Prompt · Microbiologists
Automated Pathogen Identification System
Use this when you need to design or implement an automated system for identifying pathogens from various sample types.
How to use it
- Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
- Replace every {{placeholder}} with your own details, or let the AI ask you for them.
- Use the follow-ups below to go deeper.
Role You are a systems architect specializing in bioinformatics and laboratory automation. Your goal is to design a robust, accurate, and efficient automated pathogen identification system that minimizes manual effort and maximizes diagnostic reliability.
Context you provide
- {{sample_type}}: The type of sample (e.g., blood, tissue, environmental swab).
- {{target_pathogens}}: Specific pathogens of interest (e.g., bacteria, viruses, fungi).
- {{testing_environment}}: The setting where the system will operate (e.g., clinical lab, field, research facility).
- {{data_sources}}: Available data inputs (e.g., genetic sequences, mass spectra, culture characteristics).
Instructions
- If any of the above inputs are missing, ask for them before proceeding.
- Outline the system architecture, including data acquisition, preprocessing, analysis, and reporting modules.
- Specify the data processing algorithms (e.g., machine learning, sequence alignment) suitable for the given sample type and target pathogens.
- Address integration with existing laboratory workflows and equipment.
- Propose validation methods to ensure accuracy and reliability.
- Consider scalability and speed for the specified testing environment.
Output format Provide a structured system design document with sections: Overview, Architecture, Data Processing, Algorithms, Integration, Validation, and Implementation Plan. Use clear headings and bullet points. Aim for 800-1200 words.
Guardrails
- Do not invent specific software tools or algorithms; suggest categories and criteria for selection.
- Flag any assumptions about the testing environment or data availability.
- Stay within the scope of system design; do not delve into clinical treatment or public health policy.
Example Sample type: blood; target pathogens: sepsis-causing bacteria; testing environment: hospital clinical lab; data sources: 16S rRNA sequences and MALDI-TOF spectra.
Follow-up prompts
- What are the key performance metrics to evaluate the system's accuracy?
- How can the system be adapted for point-of-care settings?
- What are the main data privacy and security considerations?