Novartis

“We've had to spend most of the time just cleaning the data sets before you can even run the algorithm. That's just taken us years just to clean the data sets. And I think people underestimate how little clean data there is out there and how hard it is”

“It used to be, we think about reimbursement as we got to launch. Now we're thinking about it really early in development.”

“You know, we had actually an aging program, a small aging program for some time where we were trying to work on things like sarcopenia, which is muscle wasting and similar, similar kinds of conditions. It turns out to be very, very difficult to, because again,…”

“I would say roughly 80%.”

“The other area, interestingly, in the financial area as well, we find that AI does a great job predicting our free cashflow, predicting a lot of our sales for key products, and it does better than our internal people because it doesn't have the biases and the …”

“I mean, one example we launched in the U S a digital medicine. I mean, with paratherapeutics, this is the first digital app with an FDA label that's being used for opioid addiction and other psychiatric illnesses. And it is literally an app That has run clinic…”

“I mean, I think the holy grail of kind of having unstructured machine learning Go into big clinical data lakes and then suddenly find new insights. We've not been able to crack mostly because the data to link it up.”

“So we've built an operational command center. Take us, as I said, two and a half years to build it. We call it sense. And what it enables us to do a team sitting centrally in our headquarters to look at all of our clinical trials in the world. And AI is predic…”

“Because if you take another program on, that means that there's another program you have to stop. I mean, it's a zero sum game for us.”

“We transacted in 2018 around fifty billion dollars of deals to really change the shape of the company.”

“We've done fifteen billion dollars of acquisitions just last year in the space, not, not including all of our internal work in each of these areas.”

“We have 17,000 R&D people and spend nine, nine billion dollars plus a year in, in R&D.”

“Well, I have to first say, I completely agree about the hype cycle here. I mean, as we've gotten quite scaled and working on digital health and data science, we've learned that there's a lot of talk and very little in terms of actual delivery of impact.”

“We internally have just set a very clear bar now for ourselves, primarily because we live in a world now where nobody wants a me too medicine or a medicine that's just incrementally better. We say to ourselves, it has to replace the standard of care.”

“We've actually been fortunate at our company. We average in that same metric about eight to 10%.”

“He made two acquisitions in the radio label target oncology space. So with AAA and Endocyte being the most recent acquisition they were able to secure that supply chain for that specific radio isotope.”

“So the lead asset AXVS- one-on-one it, you know, certainly is going to be probably best in class for SMA, but it also gave Novartis an AAV nine vector platform that it could use to deliver other gene therapies.”

“China, India, and the Islamic empires were a lot like the Merck, Pfizer, and Novartis of today. They were global, everywhere, dominant. They're phenomenal at franchises. So in India, you've had the Taj Mahal. You know, in China, they built the Great Wall and j…”

“You know, in the case of treating a baby that had, you know, something like somatic muscular atrophy that would have otherwise died, a one and done gene therapy from Novartis, this is a therapy that's worth about, it's cost about 2.1 million dollars, effective…”