Thanks for sharing this interesting article on machine learning in an important industry. It sounds like BenevolentAI offers a novel technology that could dramatically speed up the drug discovery process in a cost-effective manner. I wonder if they would benefit more by leveraging their technical expertise to partner with large pharmaceutical companies who have the know-how and infrastructure to turn a computer-generated drug candidate into a reality. I also wonder if they are using their machine learning technology to develop completely novel drug candidates or to repurpose previously used medications to treat new conditions, which has recently become a hot topic in medicine. Ideally, they would be able to do both. My concern, however, is that they are limiting the possibilities for drug candidates if their predictions are based only on clinical trials data and academic papers, both of which would mostly include drugs that have produced some finding worth publishing. They would have to incorporate pharmacologic and biochemical principles and constraints into their algorithm for it to be most effective.
Thanks for sharing your interesting take on an increasingly popular topic. While I applaud 23andMe for being a first-mover in this space, I share many of the same concerns that you do. I’ve actually used their kit for both ancestry and health. The ancestry results are much easier to believe and likely more accurate than the health data provided. Even as someone who has learned about genetics in medical school and has a developing understanding of medicine more generally, I find it very challenging to know what to do with the health data provided. I can only imagine how much more difficult it would be for someone without a medical background. The entire field of genetics is still very specialized with a small number of experts who really understand how to use this rich genomic data and doctors in general aren’t adequately trained to offer evidence-based advice on these subjects. Because of these issues, 23andMe has an ethical obligation to clearly communicate the limitations of its data, which could potentially undermine its business strategy. Finally, the accuracy of 23andMe’s health data will continue to be a serious question in my mind, as will any studies supported by pharmaceutical companies like Pfizer who stand to gain from identifying more people at-risk or suffering from conditions like depression (Pfizer produces Zoloft, a common depression treatment). Nonetheless, I see 23andMe as continuing to be an important player in this space. My hope is that they do so in a responsible manner.
Thanks for sharing your very interesting perspective on a very important topic. In an ideal world, open innovation in research would be incredible! But, as someone who has spent the past four years at highly academic, research-driven institutions, I have firsthand experience with the paradigm you highlighted in your post. Unfortunately, I don’t see this trend changing anytime soon. Researchers’ future work and salaries (to some degree) depend on the journals they publish in. They are highly incentivized to guard their findings until they are published and because of this, the term “scooping” has become common to describe what happens when one researcher beats another to publish similar work. Limited funding in today’s research environment only exacerbates the issue and concentrates the most cutting-edge research and collaborations in the top academic institutions (the rich get richer). Your question of who should benefit from innovations that build on similar work is not a trivial one. A specific recent example of the controversy that arises in these situations is the battle for credit and patents over CRISPR-Cas9 technology, which revolutionized DNA editing and is driving therapeutic development efforts of numerous biotechnology companies . The short answer is, it’s complicated and often has to be settled legally.
This was a very interesting article about a product that I had previously encountered, but not realized was an application of 3D printing. To address some of the previous comments, Invisalign can result in an optimal treatment outcome (i.e. equivalent to that of traditional braces), but it really depends on the orthodontic problem being fixed. In other words, it is not the ideal treatment for everyone, but can offer a more aesthetically pleasing solution for someone who wishes to avoid metal braces. Traditionally, that decision ultimately has rested in the hands of orthodontists when they offer various treatment options. To maintain their competitive advantage on startups like SmileDirectClub that are seeking to offer aligners at even lower costs, Align Technology should leverage the patient data that they have gathered to date to generate outcomes data. If they can prove that their technology is comparable to traditional braces in a majority of cases, they will remain differentiated from the startup aligner companies that are currently more limited in the cases they can treat.
Thanks for sharing such an exciting topic! I had no idea that companies like Contour Crafting existed and it seems like there is tremendous potential for them to make a real impact in developing countries. Exploring partnerships with governments might allow them to scale the technology faster and more adeptly in unfamiliar settings, but there are clearly some challenges they will need to work through related to cultural and language barriers. Contour Crafting should focus most of its resources on addressing the issue of homelessness around the world and a very small portion of efforts on more aspirational projects like building homes in space. One final concern that I have relates to the quality of a 3D-printed home. To maximize their impact, Contour Crafting should validate that the quality of their 3D-printed homes is comparable to traditionally constructed homes.