8 Tech Innovations Transforming the Field of Oncology
Cutting edge research and tech innovations are transforming the field of oncology. While Chemotherapy and Radiology would continue to remain mainstream, novel technologies are being worked upon as an add on to the traditional therapeutic options.
Here are 8 promising applications of oncology technology that are transforming the field of cancer diagnosis and treatment.
1. Artificial Intelligence for cancer diagnosis
The widening array of digital tools paired with AI analytics holds the promise to boost diagnosticians’ accuracy and speed. Artificial intelligence is making breakthroughs in healthcare and diagnostic tools can be trained to read tissue samples and radiologic scans.
AI algorithms are now capable of detecting melanomas in the pictures of skin lesions clicked through smartphone cameras with incredible precision.
Researchers at Helmholtz Zentrum München and the University Hospital of LMU Munich in Germany have leveraged deep learning algorithms to automatically classify cells within blood samples for signatures of acute myeloid leukemia (AML). The accuracy levels of AI algorithms in the detection of AML matched that of the cytologists who examined the same.
In another study, the same AI that Google uses to identify objects online was trained to recognize forms of cancer. Artificial intelligence turned out to be successful at correctly identifying the cancer cells in a lung tissue sample as accurately as a human could, in seconds.
The diagnostic power of artificial intelligence, machine learning, and deep learning makes it an ideal candidate for cancer detection.
2. Early detection through determination of genetic predisposition
Identifying individuals at greater risk of developing cancer can boost patient outcomes and significantly bring down the mortality rates by ensuring earlier access to treatment. Technology is capable of determining the individual’s risk score for developing cancer. This is done by looking at DNA changes locations in the human genome and applying a sophisticated algorithm.
An individual’s predisposition to cancer can be determined on the basis of genetic markers. Along with the genetic makeup, the data about other genetic and environmental factors that may raise the chances of developing cancer can help catch the disease when it is in its infancy.
Telemedicine is increasingly becoming a part of hospitals’ and healthcare providers’ digital health strategy. It gives the patients the benefit of availing virtual consultations from the comfort of their homes. Cancer treatments tend to run a long course.
There are periods of home care and chemotherapy sessions interspersed with hospital stays. Teleoncology or telehealth for cancer treatment makes it easy to get the medical consultations without having to go to the hospital.
In patients undergoing chemotherapy, the immunity levels are low and teleoncology saves them from the risk of hospital-acquired infections. Cleveland Clinic launched a pilot program for the treatment of prostate cancer through teleoncology.
High-grade prostate cancers can be lethal, low-grade cases may need only monitoring and both proved to benefit from the teleoncology program at the Cleveland Clinic.
Related Read: our ultimate guide on how to start a telemedicine business.
4. Chatbots in cancer care
The fight against cancer is both physical as well as mental. Advances in chatbots and nursing assistants can help patients fare better in their fight against the disease. Chatbots are being used for retrieving information that the patient may need, answering treatment-related questions they might have, and triaging calls.
A nursing chatbot will try to learn what ails you by asking about your symptoms and tapping into data from patient’s wearable devices and the crowdsourced health records of others in the database. Cancer patients can seek counseling from a virtual therapist programmed to converse as a human would, offer self-help guidance, and lend a sympathetic ear.
5. Smart devices for cancer therapy
From diagnosis to treatment, smart devices included in the internet of medical things (IoMT) are making their presence felt in the field of oncology. Researchers at the University of Michigan have come up with a tiny implantable device that is capable of detecting cancer at the early stages.
The device draws cancer cells toward itself for gene expression analysis. Made out of biomaterial, the device has a scaffolding designed to allow the circulating cancer cells to settle within. Analysis of these cells allows for diagnosing cancer at the early stages of disease progression.
A device for creating 3D images of tissues is also in the works. The researchers at Nanyang Technological University, Harvard Medical School, and The University of Alabama have collaborated to develop a prototype device capable of imaging through tissues at resolutions down to 1 micrometer (μm) using optical coherence tomography (OCT) at wavelengths between 700 and 950 nanometers.
At these wavelengths, the near-infrared light can penetrate a few millimeters below the skin, as well as other soft tissues, to elucidate the structure of individual cells below. A computer algorithm then converts the data into 3D reconstructions of the tissues.
Smart devices such as skin patches are also helping in the treatment of melanoma. Scientists at Purdue University are developing a skin patch that can deliver chemotherapy into tumor tissue in an effective, convenient, and painless way. A wearable skin patch with miniature needles that gradually dissolves under the skin as well is the ultimate device for delivering chemotherapy in case of skin cancer.
Related read: A Detailed Guide To IoMT Implementation in 2020
5. AI-powered precision medicine
Precision medicine holds enormous potential in improving patient outcomes. Caris Life Sciences has developed the MI Genomic Profiling Similarity (GPS) score to compare the molecular characteristics of specific tumors against those in the database. AI can analyze and understand the molecular drivers of disease so that we can identify optimal treatment strategies for each patient.
This allows clinicians to identify the molecular subtype of their patients’ tumors and paves way for personalized treatment. The system is driven by machine learning algorithms and very useful in guiding the treatment of cancers in case of ambiguity about the tissue of origin and in other atypical or difficult to treat cancers.
AI has also been used to model the precise dosage of a cancer drug to shrink tumors but cause minimal toxic side effects.
7. Nanotechnology in cancer treatment
Nanomedicine is a form of nanotechnology applied to the biomedical field, in which engineered nanoparticles (NPs) with dimensions of less than 100 nm are used to treat cancer. The field of theranostics combines therapy with cancer diagnostics. Specially engineered and functionalized nanoparticles for cancer treatment and molecular imaging smart nanoparticles are able to successfully visualize and kill cancer cells in vitro.
Multi-functional nanoparticles are able to perform imaging and diagnosis of cancer cells while simultaneously treating them at the same time. The therapy delivered in a multi-modal approach, attacks the cancer cells with different mechanisms like hyperthermal, photothermal, or photodynamic treatments making cancer treatment much more effective, targeted and controlled.
Scientists of Wyss Institute at Harvard University have developed erythrocyte leveraged chemotherapy- a technique to deliver chemotherapy to the lungs by using nanoparticle infused red blood cells. Using the cells of one’s own body to deliver nanoparticles avoids their clearance by liver and spleen and results in more efficacy of the chemo treatment.
8. Technology in Clinical drug trials and cancer research
Clinical drug trials in cancer research are time-consuming and resource-intensive endeavors that take up years of hard work and cost millions of dollars. However, despite the researcher’s best efforts, only a handful of drugs manage to be successful in the clinical trial stage while a vast majority move out of the race. Every approved drug trial is estimated to cost upwards of $2 billion.
Technologies like Artificial intelligence and Machine learning have the potential to make drug discovery faster, accelerate clinical trials and increase the chances of success.
From optimizing patient selection to aiding data processing through AI powered algorithms, the applications of artificial intelligence in clinical drug trials and cancer research is just beginning to show it’s promising results and has vast untapped potential.
We have just begun scratching the surface of the possible applications of technology in the field of oncology. Which of these developments do you think would have the greatest impact on cancer treatment in the years to come?