Using Document Summarization Successfully in Biotech Research
A biotech company partnered with PTP to deploy an AWS Bedrock-powered summarization system thatreduced document review time by 50% , improved collaboration, and ensured sensitive research data remained secure.
Overview
As a pioneer in allogenic cell therapies, the Company manages enormous volumes of research documentation. From peer-reviewed publications and preclinical trial data to internal experimental reports, the sheer weight of information often slowed the ability of scientists, clinicians, and executives to extract the insights that mattered most.
The problem was not access — the Company had plenty of data — but speed and clarity. Key findings were often buried in 50-page reports or technical papers that took hours to digest. Scientists were spending precious time parsing documents instead of running experiments. Executives, meanwhile, needed concise and regulator-ready summaries to make informed strategic decisions.
The Company recognized the potential for Generative AI (GenAI) to transform this workflow. However, like many biotech companies working with sensitive data, the Company had strict security requirements that ruled out SaaS-based LLMs. Public AI services carried risks of intellectual property leakage and compliance violations. The Company turned to PTP to design a secure, AWS-native summarization solution that met both technical and regulatory needs.
The Challenge
The barriers the Company faced were familiar across biotech, but particularly acute in high-stakes cell therapy research:
1. Information Overload
Internal teams were consuming dozens of dense scientific papers and clinical trial reports weekly. Extracting actionable findings took too long.
2. Inconsistent Summaries
Human-created summaries varied in quality and clarity. The lack of standardization created friction in cross-functional collaboration.
3. Security Concerns
With sensitive internal research data at stake, SaaS LLMs were not an option. Any solution had to operate within the Company’s secure AWS environment with guardrails for HIPAA and GxP compliance.
The Company wanted a system that could:
- Rapidly summarize both internal documents and external publications.
- Provide consistent, regulator-friendly outputs.
- Operate entirely within a secure, compliant AWS architecture.
The Solution
PTP architected and delivered a secure, GenAI-powered summarization framework running on AWS Bedrock. The solution balanced cutting-edge AI capabilities with the compliance, scalability, and security posture biotech companies demand.
Key Solution Components
AWS Bedrock for Summarization
Bedrock was selected for its flexible access to multiple foundation models through a single API. PTP used prompt engineering and light fine-tuning to optimize summaries for research clarity and regulatory tone.
Amazon S3 as a Secure Document Repository
Internal research documents and curated external publications were ingested into Amazon S3, providing a single, secure repository. This ensured data stayed within the company’s AWS boundary.
Amazon Textract & Kendra for Preprocessing
Amazon Textract converted PDFs and scanned documents into structured text. Amazon Kendra added intelligent search across documents, ensuring the summarization system could pull relevant context before generating outputs.
Custom Prompt Engineering
PTP developed domain-specific prompts that emphasized clarity, neutrality, and regulator-friendly formatting. This ensured that summaries were not only concise but also aligned with FDA communication standards.
Researcher-Facing Chatbot Interface
Instead of adding another dashboard, PTP delivered a simple, secure chatbot UI powered by Open WebUI. Scientists could upload a document, ask for a summary, or request key findings, and receive results in seconds.
Why AWS
The company selected AWS as the backbone for this project because of three critical advantages:
Security and Compliance
With sensitive research data at the core of operations, AWS provided a secure, compliance-ready environment. S3, SageMaker, and Bedrock operated within the company’s isolated VPC, ensuring data never left the secure boundary.
Breadth of Model Choice
AWS Bedrock offered access to multiple foundation models through a unified API, allowing experimentation with ProtGPT2, ProtBERT, and other specialized models without costly redevelopment.
Scalability
AWS’s elastic infrastructure meant the company could scale computationally intensive protein folding workloads up or down as research demands shifted. This flexibility allowed acceleration without overinvesting in static infrastructure.
Why PTP
The company chose PTP as its partner because of its deep expertise in both AWS consulting and life sciences R&D.
Life Sciences Competency
As an AWS Life Sciences Competency partner, PTP brought domain-specific knowledge of biotech workflows, regulatory constraints, and scientific data handling.
Proven AWS Delivery
With years of AWS consulting experience, PTP designed and delivered a pipeline that adhered to AWS best practices while meeting the company’s unique research needs.
Innovation and Enablement
Beyond building the system, PTP enabled the company’s team with training, documentation, and extensibility—ensuring they could independently grow the framework to support future research initiatives.
The Results
The deployment produced immediate benefits:
50% Faster Document Review
Scientists reported cutting review time in half. Instead of spending hours parsing journal articles, they received concise, contextually accurate summaries in minutes.
Improved Cross-Team Collaboration
Standardized summaries meant clinical, research, and executive teams were aligned faster, reducing friction and duplication of effort.
Greater Focus on Research
Scientists spent less time on administrative reading and more time in the lab, directly accelerating experimental throughput.
Secure and Scalable Foundation
By operating fully on AWS, the Company eliminated the risks associated with SaaS GenAI tools and built a foundation it could extend to future research applications.
Conclusion
The Company’s use of AWS Bedrock-powered summarization demonstrates how secure, domain-specific GenAI can solve one of biotech’s most pervasive challenges: turning mountains of research documents into actionable knowledge.
By partnering with PTP, the Company accelerated document review, improved collaboration, and gave scientists more time to innovate—all while keeping sensitive data protected. The project illustrates the power of combining AWS’s secure AI services with PTP’s life sciences expertise to deliver measurable, real-world impact.
Unlock Faster, Smarter Research with AI-Powered Summarization
Accelerate discovery by transforming dense scientific documents into concise, regulator-ready insights. Partner with PTP to deploy secure, AWS-native AI solutions that save time, improve collaboration, and keep sensitive data protected.
Schedule your free consultation today.
Tell us a bit about your project to get started with PTP. Fill out the form below and our team will be in touch shortly.