The future of healthcare
In 1854, a sudden and deadly outbreak of cholera spread through London’s Soho neighbourhood, killing 616 people. Until then, it was generally believed that the disease spread through a noxious bad air known as a miasma.
However, during this outbreak Dr. John Snow did something different.
He began mapping the location of each death. Combining this data with conversations with local residents, Dr. Snow identified the source of the outbreak as a water pump on Broad Street.
This use of data analytics saw the birth of epidemiology. It also led to a fundamental change in municipal water and waste systems globally, and a significant improvement in general public health. 166 years later, large scale data analytics and machine learning (ML) are providing opportunities to completely transform healthcare outcomes, including the fight against COVID-19.
166 years later, large scale data analytics and machine learning (ML) are providing opportunities to completely transform healthcare outcomes.
The cognification of healthcare
An early detection, multi-cancer blood test earned Grail, a Silicon Valley healthcare company, FDA Breakthrough Status in May 20191. The test combines state-of-the-art high-intensity genomic sequencing of a patient’s blood with complex artificial intelligence (AI) algorithms and large data sets in the cloud to detect very early stage cancers.
The latest data from their clinical research program – expected to be one of genomic medicine’s largest ever pursued– shows the test can detect a strong signal for 50 cancer types across all stages with less than 1% of false positives2.
This impressive technology, with investment backing of tech heavyweights such as Amazon, Tencent and Bill Gates, is only achievable thanks to recent advances in AI and cloud-based data analytics.
If the company successfully develops a widely used low-cost, early-stage multi-cancer detection test, this will have profound implications for many traditional healthcare business models.
In the US, healthcare spending accounts for roughly 21% of personal consumption expenditure, with around US$80bn spent each year on cancer treatment.
In the US, healthcare spending accounts for roughly 21% of personal consumption expenditure, with around US$80bn spent each year on cancer treatment3. This includes chemotherapy, inpatient hospital care, outpatient care and drug costs that can exceed US$400k.
The potential deflationary impact of a sub-$1,000 gene-sequenced blood test to identify cancer at an early stage when treatment is much cheaper will be significant to both the industry and the economy4.
The opportunities to improve global healthcare with AI extend across the entire patient journey. Wearable technology is encouraging healthier behaviour in individuals while ML neural networks are providing much faster and more accurate diagnosis of many diseases than capable by a human5. Predictive analytics using big data sets can also help doctors to make faster decisions, freeing up time for patient interaction.
Meanwhile, AI is being increasingly used to better identify potential new drug molecules; reducing cost, time and research and development failure rates. Researchers at MIT recently used an AI tool based on the structure of the brain to identify a powerful new molecule capable of eradicating antibiotic-resistant bacteria – advancing our fight against growing drug resistance6.
The COVID-19 epidemic has also seen the adoption of AI tools accelerate to support diagnosis, epidemiological trend analysis and vaccine discovery. In China, introducing an AI system that classifies the severity of pneumonia caused by the virus on a patient’s lungs cut the time needed for analysis from six hours to under three seconds7.
Natural language processing technology has also been used in Wuhan to carry out up to 1.5 million automated calls daily with households, where the AI is able to ask questions and understand the semantic meaning of conversations, allowing better tracking of the epidemic8. These tools have been critical in helping reduce the virus’ impact.
Intellectual property-focussed solutions are allowing these businesses to build strong barriers to entry and high levels of pricing power, whilst generating above-market levels of cash flow generation.
Within our investment strategy, several of the businesses we invest in are developing highly innovative and technological solutions to address some of the greatest healthcare challenges. Intellectual-property focussed solutions are allowing these businesses to build strong barriers to entry, high levels of pricing power, whilst generating above-market levels of cash flow generation.
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