ICFs). These documents determine whether patient biological samples can legally be used for internal research.

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Hybrid Mind Supported →

The client engaged Hybrid Mind for their AI specialism to build the extraction pipeline, accelerate delivery, and guide AI adoption within a multidisciplinary team including tech leads, data engineers, AI testers, product owners, and program managers.

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Challenge

Key Challenges We Faced

The client engaged Hybrid Mind for their AI specialism to build the extraction pipeline, accelerate delivery, and guide AI adoption within a multidisciplinary team including tech leads, data engineers, AI testers, product The program faced several major challenges:

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1. Highly Nuanced Consent Rules

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ICFs contain exception-heavy rules that historically lived only in the heads of domain experts. This knowledge needed to be formalised and embedded into an AIsystem.

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2. RareInternal Tooling

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The work required development of an internal platform unfamiliar to most engineers.

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3. Restricted LLM Access

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Compliance constraints prevented direct model access and required complex procedures for experimentation.

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4. Rapid Decision-Making Under Pressure

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After an abrupt departure of the previous AI engineer, our specialist was required to make architectural decisions quickly to meet release deadlines.

Our Contribution

Hybrid Mind Delivered

1. AI Pipeline Development

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  • Designed and implemented the end-to-end AI extraction pipeline.
  • Built data‑processing logic to handle edge cases and prepare documents for modelling.

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2. Reusable Accelerators

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  • Created a fast automatic evaluation tool for rapid comparison of model outputs. 

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3. Documentation & Compliance Readiness

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  • Produced comprehensive documentation of previously undocumented business rules.  
  • Applied regulatory-grade documentation practices to strengthen auditability.  

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4. Technical Decision-Making

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Provides rapid architectural decisions and guidance on AI testing strategy during a critical delivery period.

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Impact

Hybrid Mind works with enterprises to unlock real value from AI, from readiness to measurable impact

We combine strategic insight with hands-on technical execution to help enterprises turn AI potential into measurable, lasting business impact
  • Increased system accuracy, reliability, and overall performance for ICF codification.

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  • Introduced confidence scoring for prioritisation of AI outputs by business users.

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  • Enables faster identification of internal biological samples, reducing dependency on external purchases.

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  • Ensured continued compliance with regulatory constraints on patient consent.

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Quantifiable Benefit:

  • Initial accuracy: ~60%
  • Accuracy after project completion: 90–95%
Why It Matters?

Why It Matters?

This work establishes the foundation for a compliant enterprise consent intelligence system, unlocking more value from internal biological samples.

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It demonstrates Hybrid Mind’s strengths in:

  • AI information extraction and NLP
  • Embedding specialists rapidly into complex delivery environments
  • Translating tacit expert knowledge into robust AI logic
  • Building reliable and auditable AI systems

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