The first volume of this book explores certain areas of modern physics that have major implications for the progression of biology and medicine. Areas surveyed include biological and statistical thermodynamics applied to bioenergetics, biophysics’ growing and potentially explosive subfield of quantum biology, as well as complexity and chaos theories. Particularly crucial is the notion of phase transition, a concept within the domain of statistical thermodynamics that successfully reduces complex systems composed of many interacting entities into a manageable number. Importantly, this has led to the introduction of order and control parameters as well as bifurcation points where instabilities built into such systems cause catastrophic changes in the system’s behavior. In the context of human physiology for example, a bifurcation point in the functioning of the organism is tantamount to the reciprocal transition from a healthy state to a disease state. This powerful methodology has found numerous applications beyond physics and physiology in fields such as materials engineering, sociology, and even environmental science.
A central theme that connects all of the Chapters in Volume 1 is the clear understanding that various disciplines in modern physics can be instrumental in gaining quantitative insights into biological systems. Areas such as phase transitions and quantum biology along with chaos theory and systems biology offer an integrated representation of the hierarchical, interconnected, and synchronized organization of the systems that living matter embodies.
Of the body’s response to external stressors, any underlying quantitative framework employs a multi-dimensional representation of it in the form of a fitness function analogous to the function of thermodynamic free energy. Here, in the second volume, we adopt this concept and refer to it as the Physiological Fitness Landscape (PFL). We can tie this to the use of big data metabolomics ingested by AI algorithms that include the PFL. In order to properly exploit the advances physics has made toward our understanding of natural phenomena, we discuss emerging physical areas such as quantum biology, which represents an effort to explain subtle effects of electromagnetic fields on living systems (e.g. in photosynthesis) alongside large-scale phenomena including organism-wide synchronization of biological functions via coherence. Of particular importance to this book is the theory of quantum metabolism, which employs empirical quantization rules for mitochondrial enzymes in close analogy with the Debye theory of vibrations in solids (whereby below a certain temperature the behavior of a solid material changes, while above it the behavior stays constant) .
Through the use of elegant mathematics, quantum metabolism has been able to elucidate the emergence of allometric scaling laws of physiology (equating the relationship of metabolic rate to body weight), a problem left unresolved for more than a century. Equal in significance is the conclusion that inefficient energy production, characteristic of disease states like cancer or Alzheimer’s, manifests by isometric scaling laws of classical metabolism (i.e. a linear correlation of metabolic weight with body weight) while optimum states of human health result from quantum metabolism’s efficient and synchronized mode of energy production .
Beyond the sheer joy of discovery, it is the author’s strongly held conviction that these multidisciplinary approaches will support problem solving in clinical medicine, especially when integrated with Big Data and AI algorithms. This is the bridge to future medicine, which will be personalized, predictive, and precision-based. The future of medicine is indeed bright.