“Biomarkers of Longevity: Most Comprehensive and Minimum Required Panels of Biomarkers of Aging” is an upcoming open-access special analytical case study by Aging Analytics Agency that uses comprehensive analytical frameworks to rank and benchmark existing panels of biomarkers of aging, health and Longevity according to their ratios of accuracy vs. actionability, identifying the panels of biomarkers that can have the greatest impact on increasing both individual and national Healthy Longevity in the next few years.
The use of biomarkers is an indispensable component of industry analytics and assessment. It is the foundation upon which measurement of Healthy Longevity and the effectiveness of Longevity therapeutics is built. Biomarkers are also the primary metric in P4 (precision, preventive, personalized and participatory) medicine, which involves continuously monitoring of the progress of a disease state and recommending a series of corrective interventions in response, to keep patients’ state of health in an optimal mode for as long as possible.
Aggregating biomarkers of aging (rather than biomarkers of disease) is particularly difficult however, as by definition, they must be sought in populations of healthy people rather than from among the health data of the hospital populations. Furthermore, as the scope of P4 medicine broadens, the number of biomarkers and technologies will increase rapidly to the thousands in the coming years. This makes the implementation of P4 medicine impractical by current, manual means.
Some possible solutions to these problems include the use of AI for the development of an optimal panel of biomarkers of aging, for the analysis of individual patients’ biomarkers of aging, and for orchestrating therapeutic interventions in response to fluctuations in those biomarkers. As the number of data points increases, it becomes not only optimal, but strictly necessary, to use AI and big data analysis for these purposes.
It is important in any domain of science or technology never to let the perfect be the enemy of good. It is desirable therefore to develop a minimum viable panel (MVP) of biomarkers: a panel of biomarkers which though not as precise as possible are precise enough and easily implementable.
The report also presents a “most comprehensive” list of biomarkers of aging, devotes analysis to recent novel biomarkers of aging just entering R&D processes today, and highlights why the use of AI in biomarker discovery and development will come to be a necessary and indispensable component of Longevity biomarker R&D as the volume of data on both biomarkers and the complex networks of how they interact together continues to grow.