Eternal life is something that humanity has been yearning for ages. Although that’s unrealistic as of now, the mortals have significantly improved their longevity prospects over the last few decades. Moreover, artificial intelligence (AI) can help people live even longer and healthier lives, bringing all the collective experience to the altar of longevity.
A few centuries ago, people were lucky enough to reach their forties. However, today the average life expectancy globally is over 70. For some regions, the numbers go well beyond 80-85. The scientific and medical progress have contributed to this impressive growth. However, not only vaccines and more efficient medical treatments are to thank for our chance to live long enough to meet our great-grandchildren.
Technology has taken great strides over the past century and continues to develop even more rapidly since the 2000s. It empowered people to live longer in many ways. To begin with, technology has substituted humans in many physically exhausting labour activities. It also took a lot of stress out of our daily routines, enabling people to dedicate more time to their well-being.
Finally, you are surely aware of the impact technology has on the healthcare sector. It empowers doctors to diagnose and treat patients with great precision, consult ill people remotely and monitor critical health aspects 24/7. Technology has also paved the way for innovative healthcare solutions like bionic prostheses, genetic engineering, in vitro fertilisation (IVF), or AI-driven histopathology.
The latter example is just the tip of the iceberg when it comes to the influence of artificial intelligence (AI) on healthcare and longevity. Being one of the most progressive and impactful technologies of today, AI has the potential to revolutionise modern medical protocols, improve both research and treatment, and empower even more extended life expectancy.
AI Improves Drug Development
According to Morgan Stanley’s report, developing a novel therapy type on average requires more than $1 billion in funding. It also takes at least a decade to receive government approval for the development and launch. Moreover, only around 10% of novel therapies that undergo clinical studies make it through the legal approval process.
By leveraging AI, the pharmaceutical industry can streamline drug development processes, reduce failure rates, and bring innovative therapies to patients faster and more efficiently. Biotechs are experimenting with applying AI and machine learning to early-stage drug development. A new wave of AI-empowered drug development platforms helps quickly identify patient response markers and develop viable drug targets, enhance predictive diagnostics with vast data analysis, and enable earlier identification and treatment of higher-risk patients.
Morgan Stanley Research believes that even modest improvements in early-stage drug development success rates could lead to an additional 50 novel therapies over a 10-year period, and a $50 billion opportunity. Even a 1% improvement in preclinical drug development success enabled by the use of AI and machine learning could bring an incremental $15 billion in value for the biotech industry over 10 years. Once it comes to clinical trials, AI can analyse patient data to identify suitable candidates more efficiently, ensuring a better match between the trial’s requirements and participants.
Besides, AI can potentially enable tailored drug development and treatment plans to personalise therapies for individual patients or certain categories of patients based on their genetic makeup, lifestyle, and environmental factors, leading to more positive outcomes. AI algorithms can also identify existing drugs that could be repurposed for new therapeutic uses. Such a task requires analysing vast existing data on drug interactions, mechanisms of action, and disease pathways that could be tiresome for human personnel.
By automating and optimising various aspects of drug development, AI can significantly reduce the time and cost associated with bringing new drugs to market. Morgan Stanley Research biotechnology analysts Matthew Harrison and Vikram Purohit estimate that “a 20% to 40% reduction in costs for preclinical development across a subset of U.S. biotech companies could generate the cost savings needed to fund the successful development of four to eight novel molecules.”
Understanding the opportunity now, data storage providers, designers of digital tools, and companies focused on AI and machine learning for diagnostic and clinical applications should focus on their computing power offerings that might empower AI drug discovery.
AI Contributes to Early Detection of Diseases and Objective Treatment
AI can analyse medical images, e.g. X-rays, CT scans, and MRI scans, and detect even the slightest abnormalities that may indicate critical diseases that take millions of lives each year such as cancer, stroke, or pneumonia. Deep learning can also be used to analyse histopathology images, helping automatically detect and classify cancer cells, measure tumour size and grade, identify biomarkers and mutations, and even predict survival chances and possible response to therapy.
Interpretation of medical data often relies on human expertise prone to errors and bias. Meanwhile, AI algorithms can avail so much more data than a single person, providing standardised and objective interpretations of the given disease-related information. AI can analyse complex datasets and identify patterns that might be missed by human observers, reducing diagnostic errors.
For example, a patient might have a few different health issues that are seemingly not interconnected and require treatment by different medical specialists. AI can avail different Electronic Health Records (EHRs) to provide a more rounded overview of one’s health and longevity pictures. It might reveal unexpected disease hints and also help avoid using contradicting treatments for different diseases or drugs which may bring significant adverse effects.
Early detection of disease can not only improve the health outcomes for a patient but also reduce healthcare costs by avoiding late-stage treatments and hospitalisations. The technology can also assist in monitoring the healthcare quality, checking the accuracy of diagnoses based on provided data and completeness of the medical profiles or diagnostic procedures.
AI-powered wearable devices can continuously monitor vital signs, physical activity, and other health metrics, contributing to the users’s longevity by detecting anomalies that may signal the onset of a disease, as well as helping to verify the efficiency of the prescribed treatment. Late-stage treatments often occur when patients have no immediate access to proper care. AI can enable remote diagnosis and consultation by connecting patients and health care providers through digital platforms as well as power self-diagnosing devices and tools.
Reproductive Technologies Can Benefit From AI Use
Infertility or other troubles with conceiving or carrying a baby are becoming more common today. The increased longevity also led to the fact that the average age of first-time parents is now much greater than two hundred years ago. As we know, fertility declines with increasing age and women’s age at the birth of their first child has risen markedly in many countries in the last few decades.
The statistics of reproductive factors, such as a woman’s age at first childbirth, parity, age at last reproduction, and age at menarche and menopause are increasingly shown to be associated with longevity. Despite the absence of comprehensive conclusions, researchers continue to explore the connection between reproduction and longevity.
Moreover, researchers are currently learning to slow the rate of ageing in female ovaries as women who have later menopause tend to live longer and have an enhanced ability to repair their DNA. It is suggested that early menopause dramatically increases the risk of stroke, heart disease, cognitive decline, insomnia, osteoporosis, weight gain, arthritis, and other issues that affect female longevity. Hence, extending fertility with the help of AI technology and medicine can also improve longevity for this population category.
Taking aside natural fertility, many couples today avail themselves of the reproductive technologies that assist in conceiving. Not only is it costly, but it also may affect the health of a woman, when hormone replacement therapy is involved.
AI can improve the success rates of embryo selection in IVF treatments, with a boosted accuracy of 78% compared to current rates of 13.8% to 66.3%. It also can enhance the assessment of embryo quality and may even help develop personalised strategies for embryo selection. That can significantly improve the chances of getting pregnant on the first IVF, instead of going through multiple procedures.
Besides, AI can help more effective reproductive patterns for couples who have trouble conceiving naturally. Various apps use AI to predict ovulation and fertility windows, helping couples to time intercourse or insemination procedures more effectively. The smart technology can also help identify patients who may need additional emotional support and provide them with required resources or advice via chatbots or refer to counselling services.
Bottom Line
Artificial intelligence is the most promising technology of today. Its practical application enhances many industries and sectors. Surely, the meaning of AI for human longevity should not be overlooked as well. Investors interested in both artificial intelligence and increasing life expectancy should pay attention to projects that work at the intersection of technology and drug development, disease discovery, fertility and reproduction, and medical data interpretation. Besides, data storage providers, designers of digital tools, and companies focused on AI and machine learning for diagnostic and clinical applications may also seize the emerging opportunity.
