This post is from a talk at the 2021 Link Ventures CEO summit.
Original talk:
Transcript:
The practice of medicine has always been an information problem. Clinicians seek to diagnose an ailment and to prescribe a cure based on an incomplete understanding of what’s happening in a patient’s body as it relates to an incomplete set of knowledge about diagnoses and treatments.
This aspect of medicine has remained the same for centuries even as our collective understanding of medicine has gone through three major phases.
- Until the 18th century, much of medicine was based on what my colleague Dr. Marc Herant likes to call empirical charlatanism. Illness arose when there was an imbalance in bodily fluids or humors and, therefore, treatment was centered on restoring that balance. Physicians used dubious approaches such as trephination, literally cutting a hole in the head, and bloodletting but they also figured out how to set broken bones and stumbled upon some effective treatments such as using acetyl salicylic acid extracted from tree bark, what we all know as aspirin.
- Then picking up steam in the 19th century was an increasing systematization of medical knowledge and training and advances in understanding physiology. We believed we could discover cures from first principles. While this led to many surgical and therapeutic innovations, over time people realized that what seemed to make sense a priori often did not work, and what did not seem to make sense from physiological principles sometimes did. Humans it turned out were just too complex for the reductionist biology of the time.
- So by the middle of the 20th century we saw a return to empiricism, but this time based on an edifice of statistics — the clinical trials and studies that define practice guidelines and treatment protocols today.
But even as these shifts, from empirical charlatanism to the reductionist view of early modern medicine and finally to today’s evidence based approach, might appear revolutionary to us now, they were just evolutions because the role of the physician remained essentially the same — to try to solve a mystery. A mystery. by definition, a conundrum without a definitive answer.
But today we stand at the cusp of a revolution in human biology that will change this paradigm by making the practice of medicine more like solving a puzzle. Unlike a mystery, a puzzle has a definitive answer as long as you can sort all the pieces of information.
We can now think of disease as the result of a defect in information within the human body. This could be a glitch in the way information is encoded in the genome, proteome, or other -ome. It could be a departure from a structural template such as happens in osteoarthritis. It may be a communication error in complex feedback systems as happens in autoimmune disease. Or some combination of these.
At any rate, all of these are informational defects, and, for an increasing number of diseases, we are starting to understand how the body uses information and what tools we need to fix this information when it accumulates errors.
For instance, we already use cell and gene therapies to cure some cancers and rare diseases by either eradicating corrupted information or correcting a genetic mutation. We have learned how to regenerate tissue to provide missing or faulty structural information. And we can tamp down the body’s maladaptive responses to say food allergens by using immunotherapy to retrain certain feedback mechanisms.
Imagine a future in which these examples are not the exception, but the rule. In this world, the problem is not of incomplete information but of too much information.
Way too much for a human to puzzle through. We will increasingly turn to AI to parse the nature of information defects and follow AI generated treatment algorithms.
This is a profound change in the role of the physician and will consequently place very different demands on the healthcare ecosystem: lifesciences, health insurance, and digital health.
How long it will take us to fully cross over into this future, a decade or a generation, will not just depend on the pace of scientific discovery and translation but also on how quickly society is prepared to enter this new world. I imagine that we’ll see some version of Amara’s law, which says “We tend to overestimate the effect of a technology in the short run, and underestimate the effect in the long run.”
Either way, you can play a key role in accelerating and even shaping this future by driving innovation that moves medicine from the realm of mystery to the domain of puzzles.