Julia FröhlichIn the fast-paced world of healthcare, staying informed about the latest medical buzzwords and trends is essential to understanding where the future of medicine is heading. From computer-aided diagnosis and personalized medicine to bioprinting and spatial biology, new technologies and innovative approaches are reshaping healthcare delivery and patient outcomes. This article delves into 15 emerging buzzwords and trends that are set to redefine the medical landscape. Whether you’re a healthcare professional, researcher, or simply curious about the cutting-edge of medicine, join us as we explore these transformative developments at the forefront of healthcare innovation.
The most important medical buzzwords and trends
| Personalized Medicine | Every human is unique, has a unique biochemical, physiological, environmental expose, and behavioral profile. Different persons need different interventions during a disease. DNA sequencing, proteomics, imaging protocols and wireless health monitoring devices are useful components for the decision of personalized treatments.1 |
| Digital Twin | Digital twins are modelling a physical object as a concrete person. For this application, much detailed data is needed to form the digital replicas with proteomics, transcriptomics, biofunctional data, morphological data, and much more. In addition to that, AI is used to simulate 3D surgery or to monitor disease progression better, and to optimize the treatment plans. Nevertheless, data security is an important topic because of very personal data.2 |
| Telemedicine | Telemedicine is a kind of medical care that involves distance. Commonly, consulting hours are offered online for patients. Even if there is a distance between doctor and patient, diagnostics, consulations, monitoring, and emergency medical service are provided. This enables better medical care for persons living in rural areas as well as for medical care during pandemics.3 |
| eHealth | As a collective term for digitalization of organized care for the body, eHealth affects medicine, healthcare, insurance sectors, nutrition, sport, yoga, and other self-techniques. It offers the possibility to improve experiencing, thematizing, visualizing, and managing bodies. Some examples are digital presciptions for medication, health apps for prevention and treatment of diseases, and tele medicine.4 |
| mHealth | The use of mobile phone technology for health-related purposes is known as mobile health (mHealth). This is where mHealth differs from eHealth: eHealth refers to the general use of digital solutions, not just mobile ones. Smartphone apps can be used for tracking medical data recorded by sensors as well as for therapy applications.5 |
| Wearables | Smartwatches are probably the first thing that comes to mind when thinking of wearables. Nevertheless, many more gadgets are called wearables. Hearing aids, smart clothes, electronic socks and shoes, tatoos, and subcutaneous sensors are only a few other examples. They are used for personal analytics, measurement of the physical status, as well as recording, and the information for the medication schedule. An important characteristic is the flexibility of the devices. In combination with telehealth, they can change the medical system. Additionally, the more available data of a patient, the better the personalized medicine.6 |
| Data mining | Because of the ongoing digitalization more and more health data are stored. The huge amount of data can be used to extract useful knowledge by using data mining. This is the process of pattern discovery and extraction of huge datasets. This generalized information about medical questions is used to improve healthcare by providing and comparing health data.7 |
| Computer-Aided Diagnosis (CAD) | By utilizing artificial intelligence (AI), medical images can be analyzed for abnormalities, facilitating the detection of cancer or subtle changes, and aiding doctors in their diagnosis. Nowadays, CAD serves as a “second opinion” for physicians, with computer algorithmics suggesting diagnosis while doctors make the final decision. Further studies are needed, however, to be able to use CAD systems as the main diagnostic tool.8 |
| Biomarker | In general, biomarkers are characteristic indicators of biological processes in the human body that can be measured in body fluids. There are different types of biomarkers. Among others, there are diagnostic biomarkers to detect and confirm a disease by a probe of the patient. Prognostic biomarkers, on the other hand, can predict a clinical event or the recurrence of disease as well as the progression of a disease.9 |
| Companion Diagnostics (CDx) | Companion diagnostics are specialized medical tests that assist doctors in determining whether a specific treatment will be effective for a particular patient. This is achieved by testing for the presence of a specific biomarker. If the biomarker is present, the corresponding drug can be used and is likely to be effective. CDx can therefore improve personalized medicine, reduce side effects, and increase the chances that the treatment will work well.10 |
| Point of Care | Point of Care is also referred as near patient, bedside, or extra laboratory testing. The goal is to get fast results without sophisticated laboratory equipment in order to implement the most appropriate treatment for the patient. Point of Care is especially used when immediate action is required based on test results. Even though point-of-care testing is more expensive than laboratory testing, it can shorten hospital stays, reduce complications, and generally improve adherence to treatment.11 |
| Spatial Biology | Spatial Biology can be described as the three-dimensional biology with a high resolution. It can be splitted into two sub items: transcriptomics and proteomics. All topics named with -omics are part of spatial biology (read more in our Molecur Biology 101 for Techies). Transcriptomics represents the discovery of three-dimensional structures of RNA, the copy of the DNA, including the human genetic code. Proteomics represents the discovery of three- dimensional protein structures, interactions with other cell compartments or other cells, and can optimize the information about different mechanisms in the body. The gained knowledge can lead to a better understanding of diseases and can improve drug discovery.12 If you’re interested in exploring spatial biology further, our Spatial Biology 101 course is a great starting point. |
| Tissue Engineering | The main aim of tissue engineering is the restoration, improvement, and maintenance of damaged tissues or organs. Therefore, living cells, growth factors, and so-called scaffolds as a matrix are needed and mixed. During cell regeneration, the matrix is temporarily helping the cells growing and degrading afterwards. Due to the limited availability of organ transplants in clinical medicine, tissue engineering has garnered significant interest.13 |
| Bioprinting | The concept of bioprinting is based on three-dimensional printing technology and represents a growing field with a revolutionary impact on medical and pharmaceutical sciences. Instead of using traditional polymers, bioinks composed of living cells combined with growth factors are utilized as forming gels. As a result, various tissues can be mimicked by using different bioinks. Bioprinting has the potential to enhance regenerative medicine, transplantation, clinical applications, drug screening, and cancer research.14 |
| CRISPR-Cas | CRISPR-Cas is a revolutionary gene-editing technology that allows scientists to make precise changes to DNA. It uses a guide RNA to target specific DNA sequences and a Cas protein (like Cas9) to cut the DNA at the targeted location. In personalized medicine, CRISPR-Cas can be used to tailor treatments to an individual’s genetic profile, potentially correcting genetic disorders and enhancing the effectiveness of therapies.15 |
- Laura H. Goetz, Nicholas J. Schork, Personalized medicine: motivation, challenges, and progress, Fertility and Sterility, Volume 109, Issue 6, 2018, Pages 952-963, ISSN 0015-0282, https://doi.org/10.1016/j.fertnstert.2018.05.006. ↩︎
- Cellina, M.; Cè, M.; Alì, M.; Irmici, G.; Ibba, S.; Caloro, E.; Fazzini, D.; Oliva, G.; Papa, S. Digital Twins: The New Frontier for Personalized Medicine? Appl. Sci. 2023, 13, 7940. https://doi.org/10.3390/app13137940 ↩︎
- https://www.bmj.com/content/323/7312/557.1?change_country=1 (accessed on 27.06.2024),
https://www.bundesgesundheitsministerium.de/service/begriffe-von-a-z/t/telemedizin#:~:text=Telemedizin%20erm%C3%B6glicht%20es%2C%20unter%20Einsatz,wichtiger%20Bestandteil%20der%20medizinischen%20Versorgung (accessed on 27.06.2024) ↩︎ - Engemann, C. (2020). eHealth. In: Kasprowicz, D., Rieger, S. (eds) Handbuch Virtualität. Springer VS, Wiesbaden. https://doi.org/10.1007/978-3-658-16342-6_18 ,
https://www.bundesgesundheitsministerium.de/service/begriffe-von-a-z/e/e-health (accessed on 27.06.2024) ↩︎ - Betjeman, Thomas J., Soghoian, Samara E., Foran, Mark P., mHealth in Sub-Saharan Africa, International Journal of Telemedicine and Applications, 2013, 482324, 7 pages, 2013. https://doi.org/10.1155/2013/482324,
https://www.healthcare-digital.de/was-ist-mhealth-a-a78b44cb9dde4423806bc04883b2d01c/ (accessed on 27.06.2024) ↩︎ - Yetisen, A.K., Martinez-Hurtado J. L., Ünal, B. Khademhosseini A., Butt H. Wearables in Medicine Advanced Materials (vol. 30, 33) 2018 https://doi.org/10.1002/adma.201706910 ↩︎
- Neesha Jothi, Nur’Aini Abdul Rashid, Wahidah Husain, Data Mining in Healthcare – A Review,Procedia Computer Science,Volume 72,2015,Pages 306-313,ISSN 1877-0509, https://doi.org/10.1016/j.procs.2015.12.145 ,
https://www.gesundheitsindustrie-bw.de/fachbeitrag/dossier/data-mining-neue-chancen-fuer-medizin-und-gesundheit#:~:text=Praktischer%20Nutzen%20im%20Gesundheitswesen&text=Auch%20in%20der%20medizinischen%20Versorgung,%2C%20Diagnose%2C%20Therapie%20oder%20Nachsorge (accessed 27.06.2024) ↩︎ - Doi K. Computer-aided diagnosis in medical imaging: historical review, current status and future potential. Comput Med Imaging Graph. 2007 Jun-Jul;31(4-5):198-211. doi: 10.1016/j.compmedimag.2007.02.002. Epub 2007 Mar 8. PMID: 17349778; PMCID: PMC1955762. ↩︎
- Califf RM. Biomarker definitions and their applications. Experimental Biology and Medicine. 2018;243(3):213-221. doi:10.1177/1535370217750088 ↩︎
- https://www.johner-institut.de/blog/regulatory-affairs/companion-diagnostics-cdx/ (accessed 27.05.2024) ↩︎
- Price C P. Point of care testing BMJ 2001; 322 :1285 doi:10.1136/bmj.322.7297.1285 ↩︎
- Silas Maniatis, Joana Petrescu, Hemali Phatnani, Spatially resolved transcriptomics and its applications in cancer,Current Opinion in Genetics & Development, Volume 66,2021, Pages 70-77, ISSN 0959-437X, https://doi.org/10.1016/j.gde.2020.12.002. ↩︎
- Eltom, Abdalla, Zhong, Gaoyan, Muhammad, Ameen, Scaffold Techniques and Designs in Tissue Engineering Functions and Purposes: A Review, Advances in Materials Science and Engineering, 2019, 3429527, 13 pages, 2019. https://doi.org/10.1155/2019/3429527 ↩︎
- Ibrahim T. Ozbolat, Weijie Peng, Veli Ozbolat, Application areas of 3D bioprinting, Drug Discovery Today, Volume 21, Issue 8, 2016, Pages 1257-1271, ISSN 1359-6446, https://doi.org/10.1016/j.drudis.2016.04.006
Bioink properties before, during and after 3D bioprinting Katja Hölzl7,1,2, Shengmao Lin7,3,6, Liesbeth Tytgat4,5, Sandra Van Vlierberghe4,5, Linxia Gu3 and Aleksandr Ovsianikov1,2 Published 23 September 2016 • 2016 IOP Publishing Ltd
Biofabrication, Volume 8, Number 3 ↩︎ - Jennifer A. Doudna, Emmanuelle Charpentier ,The new frontier of genome engineering with CRISPR-Cas9.Science346,1258096(2014).DOI:10.1126/science.1258096 ↩︎
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