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.
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.
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.
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.
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.
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Dr Vinati Kamani writes about emerging technology and its application across industries for Arkenea. She is an avid reader and self proclaimed bibliophile. When Vinati is not at her desk penning down articles or reading up on the recent trends, she can be found travelling to remote places and soaking up different cultural experiences.