Abstract
Biological age is a concept that reflects the physiological state of an individual rather than the chronological time since birth. It can help assess the risk of age-related diseases and mortality and the effects of interventions to slow down or reverse aging. However, there is no consensus on measuring biological age best, and different methods may yield different results. In this paper, which includes 140 relevant pieces of literature, out of 33,000, we review some new methods to measure biological age based on recent advances in biotechnology and data science. We discussed some novel biomarkers and algorithms that can capture the dynamic and multidimensional aspects of aging at different levels. We evaluate their performance and validity using various datasets and criteria and compare them with existing methods. We also discuss their potential applications and implications for aging research and clinical practice. We conclude that the new methods offer more accurate and reliable estimates of biological age and open new avenues for understanding and modulating the aging process.