1. First, describe a biological engineering application or tool you want to develop and why. This could be inspired by an idea for your HTGAA class project and/or something for which you are already doing in your research, or something you are just curious abou

Breath-based mutation sensor

This is A biosensor concept inspired from a research paper I read. This was a very fascinating concept of real time, noninvasive detection of SARS-CoV-2 at room temperature via a wearable that integrated a lyophilized CRISPR sensor.

Here is a breath emission simulator mimics real breathing and aerosolized viral emissions demonstrating the working of this mask:

Screenshot (134).png

Screenshot (133).png

The face-mask-integrated sensor demonstrated the ability to detect SARS-CoV-2 RNA from exhaled aerosols within 1.5 hours, with a detection limit of 500 copies (17 aM), matching lab-standard RT-PCR sensitivity. The system operates without power, handles autonomous reactions at ambient temperatures, and provides visual outputs via an LFA strip, showing high specificity without cross-reactivity to other coronaviruses. Designed for simplicity and portability, the mask combines viral detection with respiratory protection, offering potential for real-time diagnosis and variant discrimination.

How do we integrate this mechanism to develop a wearable, real time, breath-based mutation sensor?- My ideation

A breath-based mutation sensor could analyze VOCs, nucleic acids, or proteins in exhaled breath for the detection of genetic mutations responsible for diseases like cancer, metabolic disorders, or genetic conditions.

This could be done in several ways-

Exhaled breath condensates are biofluids collected from exhaled air, containing small amounts of DNA, RNA, proteins, and metabolites. Genetic mutations may result in the presence of circulating tumor DNA or microRNAs in exhaled breath condensates, acting as biomarkers for detecting the disease
Mutations can alter metabolic pathways, leading to specific volatile compounds in the breath
Mutations may produce abnormal protein expression, possibly emitted in aerosolized form

Sensor mechanism:

CRISPR based biosensors that can detect specific DNA/RNA sequences
Nanopore Sequencing for Mutation Detection in Breath
Electronic Nose (E-Nose)

Mechanism of detection

graph TD
    A["User Exhales into Collection Device"] --> B["Filtration & Preprocessing"]
    B --> C["Detection Module"]
    
    C --> D["VOC Analysis"]
    C --> E["DNA/RNA Detection"]
    C --> F["Protein Screening"]
    
    D --> G["Gas Sensors"]
    E --> H["CRISPR Biosensors"]
    E --> I["Nanopore Sequencing"]
    F --> J["Antibody-based Assays"]
    
    G --> K["Data Processing"]
    H --> K
    I --> K
    J --> K
    
    K --> L["Result Output"]
    
    %% Subprocesses for clarity
    style C fill:#f9f,stroke:#333
    style K fill:#bbf,stroke:#333
    style L fill:#bfb,stroke:#333

2.Next, describe one or more governance/policy goals related to ensuring that this application or tool contributes to an "ethical" future, like ensuring non-malfeasance (preventing harm). Break big goals down into two or more specific sub-goals.

Ensuring Non-malfeasance of a breath-based mutation detector: Benchmarks

Etablish regulatory approval for sensor accuracy
Implement false positives (incorrectly detecting a mutation) and false negatives (failing to detect an actual mutation) to avoid misdiagnosis

Benchmark 1: Making sure that the said device is safe to use
Usage of Artificial intelligence and softwares for better accuracy and best detection

Benchmark 2: Integrating the device into healthcare services

Ensure compatibility to give clinician usability open to any clinical use
If a test result is uncertain,it should go for confirmatory testing rather than making a definitive diagnosis
If a detected mutation indicates a high-risk disease, immediate referral to a specialist should be mandated

Benchmark 3: Ensuring Responsible Use & Patient Well-Being

Only certified doctors or genetic specialists should explain results to avoid misinterpretation
The system should guarantee that if a patient goes wrong, there should be a region for such patients to make complaints and receive medical and legal assistance
Patients should properly be counseled before the test, so amended they understand why it is done and what limits it has, and afterwards, to discuss next steps relating to the results

3.Next, describe at least three different potential governance "actions" by considering the four aspects below (Purpose, Design, Assumptions, Risks of Failure & “Success”)

Policies Aspects	1. Mandate	2. Security Policies	3. Clinical implementation	4. Awareness
Purpose	Ensure the tool meets safety, reliability, and efficacy standards for clinical use	Protect patient data from misuse	Ensure sensitivity and accuracy in clinical setting	Educate the public about the tool’s capabilities and limitations
Design	Develop clear guidelines for clinical use and regular performance assessments	Implement end-to-end encryption for all patient data collected via the device	Proper calibration and prototyping	User friendly and transparent design
Assumptions(uncertainty)	No Recognition by government regulatory bodies	Patients trust the device with their sensitive data	Acceptance from healthcare services	The public will have access to clear, accessible information about the tool

| | Risks of failure | Errors in testing protocols can result in incorrect results or failure to comply with regulatory standards | can lead to privacy and legal consequences

4.Next, score (from 1-3 with, 1 as the best, or n/a) each of your governance actions against your rubric of policy goals. The following is one framework but feel free to make your own:

Policies Framework	1. Mandate	2. Security Policies	3. Clinical implementation	4. Awareness
Feasibility	2	1	2	1
Safety	1	1	1	2
Sustainability / Environmental impact	2	n/a	3	3
Longevity	1	2	1	3

5.Last, drawing upon this scoring, describe which governance option, or combination of options, you would prioritize, and why. Outline any trade-offs you considered as well as assumptions and uncertainties

Priority 1: Clinical implementation

Clinical integration is essential for improving patient outcomes. The tool must be seamlessly incorporated into existing clinical workflows to ensure safety and effectiveness in real-world settings

Trade-off:

Successful clinical implementation demands significant resources, staff training, and infrastructure modifications—challenges that are particularly acute in resource-limited settings

Assumptions and uncertainties:

Healthcare workflows can accommodate the new technology, and medical professionals will embrace its adoption
Substantial upfront costs may slow implementation, particularly in healthcare systems with limited funding

Priority 2: Security Policies

Security policies ensure patient safety by protecting privacy and data integrity, especially with sensitive genetic and personal information. This action scored well in Feasibility (1) and Safety (1), making it a priority

Trade-off:

While effective and feasible, security policies can complicate data handling and require ongoing updates to address new cybersecurity threats

Assumptions and uncertainties:

Assumes that technology providers and healthcare institutions will prioritize strong security and regular audits
The evolving nature of cyber threats and the cost of maintaining robust security infrastructure could pose long-term challenges

Resources and references:

*Nguyen, P.Q., Soenksen, L.R., Donghia, N.M. et al. Wearable materials with embedded synthetic biology sensors for biomolecule detection. Nat Biotechnol 39, 1366–1374 (2021). https://doi.org/10.1038/s41587-021-00950-3

OpenAI ChatGPT (2025). Corrected grammar, explained concepts. OpenAI. Retrieved from https://openai.com/chatgpt*