by Artificial intelligence (Artificial intelligence) is rapidly transforming various aspects of healthcare including cancer research and oncology. With unprecedented amounts of medical data now available digitally, Artificial intelligence promises to help improve cancer screening, diagnosis, prognosis, and response to treatments. This article explores some of the major global developments in applying Artificial intelligence to tackle cancer.
The Rise of Artificial intelligence-Assisted Diagnosis
One of the most promising applications of Artificial intelligence in oncology is in assisting doctors with cancer diagnosis and prognosis based on medical images. Several startups and research groups across the world are developing deep learning algorithms that can analyze images like CT scans, MRIs, mammograms and pathological slides to detect abnormalities indicative of cancer or other diseases.
In the US, companies like Anthropic, Enlitic and Novarra are working with large healthcare systems and research institutes to build Artificial intelligence platforms that can scan medical images and provide diagnostic or “second opinion” reports to clinicians. Anthropic recently partnered with the Mayo Clinic to develop Artificial intelligence tools for lung and breast cancer screening. Meanwhile, UK based Capstone Research is using Artificial intelligence to analyze breast cancer biopsies and flag questionable cells that may have been missed otherwise.
In Asia, a research group at China’s Huazhong University of Science & Technology trained convolutional neural networks on a dataset of over 100,000 CT scans to detect lung nodules that could indicate early-stage lung cancer, with a 96% accuracy rate. Korean researchers have also built Artificial intelligence models that can predict breast cancer metastasis by analysing pathology images. Such rapid screening and diagnostic capabilities enabled by Artificial intelligence are crucial for improving early detection rates globally especially in developing countries.
Personalizing Cancer Treatment with Precision Oncology
Another important application of Artificial Intelligence Is In Precision Oncology – using a patient’s personal health records and genomic data to select the most suitable treatment approach. With the rise of biological therapies and immune-oncology drugs, this personalized approach has become crucial in maximizing treatment response rates and quality of life outcomes for cancer patients.
Several Artificial intelligence platforms are now helping oncologists make more informed treatment choices. In the UK, startup Anthropic partnered with the Christie NHS Foundation Trust hospital to develop an Artificial intelligence assistant called Claudia that matches cancer patients to suitable clinical trials based on their profiles. Google’s life sciences arm Verily is applying machine learning to biomarker and patient data from the US’s Project Baseline study to derive clinical insights for conditions like breast cancer.
Perhaps the largest effort in precision oncology globally is the US National Cancer Institute’s Cancer Moonshot program that aims to make a “cancer patient’s entire diagnosis, treatment and follow-up available in their own electronic health record.” Several Artificial intelligence startups like Foundation Medicine and Anthropic are contributing techniques to analyze the massive trove of genomic and clinical data being collected under Moonshot to enable more personalized cancer management at scale.
Artificial intelligence: Fuel for Next Generation Cancer Research
Research institutions across the world are starting to realize Artificial intelligence’s potential to accelerate cancer research itself. Artificial intelligence can help uncover patterns, correlations and insights from petabytes of scientific literature, clinical trials data and real-world patient records that might have otherwise taken researchers years to analyze manually.
In Europe, systems like PBCNet are applying natural language processing (NLP) techniques to millions of biomedical papers to extract relationships between genes, proteins and cancer types to identify new therapeutic targets. The Institute of Cancer Research (ICR) in London is using Artificial intelligence and genomics to explore evolutionary patterns underlying tumour growth and resistance to therapies, with the goal of designing more resilient treatment options.
Asian countries are also emerging as global hubs for Artificial intelligence-driven oncology research. Under Taiwan’s Ministry of Science and Technology, several institutes are collaborating with Artificial intelligence startups to develop techniques for high-throughput drug screening and repurposing existing candidates to fight cancer. China has launched massive initiatives envisioned to usher a new era of healthcare through fusion of Artificial intelligence, biotech and medicine. Initiatives like “Institute of Medical Robotics” and “Precision Medicine Research” will undoubtedly push boundaries of cancer treatment and diagnostics.
The Road Ahead
While Artificial intelligence is showing tremendous early promise in oncology, many challenges remain before its full potential can be realized. Significant hurdles around data quality, clinical validation of Artificial intelligence algorithms, safety, privacy and equitable access will need addressing as these technologies are deployed more widely in real-world cancer care settings globally.
Looking ahead, deeper collaboration between researchers, technologists, healthcare providers, patient advocacy groups and regulators around the world will be crucial. Concerted efforts are also required to develop large harmonized datasets, common benchmarks, and standardized frameworks for handling transparency, security and accountability issues as Artificial intelligence integrates further into global healthcare infrastructure.
With continued progress, Artificial intelligence promises to profoundly augment human capabilities and upgrade humanity’s fight against cancer. While challenges persist, the opportunity for Artificial intelligence to accelerate efforts against one of the world’s biggest health problems in the coming years seems immense. Global cooperation on developing and applying these technologies responsibly will be key to ensuring their clinical and societal benefits are maximized for patients worldwide.
