Innovative Treatments the Medical World Needs Right Now

Use of big data analytics to better understand disease

As the name implies, “big data” refers to large amounts of data that are too diverse and complex to be analyzed by traditional means. In healthcare, big data analytics uses large datasets related to patient records, such as genetic data and demographic data, to make the entire healthcare system more efficient and effective for patients and healthcare workers. For example, biological samples and medical imaging banks have been used to train artificial intelligence models to accurately detect diseases that could be missed by a human. Analysis of big data can enable the detection of disease trends, reduce treatment costs, and improve the quality of care.

More accurate diagnoses of endometriosis

Endometriosis is a health condition in which tissue that should grow inside of the uterus, grows outside, causing severe and even debilitating pain and, in many cases, infertility. Although the disease affects around 10 percent of women, it is poorly understood and lacks reliable methods to diagnose it. Because endometriosis symptoms can mimic other reproductive health issues like uterine fibroids, many women suffer for years or decades without a diagnosis. Currently, the only way to confirm endometriosis is with laparoscopy, an invasive surgery performed under general anesthesia. An accurate diagnosis method is desperately needed for a condition that impacts so many women.

Precision treatments for autoimmune diseases

Autoimmune disorders are incurable diseases that affect around 8 percent of the population and include type 1 diabetes, multiple sclerosis, and rheumatoid arthritis. In patients with autoimmune disease, the immune system mistakenly attacks the body’s cells rather than foreign invaders like viruses. Most autoimmune diseases target specific cells or organs but are treated with steroids and immunosuppressants, powerful drugs that affect the whole body, cause serious side effects, carry risks with long-term use, and are not effective in a large portion of patients. Precision therapies assess patients’ clinical and genetic data to predict which treatments will be most effective.

Bionic eyes that are as good as (or better than) human eyes

For the 40 to 45 million people around the globe who are blind, bionic eyes could potentially restore sight. Bionic eyes are linked to the visual cortex, the part of the brain that takes in visual information from our eyes and creates the images that we recognize as sight. This happens so quickly that we are not even aware of it. Technology is not quite advanced enough to perfectly reproduce the seamless communication between the eye and brain but it might in the near future. Eye implants that allow patients to visualize shapes and colors and a brain microchip that creates artificial vision using a small camera already exist.

Patient-specific, lab-grown organs and blood

The need for donated blood and organs typically greatly exceeds availability, forcing patients to wait on long waiting lists, often as their health is deteriorating. Even after organ transplants are performed, there is a significant risk of the body rejecting the new organ, requiring recipients to spend the rest of their lives on drugs to keep their immune systems from attacking the donor organ. If organs, tissue, and blood that perfectly are matched to patients could be grown in a lab from the patient’s own cells, transplants could happen faster and more efficiently with less risk of organ rejection.

Wearable or implantable health records

When you go to the new doctor or to the emergency room, healthcare providers typically have to rely on you to remember what medications you’re taking and when you had your appendix out. But if you could carry a digital record of your medical history with you wherever you go, doctors would be able to treat you with complete confidence and with a much lower risk of dangerous drug interactions or allergic reactions. Wearable health devices are increasingly popular but the ability to sync that technology with health databases on a national or even global scale would be game-changing.

Bones that are 3D-printed inside the body

While functional bones printed in a lab may sound like science fiction, a group of researchers has developed a cutting-edge approach to 3D-print synthetic bones. The mimic bones are made of ceramic-based ink mixed with living cells and the compound calcium phosphate, which is frequently used to help regenerate bone. Because these synthetic bones can be printed at room temperature, the researchers who developed them believe that they can safely be constructed inside the body. The technique has shown promise in the lab but has not yet been tested in humans.

3D-printed skin to heal burns and other scars

3D printing technology is likely to play a critical role in the future of regenerative medicine, a field focused on replacing tissues that have been damaged by disease or injury. The treatment of burns and other scar tissue is particularly well suited to the technology as they are notoriously difficult to repair. Several research teams are working to develop a 3D-printing tool that can deposit layers of healthy, living skin, including some with blood vessels already incorporated, to speed up the healing of burns and wounds. So far none of the tools have made it to a clinical setting, but the outlook is bright.

Brain implants to map and treat neurological disorders

Our brains are incredible machines capable of extraordinary actions. But sometimes the brain doesn’t work exactly as it should. Nerves that should fire don’t or fire at the wrong time. Deep brain stimulation, which uses electrodes to direct electrical signals to a specific part of the brain in the brain, is used to treat some neurological disorders, including Parkinson’s disease and epilepsy. Newer therapies for depression, anxiety, and addiction would use these electrodes to create a map of electrical activity in the brain that is specific to each patient, allowing researchers to pinpoint what brain activity corresponds with symptoms and target that activity for the treatment.

Drugs that are prevention for severe allergies

Medicines that are perfectly matched to your DNA

Gene editing to treat and prevent diseases

CRISPR gene editing allows researchers to change DNA, including repairing mistakes. Although it’s a relatively new technology, it has already had a substantial impact on medicine and earned Nobel Prize in Chemistry its inventors. The technology has been tested as a treatment for rare blood disorders, cancers, heart disease, and Alzheimer’s disease, with many more on the horizon. But CRISPR’s potential isn’t limited to its ability to treat diseases; it may also be able to prevent them from ever developing. It may also be used to prevent inherited diseases as well as certain cancers, neurodegenerative diseases, or immune disorders that are caused to single gene mutation.

Virtual reality that diagnoses and treats disease

From video games and augmented reality apps to career training and socializing, virtual reality has caught on in a big way. Unsurprisingly, the tech has also made an impact in the healthcare field with exciting tools like virtual reality surgical studios that let surgeons visualize every aspect of a procedure before the patient is even in front of them. One of the next frontiers of virtual reality is likely to be the diagnosis and treatment of mental illnesses. Studies are already underway that explore virtual reality as a tool to detect post-traumatic stress syndrome (PTSD), attention deficit/hyperactivity disorder (ADHD), and anxiety.

Machine learning models that predict disease risk

Imagine getting a personalized, artificial-intelligence-driven prediction of diseases that you are most at risk of developing. You could be empowered to make lifestyle changes or begin preventative care to decrease your risks. Augmented artificial intelligence models are a type of machine learning designed to pull data from multiple sources to assist in humans making more accurate decisions. A model that uses input from a dozen electrocardiograms (ECGs) — tests that measure electrical activity in the heart— to predict heart issues and an artificial neural network (a simplified model of the human brain) that can accurately predict chronic illnesses are two recent examples of ambitious uses of machine learning to determine disease risk.

Where Do We Find this Stuff? Here Are Our Sources:

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