We have designed two versions of hydrogen sulfide detectors: one is a home-use device, and the other is a laboratory/medical-level device. These detectors serve two key purposes: helping obese patients to monitor the amount of hydrogen sulfide in their intestines as well as supporting medical and scientific research.
The home-use version is particularly practical, as it allows patients to carry out self-monitoring at home. Through breath detection, the collected data is transmitted to the mobile phone.
The laboratory/medical-grade version provides highly accurate results, which support medical blood glucose management and scientific research. It is particularly helpful for evaluating the efficacy of blood glucose regulation and fat reduction strategies—including the effectiveness of protein capsule consumption and the impact of changes in hydrogen sulfide levels on fat reduction processes.
Figure 1. Schematic Diagram of Hydrogen Sulfide Detector: Laboratory (Medical) Version (A); Home Version (B)
The application of synthetic biology in developing protein capsule for managing blood sugar and fat content faces a significant translational challenge: the lack of convenient and accurate methods to monitor key confounding variables, particularly intestinal hydrogen sulfide (H₂S). This gap impedes both clinical adoption and scientific validation. For patients, the inability to track H₂S fluctuations at home prevents real-time feedback on the pill's efficacy, undermining adherence and personalized management. Concurrently, clinical research lacks robust detection systems to objectively assess the intervention's impact, hindering the mechanistic validation of these synthetic biology-driven therapies. Currently available detection tools are insufficient; they are often either operationally complex for routine use or limited to a single context (e.g., exclusively clinical), failing to bridge the diverse needs of home-based monitoring and rigorous scientific inquiry.
Conventional large-scale hydrogen sulfide (H₂S) detection primarily relies on bulky, laboratory-bound equipment, rendering it unsuitable for home use. While some simplified detection gadgets exist, they often lack the necessary precision and yield non-intuitive data. Specifically, within the context of synthetic biology applications for blood sugar control and fat reduction, existing instrumentation fails to integrate the essential dual requirements of home-use convenience and clinical-grade accuracy. Consequently, these tools are incapable of supporting a comprehensive assessment of the causal relationship between H₂S clearance facilitated by protein tablets and subsequent physiological outcomes like fat reduction. This inadequacy makes them unable to satisfy the project's need for a seamless, end-to-end detection solution that bridges domestic monitoring and clinical validation.
Our project aims to develop an orally administered protein tablet based on synthetic biology to achieve blood glucose control and fat reduction. Its core technological principle lies in the tablet's ability to actively eliminate excess hydrogen sulfide (H₂S) in the gut through specific proteins it contains. This removal promotes the secretion of glucagon-like peptide-1 (GLP-1) in the gut, which in turn stimulates insulin secretion. This dual mechanism ultimately regulates blood glucose levels and promotes fat reduction.
To precisely evaluate the tablet's efficacy, we incorporate specialized equipment to monitor changes in intestinal H₂S concentration. This monitoring data serves as the foundational evidence chain for directly demonstrating the tablet's effectiveness. It will help healthcare professionals and patients understand the entire physiological pathway-from H₂S clearance to GLP-1 elevation, insulin secretion, and ultimately fat reduction. It assists medical staff and obese patients in understanding the process of fat reduction, which is a valuable auxiliary instrument in determining the blood sugar regulation and fat reduction impact of the protein pills. Assist the project towards the object of moderate and effective weight management.
The home version of the device is portable and features user-friendly air-breathing sensing. The data interface, accessible via mobile apps, is streamlined for ease of use, meeting the requirements for long-term at-home patient monitoring. Its high portability allows patients to use it effortlessly during daily activities and travel, enabling convenient monitoring at any time.
The laboratory (medical) version of the apparatus is engineered to deliver highly accurate and reliable data, making it indispensable for rigorous clinical blood sugar management and advanced scientific research. Its primary application lies in quantitatively assessing the efficacy of novel interventions, such as protein capsule consumption, on glycemic control and fat loss. By precisely tracking fluctuations in hydrogen sulfide (H₂S) levels within a controlled setting, this device provides critical insights into the underlying biochemical processes-namely, how H₂S modulation facilitates fat reduction. It thus serves as a vital tool for validating the mechanisms and effectiveness of synthetic biology-based therapeutic strategies.
The development of the hydrogen sulfide (H₂S) detection platform followed a structured iterative design process, with each version addressing limitations of its predecessor while introducing new functionalities to meet the dual requirements of accurate clinical measurement and practical home use. The evolution of the device is summarized in Figure 2 and detailed below.
Figure 2. Evolution of the H₂S Detection System: An Iterative Design Process
Version 1.0 (Proof of Concept): The initial design, inspired by methodologies outlined in a foundational Nature article, established the core function of H₂S detection. However, this prototype suffered from critical drawbacks: the lack of an exhaust gas recovery system, an inconvenient sample introduction mechanism requiring frequent stopper replacement, and a reliance on qualitative test strips that yielded unclear results and were prone to ejection.
Versions 2.0 (Process Zoning): To address the procedural inefficiencies of V1.0, these iterations introduced a conceptual framework of zoned sample handling. This design optimization aimed to compartmentalize the workflow, thereby facilitating future integration of tail gas management. Despite this improvement, the system remained non-hermetic, allowing for gas leakage, and the qualitative analysis approach still lacked portability and precision.
Version 3.0 (System Integration and Quantification): This version marked a significant advancement by synthesizing the components into an integrated unit and incorporating a quantitative concentration sensor, replacing the unreliable qualitative strips. Two major disadvantages emerged: first, the sample introduction process required opening a display window, leading to substantial loss of the target H₂S gas and consequent inaccuracy; second, the issue of exhaust gas recovery was neglected, posing a potential environmental hazard.
Version 4.0 (Throughput Enhancement): Building upon the integrated design of V3.0, this iteration focused on improving operational efficiency. The key advantage was the capability for simultaneous testing of three samples, significantly enhancing throughput. Nonetheless, it inherited the fundamental flaws of gas loss during sampling and lack of exhaust treatment.
Version 5.0 (Stabilization and Conceptual Pivot): This stage prioritized enhancing the system stability of the V4.0 platform. More importantly, it represented a critical conceptual pivot with the formal proposal of a dedicated home-use version, explicitly defining the need for a device tailored to patient-centric monitoring outside clinical settings.
Version 6.0 (Environmental Compensation and Data Accuracy): The current iteration (V6.0) further improved stability and introduced critical sensors for environmental data compensation. Specifically, temperature and humidity sensors were integrated alongside the MQ-136 H₂S semiconductor sensor. Given that the electrical response of semiconductor sensors is highly susceptible to ambient temperature and humidity fluctuations, this addition enables real-time data correction. This compensation is essential for eliminating measurement errors and ensuring the accuracy and reliability of the H₂S concentration readings in diverse usage environments.
Temperature dependence of the sensor: The core of the electrochemical sensor (the most commonly used H₂S detection tool) is the electrode reaction: H₂S is oxidized to H₂SO₄ or S on the working electrode, and the current generated is proportional to the concentration of H₂S. However, the electrode reaction rate is significantly affected by temperature - according to Arrhenius' law, for every 10℃ increase in temperature, the reaction rate may increase by 2 to 3 times, resulting in a larger detection current at the same concentration. If the temperature is too low, the reaction rate will decrease and the current will be smaller.
Semiconductor sensors detect concentration by the adsorption reaction of H₂S with metal oxides (such as SnO₂), which causes resistance changes. However, the adsorption/desorption equilibrium constant varies with temperature, directly altering the resistance response value and leading to misjudgment of concentration.
Temperature effect of gas volume: As a gas, the molecular motion and density of H₂S follow the ideal gas equation of state (PV=nRT) : under constant pressure, an increase in temperature will cause the gas volume to expand, and the number of H₂S molecules per unit volume will decrease (apparent concentration reduction). When the temperature drops, the molecular density increases (the apparent concentration rises). Even if the actual concentration remains unchanged, temperature fluctuations will cause changes in the "molecular collision frequency" detected by the sensor, resulting in errors.
Humidity interference of the sensor: In a high-humidity environment, water vapor condenses on the surface of the sensor's breathable membrane, hindering the diffusion of H₂S molecules to the electrode/sensing layer, resulting in a lower detection signal. Meanwhile, water vapor may dissolve H₂S (H₂S is highly soluble in water with a solubility of approximately 4.6g/100mL), forming an H₂S aqueous solution and altering its reaction path with the sensor.
Low humidity environments may cause the sensor surface to dry out, especially the evaporation of the electrolyte in electrochemical sensors, which disrupts the ion conduction at the electrode interface and reduces the sensitivity. Semiconductor sensors may have their resistance stability affected by static electricity accumulation in low humidity conditions.
Humidity requirements for chemical detection methods: If the chemical colorimetric method (such as lead acetate test paper) is adopted, H₂S must first be dissolved in water vapor to form HS⁻ before it can react with Pb²⁺ to produce black PbS. When the humidity is too low, H₂S dissolves insufficiently, resulting in slow color development or a lighter color, leading to an underestimation of the concentration. Excessive humidity may dilute the reaction reagents on the surface of the test paper, which also affects the color development intensity.
By collecting the ambient temperature (T) and relative humidity (RH) in real time, the detection system can invoke the compensation algorithm.
For temperature: Based on the temperature-response curve of the sensor (for example, if the calibration value at 25℃ is known, correct the detection results at 30℃ or 20℃);
For humidity: Adjust the signal at 80% RH or 30% RH through the humidity-sensitivity relationship (such as the correction coefficient at 50% RH).
Ultimately, the original data affected by environmental interference is corrected to the concentration values under standard conditions (such as 25℃, 50% RH) to ensure measurement accuracy. In short, the temperature and humidity sensor is an ‘environmental interference corrector’, and its principle is based on the physical/of H₂S detection.
The components of the device, arranged from bottom to top, are: an air pump, a gas recovery tank, an H₂S concentration sensor, a temperature and humidity sensor, a platform, test tube clamps, two pipes connected to the clamps, a digital display screen, and a microcontroller.
Figure 3. Medical version Actual Product Image
Modeling Software: We use Solidworks to draw the model of hardware.
The Shell: It is constructed using aluminum profiles to form the corner framework, with glass panels serving as the planar surfaces. Lightweight, with high mechanical strength and excellent corrosion resistance, aluminum profiles are highly suitable for the framework construction and assembly of our product. This design ensures stability while maintaining visibility during operation.
Test Tube Clamp & Screw Thread: The sampling process requires manual intervention. An operator first opens the sample tube cap externally and inserts the tube into a circular hole on the platform. After the tube is manually rotated and secured via its screw thread, an internal tube clamp within the device immediately engages. This mechanism ensures a rapid and airtight seal, effectively preventing sample contamination during the testing procedure.
Air Pump: It is designed to force gas into the tube, compressing the hydrogen sulfide (H₂S) inside and ensuring it fully contacts the two sensors located below the clamp, and to force the gas through the other pipe into the gas recovery tank eventually.
Adsorbent: It is a mixture containing CO₂ adsorbent, activated carbon, silica gel particles, etc., for treatment and recycling.
Display Screen: Convenient, direct and fast data display.
Figure 4. Medical version Detail Dissection Diagram
MQ136-H2S Concentration Sensor: The MQ136 is a semiconductor-type gas sensor whose sensitive material is tin dioxide. In clean air, tin dioxide has relatively low conductivity. When hydrogen sulfide gas is present, the conductivity of the sensor increases with the concentration of H2S gas—the higher the concentration, the greater the conductivity. The sensor converts the collected conductivity into analog voltage signals, which are then converted into digital signals via an analog-to-digital converter (located between the sensor and the microcontroller) for processing by the microcontroller. These digital values can then be processed and used to represent the H₂S concentration.
Figure 5. MQ136-H2S concentration sensor
SHT30-Temperature And Humidity Sensor: Fluctuations in temperature or humidity can affect the voltage values collected by the MQ136 sensor. To eliminate this interference, we use the SHT30 sensor to collect temperature and humidity values, and then incorporate these two parameters into the calculation.
Figure 6. Temperature and humidity sensor
To meet the requirements for "ease of operation" and "portability" in home-use detection devices, we have focused on simplifying the operation process and adopting a lightweight shell structure in our design, ensuring users can perform detections anytime, anywhere.
Figure 7. Home version Actual Product Image
Modeling Software: We use SolidWorks to create the 3D model of the detector's structure.
Mouthpiece: It is designed for blowing gas into it, detecting H₂S concentration in exhaled breath.
Perforated Partition Layer: It contains a CO₂ adsorbent to adsorb carbon dioxide and water molecules without absorbing H₂S, preventing large volumes of saliva from entering the detection part.
Ventilation Holes: It allows gas to escape.
Sensor: The lower separated compartment houses the sensors. The base of the cup contains the circuit board, chips, and other electronic components, connected to a charging port.
Program: The program part contains the internet connection, and the microcontroller's control of sensors and LCD screen. The algorithms in the program primarily involve the data collection routine of the MQ136 sensor and the screen contents that can be controlled via buttons(See the software page for code and other details).
Figure 8. Program
The experiment covered the variation ranges of humidity(63-75) and temperature(35.0-38.0). However, regardless of how the temperature and humidity fluctuated, the sensor will block out some interfering data. The sensor's displayed value is positively correlated with the hydrogen sulfide concentration (the higher the concentration, the larger the value), and within the experimental temperature and humidity range, this rule is stable, verifying the reliability of the sensor in detecting the hydrogen sulfide concentration gradient.
Figure 9. Temperature and Humidity Error Correction Analysis Chart
In the pretreatment experiment for hydrogen sulfide detection, each 20 mL tube of MG1655 bacterial culture was first divided into three groups: the blank control group received no L-cysteine addition, while the other two groups were supplemented with low and high concentrations of L-cysteine, respectively. Subsequently, the tubes were incubated for 6 hours at 37°C and 220 RPM in a shaking incubator to promote hydrogen sulfide production. Upon completion of incubation, centrifuge tubes were immediately inserted into the device interface to ensure sealing. The gas exchange pump was then activated, at which point the hydrogen sulfide sensor began real-time concentration detection, with data displayed synchronously on the screen.
Hydrogen sulfide (H₂S) detection results indicate that different L-cysteine addition concentrations exert a clear influence on the H₂S production capacity of the MG1655 strain. The H₂S detection value for the blank control group (without L-cysteine addition) was 1666, while the experimental groups with low and high L-cysteine concentrations showed increased values of 1714 and 1800, respectively. This data trend indicates that L-cysteine, as a key precursor for H₂S biosynthesis, exhibits a positive correlation between its concentration and the final H₂S yield-higher concentrations induce greater H₂S production. This result aligns with the expected biochemical pathway and validates the effectiveness of this detection system in distinguishing different levels of H₂S generation.
Figure 10. Detection of Different Concentrations of H₂S Analysis
In the second test, the pretreatment experimental steps were as follows: First, group preparation was conducted by dividing each 20 mL tube of MG1655 bacterial culture into four groups: low hydrogen sulfide concentration group, low hydrogen sulfide concentration + SQR\FCSD enzyme group, high hydrogen sulfide concentration group, and high hydrogen sulfide concentration + SQR\FCSD enzyme group. Subsequently, induction cultivation was performed: L-cysteine was added to each bacterial culture, which was then placed in a 37°C shaker at 220 RPM for 6 hours to induce hydrogen sulfide production. Subsequently, in the corresponding enzyme-treated groups, SQR\FCSD enzyme at a concentration of 10 mg/mL was added. Cultivation continued at 37°C and 220 RPM for 2 hours to allow SQR\FCSD enzyme to decompose hydrogen sulfide. Upon completion of cultivation, the centrifuge tubes were immediately inserted into the device interface to ensure sealing. The gas exchange pump was activated, with hydrogen sulfide concentration monitored in real-time by the hydrogen sulfide sensor and data displayed synchronously.
Compared to the control group without enzyme addition, both the SQR enzyme and FCSD enzyme treatment groups resulted in significantly reduced sensor readings. This indicates that both enzymes effectively decompose or consume hydrogen sulfide (H₂S) within the system, thereby lowering the actual H₂S concentration in the environment.
Further comparison revealed that SQR enzyme exhibited a more pronounced decomposition effect, reducing sensor readings by approximately 129 units (from 1714 to 1585), demonstrating superior H₂S decomposition capability. In contrast, FCSD enzyme showed relatively weaker activity, lowering readings by only about 58 units (from 1714 to 1656), with decomposition efficiency lower than that of SQR enzyme.
Figure 11. Detection of H₂S Concentration After Different Enzyme Treatments Analysis
Based on the experimental data, this study validates the high precision of the detection hardware and its reliable adaptability to environmental variables such as temperature and humidity, thereby supporting the feasibility of the medical-grade device concept. Furthermore, the results confirm the significant hydrogen sulfide removal effects of both SQR and FCSD enzymes, with SQR exhibiting stronger decomposition capability.
Regarding the development plan for hydrogen sulfide (H₂S) detectors targeting obese patients, we sought input from multiple experts on technical feasibility, application scenarios, and detection efficacy. The consolidated feedback is as follows: these recommendations provide crucial guidance for defining the functional specifications and optimizing the design of both versions (home-use and medical-grade) of the detector.
Professor Ma and Dr. Huang indicated that they would recommend the device to patients if it ensures effective testing and simple operation. They emphasized that a scientifically sound design framework and rigorous controlled experiments form the foundation for reliable results. This suggests that the home-use version must prioritize intuitive operation and data readability, while the medical version requires rigorous system calibration and experimental design to support research-grade applications. This aligns perfectly with our original design intent. Following expert advice, we conducted multiple rounds of laboratory testing to validate the device's detection efficacy (see Results page for details).
Dr. Xie pointed out that exhaled gas is susceptible to environmental interference. He suggested exploring the correlation between intestinal H₂S and blood concentrations, referencing blood glucose meters to develop a fingerstick blood testing solution. This approach would enhance the accuracy and convenience of home testing, offering an alternative technical pathway to breath testing for home-use versions.
Professor Yu Xiaofei proposed several recommendations regarding sample processing and sensor specificity, which also represent areas requiring further improvement in the future.
- Sample pretreatment: It is recommended to add acid to the sample prior to detection. This “strong acid displacing weak acid” approach releases bound H₂S, preventing underestimation of concentrations. This step provides direct guidance for sample preparation procedures in medical applications.
- Anti-interference design: Given H₂S's susceptibility to oxidation, vacuuming or oxygen isolation in detection containers is recommended. This is critical for maintaining stable detection results in both device types;
- Sensor Calibration and Validation: It is recommended to prepare pure H₂S using sodium sulfide with acid, calibrate the hardware detection upper and lower limits, and validate the sensor's specificity for H₂S. The colorimetric principle of lead acetate test paper can be referenced for comparison to ensure data reliability.
Based on expert consensus, both detectors should strike a balance between portability, ease of operation, and data accuracy while maintaining reasonable cost control.
The home-use version should prioritize user-friendly interaction, rapid feedback, and convenience for daily monitoring. It may incorporate breath or fingerstick blood methods to help patients intuitively track changes in H₂S levels and assess the efficacy of fat-reducing protein tablets. The medical version should enhance detection precision, sample preprocessing capabilities, and environmental interference resistance to meet the stringent requirements for data reliability and reproducibility in clinical research and long-term efficacy evaluations(See the IHP page for details).
These recommendations provide a clear technical roadmap and design principles for subsequent product iterations and experimental validation.
We organize the fabrication processes of the home version and medical version devices with the principle of “clarity and reproducibility”, combined with disassembly diagrams and detailed instructions:
Home Version:
Step 1: Prepare the transparent main body shell (such as cutting medical-grade plastic pipes) and food-grade silicone mouthpiece, clean and disinfect for later use;
Step 2: Embed the H₂S gas sensor communication circuit board inside the main body and debug the signal transmission;
Step 3: Install the mouthpiece, seal the connection, initiate the test of blowing detection function using the mobile phone.
Figure 12. Home Version Assembly Diagram
User Manual - Home Version (For Obesity Patients at Home)
Start: Open the browser and initiate the test.
Preparation: Take your personal mouthpiece, disinfect it with an alcohol wipe, then place it in your mouth.
Testing: Blow steadily and deeply into the mouthpiece.
Reading Results: After approximately 10 seconds, the browser will automatically receive and display the current hydrogen sulfide (H₂S) concentration value.
Medical Version:
Step 1: Assemble the medical version frame according to the 3D model (build with aluminum extrusions, encapsulate with acrylic boards), reserve the centrifuge tube installation position and gas-path interface;
Step 2: Connect the ventilation pump and pipes, connect to the 50ml centrifuge tube and activated carbon recovery component, and test the gas-path tightness;
Step 3: Embed the H₂S gas sensor communication circuit board inside the main body and debug the signal transmission, the data collection and storage functions.
13. Medical Version Assembly Diagram
User Manual - Medical Version (For Healthcare Professionals and Researchers)
Sample Loading: Screw the 50ml centrifuge tube containing the sample into the device interface, ensuring a secure seal.
Parameter Setup: Configure parameters such as flow rate and cycle count for the ventilation pump via the screen or host computer software.
System Connection: Connect to the laboratory data acquisition system and verify normal communication.
Sample Introduction: Introduce test samples (e.g., patient breath collection bags, simulated intestinal gas samples) into the system.
Initiate Testing: Start the testing program. The system will automatically record real-time H₂S concentration curves and store raw data for analysis.
Figure 14. Cost Analysis
To enhance detection accuracy, future iterations of the home version will incorporate advanced electrochemical sensors capable of minimizing interference from environmental variables such as temperature and humidity. Further improving reliability, an acidification module will be integrated to treat samples prior to measurement, ensuring more complete release and precise quantification of hydrogen sulfide. In addition, vacuum-sealed or oxygen-free sampling chambers will be implemented to prevent H₂S oxidation, thereby preserving sample integrity.
Specificity of the sensor will be rigorously validated against pure H₂S generated via sulfide acidification and cross-referenced with established methods such as lead acetate test strips. Beyond hardware upgrades, the supporting mobile application will evolve into an intelligent health analytics platform. By synthesizing H₂S readings with user-logged data on protein tablet intake, diet, and exercise, the system will generate personalized feedback-such as adjustments to tablet timing or meal composition-to optimize glucose control and weight loss outcomes.
To meet the demands of clinical studies and mechanistic research, the laboratory version will be upgraded toward automation, multi-parameter detection, and rigorous calibration. An automated sample injection system utilizing robotic arms will be implemented to enable high-throughput processing, facilitating large-scale experiments across diverse patient populations and conditions. Beyond hydrogen sulfide, the system will also integrate sensors for other intestinal biomarkers——such as short-chain fatty acids and additional gases——to provide a comprehensive profile of the gut microenvironment and support deeper investigation into the action mechanism of protein tablets.
Furthermore, the hardware will undergo systematic calibration and range validation using standardized H₂S sources (e.g., Na₂S + acid) to define its accurate detection limits and ensure measurement reliability under varying experimental conditions.
The home version of the H₂S detector will be marketed as an auxiliary health device for metabolic monitoring. It can be bundled with our core enzyme-based pills to form an integrated "detection-and-intervention" solution, targeted at individuals managing obesity or diabetes. Distribution will leverage e-commerce platforms and partnerships with healthcare facilities. Meanwhile, the medical-grade version will be adopted by hospital laboratories and third-party testing agencies, generating revenue through equipment sales and providing professional analysis services of the intestinal microenvironment for clinical and research purposes.
By leveraging H₂S data and its correlation with medication adherence and lifestyle, we will develop personalized health management packages for fitness centers and wellness companies. These packages will include tailored tablet intake schedules, real-time H₂S tracking, and customized nutritional guidance. This data-driven approach aims to establish a new business model in the preventive care market, offering actionable insights for long-term health optimization.
A simplified, teaching-adapted version of the medical-grade detector can be integrated into undergraduate and graduate courses in bioengineering, synthetic biology, and environmental monitoring. This platform offers students hands-on experience with gas detection principles, sensor technology, and real-time data analysis. By linking laboratory exercises to real-world health applications——such as monitoring metabolic biomarkers——the system helps illustrate the translational pathway of synthetic biology from research to practical solutions.
The home detector serves as an engaging tool for science communication at community health events, school science fairs, and public workshops. Interactive demonstrations——such as voluntary breath testing coupled with real-time data visualization via the mobile app——can help demystify synthetic biology and showcase its relevance to everyday health. These activities not only improve public understanding of metabolic health but also foster broader interest in biotechnology and its potential to address personal and community health challenges.
The development of the H₂S detection system extends beyond immediate application——it establishes a scalable model for enhancing the entire synthetic biology research ecosystem. By providing a tangible tool to quantitatively validate biological interventions, the device strengthens the foundational Design-Build-Test-Learn (DBTL) cycle. This hardware-assisted validation approach can be adapted to future synthetic biology projects, accelerating the iterative optimization of bio-products and supporting more efficient translation from concept to functional solution.
Looking forward, the dual-version hardware framework serves as a bridge between laboratory research and real-world clinical or personal health management. It offers a replicable model for other research teams to simplify patient monitoring and data collection during clinical trials. By facilitating smoother, data-driven transitions from experimental innovation to practical deployment, this approach can help streamline the broader pipeline of synthetic biology solutions, ultimately supporting their responsible and effective integration into society.
