Updated: Nov 20
By Shankar Nishant
Breast cancer is one of the most prevalent types of cancer worldwide, affecting millions of people every year. According to the World Health Organization, breast cancer is the leading cause of cancer-related deaths among women, with over 600,000 deaths in 2020. Despite the alarming statistics, there have been significant advances in breast cancer therapeutics in recent years, leading to improved outcomes and better quality of life for patients.
This progress has been driven by the development of new targeted therapies, immunotherapies, and precision medicine approaches, as well as improvements in supportive care and radiation therapy. Additionally, advancements in artificial intelligence (AI) show promise for various applications in the detection and treatment of breast cancer.
Continue reading to learn about AI’s role in mammography, breast cancer risk assessment, treatment plans, and drug discovery.
AI and Mammography
Artificial intelligence has shown significant promise in the detection and diagnosis of breast cancer using mammography. One advantage of AI in this field is its ability to improve accuracy and reduce false positives and false negatives. AI algorithms can analyze large amounts of data, including thousands of mammograms, to identify patterns and subtle changes that may indicate the presence of cancer. This can lead to earlier detection and treatment, which can improve patient outcomes and potentially save lives.
One notable advantage of employing AI in this particular domain lies in its remarkable capacity to enhance accuracy while simultaneously diminishing the occurrence of both false positives and false negatives. AI-driven algorithms possess the capability to meticulously scrutinize vast volumes of data, encompassing thousands of mammograms, with the intention of discerning intricate patterns and subtle alterations that might signify the existence of cancerous growths. Consequently, this technological advancement holds the potential to facilitate earlier identification of the disease and prompt commencement of treatment, thereby improving patient outcomes and potentially saving lives.
In March 2023, Lunit showcased its AI solutions for breast cancer diagnosis called Lunit INSIGHT DBT in the European Congress of Radiology (ECR) 2023, held in Vienna, Austria. Moreover, Lunit showcased its FDA-cleared AI solution for mammography called Lunit INSIGHT MMG. The solution uses deep learning algorithms to analyze mammograms and aid in the detection of breast cancer. Lunit INSIGHT MMG has been trained on a large dataset of mammograms to recognize patterns and identify suspicious regions that may indicate the presence of cancer.
In November 2022, Google Health and iCAD, Inc., a mammography AI vendor, announced a strategic partnership to integrate Google Health’s AI technology into iCAD’s portfolio of breast imaging AI solutions in an effort to improve breast cancer detection and short-term personal cancer risk assessment.
Under this definitive agreement, Google has licensed its AI technology for breast cancer and personalized risk assessment to iCAD. iCAD aims to apply this technology to further improve its 3D and 2D AI algorithms and plans to commercialize developed products to help breast cancer patients in the near future.
Predictive Analytics for Breast Cancer Risk Assessment
Predictive models, driven by artificial intelligence, assess a person’s breast cancer risk based on various factors such as genetics, family history, and lifestyle. These models enable healthcare providers to identify individuals who may benefit from more frequent screening or preventive measures. Tailoring risk assessment to each patient, AI optimizes healthcare resources and provides targeted preventive strategies, enhancing patient care and streamlining the healthcare system.
In February 2023, The University of Waterloo unveiled an AI algorithm that can pre-evaluate the suitability of chemotherapy for people with breast cancer before surgery. This AI system holds the potential to forecast a patient’s responsiveness to a specific treatment, thereby equipping doctors with the necessary tools to prescribe the most personalized and effective treatment for enhanced recovery and increased chances of survival. This significant advancement signifies a shift toward more tailored treatment decisions, sparing some patients from undergoing unnecessary chemotherapy and elevating their overall quality of life.
Moreover, the AI algorithm stands to optimize surgical outcomes for eligible patients. As evidenced by a systematic review, AI algorithms have demonstrated the capacity to predict, diagnose, and monitor various forms of cancer by analyzing medical imaging.
Personalized Breast Cancer Treatment Plans
Breast cancer is highly heterogeneous and demands tailored treatment approaches. AI algorithms analyze vast datasets to identify the most effective treatment options for an individual, considering factors like genetic makeup, tumor characteristics, and treatment responses. Providing oncologists with comprehensive insights, AI aids in informed decisions about chemotherapy, targeted therapies, and immunotherapies. Personalized treatment improves outcomes and reduces adverse effects. AI can be used to continually monitor treatment responses, allowing real-time adjustments to optimize care.
Drug Discovery and Development
AI accelerates drug discovery for breast cancer therapeutics by analyzing extensive genomic and molecular data. It identifies potential drug candidates and predicts their effectiveness against specific breast cancer subtypes. This expedites the development of new treatments, offering hope for patients who may have exhausted conventional options. AI-driven drug discovery unveils novel therapeutic approaches targeting breast cancer with unprecedented precision.
Insilico Medicine, a clinical-stage, end-to-end AI-driven drug discovery company, has made recent developments in AI-driven drug discovery for breast cancer therapeutics. In December 2022, Insilico announced the nomination of a preclinical candidate targeting KAT6A for ER+/HER2- breast cancer therapy. The candidate was discovered using Insilico’s end-to-end AI engine, which accelerates drug discovery by analyzing extensive genomic and molecular data to identify potential drug candidates and predict their effectiveness against specific breast cancer subtypes. In September 2023, oncology-focused biotech company Exelixis announced that it will license the global rights to develop and commercialize an investigational cancer treatment that was derived from Insilico Medicine’s AI-designed cancer drug. These developments are significant because they expedite the development of new treatments for breast cancer and offer hope for patients who may have exhausted conventional options.
Breast cancer remains a significant health concern worldwide. Artificial intelligence, when used in breast cancer detection and treatment decisions, may improve outcomes for patients. AI can also lead to the approval of new drugs for breast cancer treatment. Advancements in artificial intelligence, coupled with ongoing research, will continue to improve breast cancer detection and treatment.
About the Author:
Shankar Nishant is a researcher at Next Move Strategy Consulting with a cumulative experience of more than four years. Shankar is enthusiastic about new technology, enjoys working with a diverse range of global clients, and has delivered numerous market reports in multiple domains. He can be reached at firstname.lastname@example.org
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