00:00We talk about how biotech has been caught in the crosshairs of U.S. China trade war.
00:03Is it giving biotech a bad name? Is it impacting investment appetite, for instance?
00:09So, sure. I prefer never to comment on politics.
00:14However, life is the fundamental human right, and now we see that even that right is being debated
00:23in terms of the biotechnology trade war.
00:27And it's no secret that some of those close ties that were keeping us together in communication
00:40between different countries are now under threat.
00:45And it's coming from the regulatory perspective.
00:48It's coming from the research perspective.
00:53And most importantly, it started propagating into the ideology.
00:57So we see that even the mindset that people are developing is very confrontational.
01:03And I am very, very afraid of that.
01:07That's why, for example, at InSilica, we've managed to compartmentalize certain critical technologies
01:12to avoid this kind of geopolitical tensions.
01:16I went to the Middle East.
01:18Our generative AI is done in Canada.
01:20I'm Canadian by citizenship.
01:21Pretty much diversified then, right?
01:24To minimize the risk.
01:26A lot of talk about China's AI innovation.
01:31Put that in perspective for us.
01:33How is it doing compared to the rest of the world?
01:36Well, there is no secret.
01:37China is exploding in innovation in every perspective, from every angle.
01:43You already see that the Chinese scientists are publishing the majority of really great papers
01:50and top journals.
01:52It's just sheer numbers and focus on education and academic excellence.
01:57You cannot really fight that because that's been done over many, many years as a strategy.
02:04Academic excellence and transparency, reproducibility is amazing here.
02:10And Chinese scientists now propagate around the world and come up with new ideas.
02:17So in the past, they were trying to do things marginally better.
02:22Now some concepts that are being invented here are truly breakthrough and revolutionary.
02:30It's starting to propagate into biotech, which gives me a lot of hope.
02:34Because in biotechnology, one thing to realize is that every year only about 50 drugs get approved.
02:42Maybe seven of them are innovative.
02:44At the end of the day, all of us are patients.
02:47All of us are going to lose function and die.
02:50And that terrifies me because every year, seven innovative drugs.
02:54Without the help of China, India, the rest of the world, we are likely to die sooner.
03:02So that's what we should be focusing on and not about who has more economic power.
03:07We need to strive towards global prosperity and global health.
03:12So Encyclico is not the only company tapping AI to develop drugs.
03:18The question really is, why isn't there already a commercially viable drugs developed by AI?
03:25So many pharmaceutical companies use AI kind of in a piecemeal manner at every stage of pharmaceutical R&D.
03:33So they might see some incremental improvements.
03:36In terms of the fully AI-generated novel target hypothesis, novel molecule, all the way to the clinic,
03:44it still takes you a lot of time.
03:46So AI allows you to significantly reduce time and cost to the clinic.
03:53But then you need to move with the speed of traffic and comply with every regulatory procedure in every country.
04:00Currently, if you use the traditional approach from zero to developmental candidate,
04:09one step before clinical trials, using traditional approach, it's four and a half years.
04:14We've demonstrated that using generative AI on over 22 developmental candidates,
04:21typically it takes us about 13 months.
04:23The shortest one was nine months, just as much it takes a human to produce a baby.
04:28So we cut significantly.
04:31And in terms of the cost savings, enormous savings.
04:34But once you get into clinical trials, you have to move with the speed of traffic.
04:39You cannot cut corners.
04:40And you shouldn't, because the safety of the patient is ultimate priority.
04:44And that's where additional nine to ten years of the development time is locked.
04:51Deep learning is very new.
04:52So ten years ago, we've seen the revolution generated by AI.
04:57Five years ago, we are going to see those drugs.
05:00It will take time.
05:01So far, everything failed.
05:02If you were to hazard a guess, when might we see that drug generated by AI quickly?
05:07I would be surprised if we don't see it within the next five to six years.
05:11I hope we're going to be the first ones.
05:13We have more than 40 programs internally, but you never know.
05:18Alex, you filed for the third time an IPO in Hong Kong.
05:22What's different this time?
05:23How confident are you it's going to happen?
05:25I'm not allowed to comment on the IPO or anything financial.
05:29I can tell you that now the company is in the best shape it has ever been.
05:37So if you think about, you know, an MMA fighter, we are at our peak.
05:42And we really hope that this will allow us to make more drugs, faster, cheaper,
05:49and transformative to the entire pharmaceutical industry.
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