When Mainstream Cancer Care Runs Out of Options — The SCIENTIFIC Alternative to Alternative Medicine
Warning: THIS IS A PHILOSOPHICAL TREATISE ON THE EXISTENCE OF AN UNEXPLORED TERRITORY OF EPISTEMOLOGY (THE STUDY OF HOW WE ACQUIRE KNOWLEDGE) THAT LIES OUTSIDE OF BOTH MAINSTREAM ONCOLOGY AND ALTERNATIVE MEDICINE BUT THAT FULLY EMBRACES SCIENCE.
Over just the past few years, owing to new “omics’” technologies, an enormous amount of factual knowledge about the molecular wiring diagram of tumor cells and the dynamics of tumor behaviors have been collected and deposited in vast databases. However, cancer treatment still has to follow the traditional, lengthy path of drug development, clinical trials and approval. Currently, there is no room for using theoretical reasoning and logical deduction, as is standard in engineering and in the physical sciences, to derive strategies for solving a problem. Instead, all advance relies on the empiricism of trial-and-error gathering of evidence for therapeutic efficacy. Thus, only a tiny fraction of all existing human knowledge about cancer that is scientifically sound and could motivate a safe treatment ever reaches the patients.
But this could change in the near future. It is herein claimed that in the landscape of cancer treatment, there exists a no-man’s land, a territory that is off the radar screens of both mainstream medicine and of Alternative Medicine. This epistemologically uncharted territory exists because mainstream medicine overtly relies on empirical evidence and eschews scientific reasoning, and because Alternative Medicine departs from scientific principles. Moreover, both share views on cancer that are not compatible with the scientific concept of a tumor as a complex dynamical system and that remain unquestioned. This unclaimed epistemological territory offers a fertile ground for identifying non-approved but scientifically sound and safe (“NSSS”) therapy options that have not (yet) entered standard of care.
It is understandable that terminal cancer patients, when told that state-of-the art medicine has run out of options, seek refuge in Alternative Medicine. In cancer care the proclivity for embracing unorthodox approaches is particularly prevalent because of the limited options for curative therapy and the multifaceted nature of cancer which stimulates our imagination of plausible treatments approaches.
“Alternative medicine” commonly refers to approaches that lie outside of “mainstream medicine” or standard care and is roughly defined by the absence of scientific evidence of effectiveness and even, of safety. Often, they rely on some sort of plausible ad hoc mechanisms that appear to intuitively make sense but do not qualify as scientific. But the point I would like to make here is: not everything outside of mainstream medicine is unreasonable or unscientific. Of course, “absence of evidence is not evidence of absence” — a mantra whose aura of veracity is magnified by desperation and hope, and thus readily adopted by Alternative Medicine. But this is not how medical sciences work. Positive empirical evidence of efficacy (and of safety), obtained by clinical trials, is required, and the bar for the quality of such evidence, set by the FDA, is high.
Now, mainstream medicine and Alternative Medicine do not occupy a binary world. The apparent dualism is much more complex. These two domains cannot be separated by a straight line. There exists a grey zone outside of standard care that nevertheless is not Alternative Medicine. There is room for an alternative to Alternative Medicine. This alternative to Alternative Medicine, currently only imagined, is as scientific as mainstream medicine –perhaps more so, as I will show.
First, there is a hidden irony. Mainstream medicine and Alternative Medicine have something in common: they both take for granted a shared set of concepts that they tacitly accept as biological truth and that they then never question. Orthodoxy is blinding. The NIH, CDC and FDA, etc. are the major institutional embodiment of mainstream medicine but they are by design not good at questioning well-established principles. They lack the intrinsic facility of seeing beyond orthodoxy. They have erected a self-referential “thought collective” that steadfastly maintains itself through intellectual incest and mutual confirmation (for more about this phenomenon in cancer research, see here). But ironically, even alternative medicine is part of this system of self-fulfilling prophecy that cements existing concepts, thus stifling innovation.
Some of the concepts shared by mainstream and Alternative Medicine, and thus never questioned by either party, may actually be scientifically questionable. What if mainstream and alternative approaches have a common blind spot that prevents them to see a scientific alternative to the concepts that both embrace as “ground truth”? To comprehend the “alternatives to the alternative”, requires a more encompassing category of thought. This alternative to the alternative may offer a treatment option that is safe and scientific when mainstream medicine has run out of options and one resists, rightly, to accept Alternative Medicine because it lacks scientific rigor.
One example of a fundamental misconception shared by both mainstream and Alternative Medicine is the idea, almost never questioned, that killing tumor cells is necessary and the sole strategy for controlling cancer. Mainstream and Alternative Medicine then differ only in the means for doing so: Is their efficacy verified by clinical studies or not? For instance, scientifically, killing tumor cells, hence creating a wound in the neoplastic tissue that triggers generation of stem cells, may perpetuate the tumor; hence despite shrinking the tumor, killing of tumor cells may actually plant the seed for relapse by fueling abnormal never-ending regeneration. The detailed biology behind all this is explained elsewhere. Let us now focus on the epistemology of the (scientific) alternative to Alternative Medicine in pushing the innovation of better treatment.
I. MAINSTREAM MEDICINE AND ALTERNATIVE MEDICINE ARE NOT JOINTLY EXHAUSTIVE
The term ‘Alternative Medicine’ exists because of a dualistic worldview: One the one hand, there is the accepted “mainstream” standard of care which has a scientific basis, and on the other hand, everything outside of mainstream medicine is considered Alternative Medicine and by implication (and here is the error of thought), non-scientific. But these two are not jointly exhaustive as the logician would say: the two options that they cover together are not the only options — the world is not binary. The problem is that mainstream medicine itself is not exhaustive in embracing all scientific views. It is agnostic of any scientific rationale outside of itself because it has equated ‘scientific’ with ‘supported by evidence’: Mainstream medicine it is now essentially identical with “evidenced-based medicine” — a movement in clinical medicine that started in the late 1980s and puts emphasis on treatment for which there is “evidence” of efficacy. The term ‘evidence’ refers to the empirical demonstration of efficacy (and of safety) of a given new treatment, obtained in a clinical study that compares patients who are treated vs. not-treated with said treatment. Clinical trials (which must meet some design criteria) is the gold-standard to establish a standard of care.
Mainstream medicine works. But is not perfect. It does not represent everything under the sun that is scientifically meaningful. It is a subset of the scientifically meaningful. It is stuck in a self-constraining worldview that is inert, if not hostile, to new ideas. It defies Shakespeare’s insight that “good ideas give place to better ones”. The resistance of mainstream medicine to advance is understandable because “good ideas suppress better ones”, as psychologists have observed. Thus, there is room for scientific alternatives that are neither standard care nor Alternative Medicine. Since standard care and Alternative Medicine are not jointly exhaustive, they leave space for non-mainstream but scientific alternatives. As mentioned, current mainstream medicine and its complement, Alternative Medicine share many ideas on the nature of cancer treatment that may not be entirely “correct”. What if in the realm of an alternative to both, there exists effective therapies that could drastically prolong life of cancer patients but we don’t know about and never will if we follow the trajectory of progress dictated by mainstream medicine?
II. THE EPISTEMOLOGICAL BACKGROUND
Current medicine is a prisoner of evidence-based medicine (EBM), which has become a major rate-limiting factor that slows down innovation because evidence of efficacy is tedious to obtain, requiring large and lengthy clinical studies, and in addition, safety must be demonstrated. The fact is that there is no way around obtaining empirical evidence through rigorous clinical trials (which essentially means: randomized, blinded, controlled studies in sufficiently large cohorts). For all its virtues, clinical studies are also riddled with obvious and less obvious technical issues — this is not the subject here. But there is a more subtle, profound concern: In a culture in which empirical evidence from clinical trials is everything, few appreciate that in the grander scheme, empirical proof is not the only pillar of a scientific knowledge. Moreover, limiting medical research to gathering evidence from trials stifles creative use of the human mind — the driving force of innovation.
In the broader epistemic perspective, one can crudely distinguish between two pillars of knowledge of “truth” in the natural sciences which have been at the center of contentious scholarly discussions among philosophers and scientists ever since Aristotle. One is that all knowledge requires empirical evidence, as discussed, above, and even, that all abstract reasoning is meaningless, which is advocated by the movement of empiricism. The other is theory, or logical reasoning, which is related to the traditional movement of rationalism. (Note that theory itself can be derived with help of observation, thus these tow perspectives are not mutually exclusive). This is a crude black-and-white scheme for sake of argumentation — there are of course nuanced details here that I must omit.
In medicine, a rationale that underlies our “knowledge of facts/truth” about a disease or an intervention is a “mechanism”. The mechanism comes from theoretical knowledge (which in turn has been previously established based on observations and tested in experiments) and from logical thinking that connects the dots of existing knowledge, with the goal to “explain” or “predict” a new behavior in a new context.
The “mechanism” is typically embodied by genes, bio-molecular pathways, cell behaviors, organ functions, physiological principles, etc. and explains, e.g., how a disease develops or how a drug works. Neither empirical observation (“it is merely descriptive and qualitative, not generalizable and predictive”) nor reasoning (“it may miss important facts of nature”) alone are sufficient. For instance, from knowing the fact that cigarette smoke contains substances that can cause genetic mutations in lung cells and also can irritate the lung tissue and promote inflammation, one can logically deduce that smoking may cause cancer. However, the other pillar, empirical evidence from epidemiological studies is still required to “validate the theory” and establish the medical fact that smoking causes cancer. Conversely, observation of a correlation between smoking and lung cancer alone is of course not satisfactory since such a relationship is subjected to spurious patterns and specific conditions, and thus, is of unknown generalizability. Moreover, lay people are told again and again that “correlation does not imply causation”, and that we need a “mechanisms”.
Thus, empiricism and rationalism are both necessary — they synergize. In practice, we need both and there is no particular sequential order for which of the two pillars of a medical fact is first established.
There is a convoluted process between the two pillars of knowledge. For instance, reasoning based observational data can lead to a hypothesis about “causal” connections, which can be tested in empirical studies. Alternatively, in unbiased studies (not motivated by a particular mechanistic question) an unexpected correlation may spring to eye — such as the association of consumption of nuts with health. Such observations from large epidemiological studies, provided spurious correlations are excluded, could prompt experimental studies guided by theoretical knowledge of biochemistry, metabolism and pathophysiology to establish a mechanism. Conversely, knowing the biochemical composition of nuts (poly-unsaturated fatty acids!) and their pathophysiological activity, a scientist may reason (deduce) that nuts are healthy and propose an epidemiological or even interventional study to test her hypothesis.
Whereas medicine has always stressed empirical knowledge, there are domains of science and engineering where our knowledge of truth as the basis of our actions is not empirical evidence but almost pure deductive reasoning, often formalized in the language of mathematics. For instance, predicting the course of a hurricane, planning the position and timing of a rocket launch for landing on the moon, or designing a chemical reaction for synthesizing a drug molecule, all require a lot of theory. We do not compare 1000s of moon landings to learn about the best launch parameters, or measure 1000s of hurricanes to predict purely based on statistics the exact course of the next hurricane; we do not measure 1000s of random mixtures of starting chemical compounds to learn how to set up a chemical synthesis to make a drug. We do not simply rely on empirical evidence, however systematically acquired and analyzed with help of statistics, to acquire knowledge about the laws of nature and to predict the specific course of a process, be it a hurricane, a moon landing or a chemical reaction. Instead, we use formal reasoning (theory) and apply it on data on the actual instance combined with established fundamental laws and general principles to deduce (“figure out”), compute, simulate and predict the behavior and future course of a specific case of a moonshot, hurricane or chemical reaction, etc. ..
Such practical application of general theory to a given instance of a system and “figuring out” its future behavior and its problem and its remedy, will require logical reasoning and a formal theory. The uniqueness of a constellation of a particular system prevents empirical studies in large cohorts of replicates as in the clinical trials with thousands of patients. This is rationalism. This is the dream of future medicine: To advance the science so that we so not rely on empirical studies to know how to solve a problem, but can act like engineers!
III. THE PERCEIVED PROBLEM OF MECHANISTIC REASONING AND THE OVERREACH OF EMPIRICISM
The current problem with such rationalism and the associated mechanistic reasoning in medicine is that the living organism is so complex that logical deduction based on a mechanistic rationale and elementary principles, even with supporting experimental evidence, cannot be trusted, and thus, cannot be applied to a given, real clinical scenario. Few generally valid fundamental principles exist in the biomedical sciences. There are too many unaccounted for, often individual-specific details left out of the equations, making the latter unreliable. (I will write on Personalized Medicine and “N-of-1 trials” another time).
Take for instance, the story of vitamin C: Based on its elementary anti-oxidative properties and its observed action on immune cells, high-dose Vitamin C had (in)famously been theorized as a cure for common cold, and even, of cancer. Such reasoning is what scientists call a “mechanistic hypothesis”. But there is scant empirical evidence from controlled clinical trials to support the beneficial effect of high-dose Vitamin C.
The path to failures in the history of medicine is paved with well-meant, apparently plausible and clever mechanistic rationales.
Hence the understandable distrust of clinicians in theorizing. This is not to say that there are no rare cases where logical reasoning based on a mechanistic rationale can work like a charm: For instance, scientists had once reasoned that blocking the beta-lactamase enzyme in bacteria could overcome antimicrobial resistance to penicillin because beta-lactamase is the enzyme that some bacteria make to degrade the penicillin that fungi produce to kill bacteria. A dual-compound drug that contains a mixture of a beta-lactamase blocker and a penicillin-type antibiotic is still the one of the most powerful, commonly prescribed anti-biotic drug. In this case we have a crisp rationale to design a combination therapy composed of two compounds. Combination therapies in cancer treatment do not such have such a rational basis — the combination of chemotherapy drugs used in one setting is based on hand-waving, educated guess, ad hoc plausibility arguments, etc..
Most of the time, mechanistic rationales about the human body (the right pillar in the figure above), notably in oncology, do not readily translate into real-world effect. This is the reason why in medicine, empiricism trumps over rationalism, and why therefore, clinical studies, especially randomized clinical trials, have become the gold standard for establishing “medical facts”. (And this is also why “Precision Medicine” works so poorly — including “Precision Oncology”, because simply targeting mutations is just so naïve!).
Take for instance those modern anticancer drugs that target specific molecular pathways (“target-selective drugs”), the epitome of cancer therapy based on a precise mechanistic rationale: In principle, based on the underlying reasoning, they “must” work. Yet, target-selective drugs still rarely (with Glivec® being the best known exception) systematically achieve long-term cancer control despite the clear-cut molecular rationale (in fact, most of them do not extend life of cancer patients by more than six months — see figure above). But even if they do work, in reality, because of the sheer complexity of the network of molecular pathways and myriads of cells involved in tumor growth, often, the actual mechanism of action of a drug may be more complicated than the scientific rationale that originally motivated its development. For instance, Glivec®’s anti-tumor action may not solely depend on its blockade of the vital biochemical pathway (the oncogenic Bcr-Abl kinase) in the cancer cells, but may also work via the blockade of tumor angiogenesis or via stimulation of anti-tumor immunity.
The distrust in mechanistic thinking and theory-based reasoning in medicine is thus understandable. The continuous stream of epidemiological studies that disprove long-held assumptions on the health benefits of certain diets or supplements, such as the recent large study confirming the lack of any significant health benefit of supplements or even of low-fat diet, undermines confidence in theoretical medical knowledge. Such health benefits were originally proposed based on biochemical and physiological reasoning. No wonder that reflections on human biology had to yield to the reflexes of calling for clinical studies. The emphasis on empiricism has only grown in the days of big data, up to an excessive extent in “data science”, where the blind and brute-force, theory-free “data analytics” in medicine now threatens to take over scientific thinking.
But the problems of such hyper-empiricism, now manifest in the rather thoughtless reliance on “data”, is already felt at the front of drug development for anti-cancer therapeutics. By insisting on clinical evidence as the litmus test for potential benefit, even mistaking it for the sole reason to warrant pursuit of new ideas for therapies, we delay, even deny many potentially beneficial new treatment modalities that originate in theoretical knowledge and in deeper reasoning about the biology of tumors.
In the current culture that equates medical knowledge with just the one pillar of empirical clinical evidence, we abnegate an entire domain of possibilities outside of existing paradigm that can only be reached by first some deductive reasoning that utilizes the enormous amount of existing medical knowledge. Such scholarly capacity of synthesizing a broad amount of information, based on a rigorous mastery of all what is known –pretty much like what Charles Darwin did to conceive of the idea of evolution of species after decades of observations–- is not taught anymore. Instead, we promote doctors who manage clinical trials that test incremental changes for a narrow question (e.g. on schemes of drug administration) while we sideline doctors who reason about those fundamental properties of tumors that make them so hard to control. In other words, medical academia nowadays favors superficial transactional activities over deep scholarly activities.
IV. A NEW UNCHARTED LAND OF THE SCIENTIFIC SOUND AND SAFE THAT IS NOT MAINSTREAM
Times are changing. The intellectual climate that has nurtured the culture of hyper-empiricism is evolving. In the past decades our knowledge of the function of the human body, from molecules to cells to organs, has drastically increased. The amount of factual knowledge deposited in medical knowledge sources, from PubMed to gene ontology and pathway databases to disease compendia has exploited. Moreover, our understanding of the theoretical principles of how the human body works has revived interest in logical reasoning and mechanistic rationales. The pendulum in the oscillating historical confrontation between empiricism and rationalism shows signs of swinging back towards the latter. One sign for this development are the physical science inspired research funding programs for cancer research established by the NCI and NSF (although execution still lacks, see here).
Compared to historical periods of rationalism, this time, logical reasoning and the quest for connecting the dots to gain new insights before verifying them in clinical trials have a new companion: the vast online databases of molecular, cellular and physiological measurements and new computational tools that places such information at the finger tip of every researcher. Although “data science” still ignores the actual medical science behind the data, the era of big data opens new opportunities for the pillar of rationalism.
We can distinguish between two distinct classes of biomedical “data”. (Unfortunately, many leaders of big data efforts, private or public, have not yet learned to make the epistemic crucial distinction between these two fundamentally distinct types of “data”.
(A) First, knowledge-databases of established “facts” — so to speak the Google and Google map of the entire, existing body of knowledge of all the genes and biomolecules and molecular wiring diagrams, of their role in diseases and of all the cell types in the human body, with all their known properties, as well as of all the synthetic substances and how they interact with the human body. Such databases of material and functional facts of how the human body works will provide the substrate for scientific reasoning about diseases and cures and for erecting new theories that will be needed when simple “hand-waving” type of arguments, typical of clinical medicine, fail to deal with the complexity. But their content will require detailed knowledge of biology, physiology and pathology as well as of complex systems theory to query, navigate and interpret.
(B) Second, the new, but growing raw (=measured) data consisting of all the data-points from the “multi-omics” measurements of millions of variables for each individual (from genome to transcriptome to proteome and metabolome in various tissues, and clinical phenotype). Such measured data, now available for increasingly larger and larger populations, could one day be used to erect, test and refine theories and hypotheses and to gather supporting preliminary evidence even without dedicated clinical studies. A currently available resource of this kind, The Cancer Genome Atlas (TCGA), which contains the molecular profiles of several hundred cases per tumor type, is only a start. Soon many more such “raw data” depositories (B) will link molecular profiles with the clinical health information of actual individuals, provided by a variety of initiatives (such as All-of-Us, UK Biobank, etc). They will complement the overtly gene-centered TCGA.
Currently, the data collecting and curating efforts are still driven by a pure empirical mindset that equates data with knowledge. This led to the entry of “big data” and its companion, “data science” into the domain of medical sciences. However, data science is, like evidence-based mainstream medicine, agnostic of the pillar of rationalism that adds a third necessary ingredient in addition to medical knowledge (A) and the raw data from measurements (B): formal theory and knowledge-based reasoning. Without theory and medical knowledge, there is only so much one can achieve with data — but “data scientists” in health care still have not recognized what they miss and continue to bark up the pillar of empiricism while ignoring theory — and the imagination and innovation that comes with it.
“Theory” is not an abstract epistemological alternative. Specifically, advances in applying the theory of complex non-linear dynamics to the biology of cancer and the (patho)physiology of tissues homeostasis has been off the radar screen of empiricists and of evidenced-based medicine, and of “data science”. (For more on why cancer research requires theory — see here). Most importantly, if empiricism is equated with ‘practical’, this does not mean that ‘theoretical’ is the opposite to ‘practical’.
Theories of complex system dynamics offer a new tool box with tools for reasoning to make sense of the spate of data far beyond the ad hoc interpretation of the empirical approach. Theory-based reasoning in cancer biology will open up an entirely new territory in the epistemological landscape for cultivating new ideas on therapeutic strategies that are derived from theory and the integration of all existing biological knowledge that has accumulated over almost a century. Mainstream oncology has long ceased to be a scholarly endeavor with the ambition to consider all existing knowledge in a systematic fashion (à la Darwin), which in the case of cancer therapy would seek to be consistent with all empirical observations and to understand the biological principles behind therapy failure for each individual case. Instead, since mainstream research consists now of transactional activities, failure of a treatment typically calls for some modification of the treatment proposal based on an ad hoc intuitive idea of what went wrong (which is more reminiscent of an excuse than a scientific explanation) and of “what could be improved” (e.g. dose escalation, a new combination of drugs) in the next clinical trial. Variation to a theme, often clever, in some superficial way, but without much scientific reasoning.
The scientific approach that seeks coherent theories and that values the rationalism of logical reasoning on all existing biomedical knowledge lies outside the bounds of current medical empiricism. But not only is it outside of mainstream medicine, it nevertheless also cannot be equated with Alternative Medicine for, unless the latter it adheres to rigorous scientific thinking. Therefore, rationalism, given sufficient knowledge and data –but without need for clinical studies– is yet another “alternative” in a more encompassing way. It defines a new uncharted territory for finding new treatment options that may work given our knowledge of the mechanisms and that can be predicted to be safe given the databases of accumulated clinical experience and pharmacology knowledge. I hence call this potentially fertile “no-man’s land” in the landscape of cancer treatments the domain of Non-approved but Scientifically Sound and Safe (NSSS) therapies.
We now understand this figure, shown at the beginning:
Concretely, the emphasis in NSSS is on SCIENTIFICALLY SOUND in the sense that these therapies are based on rigorous (bio)logical reasoning supported by exhaustive analysis against all existing databases but have not yet been embraced by the mainstream community because of lack of empirical evidence of efficacy. If the treatment involves compounds that are already in use, either as a supplement, diet or drug for a non-cancer indication, such a treatment could be considered to have been demonstrated to be SAFE. The safety of a compound could also be tentatively predicted based on its known chemical degradation and metabolic elimination pathways and its pharmacological “interactome” –if the profile of its molecular interactions with all endogenous proteins and biomolecules has been determined. Such prediction requires knowledge and theory.
Sure, NSSS treatment shares with Alternative Medicine that a treatment option has not undergone evaluation by clinical trials, but it makes good for that by the strict scientific rationalism: theoretical assessment, now aided by interrogation against all existing medical knowledge. Moreover, NSSS does not eschew synthetic chemicals (such as the repurposing of a painkiller or antidepressant for cancer treatment if they blocks a critical function in the tumor) which are rejected by the romantic side of Alternative Medicine. This is what I mean with a scientific “alternative to Alternative Medicine” that is not mainstream medicine.
Finally, the NSSS territory is the territory that expands into new lands of treatments — for after all, its emphasis on thinking affords a vital source of creativity: Innovation comes from imagination, which itself emanates from the creativity of the human mind. And thinking takes much bigger steps into the unknown than the inherent incrementalism of empirical clinical trials.
V. A NEW ERA OF SCIENTIFIC UNDERSTANDING STRENGTHENS THE USEFULNESS OF LOGICAL REASONING IN MEDICINE
When a late-stage cancer patient proposes an Alternative Medicine treatment that is deemed safe, doctors often empathetically refrain from objecting, independent of any assessment of efficacy. If the alternative therapy, such as high doses of vitamins or an exotic dietary supplement is known to be safe and does not interfere with standard care, then, so goes the thinking, in the worst case “it won’t help but won’t hurt” and in the best case “it might help”. But now the unprecedented scientific knowledge base of molecular and physiological pathways together with new theoretical tools to study tumor behavior dynamics affords the new capacity to support or reject, at a new level of scientific rigor, treatment strategies proposed by both traditional Alternative Medicine (“this dietary compound may stimulate your immune system”) as well as Precision Oncology (“this gene is mutated in your cancer, so let us target its product”) BEFORE empirical evidence of efficacy is obtained. So far such proposals have been based on plausible, albeit superficial, hand-waving type of rationales. But the new epistemological territory of NSSS also could lead to the identification of specific molecular and cellular “lever points” for specific instances of tumors, based on the tumor and the patient’s molecular profile.
New computational approaches are being developed towards this vision. First we must democratize, simplify and unify access to the vast biomedical knowledge sources that contain millions of molecular states and regulatory wiring connections in human cells, tissues and disease processes and other biomedical facts (data-type A, see above), which are still difficult to process. NIH-funded efforts are under way, taking baby steps towards realizing the vision of uniting all biomedical factual knowledge into one system for scientists and clinicians to utilize. One possibility is that this body of all humanly knowable medical facts will be stored as a gigantic knowledge graph . The challenge is how to allow the physician to access it in order to interpret the molecular multi-omics profile of her patient (data-type B, see above— the new data type that will increasingly become available.
But even more ambitious are the early attempts to combine these vast biomedical knowledge databases (data-type A) with their instance-specific “biological embodiment” by a real existing person whose clinical data, and personal multi-omics profile (data-type B), which soon will be part of their electronic health records. This will require a new type of in silico empiricism, and a new type of synergism between the two pillars of empiricism and rationalism. (More specifics will follow in future essays here).
Cancer is a natural phenomenon, and time is ripe to tackle cancer, and its treatment, including treatment failure, as a scientific and engineering problem by utilizing formal tools and reasoning, and not, as mainstream medicine sees it, as a logistic, statistical and regulatory problem to be tackled by purely transactional activity of managing data analytics and clinical trials. Such automatism of clinical research must make some room for the autonomy of the human mind if we are to be creative in cancer research. Cancer is more complex a phenomenon than what can be framed in terms of ad hoc causal pathways extracted from the data that only need to be blocked by a target-specific drug.
I have described a very abstract and hard to articulate problem that most likely will evade most readers since I may have not succeeded in explaining it. At the heart, the problem is simple: The entirety of the body of current factual biomedical knowledge is vast, but because of the arcane drug development process, and the neglect of theory and biological reasoning in mainstream medicine with its myopic focus on empirical evidence, only a tiny fraction of this knowledge currently can ever be converted to benefit a patient. But there is a moral imperative to change this. We need to enter and chart the unexplored territory of the NSSS. Hopefully we are at the beginning of this process.
