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A biosensor is a device that pairs a recognition or sensing element with a transducer, which turns a biological or physiological event into a readable signal. In healthcare the term covers three broad families: tests run on blood, saliva or urine; continuous-monitoring systems that record a signal over time; and wearable biosensors that sit on or near the body. They differ in what they measure, how they collect the signal, and whether they give a single result or a running record. “Virtual biotech” is not a standardized product category. In this guide it is an editorial umbrella for computer-supported biology and drug development, including digitally derived measurements in clinical studies and laboratory models that carry embedded sensors.
What makes a device a biosensor
Every biosensor has two parts. The recognition or sensing element responds to the thing being measured, such as an enzyme that reacts with glucose, an antibody that binds a target protein, or a element that registers temperature or motion. The transducer converts that interaction into an electrical, optical or other measurable signal.
The definition does not require chemistry. Many devices marketed as wearables capture physical or electrophysiological signals rather than biochemical ones. Biochemical sensing from accessible fluids is possible, but it brings sampling and interpretation problems of its own.
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The three healthcare families
A 2023 review by Kim et al. in Trends in Biotechnology, “Biosensors for healthcare: current and future perspectives,” describes healthcare biosensors in these three groups. The table shows how they differ in practice.
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| Family | What it measures and how | Typical output | Examples |
|---|---|---|---|
| In-vitro diagnostic biosensors | An analyte in a blood, saliva or urine sample, usually collected and processed outside the body | Typically one result at one point in time | Lateral-flow assays and microfluidic or electrochemical paper devices, which the review literature treats as established formats |
| Continuous-monitoring biosensors | A signal sampled repeatedly over hours or days, often through a sensor placed on the skin | A time series | Continuous glucose monitoring systems, such as the Dexcom G7 and Stelo entries on FDA’s sensor-based device list |
| Wearable biosensors | Physical, electrophysiological or biochemical signals captured by a device worn on the body | A time series or spot-check readings, depending on the product | Wearable devices on FDA’s sensor-based list intended for continuous or spot-check monitoring in nonclinical settings |
The families overlap. A continuous glucose monitor is both a continuous-monitoring system and a wearable, so the same product can fit more than one label depending on the question you are asking.
Where wearables sit in digital health
FDA’s “What is Digital Health?” page uses the term for technologies that use computing platforms, connectivity, software, and/or sensors for healthcare and related uses. That umbrella runs from general wellness products to medical devices. The same overview places wearable devices alongside mobile health, health information technology, telehealth and personalized medicine. NIBIB’s “Digital Health” explainer also describes sensor wearables as part of the field.
Four settings, four different standards
The same sensor can appear in different settings, and the setting determines what a reading is allowed to support.
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| Setting | Typical purpose | Authorization or evidence standard | What a reading can support |
|---|---|---|---|
| Consumer wellness | Personal fitness, sleep and general health tracking | FDA distinguishes general wellness applications from technologies that may meet the medical-device definition. A wellness claim is not a device authorization for clinical use. | Personal awareness and trends, not a diagnosis |
| Regulated medical device | A defined clinical or monitoring use | Authorization is specific to the device and its intended use | Only the uses named in the authorization and labeling |
| Clinical-investigation tool | Remote data collection in clinical studies | Digitally derived measures must be evaluated before they are relied on, and validity is judged metric by metric (FDA, “Digital Health Technologies (DHTs) for Drug Development”) | A study measure whose validity is established for that specific metric, not for the whole device |
| Laboratory model | Drug-development and tissue research using bioengineered models | Judged by how well the model has been benchmarked against biological or clinical evidence | Mechanistic and hypothesis-generating work inside the model, not statements about human patients |
What FDA’s sensor-based device list shows
FDA’s list of medical devices that incorporate sensor-based digital health technology identifies certain devices authorized for marketing in the United States. It includes noninvasive or minimally invasive wearables intended for continuous or spot-check health monitoring in nonclinical settings. FDA states that the list is not comprehensive and that it is updated periodically. Its entries include the Stelo Glucose Biosensor System and Dexcom G7 continuous glucose monitoring systems, which carry 2026 final-decision dates in the list.
Being on the list confirms authorization for the uses described in that entry, in the US. It does not transfer to a different wearable, to a different intended use, or to a market outside the US. A watch that measures a similar physical signal is not covered by a glucose entry. Check the product’s labeling and the live list before assuming any reading carries regulatory weight.
How accurate are wearable biosensors?
No single accuracy figure applies to “wearable biosensors,” and this guide does not offer one. Accuracy belongs to a specific device measuring a specific metric in a specific population, compared against a reference method. The field’s own reviewers are cautious. A 2021 peer-reviewed review, “Wearable biosensors for healthcare monitoring,” states:
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“Despite rapid progress in wearable biosensor technology over the past 5 years, we are only at the beginning of understanding how wearable biosensor technologies can improve health and performance.”
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A separate peer-reviewed review, “Translational gaps and opportunities for medical wearables in digital health,” identifies the same kind of gap between a working sensor and a clinically useful one. When you evaluate a claim, check these points:
- Validation population: who was tested, by age, health condition and activity level, and whether those people resemble you.
- Reference method: what the readings were compared against. A comparison with a laboratory or clinical measurement is different from a comparison with another consumer device.
- Metric fit: whether validation covered the exact number the device displays, not a related one.
- Wear conditions: wear time, placement, calibration and comfort all affect data quality.
- Stated intended use: whether the product is presented for wellness, for a clinical decision, or as a research measure.
- Data access: whether you can export the underlying data and whether a clinician can see it.
Continuous data is not automatically actionable. A long time series can reveal trends, but whether a trend matters clinically depends on validation and on clinical relevance, which is where the translational challenges sit.
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Can a smartwatch measure health biomarkers?
Many wearables, smartwatches included, capture physical or electrophysiological signals rather than biochemical ones. That is the category where most wearable health readings sit. Biochemical biomarkers are the harder case, for the reasons already noted about accessible fluids.
The answer therefore depends on the signal and the product. For any specific watch, ask three questions: which signal does it measure, has that signal been validated for the use you have in mind, and is the reading authorized for a medical purpose or presented only as wellness information? The manufacturer’s labeling and FDA’s sensor-based list answer the last question. A reading on a screen does not answer it.
Biosensors inside engineered tissue
An organ-on-a-chip combines bioengineered tissue with microfluidics, which means tiny channels that move fluid over and around the cells. The system reproduces selected features of organ or tissue physiology. It is a laboratory model, not a miniature complete human organ, and its results describe the features it was built to capture.
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Integrated biosensors track conditions inside the chip over time instead of relying on a sample taken at the end of an experiment. According to a peer-reviewed review, “State of the art in integrated biosensors for organ-on-a-chip applications,” the main modalities are electrochemical and optical sensing. Physical measurements such as dissolved oxygen, pH and temperature are also common, and sensors can follow metabolic activity and tissue function. The goal is to observe model behavior more promptly and in an integrated way. These platforms support drug-development and personalized-medicine research, but their output must be benchmarked against biological or clinical evidence before it says much about people.
How to compare organ-on-a-chip platforms
| Axis | Question to ask |
|---|---|
| Tissue model | Which cell types and tissue architecture are used, and which organ or tissue function is being reproduced? |
| Sensor modality | Is the sensing electrochemical, optical or physical, and where does the sensor sit relative to the tissue? |
| Monitored parameter | Which variables are measured, such as dissolved oxygen, pH, temperature or metabolic activity? |
| Sampling frequency | How often are readings taken, and does that match the timescale of the biology under study? |
| Benchmarking | Has the model’s output been compared with biological or clinical evidence, and which evidence was used? |
What “virtual biotech” means
“Virtual biotech” is not a standardized product category, and this guide uses it as an umbrella for the computational and digitally enabled side of biology and drug development. Two concrete examples fall under it.
- Digitally derived measures in clinical drug development. FDA’s page on digital health technologies for drug development describes portable devices that may be worn, implanted, ingested or placed in the environment to collect data remotely during clinical investigations. It also covers comparing digital measurements with traditional ones and developing novel endpoints. These are active evaluation tasks. A digital measure is not automatically a valid substitute for a clinical assessment.
- Organ-on-a-chip models with integrated biosensors. They turn tissue behavior into sensor data for laboratory study.
Do not treat virtual biotech as a synonym for organ-on-a-chip or for digital twins. Those terms may overlap with the umbrella, but the sources cited here do not establish that they are equivalent.
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