The line between basic and applied research; episteme/science vs techne/art

Exactly two months since my last blog post–not sure where the time went!

A NY Times article today provides an excellent story to illustrate the distinction (and hand-off point) between basic and applied research. For purposes of my Means of Innovation and ASTL (art, science, technology, law) constructs, it also illuminates the distinction, and recursive iteration, of science/episteme, art/techne, and technology. Further, it allows me to demonstrate my view on how we should draw the lines between patent ineligible principles and patent eligible practical applications.

Path is found for spread of Alzheimer’s

OK, so let’s dive into the details.

Scientists at Harvard and Columbia have finally been able to amass strong evidence that Alzheimer’s spreads through the action of faulty tau proteins. The normal version of these proteins provides scaffolding to support the microtube in a brain neuron cell

Illustration of normal and faulty tau proteins in neurons

Previous research had often focused on the action of plaque-like beta amyloid proteins that appear near the diseased parts of Alzheimer’s patients’ brains. The question was whether the beta amyloid developed and then the disease progressed as different neurons in the brain succumbed at different rates, or whether some other agent transmitted the disease from neuron to neuron in the manner of an infection.

The state of the art for experimentation to test these two hypotheses was inadequate until the development of genetically engineered mice that expressed the faulty human tau in one specific part of their brains.

Point 1. Scientists needed an advance in the state of the art in genetic engineering (an applied field or techne) before they could answer a question in science (basic research or episteme). One hallmark of the “new sciences” ever since Galileo and Bacon has been the use of experiments–manipulations of natural or physical phenomena–to test hypotheses that are proposed as contemplative principles about how something works in the world. This can be thought of as the distinction between knowledge how (know-how) and knowledge that (propositional statements), or procedural knowledge and declarative knowledge. Crucially, the object of the Alzheimer’s research was only the propositional or contemplative knowledge of which path leads to the progression of Alzheimer’s.

The researchers likely had grant funding for this research. I would speculate that the grant application targeted the determination of this propositional knowledge as the intended outcome of the research, even as it couched this specific proposal in the larger context of the search for Alzheimer’s treatments. But the object of this specific research was almost certainly not an Alzheimer’s treatment (which would be simply impossible to propose given that the researchers did not yet know which path led to the spread of the disease). Thus, this was classic “basic science” research, intended to provide epistemic statements (propositional or declarative knowledge) about how Alzheimer’s spreads. The primary output of such research will be written works including data, analysis, and conclusions. Secondary outputs may be methods or know-how in performing this research.

At this stage, there is no patent eligible invention in the primary output of the research. It is pure principle and not a practical application. The write up of the research results may be copyrightable, and the data may be able to be protected as trade secrets (although the researchers, their institution, or their funders may frown on or even prohibit this). And this, in turn, is related to arguments that the framers of the U.S. Constitution thought of the output of “science” as writings produced by authors for purposes of the Progress Clause (U.S. Const. Art. 1, Sec 8, cl. 8, Congress is empowered to grant exclusive rights to authors and inventors to “promote the progress of Science and useful Arts”). The researchers’ use of practical applications–the genetically engineered mice and techniques to test how the tau proteins spread from neuron to neuron–does not change that this project had as its object propositional knowledge and thus constitutes primarily basic research.

However, now that the tau “infection” pathway is determined (or at least reasonably evidenced) as the means by which Alzheimer’s spreads, this propositional knowledge has “immediate implications for developing treatments,” as the article states.

But contrary to what many of those outside biotech and pharma industries might expect, these treatments are not now self-enacting. We know what we need to do: disrupt this spread of the faulty tau proteins. But we do not yet know how to do this. Accordingly, the next phase in the larger project to treat Alzheimers is translational. We need to begin envisioning ways in which we might disrupt this pathway. The article suggests an antibody that blocks tau as one possibility. But healthy tau is important as a supporting structure in the neuron microtubes. So, we need to focus these antibodies on only faulty tau. At the same time, it may be that we could find a pathway for how healthy tau turns faulty. Is it congenital–meaning that some kinds or expressed tau will almost always become defective by their very structure or nature? Or is it environmental in that all the tau expressed in the Alzheimer’s patient is fine until and unless some kind of environmental trigger causes it to go faulty?

I am not a scientist, so I don’t pretend to know how to go about real hypothesizing and testing for this translational phase. But as someone who has worked with, and studies, the commercialization of life sciences innovation, I can say that this translational phase is not going to be easy or self-evident. It requires application oriented researchers who may or may not be the same researchers who are good at the basic research phase. They will also need substantial funding to do this work.

At the same time, researchers may find that they need another phase of basic, propositional knowledge-oriented research–this time focused on how tau turns defective and spreads. Or, the translational researchers may be able to proceed directly to testing ways to disrupt the spread of defective tau from neuron to neuron. Or maybe we’ll do both. A short term applied focus on simply stopping the infectious spread of defective tau, and a long term basic research plan to determine how tau goes bad, with the hope to later disrupt that pathway instead.

Point 2. Assuming translational researchers can proceed directly to developing disruptions to the spread of defective tau, they will engage in applied research with the object of a practical application–where the output of the research will primarily be knowledge how (procedural knowledge) to disrupt this spread. Such application is patent eligible and constitutes art or techne and not science or episteme. Before the term “art” was oddly reduced to the fine arts in the nineteenth century it meant the use of rational processes to produce desired effects in the physical or mental realms. By contrast, “science” was the term for propositional knowledge, and not methods for producing physical or mental effects. Further, our practical application to disrupt the spread of defective tau is a method or art that must be practiced in the physical world. We can write about it to describe it, but its true nature is as a method to be performed on physical subjects. In other words, the written description of it (in a patent application or journal article) cannot treat anyone by producing practical effects in the physical world. Only actions in the physical world–applied or practical methods–can do this.

However, we are still not done. Even if the translational researchers demonstrate a way to disrupt the spread of defective tau, this process may produce collateral damage to a patient. Some of this may become evident from the research done in the translational phase. But at some point we must move into the next phase which is commercialization. In this phase, researchers (the same or different ones) will engage in computer modeling and animal studies to test both the efficacy and safety (toxicology) of the proposed treatment. This will require further significant funding. Its object will again primarily be the development of practical methods, although an important ancillary object is the development of data that will be required by the FDA in an Investigational New Drug application (IND) so that we can begin human clinical trials. At this stage, we may find that the proposed treatment has too many negative side effects and we will have to go back to the translational phase to find another candidate. But if we make it through computer and animal trials and the FDA approves our IND, then we could proceed to human clinical trials, which are also a component of the commercialization phase. Their primary object is to produce data required by the FDA for a New Drug Application (NDA) that, if approved, will allow a commercial firm to market a drug to the public. At the same time, our proposed treatment may take the form of a biologic and not a drug, in which case we would follow a similar clinical trials process pursuant to a Biologics License Application (BLA). If our human clinical trials either fail to show sufficient efficacy, or they demonstrate too many negative side effects, or the trade-off of the two does not seem to present an improvement over existing therapies, then we will not receive FDA approval and will have to return to the translational phase to find another candidate.

Along the way, we’ll also have to develop manufacturing and dosage know-how that allows: i) the firm to produce the drug/biologic at mass market scale; and ii) patients or their health care providers to administer the drug/biologic for treatment. These are also practical applications that may be patent eligible. And it may turn out that there is no cost effective way to produce the drug/biologic at scale, given reimbursement policies and the health care market for Alzheimer’s treatments. In this case, we once again return to the translational phase to find another, hopefully cost-effective, candidate. However, this alternate may not be as efficacious as the original, or it may have more adverse side effects.

In the end, we see that the whole process for getting from basic research to a drug/biologic “on the shelf” has recursive phases of science (to develop propositional or declarative knowledge and data) and art (to develop know-how or procedural knowledge). Each phase has its own object and arc of inquiry, or processes, that it uses. These can be seen as epi-arcs on a larger arc of technology in which we use insights and knowledge developed from scientific inquiry to guide or accelerate our artisanal innovation. In other words, by using rigorous inquiry methods to determine natural principles and relationships in the physical world (episteme or scientific knowledge) we can then propose, develop, and test practical applications to intervene in natural processes for human benefit. The former are not patent eligible. Nor are they protectable in and of themselves by copyright. But a particular written expression of them is copyrightable. The latter are patent eligible, but not copyrightable. Written descriptions of them may, however, may also be copyrightable.

Courts and commentators seem to have a hard time finding this line between principle and application.  I think this is because they often fail to focus on the object and primary intended output of any particular project. Instead, they are distracted by the fact that secondary or ancillary results may also be generated, as well as because they fail to clearly distinguish between declarative knowledge and procedural knowledge. Further, the fact that we have to capture our patent eligible procedural knowledge (methods) in written language (which begins to sound like declarative knowledge) to obtain patent protection forces us to both abstract the physical methods actually being performed and risk stating them as propositions and not methods. This in some ways is the heart of the problem in the Supreme Court’s Bilski decision, and until it is worked out we will continue to be vexed by questions of what is patent eligible subject matter.

 

About Sean O'Connor

Sean O’Connor is Professor of Law at George Mason University, Antonin Scalia Law School. He is also Founding Director of the Innovation Law Clinic and Executive Director of the Center for the Protection of Intellectual Property (CPIP). With a diverse background in music, technology, philosophy, history, business, and law, he specializes in legal issues and strategies for entrepreneurship and the commercialization of innovation in biotechnology, information technology, and new media/digital arts.
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