Pathophysiology as the Foundation of Medical Knowledge

Pathophysiology as the Foundation of Medical Knowledge:
A Rehabilitation of Theoretical Reasoning in Medicine

Claus D. Volko
(Independent Scholar, Vienna, Austria)

Abstract

Pathophysiology, understood as the study of the mechanisms underlying disease, constitutes the true foundation of medical knowledge, yet it is often sidelined in contemporary medical systems in favor of diagnostic routines and evidence-based classification schemes. This essay argues that pathophysiology is more than a subdivision of theoretical medicine: it is the epistemological core of medical reasoning. Pathophysiology is a paradigm of medical thought. It enables an understanding of the dynamic processes that link health and disease, thereby fundamentally differing from diagnostic medicine, which primarily classifies and labels symptoms.

Based on an analysis of current structures in teaching and clinical practice, the essay shows that medicine often operates nominalistically: it names disease entities instead of explaining them. Pathophysiological reasoning, by contrast, is functionalist and systemic: it examines the dynamics, feedback loops, and equilibria of biological systems. In this way, it is more closely aligned with the paradigms of systems medicine and cybernetics than with traditional diagnostics.

A form of medicine that privileges mechanisms over symptoms and the dynamics of systemic disturbance over classificatory labels gains not only scientific depth but also humanistic substance: it understands disease as a variation of life. The essay calls for a renewed emphasis on pathophysiology as an intellectual discipline that empowers medical students to think autonomously and re-establishes medicine as an explanatory science in the sense of Canguilhem and Bertalanffy.

Introduction

Pathophysiology occupies a paradoxical position within the medical sciences. On the one hand, it is regarded as an indispensable bridge between the basic sciences and clinical medicine; on the other, in both medical training and everyday practice it is frequently underestimated or viewed as an especially difficult “problem subject.” This ambivalence reflects a deeper epistemological tension between the pursuit of theoretical understanding and the drive for diagnostic simplification.

In contemporary practice, a diagnostic paradigm dominates. Diseases are defined, classified, coded, and treated typically on the basis of standardized schemes shaped by economic, organizational, and empirical considerations. This approach undoubtedly has merit: it enables comparability, predictability, and efficiency. Yet it comes at a cost. The intellectual process that leads from symptoms through mechanistic pathophysiological analysis to rational therapeutic decision-making has been increasingly shortened or bypassed. Disease no longer appears as a disturbance of a dynamic system but as a static label.

Pathophysiology represents a different mode of thinking, one that is explanatory rather than descriptive, functional rather than nominalistic, systemic rather than isolating. It asks not primarily what is happening but how: How do biological equilibria collapse? How does homeostasis shift into allostasis? Why do regulatory processes fail or reorganize themselves? From this perspective, disease is not a foreign intrusion into the living system but an expression of its intrinsic variability.

This view is not new, but it is rarely reflected upon as the epistemological foundation of medicine. Georges Canguilhem emphasized in Le Normal et le pathologique that the pathological is not the negation of the normal but its modification. Ludwig von Bertalanffy and Norbert Wiener developed models of self-regulation and feedback that provided theoretical rigor to this insight. Nevertheless, medical thought remained dominated for a long time by a reductionist ideal: disease as the malfunction of an isolated organ, a defect in a molecule, a mutation in a gene.

In the era of systems medicine and artificial intelligence, medicine is now undergoing an epistemological shift. Networks, data flows, and models are bringing pathophysiology back to the center, not as a subdiscipline but as a paradigm. This essay argues for a renewed understanding of pathophysiology in its epistemological significance: as the science of functional deviation, as a theory of the living system in disequilibrium, and as the intellectual center of medicine.

Historical Background and Paradigmatic Development

The history of medicine can be read as the history of its forms of understanding. From ancient humoral pathology to molecular medicine, it has been shaped by shifting paradigms regarding what disease is and how it should be understood. Pathophysiological thinking in the strict sense emerged only when disease was no longer viewed merely as divine punishment or as a qualitative imbalance of bodily humors, but as the disruption of mechanisms.

With the rise of experimental physiology in the nineteenth century, particularly the work of Claude Bernard, pathophysiology gained a scientific foundation. Bernard stressed that medicine’s task was not mere observation but the investigation of the “internal milieu” and its regulation. Disease, for him, was a variation of normal life functions under altered conditions, a definition that still holds true.

Rudolf Virchow’s cellular pathology (1858) shifted the explanatory focus from organs to cells, creating a new level of analysis. His maxim, omnis cellula e cellula, marked not only a biological but also an epistemological revolution: disease could now be described as a consequence of disordered cellular processes.

The twentieth century elaborated this mechanistic approach further. Biochemistry, endocrinology, and immunology opened microstructural explanatory domains, while systems theory and cybernetics, through Bertalanffy, Wiener, and Ashby, introduced thinking in terms of regulatory circuits and feedback loops. Walter Cannon’s concept of homeostasis placed equilibrium at the center and prepared the ground for modern notions of allostasis and adaptation.

At the same time, an epistemological counter-movement emerged. Canguilhem, Michel Foucault, and Hans-Georg Gadamer questioned whether medical knowledge could be fully captured by natural-scientific categories. Canguilhem argued that the normal and the pathological are not objective states but relational evaluations defined by an organism’s capacity to interact with its environment. This shifted pathophysiology toward a philosophical anthropology of illness.

In the latter twentieth century, molecular biology gave rise to a renewed reductionism. The “molecular paradigm” increasingly modeled disease as a defect within genetic or biochemical pathways. This perspective drove major advances in diagnostics and therapy, but often neglected systemic and dynamic dimensions.

Today, in the age of systems biology and data-driven medicine, a synthesis is under way. Medicine is discovering that understanding complex diseases requires neither molecular detail alone nor statistical modeling alone, but the integration of both perspectives. Pathophysiology is experiencing a quiet renaissance as a theory of dynamic systems that demands a return to explanatory rather than merely descriptive thought.

Epistemological Analysis: Diagnosis versus Explanation

Diagnostic medicine and pathophysiological medicine differ in their epistemic goals. Diagnostics primarily classifies; pathophysiology aims to understand.

Diagnostics operates nominalistically. It assigns symptoms and findings to predefined disease categories and thus creates order within clinical experience. This is practically indispensable: it facilitates communication, research, billing, and treatment planning. Yet epistemologically it remains descriptive. A diagnosis names a phenomenon but it does not explain it. It is a linguistic label, not a causal model.

Pathophysiological reasoning, in contrast, seeks mechanisms. It attempts to reconstruct the process chains that span molecular to systemic levels and generate disease phenomena. Its epistemic form is dynamic rather than taxonomic. Instead of static assignment, it seeks functional coherence.

This distinction can be illustrated by example: the diagnosis “type 2 diabetes mellitus” refers to a clinical syndrome characterized by elevated blood glucose, insulin resistance, and metabolic dysregulation. Pathophysiologically, however, it is a complex network of genetic predispositions, cellular maladaptations, hormonal feedback loops, and environmental interactions. The diagnosis names the outcome; pathophysiology reconstructs the path leading to it.

Epistemologically, these two modes of reasoning represent different scientific types:

• Diagnostic medicine is nomothetic-descriptive: it seeks classification and regularity.
• Pathophysiological medicine is causal-explanatory: it seeks mechanistic understanding.

Both are necessary, but their relationship is asymmetrical. Without explanation, classification remains superficial; without classification, explanation lacks orientation. Mature medical knowledge unites both, yet historically diagnostics has often displaced explanation.

The rise of evidence-based medicine intensified this shift. The concept of evidence became narrowly empiricist: only what can be statistically demonstrated is counted as established knowledge. Medicine thereby lost part of its theoretical self-understanding. It became a technique of measurement and comparison rather than a science of understanding.

Pathophysiological reasoning offers a way to bridge this gap. Operating at the intersection of empiricism and theory, it uses data to formulate mechanisms and uses theory to interpret data. In this sense, pathophysiology is not an “intermediate science” but the constitutive center of medicine, its epistemological pivot.

Systemic Models and the Concept of Functional Deviation

Classical pathophysiology describes disease as a disturbance of normal functions. While intuitive, this formulation raises an epistemological question: what is “normal”? And when does deviation become pathological?

In mechanistic views of the organism, normality is often equated with homeostasis, the maintenance of constant internal conditions. But modern systems biology shows that biological systems are not static but dynamically stable. They operate in a state of flux, continually adapting to internal and external influences. Health thus does not mean immutability but resilience: the ability to reorganize in the face of perturbation.

Within this framework, disease can be understood as the loss of functional adaptability. It is not mere deviation from a mean value but the inability to respond adequately to change. The criterion shifts from structure to dynamics, from being to becoming.

This yields a new definition of pathophysiology:

Pathophysiology is the science of the mechanisms of impaired self-regulation in biological systems.

The concept of functional deviation becomes the central theoretical nexus. It characterizes disease as an emergent phenomenon arising from faulty feedback loops, disrupted regulatory circuits, or dysfunctional interactions between system levels.

Endocrinology provides a clear example: primary hypothyroidism is not merely a deficiency of thyroid hormones but an expression of dysregulation within the hypothalamic–pituitary–thyroid axis. The system attempts self-correction by increasing TSH secretion, an adaptive response. Pathology arises only when this feedback fails or reaches its biological limits.

A similar pattern appears in immunology: autoimmune diseases result not from a “malicious” immune system but from miscalibrated tolerance mechanisms. Again, pathology lies not in activity per se but in misplaced regulation.

This perspective allows pathophysiology to be formulated as an interdisciplinary theory of regulatory circuits, uniting biochemistry, endocrinology, immunology, oncology, and psychiatry under a common epistemological roof. In psychiatry, for instance, many disorders can be interpreted as functional deviations within neural networks, faulty weightings of excitation and inhibition, integration and differentiation.

Disease thus becomes intelligible in a broad sense: as a special state of a regulatory system striving to maintain its integrity yet trapped in inadequate or self-reinforcing patterns. This unifies biological, cybernetic, and phenomenological aspects into a single model of medical explanation.

Implications for Research, Education, and Clinical Practice

Research

A systemic approach in research means that disease causation should be studied not as linear cause-effect chains but as networks of interactions. Modern methodologies, from multi-omics to computational modeling, provide the necessary tools.

Yet methodological innovation is less important than epistemic orientation: research should again become hypothesis-driven. Big data can reveal associations but not causality. Pathophysiological reasoning assigns meaning to data by translating them into mechanisms.

A fruitful research program would therefore develop theoretical models of pathophysiological processes and test them using open datasets or simulations. Endocrine and immunological regulatory circuits, for example, could be represented as mathematical or agent-based models to identify conditions for stability, tipping points, and dysregulation.

Pathophysiology would thereby become what it was originally intended to be: an explanatory science at the center of medicine.

Education

In medical education, pathophysiology should not be treated merely as an examination subject but as a school of thought.

Students should learn not only which enzymes, receptors, or cytokines are involved but how they form functional systems and how disturbances produce symptoms.

Case-based learning, simulations, and system models can foster hypothesis-formation. A pathophysiologically oriented curriculum trains causal reasoning, critical reflection, and theoretical creativity, competencies at risk of being lost in an evidence-based but often theory-deficient medical culture.

Clinical Practice

In clinical practice, pathophysiological thinking can initiate a paradigm shift.

Medical decision-making would focus less on diagnostic labels and more on the individual dynamics of the patient. Such an approach promotes precise individualized medicine, not only genetically but functionally personalized. It supports therapies that modulate regulatory circuits rather than merely suppressing symptoms.

Moreover, pathophysiological reasoning deepens the ethical dimension of medical care. It reminds us that disease is not simply a defect but an expression of life’s attempt to reorganize under altered conditions. The physician becomes not a mechanic but an interpreter of biological meaning.

Critique of Personalized Medicine from an Epistemological Perspective

A dominant trend in contemporary medicine is personalized (or “precision”) medicine, widely celebrated as an advance over classical evidence-based medicine. At first glance it appears more individualized, as it incorporates genomic data, biomarker profiles, and multivariate risk scores to optimize therapy decisions at the patient level. Methodologically, however, personalized medicine often relies on statistical correlations: it identifies patterns and subgroups within large datasets and bases therapeutic recommendations on these predictive associations (Joyner & Paneth, 2019; Kent & Coker, 2023).

This approach has epistemological limitations. Researchers have argued that predictive models for heterogeneous treatment effects can be unreliable at the individual level, especially when based on retrospective correlation analyses (Kent & Steyerberg & van Klaveren, 2018). The term “personalized statistical medicine” succinctly captures the critique that many clinical decisions today rely on statistical signatures without explaining underlying mechanisms (Smith et al., 2023). Moreover, studies have shown that some predictive models exhibit questionable research practices, raising concerns about their validity (Wolff et al., 2023).

Against this background, the framework developed in this essay stands in clear contrast. It understands disease not as a statistical cluster of traits but as the disturbance of biological regulatory circuits. Whereas personalized medicine operates primarily predictively, forecasting what may happen, this approach emphasizes causal, mechanistic understanding. Disease is not merely classified but explained.

This epistemological distinction has practical consequences: decisions based solely on patterns risk overlooking mechanisms relevant to therapeutic efficacy and side-effect profiles. A pathophysiologically grounded approach, by contrast, enables targeted interventions that modulate regulatory circuits (such as hormonal feedback loops or immune regulation) rather than merely addressing symptoms or risk markers.

Relation to the Existing Literature

The perspective proposed in this essay integrates and expands several established discourses. Canguilhem’s 'The Normal and the Pathological' provides the epistemological foundation by interpreting disease as a relational variation of life. Ashrafian (2018) argues that physiology and pathophysiology should be recognized as independent philosophical disciplines to preserve their theoretical coherence. Contributions from systems medicine and systems biology (Cardinal-Fernández et al., 2014; Berlin et al., 2018) demonstrate that the analysis of dynamic regulatory circuits and networks is increasingly central to understanding complex diseases. Recent reviews (Bystranowski et al., 2022) show that debates on the epistemological grounding of medical knowledge remain highly relevant.

Unlike these contributions, however, the present essay pursues a synthetic approach that views pathophysiology not merely as a theoretical discipline or philosophical object but as the central epistemological paradigm of medicine, one that bridges diagnostics, systems biology, and clinical practice. The introduction of the concept of functional deviation distinguishes this work from existing publications and underscores its original contribution to theoretical medicine.

Conclusion

Pathophysiology is more than a medical subfield. It is the epistemological axis around which the entire discipline revolves. It integrates natural science, systems theory, and anthropology into a unified understanding of the living. By interpreting the mechanisms of disease as expressions of disturbed yet meaningfully organized processes, pathophysiology guides medicine back to its fundamental task: to understand life in its vulnerable complexity.

References

1. Kent DM, Coker LH. Evidence-based medicine and precision medicine: complementary approaches to clinical decision-making. Heart. 2023;109(1):54–61.

2. Vogt H, Hofmann B, Getz L. Personalized medicine: a competitor or an upgrade of evidence-based medicine? Pers Med. 2016;13(3):239–252.

3. Kent DM, Steyerberg EW, van Klaveren D. Personalized evidence-based medicine: predictive approaches to heterogeneous treatment effects. BMJ. 2018;363:k4245.

4. Smith GC, Jones NR, Patel K. Personalized statistical medicine: reconciling prediction and explanation in clinical decision-making. Clin Med (Lond). 2023;23(4):380–386.

5. Wolff RF, Moons KGM, Riley RD, et al. Evidence of questionable research practices in clinical prediction models: a review of published models. BMC Med. 2023;21:173.

6. Mold F, Doyle M, Clark AB, et al. Precision medicine — Are we there yet? J Pers Med. 2024;14(4):418.

7. Illari PM, Russo F. Causality: Philosophical Theory Meets Scientific Practice. Oxford University Press; 2014.

8. Joyner MJ, Paneth N. Promises, promises, and precision medicine. J Clin Invest. 2019;129(2):946–948.

9. Lillie EO, Patay B, Diamant J, Issell B, Topol EJ, Schork NJ. The n-of-1 clinical trial: the ultimate strategy for individualizing medicine? Per Med. 2011;8(2):161–173.

10. Deutscher Ethikrat. Evidenzbasierung und personalisierte Medizin – ein Widerspruch? Berlin: Deutscher Ethikrat; 2013.

11. Kroenke K. Studying symptoms: sampling and measurement issues. Ann Intern Med. 2001;134(9 Pt 2):844–853.

12. Bousquet J, et al. Systems medicine approaches in healthcare. Clin Transl Allergy. 2014;4:28.