I think you may have misunderstood me. By “nanosurgery” I meant not solely Drexlerian medical nanobots (though I wasn’t ruling them out). Any drug whose design deliberately and intentionally causes specific, deliberate, and intentional changes to cell-level and molecular-level components of the human body, deliberately and consciously designed with a deep knowledge of the protein structures and cellular metabolic pathways involved, qualifies as nanosurgery, by my definition.
I contrast nanosurgery: deliberate, intentional action controlling the activity or structure of cellular-components—with medicine: the application of small molecules to the human metabolism to create a global, holistic effect with incomplete or nonexistent knowledge of the specific functional mechanisms. Surgery’s salient characteristic is that it is intentional and deliberate manipulation to repair functionality. Medicine’s salient characteristic is that it is a mapping of cause [primarily drug administration] to effect [changes in reported symptoms], with significantly reduced emphasis on the functional chain of causation between the two. As you said above, medicine is defined as “cheap tricks”. That’s what it does. That’s what it’s always been. When you’re doing something intentional to a specific piece of a human to modify or repair it’s functionality, that’s surgery, whether it’s done at the cellular or molecular level (nanosurgery) or at the macroscopic level (conventional surgery).
Prior to about 20 years ago, the vast majority of drugs were developed as medicine. Nowadays, more and more attempts at drug design are at least partially attempts to engineer tools for nanosurgery, per this definition. This is a good thing, and I see the trend continuing. If Drexlerian medical nanobots are possible at all, they would represent the logical endpoint of this trend, but I agree they represent an incredible engineering challenge and they may or may not end up being an economical technology for fixing broken human bodies.
Again, this is one of those approaches that sounds good at a conference, but when you actually sit there and think about it rationally, it shows it’s flaws.
Even if you know exactly what pathway to hit, a small molecule by definition will get everywhere and gum up the works for many, many other systems in the body. It’s almost impossible not to. Sure, there’s a tiny solution space of small molecules that are safe enough to use despite this, but even then you’re going to have side effects and you still have not fixed anything. The reason the cells are giving up and failing as a person ages is that their genetic code has reached a stage that calls for this. We’re still teasing out the exact regulatory mechanisms, but the evidence for this is overwhelming.
No small molecule can fix this problem. Say one of the side effects of this end of life regulatory status is that some cells have intracellular calcium levels that are too high, and another set has them too low. Tell me a small molecule exists out of the billions of possibilities that can fix this.
DNA patching and code update is something that would basically require Drexelerian nanorobotics, subject to the issues above.
Methods to “rollback” cells to their previous developmental states, then re-differentiate them to functional components for a laboratory grown replacement organ actually fix this problem.
For some reason, most of the resources (funding and people) is not pouring into rushing Drexelerian nanorobotics or replacement organs to the prototype stage.
Great analysis. A lot of people think that science follows an inevitable and predetermined progression of truths - a “tech tree” determined by the cosmos—but that’s clearly not the case, especially in the field of medicine.
Sometimes I rant about how computer vision’s fatal flaw is that it is intellectually descended from Computer Science, and so the field looks for results conceptually similar to the great achievements of CS—fast algorithms, proofs of convergence, complexity bounds, fully general frameworks, etc. But what people should really be doing is studying images—heading out into the world and documenting the visual structures and patterns they observe.
I think you may have misunderstood me. By “nanosurgery” I meant not solely Drexlerian medical nanobots (though I wasn’t ruling them out). Any drug whose design deliberately and intentionally causes specific, deliberate, and intentional changes to cell-level and molecular-level components of the human body, deliberately and consciously designed with a deep knowledge of the protein structures and cellular metabolic pathways involved, qualifies as nanosurgery, by my definition.
I contrast nanosurgery: deliberate, intentional action controlling the activity or structure of cellular-components—with medicine: the application of small molecules to the human metabolism to create a global, holistic effect with incomplete or nonexistent knowledge of the specific functional mechanisms. Surgery’s salient characteristic is that it is intentional and deliberate manipulation to repair functionality. Medicine’s salient characteristic is that it is a mapping of cause [primarily drug administration] to effect [changes in reported symptoms], with significantly reduced emphasis on the functional chain of causation between the two. As you said above, medicine is defined as “cheap tricks”. That’s what it does. That’s what it’s always been. When you’re doing something intentional to a specific piece of a human to modify or repair it’s functionality, that’s surgery, whether it’s done at the cellular or molecular level (nanosurgery) or at the macroscopic level (conventional surgery).
Prior to about 20 years ago, the vast majority of drugs were developed as medicine. Nowadays, more and more attempts at drug design are at least partially attempts to engineer tools for nanosurgery, per this definition. This is a good thing, and I see the trend continuing. If Drexlerian medical nanobots are possible at all, they would represent the logical endpoint of this trend, but I agree they represent an incredible engineering challenge and they may or may not end up being an economical technology for fixing broken human bodies.
Again, this is one of those approaches that sounds good at a conference, but when you actually sit there and think about it rationally, it shows it’s flaws.
Even if you know exactly what pathway to hit, a small molecule by definition will get everywhere and gum up the works for many, many other systems in the body. It’s almost impossible not to. Sure, there’s a tiny solution space of small molecules that are safe enough to use despite this, but even then you’re going to have side effects and you still have not fixed anything. The reason the cells are giving up and failing as a person ages is that their genetic code has reached a stage that calls for this. We’re still teasing out the exact regulatory mechanisms, but the evidence for this is overwhelming.
No small molecule can fix this problem. Say one of the side effects of this end of life regulatory status is that some cells have intracellular calcium levels that are too high, and another set has them too low. Tell me a small molecule exists out of the billions of possibilities that can fix this.
DNA patching and code update is something that would basically require Drexelerian nanorobotics, subject to the issues above.
Methods to “rollback” cells to their previous developmental states, then re-differentiate them to functional components for a laboratory grown replacement organ actually fix this problem.
For some reason, most of the resources (funding and people) is not pouring into rushing Drexelerian nanorobotics or replacement organs to the prototype stage.
Great analysis. A lot of people think that science follows an inevitable and predetermined progression of truths - a “tech tree” determined by the cosmos—but that’s clearly not the case, especially in the field of medicine.
Sometimes I rant about how computer vision’s fatal flaw is that it is intellectually descended from Computer Science, and so the field looks for results conceptually similar to the great achievements of CS—fast algorithms, proofs of convergence, complexity bounds, fully general frameworks, etc. But what people should really be doing is studying images—heading out into the world and documenting the visual structures and patterns they observe.