Precision medicine has progressed from an optimistic fantasy to an impactful reality due to the vast amount of scientific advancement that has been made within the field of genomics.
Drugs have always been developed on a “one size fit all” basis, in which all patients with a particular disease receive a general treatment. The ineffectiveness of this approach due to variations in genetic predisposition, ethnicity, metabolism, epigenetic factors, stages of the disease, led to the emerging use of precision medicine; which is the development of therapeutic methods specific to a patient genomic footprint and accurately predict the most appropriate course of action. These new discoveries in precision medicine have led to significant steps forward in cancer diagnosis, monitoring and treatment. For the curious minds, you might want to understand the progression of the health care system in adapting to the “new norm” precision medicine. In this article, we’ll walk you through the speed in the adoption of precision medicine by health care system, its importance, and with this, you will understand how this adoption can save millions of lives.
The Emerging Advancement Of Precision Medicine In Cancer Care
Precision oncology aims to match cancer patients with medication that target specific mutations and gene expression patterns in their tumors, with the goal of achieving long-term remission and increasing survival. The core concept is to employ high-throughput genetic testing to match patients to medications that will perform best for them, irrespective of the tissue of origin of their tumor. With this advancement, precision oncology is fast becoming a realized paradigm for managing the treatment of cancer patient.
Initially, targeted medicine followed a similar clinical development path to cytotoxic chemotherapy based on tumor location and histopathology; driven by the notion then that molecular aberrations were tumor specific. Efforts to enhance these techniques stagnated due to a lack of efficacy data in patients with diverse cancer types harboring a shared genetic aberration, as well as early observations that the functional importance of (some) aberrations varied between tumor types.
Precision oncology medicine is an emerging approach for cancer treatment and prevention. This approach allows researchers to predict accurately the treatment and prevention strategies for patients. It requires significant computing power; algorithms that can learn at an unprecedented rate (Deep Learning); and generally, a methodology that makes use of physicians’ cognitive abilities on a new scale (AI). The convergence of Artificial Intelligence (AI) in precision medicine helps to decode data in a way that has never been possible before, leading to revolutionary breakthrough in precision oncology. Healthcare systems are moving towards to direction of AI in precision oncology to give faster and more reliable predictions and treatments.
Is Precision Oncology Just Mere Speculations?
Many aspects of healthcare industry have been greatly influenced by artificial intelligence (AI) and machine learning. Technology advancements have paved the road for cost and time effective analysis of large datasets. AI is beneficial in clinical oncology and research. Cancer’s impact is felt all around the world. This includes early detection, targeted therapy by obtaining genetic information of patient, AI based drug recommendations, prognosis analysis and patient monitoring. AI’s capabilities of pattern recognition and complex algorithm is employed in modern medicine to gain relevant clinical information that will decrease errors related to diagnostics and therapies.
Precision medicine has the potential to significantly save the lives of many patients, and artificial intelligence has the potential to significantly improve those outcomes. It may also make therapies more affordable and accessible to those who are currently unable to receive them owing to cost or lack of health insurances. There are many challenges ahead for precision medicine to be perfect and be deployed din healthcare systems, but artificial intelligence can help drive us closer to these goals.
