Diagnostics are the foundation of disease detection, diagnosis, and assessment. Diagnostics inform more than 70% of medical decisions about disease treatment, management, and prevention. They are also an important tool in preventive healthcare.
While the COVID-19 pandemic overwhelmed the diagnostics industry from 2020-21, it has been racing to keep up with the Sars-Cov-2 virus and its emerging new mutants. We are already in full combat mode to meet the massive challenge of urgent doorstep sample collection, quick turnaround time, and rapid report delivery.
This has pushed everyone to develop newer tests and innovative techniques to deal with the same with upgraded equipment and implementing the most recent software applications to scale-up. The bottleneck is the demand for a growing volume of tests to be performed while maintaining strict quality control, accuracy, and affordability.
Read More: Nutraceuticals: The Diet Add On To Avoid Pharmaceuticals
The last century has seen several spectacular innovations in terms of advancements in diagnostic technologies and many more are yet to come. We’ve compiled a list of the top new medical technologies for 2022.
mRNA technology
mRNA technology has recently received attention due to the use of this science in the new Covid-19 vaccines. They offer an alternative to the traditional vaccine approach due to their high effectiveness, rapid development, and potential for low production costs.
mRNA, or messenger ribonucleic acid, is a single-stranded RNA molecule that transports genetic information from DNA. The vaccines work by giving cells a genetic code that allows them to produce viral proteins; once the proteins are produced, the body can mount an immune response. The Covid-19 mRNA vaccines’ success has boosted efforts to develop other mRNA vaccines for everything from cancer to Zika virus.
Neurotechnology
Neurotechnology encompasses all components that are developed to understand the brain, visualize its processes and even control, repair or improve its functions. These components can be computers, electrodes, or any other devices that can be set up to intercept electric pulses that run through the body.
Neurotechnology is currently used in healthcare for brain imaging, which records magnetic fields produced by electrical activity within the brain, neurostimulator, which stimulates the brain and nervous system to influence brain activity, and neuro devices, an emerging technology that monitors or regulates brain activity using an implant. Neuro Devices are still in the research stage, but they have great potential for treating brain disorders.
Neuralink is an example of this. Elon Musk‘s Neuralink is developing a device that would be embedded in the human brain, recording brain activity and transmitting it wirelessly to a computer. These findings would then be analyzed and used to electrically stimulate brain activity by researchers. If successful, it could be used to treat brain diseases such as Alzheimer’s and Parkinson’s. So far, Neuralink has only been tested on animals, but Elon Musk has stated that the company hopes to begin implanting its chips in humans in 2022.
Mental Health Tech
Depression is expected to be the leading cause of disease burden globally by 2030, making the need for new therapies more critical than ever. Many new technologies have emerged in the last year that can help patients with their ongoing mental health needs.
Some apps are increasingly capable of completing patient intakes and providing an initial diagnosis before a patient ever meets with a provider, and AI-powered tools are revolutionizing the way mental health treatments are delivered. AI chatbots, such as Woebot, can help patients practice cognitive behavioral therapy (CBT) strategies, and voice recognition software Ellipsis can analyze a patient’s voice and speech patterns for warning signs of emotional distress.
Furthermore, digital symptom tracking is proving critical for optimizing future mental health care diagnostics efficiency. Patients are encouraged to share data on a daily basis when using online symptom tracking. The data is then analyzed by an AI algorithm to identify patterns and alert providers in real time of any warning signs.
