|Year : 2018 | Volume
| Issue : 3 | Page : 106-108
Biomedical diagnostics for all: Democratization and personalization
IDTechEx, Cambridge, UK
|Date of Web Publication||18-Oct-2018|
Downing Park, Station Road, Swaffham Bulbeck, Cambridge, CB25 0NW
Source of Support: None, Conflict of Interest: None
|How to cite this article:|
Jiang L. Biomedical diagnostics for all: Democratization and personalization. Digit Med 2018;4:106-8
Biomedical diagnostics concerns all the diseases that can be diagnosed by biosensors. Pregnancy test strips are one of the most common commercialized biomedical diagnostic devices. They are lateral flow assays that test the binding of human chorionic gonadotropin ([hCG], a biomarker linked to pregnancy state) and hCG antibody (bioreceptor immobilized on the strip) and show the result as optical signals as shown in [Figure 1]a and [Figure 1]b., Another successful example is the electrochemical test strips for glucose detection. [Figure 1]b shows a diabetic patient dropping blood from the fingertip onto a thin strip and putting it into a device containing glucose oxidase (an enzyme that catalyzes glucose into hydrogen peroxide) and an electrode (it detects the concentration of hydrogen peroxide electrochemically). The patients can then read from the screen if their blood sugar level is too high or too low.
|Figure 1: Lateral flow assays for pregnancy test (a) and glucometer for blood sugar test (b)|
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These are examples of biomedical diagnostics which have been used for decades. The novel biosensor technologies have moved beyond. Similar lateral flow assays not only can tell if one is pregnant or not, but they can also test for infectious diseases, cancers, or cardiac diseases. Continuous glucose monitors enable diabetic patients to monitor blood sugar levels through a wearable device which requires no blood. Advanced materials are being investigated to enhance the detection sensitivity and also extend their applications, such as drug delivery. The promising materials include nanomaterials,, active matter, or quantum dot.
Certainly, not all the biomedical diagnoses can be carried out at home. Actually, most of them cannot, such as cancer prognosis, coagulation test, sexually transmitted infections, or genetic testing. [Figure 2] lists the key applications of biomedical diagnostics. Many complex diagnostics require large and expensive equipment, elaborate laboratory work, and well-trained staff for interpretation of results. However, the innovations in the past years are pushing the centralized biomedical diagnostics toward point of care, where the diagnosis can be performed at the bedside of the patients in a short time and at low cost. Such point-of-care devices require small sizes (ideally portable), high efficiency (sample to answer within hours), and simplified operation.,
|Figure 2: Biomedical diagnostics for daily life monitoring and diagnostics|
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Automation of elaborate laboratory work is the key path toward point-of-care devices. The concept of lab-on-a-chip is to integrate laboratory-based multitasks into a small chip, thereby automating and miniaturizing the process. The development of lab-on-a-chip is intrinsically linked to microfluidics. [Figure 3] summarizes the important theories behind microfluidics, its breakthroughs, applications, techniques, and fabrication challenges. Although microfluidics has become a mature and fast developing area, the full lab-on-a-chip devices at point of care are still rare, if any. Ideally, they should integrate sample preparation and separation, microfluidic chip, immobilized bioreceptors, sample movement control, signal transduction, and result analysis. However, the integration of some parts is possible, and desperately desirable, especially for highly complex systems, such as molecular diagnostics (MDx).
|Figure 3: Theories, applications, techniques, and fabrications for microfluidics|
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MDx is the biggest disruption for biomedical diagnostics in the past years. Unlike previous biosensor examples that detect glucose or hormones, MDx extracts genetic information, from DNA, RNA, or protein. The concept of linking genetic information to human health can be traced back to 1953 when the DNA double-helix structure was found, laying the foundation of modern molecular biology. However, it was not until 2011 that the Food and Drug Administration first approved the use of next-generation sequencing for clinical diagnostics, and the first commercialized MDx devices became available only few years ago. We see a large wave of MDx devices have rushed into the market since 2017, and there are more to come in 2019. It is backed up by large companies, such as Abbott and Roche. Their research and development priorities are shifting toward MDx, as reported in their most recent annual reports.
Why have MDx started to attract massive attention? One reason is that the health care market is expected to grow significantly in the coming years due to the increasing and aging population. Another is because MDx can detect infectious diseases precisely and also predict genetic diseases. Moreover, MDx is considered to possibly provide the ultimate solution for the personalized health care. It is also a golden path to precision medicine and predictive health care. We are not only referring to cancer or drugs. MDx will influence one's daily life in many aspects as well: alcohol consumption will be monitored and controlled at a personal level, and efficient ways of losing weight through exercise will be suggested.
Some of these applications might sound like a science fiction movie, but they are actually not far away from reality. Governments, large institutes, big hospitals, and companies are actively collecting genetic information from the public. The growth of human genome data is faster than Facebook or Twitter. Such large databases will back up the development of MDx, and revolution is biomedical diagnostics in the coming years. Biomedical diagnostics is at a rapidly developing stage, pushed by advanced technologies in biosensors and the rise of MDx. It is moving fast toward democratization and personalization of a digital health care.
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[Figure 1], [Figure 2], [Figure 3]