Machine learning is helping oncologists identify individualized cancer treatment for their patients. Image: Pexels.
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- In 2020, 58.3% of global cancer deaths occurred in Asia and by 2025 cases in India are expected to rise by 12% to 1.56 million.
- In response, the Centre for Fourth Industrial Revolution of the World Economic Forum India has initiated a cancer care project, partnering with Microsoft.
- AI technology is being used to identify and treat cancer whilst building a knowledge database to help millions of people.
Cancer is the leading cause of death around the world and a key barrier in increasing life expectancy in almost every country. The World Health Organization estimates, between 2000-2019, cancer was the first or second leading cause of death before the age of 70 in 112 of 183 countries and ranks third or fourth in a further 23 countries.
For both sexes combined, one-half of all cases and 58.3% of cancer deaths were estimated to occur in Asia in 2020, where 59.5% of the global population resides. It is this part of the world which faces composite challenges in terms of cancer care: failure to translate policy and planning into action; resource constraints in terms of infrastructure and human resources; gaps in service availability; lack of spending on healthcare etc.
Emerging technologies are the fulcrum we need to bridge the healthcare divide in the continuum of care for cancer. Artificial intelligence ( AI) has emerged to be this game changer. AI-guided clinical care has the potential to play an important role in reducing health disparities, particularly in low-resource settings. Integration of AI technology in cancer care can improve the accuracy and speed of diagnosis, aid clinical decision-making, and lead to better health outcomes.
AI can play a key role in improving cancer screening, aid in the genomic characterization of tumours, accelerate drug discovery and improve cancer surveillance. Cancer is a complex and multifaced disorder with thousands of genetic and epigenetic variations. AI-based algorithms hold great promise to pave the way to identify these genetic mutations and aberrant protein interactions at a very early stage. Modern biomedical research is also focused on bringing AI technology to clinics safely and ethically.
Keeping in mind the alacrity of the diseases burden, the Centre for Fourth Industrial Revolution of the World Economic Forum India, has initiated a project Fourth Industrial Revolution for Sustainable Transformation (FIRST) of Cancer Care. The Indian Council of Medical research has projected that by 2025 India is expected to see a rise of 12% in the number of cancer cases, adding another 1.56 million to the disease burden.
What is the World Economic Forum doing about the Fourth Industrial Revolution?
The FIRST cancer care project focusses on leveraging emerging technologies like AI, internet of things (IoT) and blockchain, which can help provide accessible, affordable and quality healthcare in India. The strategy is being formulated by partners across government, clinicians, IT solution providers, academia and civil society organizations. Microsoft has been a key partner of the Forum, and this article highlights how the IT giant is using technology to face the cancer head on.
Cutting-edge cancer projects
- Microsoft is using machine learning (ML) and natural language processing (NLP) to help the world’s leading oncologists figure out the most effective, individualized cancer treatment for their patients. An innovation, named Inner Eye is pairing ML with computer vision to give radiologists a more detailed understanding of how their patients’ tumours are progressing. It is being used by Addenbrooke’s Hospital in Cambridge to develop AI models that use the hospital’s own data to automatically highlight tumours and healthy organs on patient scans.
- BC Cancer and Microsoft Canada are collaborating on “Single Cell Genomics” which will enable medical professionals to view the genomes of single cancerous cells. This level of detail will enable targeted and specific combinations of treatments for individuals and allow oncologists to predict how individual cells within a patient’s tumour will respond to chemotherapy.
- Bio Model Analyzer (BMA), a cloud-based tool developed by Microsoft, allows biologists to model how cells interact and communicate with each other, and the connections they make. BMA has many uses, including figuring out how to detect cancer earlier and understanding how better to treat cancer by modelling which medicines will be most effective and at what point the cancer might become resistant to them.
- Microsoft and AstraZeneca have been using BMA to better understand drug interactions and resistance in patients with a certain type of leukaemia. Project Hanover is designed to automatically sort through all that fragmented information to find the most relevant pieces of data – leaving tumour experts with more time to use their expertise to figure out the best treatment plan for patients.
- The Jackson Laboratory – an independent nonprofit biomedical research institution (also known as JAX, in collaboration with computer scientists working on Microsoft’s Project Hanover – developed a tool to help the global medical and scientific communities stay on top of the continuously growing volume of data generated by advances in genomic research. The tool, called the Clinical Knowledgebase, or CKB, is a searchable database where subject matter experts store, sort and interpret complex genomic data to improve patient outcomes and share information about clinical trials and treatment options. Microsoft AI technology enables machines to read complex medical and research documents and highlight the important information they contain.
Microsoft is just one example which is changing the face of cancer care, likewise we see many start-ups which are coming forward to leverage this technology. As time progresses, we will see that by using an AI base system approach, researchers can collaborate in real-time and share knowledge digitally to potentially heal millions.
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The views expressed in this article are those of the author alone and not the World Economic Forum.
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