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Speaker 2: Right now you're listening to a Chasi's podcast, just getting
Speaker 2: back to manufacturing these pharmaceuticals. Has AI had much of
Speaker 2: a place here in terms of speeding things.
Speaker 3: Up, So this AI kind of in farmer companies and
Speaker 3: in drug discovery. It's been a topic that investors are
Speaker 3: kind of increasingly focused on and increasingly excited about. And
Speaker 3: one of the key kind of themes or takeaways I
Speaker 3: would say that I really noticed when I was in
Speaker 3: the US is just how excited companies are about the
Speaker 3: use of AI and drug discovery. Because we've already talked
Speaker 3: about how time consuming and expensive it is to develop
Speaker 3: new medicine, and what we've seen is that the developments
Speaker 3: in AI mean that you can develop new molecules around
Speaker 3: ten times as fast, or so you can design new
Speaker 3: molecules around ten times as fast. You can run simulations
Speaker 3: on those molecules around one hundred times as fast. And
Speaker 3: then there's this new concept, which I think is pretty interesting.
Speaker 3: You've heard of the concept of a self driving car.
Speaker 3: There's this new concept of a self driving lab. And
Speaker 3: so what this means is that you have AI and
Speaker 3: then you have robotics, and so you use AI and
Speaker 3: robotics together and they drive the cycle of kind of prediction,
Speaker 3: experimentation and analysis, which means that you can iteratively identify
Speaker 3: new compounds which you then run experiments on, which then
Speaker 3: mean that the whole process is much faster and then
Speaker 3: importantly more cost effective for companies.
Speaker 2: Gosh, So do we have any idea how much that
Speaker 2: would speed things up? We talked about ten years before
Speaker 2: being the time that it can take, I think for exclusivity,
Speaker 2: but I think you know, when you've got a meticine
Speaker 2: in the wings, that can take even longer, can't it.
Speaker 3: Yeah, And I think it's probably too early yet to
Speaker 3: put an actual number on how much it could speed
Speaker 3: things up. But I think what we're seeing is more
Speaker 3: and more companies are talking about it, more and more
Speaker 3: companies are using it in their drug discovery process. So
Speaker 3: I think over time we'll be able to get a
Speaker 3: better sense of how much time it actually is taking
Speaker 3: off the drug discovery process. But to the extent that
Speaker 3: it means we can develop medicines that are cheaper, I
Speaker 3: feel like that could only be a good thing given
Speaker 3: the high costs of healthcare that we're seeing around the
Speaker 3: world now.
Speaker 2: Just thinking about investors looking to invest in the sector,
Speaker 2: I mean, there are those direct stocks, they are probably
Speaker 2: quite expensive at the moment for some people. But also
Speaker 2: what about ETFs. I know on cheeseys, for instance, we've
Speaker 2: got about five or at least there's more actually pharmaceutical
Speaker 2: ETFs that people can look to. They are mainly in
Speaker 2: the US. But also I did see that there was
Speaker 2: a couple of applications for more themed weight loss ETFs
Speaker 2: by I think Amplify and round til investments. We're two
Speaker 2: though I don't think they've actually come to fruition yet.
Speaker 3: So I guess when you're thinking about healthcare, healthcare itself
Speaker 3: is super broad, and then within that there's all different
Speaker 3: kinds of companies, so hospitals, medical device companies, companies that
Speaker 3: sell chemicals that are used in farmer companies that sell
Speaker 3: tools that are used in farmer, so all of that
Speaker 3: kind of sets in the broader healthcare space. And I
Speaker 3: think if you're thinking about getting a broad kind of
Speaker 3: ETF exposure, maybe one way to get a sense of
Speaker 3: what could be better is looking back at what's happened
Speaker 3: over time. And if you look back over a significant
Speaker 3: period of time, say twenty years, the S and P
Speaker 3: five hundred Index and the S and P Healthcare Index
Speaker 3: have actually interestingly performed basically neck on neck, so they
Speaker 3: both generated around a ten percent return per year over
Speaker 3: a twenty year time horizon. If you look at farmer itself,
Speaker 3: that generated around half a percent lower return, so around
Speaker 3: nine and a half percent over that twenty year period
Speaker 3: of time. But if you had managed to pick farmer
Speaker 3: winner Novo or farmer winner Eli Lilly over that period
Speaker 3: of time, you would have generated I think from memory
Speaker 3: it's around a sixteen percent return per ANIM and then
Speaker 3: a twenty five percent return per ANIM. Picking a winner
Speaker 3: can be great. But then if you're looking at a
Speaker 3: diversified exposure, as she would suggest that rather than looking
Speaker 3: for a narrow farmer exposure, a broader health care exposure
Speaker 3: would be better. And then I think especially worth keeping
Speaker 3: in mind. With a diversified easier for Farmer, You're likely
Speaker 3: to have a higher exposure to the largest companies and
Speaker 3: they may have a higher proportion of medicines that are
Speaker 3: coming up to that loss of exclusivity and revenue and
Speaker 3: revenue dropping off. So that's a really important thing to
Speaker 3: keep in mind with Farmer itself, is what is that
Speaker 3: loss of exclusivity burden and how does that sit across
Speaker 3: the companies that are in that ETA.
Speaker 2: Investing involves risk you might lose the money you start with.
Speaker 2: We recommend talking to a licensed financial advisor. We also
Speaker 2: recommend reading product disclosure documents before deciding to invest.