Modern medicine has brought some amazing advancements. The development of antibiotics. Increasingly sophisticated and targeted cancer treatments. Medical imaging techniques, like PET scans and MRIs. Cardiac surgery, organ transplantation, and minimally invasive surgery. These advancements have led to increased life expectancy and have enhanced quality of life for many people.

The greatest strength of modern medicine, though, can also be its greatest weakness: the challenge of greater and greater specialization and precision. We seek to understand things by taking them apart, down to their most basic elements, studying individual genes, proteins, or molecules in isolation.

This approach often fails to capture the intricate interactions and dynamics that occur within living biological systems. As an integrative physician, I see this play out all the time. A patient might routinely be on 10+ prescriptions and can easily have as many physicians. The care can be extraordinarily difficult to integrate. And when you consider the experience of the patient, it can be quite overwhelming. Imagine trying to schedule appointments with 10 different doctors. And now imagine if these doctors aren’t all in the same health system. When we zoom into the fine detail of a particular diagnosis, it is very easy to lose sight of the bigger picture of the patient. This can lead to a siloed approach to care, and an inability to see that the patient might have a more clear, unifying diagnosis driven by one, or several, undiscovered root causes.

This is where systems medicine comes in.

Systems medicine is an interdisciplinary field of medicine that aims to understand complex biological systems by examining them across different scales and levels of organization. The purpose is to develop a holistic, comprehensive picture of how these systems function in both health and in disease, with the goal of improving diagnosis, treatment, and personalized approaches to care. Systems medicine incorporates the precision of the modern approach while adopting a more holistic view and considering the interactions and relationships among different parts of a system, including genes, proteins, cells, organs, and environmental factors.

Systems medicine operates on three core concepts:

1.     Multi-scale analysis – Systems medicine appreciates that biological systems operate at different scales—from molecular interactions to cellular processes to whole-organ physiology to interpersonal interactions—and seeks to integrate information across these scales to provide a comprehensive understanding of how disease develops or resolves. Systems medicine incorporates many types of data, including data from the genome, metabolome, microbiome, exposome, and sociome. The comprehensive approach allows a much more complete picture of health and disease.

2.     Homeostasis  -Homeostasis refers to the body’s ability to maintain a stable internal environment despite external fluctuations. This balance is crucial for the proper functioning of biological systems, and when it is disrupted, disease may result.  Systems medicine seeks to understand how homeostasis operates within the body, examining complex interactions and feedback loops that contribute to maintaining homeostasis and also exploring how these systems break down. The approach benefits from analyzing molecular, cellular, and physiological processes involved, and allows for a more comprehensive understanding of how interventions might impact the overall system (rather than just targeting isolated components).

3.     Complexity, emergence, and interdependence – Systems medicine appreciates that biological systems are more than the sum of their parts. They exhibit emergent properties—qualities that cannot be easily predicted or understood by analyzing individual components isolation. Complex interactions and intricate feedback loops lead to novel behaviors and phenomena. Similarly, no components exist in isolation—all parts of a biological system are closely interrelated, and biological systems themselves (ie, different people) are also deeply connected.  

From a clinical lens, the result of all of this is truly personalized medicine. By analyzing individual patient data, from multiple sources and multiple levels (including genetic makeup, molecular profile, etc) it becomes possible to appreciate the complexity and uniqueness of an individual person at a new level, and to develop personalized treatment plans. And it becomes much more clear that many factors can influence health—diet, physical activity, lifestyle, emotions, social interactions, community, career, and sense of purpose, for example. While systems medicine might have the potential to overemphasize what can be explicitly measured, it’s appreciation of complexity and emergence allows more for the immeasurable as well. For example, rather than seeking out just the symptom a person is trying to address, it appreciates that engaging in a patient’s meaning may be crucial. Rather than just describing the time course of the symptom, it calls for a broader but more personalized health assessment. Rather than developing a plan unilaterally, it allows the plan to be created collaboratively, taking into account patient-defined goals and needs.

Interestingly, while systems medicine is a relatively new concept in the modern world, the core features have been in place for millenia in traditional healing systems. Take Chinese medicine, for example. The core of Chinese medicine is the balance of qi—the body’s vital energy. This qi flows along channels in the body and keeps a person’s spiritual, emotional, mental, and physical health in balance. Traditional Chinese medicine aims to restore the body’s balance and harmony between the natural opposing forces of yin and yang, which can block qi and cause disease. These forces can be both internal and external—the environment in which one lives is crucial. Traditional Chinese medicine includes acupuncture, diet, herbal therapy, meditation, physical exercise, and massage. It describes patterns, rather than anchoring on a specific diagnosis (depression, for example, may result from a combination of causes, no). Chinese medicine is about homeostasis (the balance of qi), complexity and emergence (pattern description), and multi-scale analysis (appreciating both inner and outer factors).

Then there’s ayurveda, the ancient Indian medical system, which has also been practiced continually for thousands of years. Ayurveda comes from the words ayur (life) and veda (science, or knowledge). Similar to Chinese medicine, ayurveda is based on the idea that disease is due to imbalance. Each person has a particular pattern of energy—an individual combination of physical, mental and emotional characteristics—which comprises their own constitution. There are three major life forces—the doshas, vata, pitta, and kapha—which can exist in a nearly infinite combination. Ayurveda takes into account seasonal influences, daily routines, natural rhythms, nutrition, movement of nutrition and waste, metabolic processes, cognitive factors, and lifestyle. Ayurveda places great emphasis on prevention and encourages the maintenance of health through close attention to balance in one’s life. It is about homeostasis (balancing the doshas), complexity and emergence (the manner in which doshas are combined), and multi-scale analysis (appreciating the impact of many variables).

Systems medicine has helped understand illness and disease for thousands of years, and it is the medicine we desperately need in our complex, modern world.  Here’s a quote from Denis Noble, one of the pioneers of systems medicine, that sums it up well (the quote is from his book, The Music of Life - Biology Beyond the Genome):

“the reductionist approach has successfully identified most of the components and many of the interactions but, unfortunately, offers no convincing concepts or methods to understand how system properties emerge ... the pluralism of causes and effects in biological networks is better addressed by observing, through quantitative measures, multiple components simultaneously and by rigorous data integration with mathematical models." "Systems biology ... is about putting together rather than taking apart, integration rather than reduction. It requires that we develop ways of thinking about integration that are as rigorous as our reductionist programmes, but different. ... It means changing our philosophy, in the full sense of the term.”