This is a fascinating piece about the promise of machine learning in advancing cancer treatment. In order to assess the kind of magnitude of information that exists in the cancer pathology space, I believe this is one of the most innovative, smart, and forward-looking initiatives one could do, as provocative or controversial as it might be. You bring up excellent points about the potential for patients to feel disenfranchised by this, however I would say that one of the reasons that patients often agree to participate in clinical trials, for example, is that their participation will benefit them (potentially) but also that it may benefit people in the future (their children, their children’s children, etc). I think this is a risky endeavor for all of the reasons you point out, but the promise is huge, and if the messaging to patients is correct, it has the potential to bring enormous benefit to cancer patients for years to come. Thank you for this insightful piece!!
By the way, you might also take note of this scandal at MSK that just happened recently, where one of their most senior leaders failed to disclose his kick-backs from pharma, further pointing toward the idea that MSK has an uphill battle to fight here: https://www.nytimes.com/2018/09/13/health/jose-baselga-cancer-memorial-sloan-kettering.html
I really enjoyed reading your piece about the promise and risks of bioprinting in the context of Organovo. You have hit on a topic of significant ethical debate in the medical world (up there with George Church’s genetics and stem cell research at Harvard, among other issues). These types of concepts — generating human tissue de novo — tend to be quite polarizing, as you’ve noted in your question at the end. One company that has also grappled with this question is called FluidForm, started by HBS grads, and you might consider looking at how they have dealt with some of these issues, though they are at an earlier stage compared to Organovo. My concern, as was yours, is the question about where this type of advance will lead us. After we can recreate human organs for transplant, what is next? Surely something is next. And I’m not sure I like that something.
Thanks for sharing this excellent commentary!
I really enjoyed reading your piece about Stryker’s evolution over the past two decades in the additive manufacturing space. You point out some areas of major opportunity for the company, as well as possible limitations on their growth if they do not position themselves correctly with respect to physicians. With your suggested scenario of partnering with hospitals, I would wonder how that IP agreement would look (think MGH Enbrel case) and how to truly be partners with clinicians when the clinicians won’t be fooled by the fact that Stryker is associating themselves in part to access the clinicians’ own ideas/IP.
I really enjoyed reading your insightful piece about TKR and additive manufacturing. As you have clearly demonstrated in your evidence, this is an area of great need (with 1M TKRs performed this year in the US alone). Personalized 3D printed joints, I believe, will fundamentally change patient outcomes and satisfaction. I wonder if you know how many of those million TKRs are repeat TKRs? Despite this being quite a routine procedure, my guess is that there is a not insignificant number of repeat TKRs every year, due to poorly fitting replacements, infections, etc. I think this would offer further evidence toward a need for personalized replacements. I also would wonder what the price point is, and how this company is thinking about using this model for additive manufacturing in rural or underserved settings where you could print a joint in the middle of Nebraska, for example, where you might not have easy access to the best supply chain from Stryker, etc. Thanks for an interesting commentary!
This is a fascinating topic and a compelling argument for the use of AI to mitigate the infectiousness of “fake news”. I believe you hit the risks spot-on in detailing how inherent in this entire process is the assumption that the AI truly knows what is fake, and what is real. Unfortunately in our current world, the line between the two seems increasingly smudged, and you are correct to point out that it is difficult to teach computers to do something that we humans cannot define clearly ourselves. I appreciate your contextualization of this company in the broader AI context and hope that this type of initiative will give us hope for the future!!
I really enjoyed this piece– you describe an innovative model of affording credit in economies where constraints are broad and deep. I appreciate the lens you took on big data and machine learning, and believe you very eloquently delineated some of the major risks associated with creating this platform (e.g. hackers) as well as possible opportunities for growth (e.g. insurance, savings). This is a fascinating area of growth, it seems, and I wonder what the competitors are doing to mitigate these risks, or embrace these opportunities you site. In the same way that pharmaceutical and medical device companies come under scrutiny when running clinical trials in low-income countries due to the searing history of predatory behavior, I would also question whether this product is too invasive, and whether the regulatory frameworks are in place to prevent predatory behavior and exploitation. Thanks for a great read!