Remember Baymax, the inflatable healthcare robot from Big Hero 6? Or the tricorder from Star Trek? Well, AI and robots have been part of the world of fiction for a long time, but now the possibilities for machines that can understand, reason and learn and help us better use information have become a reality. (Editor: Hopefully not a dystopian reality.)
AI has actually been making inroads in healthcare for decades; in Africa, pilot studies concerning health worker-patient interaction in Kenya and detection of eye disorders in Egypt were conducted as early as the 1980s.
While the pandemic naturally adversely affected global healthcare systems, one benefit to emerge from the situation is accelerating investment in and adoption of AI in healthcare: according to CB Insights, in 2021, funding in the AI sector grew by 108%, with healthcare alone accounting for about a fifth of overall.
The past couple of years has seen a number of AI-healthcare partnerships emerge. Apart from the Big Pharma collabs, which have primarily focussed on drug discovery, and the furtherance of RWE in clinical trials, a lot of innovation is happening globally.
Some notable highlights from the past couple of years:
Earlier this year, Israel-based AION Labs (in collaboration with Germany's BioMedX) announced a third call for applications to establish a startup focused on antibody design and optimisation for targeted therapies. Then, the first startup to emerge from the AION partnership - OMEC.AI - was announced in late September. OMEC aims to analyse preclinical data to increase the probability of success of drug candidates in clinical trials. This process is currently done with little technological insight. Next steps for OMEC include developing the required computational platform.
In February last year, the Singapore-based Bot MD announced its $5 million Series A funding. The startup intends to take its AI-based chatbot to more doctors in the APAC region, including Indonesia, the Philippines, Malaysia and India. It will also use the funding to add new features to fulfil Covid-generated demand from hospitals; additionally, the bot plans to support Bahasa Indonesian and Spanish by the end of the year, in addition to the AI-assistant's current English.
Closer to (The Kable's) home, Mumbai-based Karkinos Technology is bringing AI-supported cancer detection to India in a strategic partnership with US-based C2i Genomics. The objective of the partnership is to co-develop the minimal residual disease (MRD) market in India. It will mark India's first whole-genome sequencing (WGS) MRD test.
China's XtalPi currently owns a platform ID4 (Intelligent Digital Drug Discovery and Development) which measures chemical indicators to predict the characteristics of drug compounds. With its 2021 $400 million Series D funding, XtalPi will collaborate with pharma companies around the globe to discover highly effective molecular compounds and their anticipated potential. Since 2021, XtalPi has invested in and partnered with META Pharmaceuticals, Kintor Pharma and Excelra, amongst others.
Post-pandemic research concerning the potential applications of AI in improving the detection of medical conditions, especially cancer, has taken big strides too.
In the July 2022 volume of the journal Gut, researchers from Aga Khan University in Kenya and the University of Michigan proposed the deployment of AI and ML to address the high incidence and mortality rates for colorectal cancer (CRC) in Africa via population-based surveillance and early diagnosis and prognosis. They predict that these advances could also positively impact maternal, newborn and child health and the detection and treatment of other cancers, diabetes and cardiovascular disease in the continent.
In Britain, the pandemic resulted in a backlog in scans for breast cancer. In 2021, the Artificial Intelligence in Health and Care Award was granted to a group of researchers from Imperial College London, Google Health, and 3 NHS trusts to mitigate the national shortage of radiographers.
Ultimately, notwithstanding these developments, the widespread adoption of AI-assisted health interventions depends on more than just funding and clinical research. Supporting infrastructure - in terms of increased internet penetration, improved quality of data collection, and governance - play a pivotal role in enabling the developing world to benefit from such technologies.
Central to training ML models are large, quality datasets, and such datasets raise issues concerning data sharing and privacy. In service of the ethical deployment of such data-reliant tech, last year, Rwanda's Chamber of Deputies legislated on the Protection of Personal Data and Privacy. The consequent secure domestic and international data flows have been leveraged to improve healthcare access.
Companies such as Babylon have enabled around 4000 Rwandans to consult doctors or nurses via mobile devices every day. With an AI-enabled triage tool and localisation (in terms of language, local health protocol, and epidemiology), Babylon's pilot study incorporated the WEF's Chatbots RESET Framework for the ethical deployment of conversational AI.
While 2021 saw healthcare funding in AI soar to never seen before levels, 2022 is seeing a bit of a slowdown. But that's not necessarily an indication of trends to come: with a CAGR of 43.4%, the AI in healthcare market size is anticipated to grow to $201.3 billion by 2030. Unsurprisingly, North America is expected to hold the lion's share of the industry, considering increasing healthcare spending and the adoption of AI technologies.
APAC, on the other hand, is poised to witness the most rapid growth given the large potential for improvements in healthcare infrastructure, governance, and investment. Additionally, the high prevalence of diseases in these regions is propelling demand for AI in healthcare.
