Dr. Krishna Maharjan studies chromosomes and cell structures. One of Nepal’s leading cytogeneticists, he broadened my understanding of how artificial intelligence is transforming health care at a recent sit down at the National Path Labs and Research Center in Kathmandu.
Maharjan demonstrated the AI-powered German software he uses for diagnosing chromosomal disorders: IKAROS with Deep Neural Networks. What looked like 46 scattered blobs from a blood sample arranged themselves into 23 neat chromosome pairs in seconds. With just a few clicks, Maharjan could identify the presence of genetic disorders.
“This used to take me three to five minutes,” he explained. “Now, it just takes 10 to 20 seconds per sample.”
That’s a productivity boost of 15 to 18 times.
The confluence of AI, DNA sequencing and gene editing technologies such as CRISPR holds the potential for a revolution in health care, with the prospect of personalized medicine on the horizon. Rather than exacerbating a health care and digital divide between the global north and south, this article highlights evidence where emerging countries are embracing and even developing these technologies to enhance health care services, particularly in diagnostics, drug discovery and distribution, population-sequencing and epidemic management.
All this at a time when government hospitals are creaking with high demand and increasing health care costs, and in desperate need of a boost in productivity and remote monitoring. The adoption of AI in health care also raises ethical questions that need to be tackled.
Diagnostics, radiology and hospital management
Qure.ai is an Indian firm revolutionizing tuberculosis (TB) detection in rural clinics across the developing world, including Nepal’s Everest region. Lengthy wait times for TB test results at overburdened hospitals have been slashed as doctors can now examine chest X-rays with high precision in seconds. The diagnostic capabilities of companies like Ada Health and Zebra Medical Vision advance diagnostics in resource-constrained environments. Patients can self-diagnose symptoms through Ada Health’s chatbot, resulting in fewer hospital visits. At a fraction of the cost of traditional testing, Zebra Medical Vision’s AI technology checks for cardiovascular abnormalities and osteoporosis.
AI-powered remote monitoring systems, combined with wearable sensors, are further enhancing real-time patient care. In Rwanda, Babyl Health uses AI-powered telemedicine to connect patients in distant regions with doctors, eliminating the need for expensive, time-consuming trips to hospitals. To reduce hospital overcrowding, wearable sensors with AI capabilities are being used in geriatric care to monitor patients at home. These developments are contributing to reducing the disparity in access to health care in places with little to no medical facilities.
Health care providers are also integrating AI into radiology workflows. For example, India-based DeepTek has developed an AI-driven automation platform for MRI and CT scan interpretation, recently receiving FDA approval. This innovation boosts scan efficiency by 30 to 35 percent, enhancing patient throughput and optimizing resource utilization.
AI is also transforming health care management systems. Using Mfine, an AI- powered platform that improves patient scheduling, bed management and incorporates chatbots for symptom triage, Manipal Hospitals in India manages more than 15,000 inpatients each month. Automation of this kind increases productivity, cuts down on wait times and ensures that critical patients receive priority treatment.
Drug discovery and supply chain management
AI is also making waves in drug discovery and distribution. At a rate unimaginable just 10 years ago, companies like BenevolentAI are using machine learning to examine massive biomedical datasets to find possible treatments for various diseases. By anticipating shortages and ensuring necessary pharmaceuticals reach patients, Google DeepMind is optimizing the medical supply chain.
These developments have a profound impact on developing nations. AI-driven research could reduce the cost of trials and production of essential medications, therefore making them more affordable, offering hope to millions who struggle to access life-saving treatments.
Advancing genetics and personalized medicine
National Path Labs in Nepal recently received a Next Generation Sequencing (NGS) machine – the first such technology in Nepal outside of universities. While doctors currently rely on it for prenatal testing, the machine introduces the potential of mass-sequencing for Nepal’s population, a process that is well underway in other countries. Advancements in AI-driven DNA sequencing are paving the way for personalized medicine.
Companies like MedGenome and Datar Cancer Genetics are using AI to evaluate genetic profiles, identify diseases before symptoms appear, and customize treatments to individual patients. MedGenome is a founding member of GenomeAsia 100K, an initiative to sequence 100,000 genomes in Asia. Countries such as India and Saudi Arabia are developing their own genetic databases, reducing dependence on western data and ensuring that treatments are better suited to local ethnicities.
In the United Kingdom, the National Health Service is rolling out a gene-editing therapy to treat sickle cell disease, caused by a gene that affects how red blood cells develop. It uses Nobel Prize-winning CRISPR technology to enable gene editing in a patient’s bone marrow stem cells. This is one of a growing number of CRISPR-based treatments. With the DNA sequencing of emerging country populations, such treatments may be optimized for release in developing countries.
Using AI to fight epidemics
AI’s role in predicting and preventing epidemics is increasingly playing a vital role in health care. By using global health data to predict possible epidemics, companies like Metabiota and BlueDot are enabling governments to take proactive rather than reactive measures. AI-based tracking systems proved crucial during the COVID-19 pandemic, assisting nations in effectively allocating resources and forecasting potential outbreaks.
TB remains a serious public health concern in many emerging nations. However, AI-powered solutions are making a difference. By employing AI to identify TB from chest x-rays, Qure.ai is assisting national health initiatives by facilitating quicker diagnosis and treatment. AI prevents disease spread through rapid diagnosis and therefore treatment that could save millions of lives.
Navigating the ethical challenges of AI in health care
Despite its immense potential, there are serious ethical concerns with AI-driven health care. Genetic data is subject to few regulations in many developing nations. This poses critical questions: Could a patient’s genetic profile be used by insurance companies to reject coverage? Could corporations or governments exploit personal health data for profit without patient knowledge?
Another layer of complexity is introduced by CRISPR gene-editing technology. Although it can treat inherited diseases like sickle cell anemia, its long-term effects remain unknown. Serious ethical discussions have been triggered by the prospect of employing gene-editing for non-therapeutic uses, including selecting physical characteristics in embryos. Such life saving technologies that promise to save lives could also be misused without adequate regulation and monitoring.
Prenatal genetic testing presents another ethical dilemma. In some countries, like India, preimplantation genetic screening (PGS/PGD) is banned due to historical misuse, where female fetuses were selectively aborted.
However, parts of Europe including the UK permit such testing. As genetic screening tools evolve, it is essential that they are implemented ethically and responsibly. Investors can play a vital role in promoting ethical standards, even in the absence of emerging market regulation.
Looking ahead at balancing innovation with responsibility
AI is undeniably transforming health care, particularly in developing nations with limited access to medical resources. By increasing access to life-saving medications, individualized therapies and sophisticated diagnostics, it has the potential to democratize health care.
Together with developments in CRISPR and DNA sequencing, AI has the potential to significantly improve health care globally by establishing clear ethical standards and ensuring responsible application. Maintaining AI as a force for good and bridging the health care gap between underserved communities and developed economies, will require striking a balance between ethical stewardship and rapid progress.
Dolma Group
Dolma Group is a Nepal-focused investment company comprising Dolma Fund Management, which oversees two private equity funds: Dolma Impact Fund I and II. These investments have generated over 11,000 jobs in Nepal across sectors such as renewable energy, technology, and health care. The group also includes Dolma Himalayan Energy, partnering with the Investment Board of Nepal (IBN) to develop a 245 MW (DC) solar farm with 80 MWh of battery storage. Founded in 2014, Dolma has played a leading role in advancing sustainable development in Nepal.
Aligned with Nepal’s Energy Development Roadmap, Dolma is raising its third equity fund, the Dolma Climate Fund, to support renewable energy projects. Additionally, Dolma is collaborating with FCDO, GuarantCo/PIDG, and Standard Chartered Bank to issue Nepal’s first international green bonds. This initiative will open access to international capital markets and expand debt capacity for renewable energy, aiming to mobilize over US$ 1 billion for Nepal.
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