The second most common application of AI is automation/service efficiency, followed by population health. The latter focuses on “leveraging the power of AI when dealing with large patient data sets to help predict and prevent disease in the general population. This could be huge in terms of public health diseases and pandemics such as COVID.
Reduce research and development costs – It can take 3 to 12 years to develop a drug. Some drugs cost $2 billion to develop, some even more. Imagine the problems of a 12 year changing environment. AI has and will have a revolutionary impact on this long cycle, especially in data analytics.
The early phase of drug discovery is a relentless process of reading and analyzing scientific literature and calculating and testing drug interactions. AI can automate much of this, saving billions of dollars in the process. This, in turn, can lower the final cost of drugs.
Funding for AI drug discovery will increase by 3,800% between 2016 and 2021, which just goes to show where the expected returns lie. According to the Financial Times, Moderna used an AI model trained on 20,000 unique mRNA sequences to design and manufacture its first batch of COVID-19 vaccine for testing in just 42 days. AI holds great promise for accelerating the drug discovery and clinical trial process.
Protecting against human surgical error – Medical errors are killers. They can maim, cripple, destroy and compromise human health. According to many studies, one in seven patients in the United States experiences a medical error. In Pakistan, the figure may be much higher.
Every day, medical negligence, fake tests and misdiagnoses bring misery to hundreds of families. The tragic death of 200 patients and sickness of over a thousand at the Punjab Institute of Cardiology in 2012 was just one such scam that exposed the fatal human errors.
In the UK NHS study, AI robots for surgery are the highest valued ($40 billion by 2026). Virtual nurse assistants were ranked second ($20 billion), which will reduce the workload of nurses and address labor shortages. One of the main causes of medical errors is misdiagnosis.
AI has dramatically reduced the error rate. Currently, 86% of NHS stroke units are using AI diagnostic tools to speed up detection and treatment. This will rise to 100% by the end of the year. This is part of a £21 million AI diagnostics fund that also includes AI technology for chest X-rays to detect lung cancer.
The global race for AI is on. The local face of AI is off and on. Pakistan’s healthcare industry struggles with a lack of resources, skills and technology. While everyone recognizes the use of technology, especially AI, few have embraced its potential. Most technical universities now have some basic AI centers.
