Technology and Dehumanization of Medicine

Abstract

The paper “Technology and de-humanization of medicine” published in 2017 relies on the insight about the nature of modern technology since its emergence in seventeenth-century Europe and its application to the domain of modern Western medicine (today called Biomedicine) from the seventeenth to the early twenty-first century. This understanding changes at different periods, first focusing on machines such as steam engines whether pulling trains or powering cotton mills such as the Quarry Bank Mill in Cheshire, one of the best preserved textile factories of the Industrial Revolution which first occurred in England. The next stage was centered less on physics but more on biology, on organisms including the human organism during the mid-nineteenth century when Darwin published On The Origins of Species in 1859. Technological outcomes are human artifacts, the ontological contrast of organisms which are naturally occurring, and therefore independent of human manipulation. However, a profoundly radical change soon occurred in modern/Western consciousness—organisms began to be perceived and understood as machines. In medicine, the patient was regarded as nothing more than a malfunctioning machine with defective parts/organs which must then be replaced by a nondefective organ/part—surgery as a technology embodies this ontological volte-face. However, biology/genetics is fast-moving. By the early twenty-first century, this mechanistic Reductionist paradigm of scientificity was overturned by the findings of the Human Genome Project, about 50 years after the discovery of DNA genetics in 1953. Today, Reductionism in biology/genetics has muted in favor of Wholism (Noble, The music of life: biology beyond genes. Oxford University Press, Oxford, 2006/2008). The Addendum takes up this theme.

Addendum (2023)

Introduction

Having reread the original 2017 paper, I have decided the best way of providing an update is via an Addendum, leaving the published paper intact. This is for the following reasons:

• 1. That paper reflected a view about science and technology which in the domain of biology, including genetics, implies a philosophical framework which was bounded by what may be called thing-ontology and its methodological implication in terms of a Reductionist model of causality which is unidirectional and monofactorial. This may be called the mechanistic Newtonian Paradigm of Scientificity/NPS.

• 2. However, surprisingly quickly, biology and genetics have moved on, within the space of a few years. A contrasting view has arisen, which is the polar opposite of the NPS, which may be called the Post-Newtonian Paradigm of Scientificity/P-NPS. It is non-Reductionist in character and is committed to Wholism.¹ Its causal model is multifactorial with feedback mechanisms (the causal arrow is minimally bidirectional).

• 3. Hence, any updating must be devoted to the radical change just mentioned, which is best done via an Addendum, rather than tinkering with the original text.

• 4. However, since 2017, another related phenomenon has taken place, the emergence of SARS-CoV-2/COVID-19 as a pandemic in late 2019/early 2020, with governments worldwide implementing in the first instance nonpharmaceutical measures to control the rate of its transmission, such as lockdowns, physical distancing, and mask-wearing. Such measures belong to Epidemiology, rather than Clinical Medicine, that domain of Biomedicine considered to be “superior.” This pandemic has also brought out the limitations of the Reductionist model of causality/NPS while reinforcing the status of the non-Reductionist character of Wholism/P-NPS.

Change of Orientation in Biology and Genetics

A quick glance at the history of modern genetics shows two distinct phases: (a) the earlier Reductionist phase and (b) the later Wholist/Non-reductionist phase. Both have taken place under the aegis of the Human Genome Project/HGP. The HGP took off with the Crick and Watson discovery in 1953 of the double-helix structure of the DNA molecule and soon after with the emergence of Biotechnology, a more powerful technology which permits intervention at a deeper level of genetic manipulation, so much so that transgenic organisms² could be constructed.

The initial reaction to the discovery of the double helix structure of the DNA molecule is one of Reductionist triumphalism. Many geneticists saw it as simply the conquest by the NPS of a domain of enquiry which had so far resisted and eluded it. This included Crick who became more than ever convinced of the correctness of Reductionism. He (1996, 14) claimed that the aim of molecular biology/genetics is to explain “all biology in terms of physics and chemistry.” James Watson, his codiscoverer (not an ex-physicist but a phage geneticist), appeared to be of like mind.

The Holy Grail of the HGP was, naturally, the genome of Homo sapiens, which was more or less completed by 2003. The publication of its findings, however, raised and/or reinforced doubts in the minds of certain people who then became explicit critics of Reductionism in biology and genetics (Noble 2006 being a notable convert). Before the HGP revealed its findings, scientists had speculated the number of genes to be between 50,000 and 140,000; instead, they found a sequence of 3 billion pairs of bases, up to 30,000 genes (25,000–30,000) at most. This astonishing finding set in train a challenge to Reductionism.

What are the presuppositions of the Reductionist program? It appears to have four (see Ho 1998, 51–54):

• 1. Genes determine characters in unidirectional causal chains; one gene gives one function.

• 2. Genes and genomes are not subject to environmental influence.

• 3. Genes and genomes are stable and unchanging.

• 4. Genes stay where they are put.

It is obvious that the HGP findings challenge these presuppositions. Once the simple-minded “ideological” controversy between Nature or Nurture has been seen off center stage, the immense complexities in the Gene-Environment relationship have come to the fore. We know that the internal as well as the external environment of a cell can affect which genes are “turned on,” so to speak. This kind of knowledge challenges, in particular, presupposition 2. For instance, hormones can “tell” a cell to activate a specific gene (internal environmental factor);³ outside temperature can change the fur color in rabbits (external environmental factor).⁴ We also know the timing of these relationships can have profound effects on the individual human being in later life as well as even transgenerationally.⁵

The complexities above are set out in figures and tables, namely, Figs. 1, 2, 3, Text Box 1a, b.

Fig. 1

Genes interacting with environmental factors, internal and/or external

Not only do genes interact with the external larger environment or with the internal environment of the body in producing certain phenotypical changes and characteristics, but they are also related with one another in a complex manner, as shown in Fig. 2.

Fig. 2

Complex inter-relationships between genes. (This figure has been downloaded from: https://evolution.berkeley.edu/evolibrary/images/evo/control_gene.gif)

The concept of a master control gene is invoked in developmental biology—a single gene whose expression can activate many other genes in a coordinated manner, ultimately leading to a specific tissue or organ being developed. Pax-6 is said to be such a gene which triggers development of the eye. However, it bears laboring the point that development of cell, tissue, organs, and whole organism depends on more than the existence of genes, as the environment, both internal and external, plays a critical role in human biology in particular and in biology in general.

Some of the complexities may be brought out via the differences between Gene Reductionism and what may be called the Integrated Systems Approach in the Text Boxes below (1a and 1b):

Text Box 1a The Reductionist Approach

Text Box 1b The Integrated Systems Approach

The Integrated Systems Approach may also be presented and explored in terms of Ecosystem-nesting/Ecosystem Science—see Fig. 3.

Fig. 3

Network of networks as Ecosystem-nesting in terms of concentric circles: 1. Atoms: carbon, hydrogen, oxygen, nitrogen, and phosphorus which make up DNA (deoxyribonucleic acid); 2. molecules at the level of genes and their DNA; 3. proteins subcellular mechanisms and pathways; 4. cells (DNA is in the nucleus of every cell); 5. tissues; 6. organs; 7. organism: the human body (each body contains trillions of cells); 8. populations of human bodies; 9. social-cultural environments in which human populations and individuals are enmeshed; and 10. larger physical environment in which human populations are embedded (such as geographical locations, climate, oceanic currents, other plants, and animals). Note: Ecosystem-nesting is intended as an analytic research tool. Depending on the context of its application, one may construct as many concentric circles as are needed for the purpose at hand

The non-Reductionist orientation in the understanding of the Gene-Environment relationship was carried a stage further when new domains of investigation emerged following the publication of the HGP findings. These are called Big-Data Science, a multidisciplinary enterprise drawing in physics, mathematics, computer science, computer engineering, and technology as well as biology (See EMBL-EBI 2022). It involves genomics (briefly looked at above), proteomics (the study of the structure and function of proteins, how they work, and how they interact with one another inside cells), transcriptomics (the study of the complete set of RNA transcripts produced by the genome, under specific circumstances or in a specific cell, using methods such as microarray analysis), and metabolomics (the study of metabolites present within an organism, cell, or tissue). Here, we will explore a little only the last mentioned type of investigation. One account of metabolomics reads:

Metabolomics is a powerful approach because metabolites and their concentrations, unlike other “omics” measures, directly reflect the underlying biochemical activity and state of cells/tissues. Thus metabolomics best represents the molecular phenotype.

…

The metabolome is the complete set of metabolites within a cell, tissue or biological sample at any given time point. The metabolome is inherently very dynamic; small molecules are continuously absorbed, synthesised, degraded and interact with other molecules, both within and between biological systems, and with the environment.⁶

These small molecules have been discovered using two analytical techniques, nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS). From the quotations cited above, one could see why metabolites have been considered as such exciting “finds.” The reasons include the following:

• 1. Their noninvasive nature, as they can be extracted from any sample of body fluids such as urine, saliva, blood, and even gut fluid.

• 2. As they are produced at the levels of cells, tissues, and organs, they can be said to be indicative of a Wholist/Integrated Systems View of the human organism.

• 3. They reflect dynamic processes of change at work within the human organism.

• 4. They act as ready biomarkers⁷ (a) of the effects of pharmaceutical interventions, (b) indicating the presence of certain risk potentials in patients, and (c) alerting the medical profession to the fact that different people may react differently to particular treatments. They are expected to be found in those with a certain disease, such as Alzheimer’s and dementia, and those without. These can act as (a) a warning about the eventual onset of the disease in an individual, (b) as an indicator of how fast the disease may be progressing in the individual patient, and (c) whether a drug given to the patient is hel** to retard the progression of the disease.

The SARS-CoV-2/COVID-19 Pandemic: Emergence of Epidemiology from the Shadows

Before this pandemic, within Biomedicine, Epidemiology had been assigned the “Cinderella” role, playing second fiddle to Clinical Medicine, which was regarded as more rigorous in its scientific methodology and, therefore, superior. The raison d’être behind this critical assessment lies in the fact that Clinical Medicine scores the highest in Biomedicine’s Pyramid of Evidence, while Epidemiology fails to reach such heights—see Table 1.

Table 1 Medical evidence (more familiarly presented as The Pyramid of Evidence) invoked today—if higher or the highest level (level I) is not available, then move down to the next best level

As set out clearly above, the highest level of probity is occupied by evidence based on RCTs.⁸ The “real mark of Cain” worn by Epidemiology is that it fails to satisfy not so much the criterion of being a controlled test but that of randomization. The technique of randomization makes eminent sense in Clinical Medicine, as it is concerned crucially with pharmaceutical measures of controlling a disease, namely, drugs (usually in the form of pills) considered to be truly effective in terms alone of their pharmaceutical potency (the active ingredients of a drug) rather than a reliance on the so-called placebo effect. Randomization, including the use of double-blinding, is then considered as critical to the control and elimination of the placebo effect.

Given the nature of Epidemiological Thinking, it cannot but fail to reach Level l of evidential probity as it cannot mount RCTs. Unlike Clinical Medicine and its RCTs, it cannot satisfy the requirements of controlling for the placebo effect as well as that of randomization.⁹ That is why in spite of the best efforts of epidemiologists, including those of Austin Bradford Hill, Richard Doll, and Richard Peto, the Nobel Prize in Medicine has so far eluded Epidemiology, including 2022, in spite of the coronavirus pandemic. It is generally claimed and accepted that the research of Bradford Hill and Doll has transformed epidemiological research, putting it on an impeccable scientific footing from the methodological point of view; and that Doll’s substantial findings cover not only the tobacco/lung-carcinoma link, but also between other substances such as asbestos and cancer, radiation and leukemia, and alcohol and breast cancer as well as establishing that smoking increases the risk of heart disease. Their work in demonstrating that tobacco is a crucial factor in the production of lung cancer, leading to the ban of smoking in public space and other measures to discourage smoking, has “probably prevented the premature deaths of millions already and … may well prevent tens of millions more.” (See Peto 2005). Doll is said also to be the most distinguished epidemiologist of the twentieth century. Following his demise on 24 July 2005, the Karolinska Institute in Stockholm announced on 5 October 2005 that the prize in medicine was to be awarded to Marshall and Warren for their discovery of H. pylori as “the cause” of peptic ulcer.¹⁰ The Nobel Committee had chosen presumably to honor the infectious-agent model of the Monogenic Conception of Disease on the centenary of its award in 1905 to Robert Koch for his discovery of the tubercle bacillus as “the cause” of tuberculosis.

In other words, to date, Epidemiology continues with its “Cinderella” status, in spite of the fact that the pandemic has thrust it forward to the center stage and people around the world were caught up in its nonpharmaceutical measures for controlling the pandemic when vaccines were not initially available and no truly effective drugs existed to deal with the virus. However, although its nonpharmaceutical measures when seriously implemented were effective in reducing the figures for serious cases of infection and death (such as in several East Asian countries, not to mention New Zealand in the East Pacific), these measures included lockdown which many Western countries in general but the USA in particular have frowned upon, as lockdown is perceived to violate America’s core value of individual rights, freedom, and autonomy. For such and other related reasons, the hope that Prince Charming will soon knock on Epidemiology’s door to bestow an enhanced status and to recognize its contribution to saving lives will not be high. It looks as if the test of the pudding is not in its eating but elsewhere such as in the murky waters of geopolitics.¹¹

Conclusion

Discoveries in basic Theoretical Science and their induced technologies produce rapid and radical changes, as evidenced by the 1953 Crick and Watson discovery of the double-helix structure of the DNA molecule. This was followed in 2003 by the findings of the HGP. We have seen that initially the 1953 DNA molecule discovery prompted a Reductionist moment of triumphalism in conformity with the NPS under which enthusiasts envisaged that physics-cum-chemistry would entrench their status as the “queen” of the sciences as they claimed that biology had fallen under its reach. Yet strange to observe, biology has successfully hit back, using the HGP itself as the vehicle to show that a Wholist/Non-Reductionist orientation, in conformity with the P-NPS, is well justified (see Noble 2008). Furthermore, studies such as metabolomics appear to have transformed medicine in the twenty-first century, by rendering two concepts, held at arm’s length by Biomedicine in the past, scientifically respectable, namely, Preventive Medicine and Individualized/Precision Medicine. However, it is not to say that this latest set of developments has displaced Reductionism or the NPS altogether from center stage; instead it may be regarded as constituting an alternative to the near-hegemonic status of the Reductionist conception of Biomedicine up to the beginning of the twenty-first century.

The SARS-CoV-2/COVID-19 pandemic of the last 3 years has also created some room for Epidemiology to make an appearance from the shadow cast upon it by the achievements of Clinical Medicine, even if it has not rescued it from its “Cinderella” status as evidenced by the fact that the Nobel Prize in Medicine so far has not been bestowed on medical scientists working in Epidemiology, in spite of the pandemic over the last 3 years. Furthermore, while Clinical Medicine occupies the highest level of probity in the Hierarchy of Evidence, Epidemiology, as it fails to satisfy the gold standard of randomization and double blinding, has been assigned to a level of probity below that of the gold standard satisfied by Clinical Medicine. However, it is beyond the nature of Epidemiology to satisfy these two methodological requirements laid down by the RCT to avoid the placebo and other confounding effects. The number of fatalities avoided in the recent pandemic through the nonpharmaceutical interventions of Epidemiology, not to mention the number of lives saved through its influence upon governments and individuals worldwide in the case of cigarette-smoking and lung cancer over the last several decades, have been impressive. Yet proper recognition seems to elude the subject. Perhaps the Nobel Prize Committee should look into its own soul and untie the knots which may have prevented it from appreciating the scientific/social/philosophical merits of Epidemiology and its thinking in Biomedicine. Minimally, it is hoped that the pandemic has opened up some space for the appreciation of the causal model of Epidemiology/P-NPS.