Daniel Isaac Kemajou Njamen

Daniel Isaac Kemajou Njamen

Dynamic and passion-driven software consultant with hands-on experience in AI-driven data management solutions, and cloud computing architectures.

Software Consultant at Pharma IT

Role: Software Consultant specialized in digital transformation and AI-driven data management solutions within the Pharma Industry.

Focus Areas: Development of pharma-compliant web applications🌐, cloud DevOps☁️, and AI-driven data management🤖.

Key Responsibilities:

  • Development of Pharma-Compliant Web Applications💊
    • Designed and developed IDMP Gap Analysis Tool, a progressive web application for the pharmaceutical industry, built with Vue.js and leveraging Vite.js for an enhanced user experience.
    • Integrated backend AI-driven systems into the application, utilizing Large Language Models (LLMs) for advanced data processing, analysis, and decision-making support, ensuring seamless data flow and regulatory compliance.
  • Cloud DevOps🚀
    • Developed, deployed, and maintained scalable cloud infrastructure across AWS and Azure, optimizing resource utilization and minimizing operational costs while adhering to pharmaceutical industry standards.
    • Implemented CI/CD pipelines and automated workflows, significantly improving the efficiency and reliability of the application lifecycle.
  • Data Workflow Management with AI Integration🔄
    • Architected a multi-stage data extraction and processing pipeline that includes AWS Lambda functions, DynamoDB🗄️ for data storage, S3☁️ for file handling, and AWS Bedrock to interact with Claude 3.5 Sonnet🧠 for intelligent data parsing.
    • Automated study creation, data extraction, and data matching workflows within the app:
      • Create Study Feature: Enables study initiation via file uploads or public health authority searches, triggering a sequence of Lambda functions to handle file uploads and process study metadata.
      • Data Extraction and Validation: Preprocessed files are parsed for required data fields, converted to JSON, and stored in DynamoDB. The app monitors data readiness through timed checks to ensure availability for further actions.
      • Data Matching Feature: Extracted data fields are compared against EMA SPOR regulatory data, with discrepancies flagged to guide users on data validation.
  • Research and Development🔬
    • Conducted research on applying machine learning techniques to medical data extraction, aiming to improve the accuracy and utility of pharmaceutical tools.
    • Employed data science methodologies for large dataset management, data parsing, statistical analysis, and the visual presentation of insights.
  • Collaborative Development and Innovation🤝
    • Worked closely with cross-functional teams to ensure solutions meet regulatory and operational standards, collaborating in the design and validation of user-facing tools.
    • Led co-design activities and iterative prototyping to refine features based on stakeholder feedback, creating incremental, validated solutions for the IDMP Gap Analysis Tool.

Impact:

  • Strengthened regulatory compliance by integrating AI-driven systems for precise and efficient data handling.
  • Reduced operational costs through optimized cloud infrastructure and automated workflows.
  • Enhanced decision-making processes by streamlining data validation and improving data integrity across workflows.

Technologies Used:

  • Programming Languages: JavaScript, Python, C++
  • Frontend: Vue.js, Vite.js
  • Backend and Cloud: AWS Lambda, DynamoDB, Amazon S3, AWS Bedrock, Azure DevOps.
  • Database Systems: AWS DynamoDB, PostgreSQL (Amazon RDS).
  • AI and Data Processing: Large Language Models (LLMs) and data integration.