Can the human aging process be stopped using the advancement of Artificial Intelligence?

The advent of more advanced technologies in AI and more modern development in programming such as Machine Learning, Deep Learning, Reinforcement Learning can help develop age predictors which can offer tremendous possibilities in anti-aging research.

The undesirable effects of aging thus are in the process of elimination and a new era is in the making where AI is set to flourish in the healthcare industry and pharmaceutical development and research practices.

What is aging?

Human aging is a series of physiological changes taking place in the body leading to senescence, deterioration of biological functions, different organs, and also of the ability to perceive and adapt to metabolic stress. It's the degenerative gradual process through which any living organism comprised of tissues and cells, nears its end.

Aging is a universally occurring common phenomenon, which brings a lot of undesirable side effects as age-related diseases along with it such as reduced energy, hearing and vision loss, loss of memory, and inefficient metabolism to name a few.

Is stopping aging necessary? Why is it desired?

Even though an inevitable gradual process, aging is not much appreciated or welcomed by all. Aging can be used interchangeably with a terminal disease that only deteriorates with time and cannot get better or reversed. The geriatric population undergoes massive physical, mental and emotional changes that are generally unpleasant, like decreasing bone density and lubrication, hearing, vision, memory loss. Even the perceived signs of aging like losing skin elasticity, wrinkles are becoming a matter of concern by many. They experience a sense of helplessness as they face retirement, income limitations, and new living arrangements, and thus these changes generate negative feelings and emotions.

These negative outcomes paired with reduced efficiency, steer a rising demand in the anti-aging research field. With the extraordinary progress in Artificial Intelligence (AI) and Computer programming like machine learning, this field of research is working vigorously towards attaining a way out of the natural aging process, to help the elder population get rid of the old age-related liabilities.

How is AI helping in the Anti-Aging research?

Age predictors can be developed through the development of more powerful AI technologies and more modern programming such as Machine Learning, Deep Learning. It can further open up a lot of doors in anti-aging research. Recent developments in generative adversarial networks (GANs) and Reinforcement Learning (RL) allow the production of various different kinds of synthetic molecular and patient data, along with identifying novel biological targets and generation of the novel molecular compound with desired properties and neuroprotectors. These new techniques can thus be implemented to biomarkers development, identify biomarkers, target identification, and prediction to help propagate pharmaceutical research and developmental practices. Hence Artificial Intelligence is all set to contribute to the pharmaceutical developmental field with its aim towards a healthier and longer life.

1. Identifying biomarkers: Artificial Intelligence has been able to identify the patterns and determine the causes of comorbidity associated with old-age through a collection of already existing discovered medical data, pictures, and processes, by using new techniques such as Machine learning, Deep learning, and Reinforcement Learning.

AI algorithms analyze these data to find out the root cause of biological aging markers and make progress in the lifespan control solutions. AI may aid in searching the recurring patterns in human aging to find biomarkers. Artificial Intelligence can detect aging trends in different populations by sifting through large amounts of data from various pathological tests, retinal scans, muscle composition, and other sources, or by comparing human data to that of other species.

2. Gene therapy: Gene therapy is a field in which Artificial Intelligence is assisting researchers a lot. In this genome of a human is searching for a potential defective hereditary gene that might cause diseases such as high blood sugar or cancer in the future and these are removed to prevent the disease. Genome editing to cure diseases has made advancements only because we are able to use machine learning and Artificial intelligence to eliminate the possibilities that are least likely. As with genome editing, there are a huge number of possible combinations to be tried out, which will take the researchers a lot of time to research each possibility. They help detect the genes that are the most useful and also the genes that may be a potential threat. This reduces the workload of researchers.

3. Brain chip implants: With age comes reduced brain functions and activity which is the most undesired effect of aging. Neural links and Chip implants in the spinal cord help with sensory and motor signals which are reduced due to the shrinking of the cortex. Scientists are also working on improving memory functions with age.