The response to this opinion on social media has been a festival of reflexive praise. However, the article is intellectually unserious. It takes a small secondary issue and inflates it into the central obstacle to curing cancer and improving human health, while ignoring the two fundamental limitations dominating modern medicine: 1.) We still do not understand human biology well enough to design drugs that reliably work. 2.) We have a health-care system that cannot afford the drugs that occasionally do. Faster Phase I trials will mostly allow us to discover faster that yet another supposedly promising cure has failed. These trials primarily determine safety, activity, and dosage. They do not establish that a drug improves health. Likely much more than 90 percent of oncology drugs entering Phase I never become approved drugs. Even candidates that get to Phase III, the final major testing stage, frequently fail because they do not work. That is not a paperwork problem. It reflects our primitive understanding of health and disease and our inability to predict how interventions will behave in the human body. The most important role for AI is not generating more tiny, uncontrolled Phase I datasets. It is building better models of human biology that predict pharmacology, toxicity and efficacy before patients are exposed. The goal should be to make drug development less dependent on enormously expensive, high-failure-rate trial and error, which is what clinical trials are. The second limitation is economic. We already have cancer and other drugs costing more than $100K per year, sometimes approaching $500K, while producing modest benefits for relatively small numbers of patients. Many patients would require multiple such drugs over their lifetimes. There is no plausible way to scale that cost across the population. Producing more experimental drugs without solving the scientific and economic problems is not health-care abundance. It is an abundance of low-probability experiments followed by an abundance of drugs that patients and society cannot afford. By all means, eliminate pointless bureaucracy. Academic medical centers charge too much for trials, pile on overhead and spend months negotiating budgets while creating far too many administrative obstacles. I have personally had clinical researchers approach me asking for roughly $800K to run a Phase I trial based on my research. The FDA was not stopping them. They were looking for someone to finance a low-probability experiment that would generate research money, pad their CVs and help them win a promotion in a system that rewards scientists for how much money they bring in. Faster Phase I trials do not solve the central problems. Our science remains inadequate and our health-care system remains broken.