Biotech, Life Sciences, Food & Drug News from NLR
Biotech, Life Sciences, Food & Drug News from National Law Review
The Wrong-Headedness of Hindsight Standards — Michelle Yeary | Drug & Device Law Blog
Dechert LLP attorney Michelle Yeary cautions against applying perfect hindsight to drug liability. "We all know hindsight is 20/20. And, it’s easy. There are dozens of television and radio programs that thrive on Monday morning quarterbacking. There’s no risk in saying the coach should have called for a pass when you already know the run didn’t work. It’s also dangerous because it’s easy. People are often too quick to point out that you should have taken path B after everyone learns path A is full of potholes. Pointing it out is one thing, holding you liable for it is another." Yeary takes a look at what happened in Holley v. Gilead Science, Inc., 2019 WL 2077845 (N.D. Cal. May 10, 2019). The case involves two of the main active ingredients in AIDS drugs: TDF and TAF. The plaintiff alleges that the defendant should be responsible for allegedly knowingly using TDF over TAF (allegedly a safer alternative). TDF was FDA approved first and TAF second. Unfortunately, Yeary wrote, hindsight "can be used to demand perfection," allowing plaintiffs to "proceed on what is essentially a stop-selling theory," that first-generation drugs should not be submitted to the FDA because, in hindsight, "later approved treatments were safer." That's what happened in Holley, she said. Read the complete post by Michelle Yeary on the Drug and Device [...]
Artificial Intelligence in the Drug and Device Industries
Are Data Divers and Miners Going to Lead Innovation?  The big tech companies are into it. Apple, IBM and Google. Roche is into it. Medtronic, as well. Artificial intelligence has been a big part of innovation in the healthcare space for several years, and its impact is only going to get bigger. "Artificial intelligence-based healthcare technologies have contributed to improved drug discoveries, tumor identification, diagnosis, risk assessments, electronic health records (EHR), and mental health tools, among others," writes Blank Rome attorney Brian Higgins in his Artificial Intelligence and the Law Blog (it's excellent, by the way). [1] Daniel Faggella of TechEmergence.com writes that machine learning healthcare applications are getting a lot of attention in the press and from the investment community. He adds to the list of machine learning's impact things like treatment queries and suggestions, and even robotic surgery. But optimism for AI's application to drug discovery seems greater than that inspired by other healthcare sectors. One reason for that, Faggella writes, is that compared to other segments where various laws and stakeholder incentives may not align, "drug discovery stands out as a relatively straightforward economic value for machine learning healthcare application creators." He adds that this application also involves "one relatively clear customer who happens to generally have deep pockets: drug companies." [2] Also writing for TechEmergence.com, Kumba Sennaa says [...]