WEBVTT 00:00:00.000 --> 00:00:02.819 Welcome to the Deep Dive. Today, we're tackling 00:00:02.819 --> 00:00:05.240 something really central to modern medicine and 00:00:05.240 --> 00:00:07.919 tech. It's this whole question of how cloud computing 00:00:07.919 --> 00:00:11.099 is changing things for the pharmaceutical industry, 00:00:11.580 --> 00:00:14.439 specifically how they handle data, and crucially, 00:00:14.779 --> 00:00:17.339 what kind of safeguards absolutely need to be 00:00:17.339 --> 00:00:20.179 locked down. Now, you, our listener, you've sent 00:00:20.179 --> 00:00:22.280 over some really fascinating materials touching 00:00:22.280 --> 00:00:24.539 on, well, all sorts of angles in drug development. 00:00:25.579 --> 00:00:27.899 So our mission for this Deep Dive is essentially 00:00:27.899 --> 00:00:30.600 to unpack how the cloud cloud is making it possible 00:00:30.600 --> 00:00:34.119 to store and analyze these just enormous data 00:00:34.119 --> 00:00:36.920 sets that farmer research generates. But maybe 00:00:36.920 --> 00:00:38.820 even more importantly, we need to really focus 00:00:38.820 --> 00:00:42.039 on why things like cybersecurity, good data management, 00:00:42.420 --> 00:00:45.500 and keeping regulators happy are so non -negotiable 00:00:45.500 --> 00:00:47.859 in this space. It's a really pivotal moment, 00:00:47.859 --> 00:00:50.340 I think, the amount of data and how complex it 00:00:50.340 --> 00:00:53.039 is. It's exploding. You see it across the board, 00:00:53.079 --> 00:00:55.640 drug discovery, clinical trials, manufacturing, 00:00:56.060 --> 00:00:58.299 even checking how drugs perform after their launch. 00:00:58.479 --> 00:01:00.659 your sources definitely paint that picture. Yeah, 00:01:00.759 --> 00:01:03.640 they do. And it just demands new kinds of solutions. 00:01:04.260 --> 00:01:06.879 So it's less about if pharma will use the cloud 00:01:06.879 --> 00:01:09.519 and more about how they could do it safely and 00:01:09.519 --> 00:01:12.299 effectively. Okay, let's set the stage a bit. 00:01:12.540 --> 00:01:15.340 This data challenge, it's almost hard to grasp 00:01:15.340 --> 00:01:18.060 the scale, isn't it? Your materials on, say, 00:01:18.239 --> 00:01:20.500 preclinical work or the clinical trial phases 00:01:20.500 --> 00:01:22.500 and even that post -market surveillance stuff. 00:01:23.340 --> 00:01:26.260 It all points to this data tidal wave. Absolutely. 00:01:26.480 --> 00:01:29.019 You've got everything from the really detailed 00:01:29.019 --> 00:01:32.500 results from early lab studies to just mountains 00:01:32.500 --> 00:01:35.420 of data coming out of human trials. That regulatory 00:01:35.420 --> 00:01:37.719 and pharmacovigilance transcript really highlights 00:01:37.719 --> 00:01:40.379 that. And then there's manufacturing data, process 00:01:40.379 --> 00:01:43.500 details, plus that constant stream of info coming 00:01:43.500 --> 00:01:45.700 back once a drug is actually being used by patients. 00:01:45.700 --> 00:01:47.459 And we have to remember what kind of data this 00:01:47.459 --> 00:01:50.019 is, yeah. Critically important. You're talking 00:01:50.019 --> 00:01:53.519 about super valuable proprietary research secrets. 00:01:53.700 --> 00:01:56.019 The company's future, basically. Exactly. And 00:01:56.019 --> 00:01:58.680 then there's the patient data from trials, often 00:01:58.680 --> 00:02:01.519 incredibly detailed personal identifiable information, 00:02:01.879 --> 00:02:05.000 plus manufacturing processes, adverse event reports. 00:02:05.359 --> 00:02:07.900 Each piece is incredibly sensitive. If it gets 00:02:07.900 --> 00:02:11.780 compromised, well, the fallout is huge. Right. 00:02:12.259 --> 00:02:17.340 So handling this flood of sensitive stuff, it 00:02:17.340 --> 00:02:19.699 needs more than just like servers in the basement. 00:02:20.139 --> 00:02:22.639 Definitely. The old on -premise systems often 00:02:22.639 --> 00:02:25.039 struggle, and that's really where cloud computing 00:02:25.039 --> 00:02:28.080 starts to look attractive. So for anyone maybe 00:02:28.080 --> 00:02:30.439 not fully up to speed when we say cloud computing 00:02:30.439 --> 00:02:33.400 here, what exactly are we talking about? We're 00:02:33.400 --> 00:02:35.460 basically talking about using a network of remote 00:02:35.460 --> 00:02:38.340 servers, huge data centers run by companies like 00:02:38.340 --> 00:02:40.680 Amazon, Google, Microsoft, accessed over the 00:02:40.680 --> 00:02:42.900 internet. Instead of buying and managing all 00:02:42.900 --> 00:02:45.080 your own hardware locally, you're essentially 00:02:45.080 --> 00:02:48.370 renting computing power, storage. software over 00:02:48.370 --> 00:02:50.870 the internet. It's a shift to a distributed web 00:02:50.870 --> 00:02:53.229 -based model. Kind of like outsourcing your IT 00:02:53.229 --> 00:02:54.969 infrastructure in a way. That's a good way to 00:02:54.969 --> 00:02:57.909 think about it, yeah. For pharma, the big draws 00:02:57.909 --> 00:03:00.310 are things like better accessibility researchers 00:03:00.310 --> 00:03:03.030 getting data wherever they are, much greater 00:03:03.030 --> 00:03:05.090 scalability, being able to handle those big data 00:03:05.090 --> 00:03:08.669 peaks and valleys, and often it can be more cost 00:03:08.669 --> 00:03:10.610 effective than building and running massive data 00:03:10.610 --> 00:03:12.729 centers yourself. Okay, let's dig into those 00:03:12.729 --> 00:03:16.949 benefits. Scalability and flexibility. That sounds 00:03:16.949 --> 00:03:18.949 like it would really map onto the drug development 00:03:18.949 --> 00:03:21.530 lifecycle. Oh, absolutely. Think about it. A 00:03:21.530 --> 00:03:25.150 small biotech doing early research has totally 00:03:25.150 --> 00:03:27.990 different data needs than a big pharma company 00:03:27.990 --> 00:03:31.289 running, say, global phase three trials involving 00:03:31.289 --> 00:03:33.669 thousands of patients. Right. Massive difference 00:03:33.669 --> 00:03:36.710 in scale. Exactly. And cloud platforms offer 00:03:36.710 --> 00:03:40.560 that. that elasticity. You can crank up your 00:03:40.560 --> 00:03:42.840 storage and computing power when you're generating 00:03:42.840 --> 00:03:46.280 tons of data, like during a big trial, and then 00:03:46.280 --> 00:03:47.699 scale it back down afterwards. You're mostly 00:03:47.699 --> 00:03:50.199 paying for what you actually use. That avoids 00:03:50.199 --> 00:03:52.680 needing huge upfront investments in hardware 00:03:52.680 --> 00:03:55.139 that might sit idle half the time. Yeah, that 00:03:55.139 --> 00:03:57.080 makes a lot of financial and operational sense. 00:03:57.360 --> 00:03:59.479 And what about the accessibility and collaboration 00:03:59.479 --> 00:04:02.000 piece? Farmer research is so global now. That's 00:04:02.000 --> 00:04:04.340 another huge one. Cloud can really break down 00:04:04.340 --> 00:04:06.879 those geographical silos. Teams in different 00:04:06.879 --> 00:04:09.039 countries different institutions can potentially 00:04:09.039 --> 00:04:11.280 access and work on the same data sets almost 00:04:11.280 --> 00:04:13.580 in real time. So speeding things up potentially? 00:04:14.020 --> 00:04:17.680 Potentially, yes. Imagine researchers in, say, 00:04:17.899 --> 00:04:21.019 Europe and the US analyzing clinical trial data 00:04:21.019 --> 00:04:23.470 together. without cumbersome data transfers. 00:04:23.970 --> 00:04:26.470 It could definitely accelerate analysis and maybe 00:04:26.470 --> 00:04:28.730 even shorten development timelines. Okay, and 00:04:28.730 --> 00:04:32.689 the advanced analytics. Your sources on AI and 00:04:32.689 --> 00:04:35.230 drug development really point towards needing 00:04:35.230 --> 00:04:37.569 serious computing muscle. Is that easier in the 00:04:37.569 --> 00:04:40.399 cloud? Yes, that's a major advantage. The big 00:04:40.399 --> 00:04:43.000 cloud providers offer this whole ecosystem of 00:04:43.000 --> 00:04:45.120 sophisticated tools, machine learning platforms, 00:04:45.339 --> 00:04:48.680 AI services, tools for handling massive big data 00:04:48.680 --> 00:04:51.540 sets. So linking back to those AI source materials. 00:04:51.579 --> 00:04:54.220 Exactly. The kind of complex algorithms and frankly 00:04:54.220 --> 00:04:56.040 the enormous data sets you need for effective 00:04:56.040 --> 00:04:58.120 machine learning and drug discovery. Trying to 00:04:58.120 --> 00:05:00.560 do that efficiently on local machines would be, 00:05:00.740 --> 00:05:02.819 well... difficult, if not impossible, for many. 00:05:03.199 --> 00:05:05.879 The cloud provides that scalable power and storage, 00:05:06.160 --> 00:05:08.319 so it directly enables the kind of advanced research 00:05:08.319 --> 00:05:10.379 you were looking at. Researchers can tap into 00:05:10.379 --> 00:05:12.519 these tools to find subtle patterns, generate 00:05:12.519 --> 00:05:15.019 insights, maybe find new drug targets faster. 00:05:15.319 --> 00:05:18.899 OK, so the upside seems pretty compelling. Scalability, 00:05:19.360 --> 00:05:24.279 collaboration, advanced tools. But this is the 00:05:24.279 --> 00:05:26.759 big but, isn't it? Cybersecurity, putting all 00:05:26.759 --> 00:05:29.480 this incredibly sensitive pharma data out there? 00:05:29.819 --> 00:05:34.079 In the cloud? That feels risky. It absolutely 00:05:34.079 --> 00:05:36.839 introduces risks. Significant ones. It's one 00:05:36.839 --> 00:05:39.639 thing to store, I don't know, holiday snaps. 00:05:39.980 --> 00:05:42.160 It's entirely different when you're talking about 00:05:42.160 --> 00:05:44.180 patient health records, clinical trial results, 00:05:44.740 --> 00:05:46.500 proprietary chemical structures. What happens 00:05:46.500 --> 00:05:48.939 if things go wrong? A data breach in this context 00:05:48.939 --> 00:05:51.540 sounds catastrophic. It can be. You're looking 00:05:51.540 --> 00:05:53.959 at potentially losing priceless intellectual 00:05:53.959 --> 00:05:56.899 property to competitors, facing massive fines 00:05:56.899 --> 00:05:59.639 from regulators, devastating damage to the company's 00:05:59.639 --> 00:06:02.000 reputation, and worst of all, potentially exposing 00:06:02.000 --> 00:06:04.800 sensitive patient information. That erodes public 00:06:04.800 --> 00:06:06.420 trust, not just in the company, but maybe in 00:06:06.420 --> 00:06:08.199 the whole research enterprise. The stakes are 00:06:08.199 --> 00:06:10.240 incredibly high, then. We hear about cyber attacks 00:06:10.240 --> 00:06:12.860 on hospitals and research places. That must be 00:06:12.860 --> 00:06:16.480 a constant worry. It is. Those attacks can steal 00:06:16.480 --> 00:06:19.879 data, lock up systems with ransomware, it can 00:06:19.879 --> 00:06:23.879 halt research, impact patient care. So yes, securing 00:06:23.879 --> 00:06:26.160 data in the cloud isn't just a nice to have for 00:06:26.160 --> 00:06:28.339 pharma. It's fundamental. Absolutely fundamental. 00:06:28.420 --> 00:06:31.060 It's about ethical responsibility as much as 00:06:31.060 --> 00:06:33.439 technical necessity. OK, so what are the absolute 00:06:33.439 --> 00:06:36.019 essentials? If a pharma company is using the 00:06:36.019 --> 00:06:39.279 cloud, what security measures are just table 00:06:39.279 --> 00:06:41.100 stakes? All right, several things are critical. 00:06:41.519 --> 00:06:45.569 First up, strong data encryption. Always. Meaning? 00:06:45.689 --> 00:06:48.490 Meaning you scramble the data, making it unreadable 00:06:48.490 --> 00:06:50.649 without the right key. And this needs to happen 00:06:50.649 --> 00:06:53.290 both in transit when data is moving between systems 00:06:53.290 --> 00:06:55.550 and at rest when it's just sitting stored on 00:06:55.550 --> 00:06:58.389 a server. Like a secret code only authorized 00:06:58.389 --> 00:07:00.629 people can decipher. Exactly. It's a foundational 00:07:00.629 --> 00:07:03.209 defense. If someone unauthorized gets access 00:07:03.209 --> 00:07:05.730 somehow, the data itself is hopefully useless 00:07:05.730 --> 00:07:08.050 to them. Okay. Encryption non -negotiable. What 00:07:08.050 --> 00:07:10.529 else? Very tight access controls. Granular access 00:07:10.529 --> 00:07:12.730 controls. So who gets to see what? Precisely. 00:07:12.939 --> 00:07:16.439 You need strict systems to check who is tricky 00:07:16.439 --> 00:07:19.319 to access data that's authentication, and then 00:07:19.319 --> 00:07:21.519 systems to control exactly what data they're 00:07:21.519 --> 00:07:24.100 allowed to see or change based on their role 00:07:24.100 --> 00:07:27.019 that's authorization. Makes sense. Least privilege 00:07:27.019 --> 00:07:29.920 principle, right? Only give access that's strictly 00:07:29.920 --> 00:07:32.560 needed. That's the idea. Someone in marketing 00:07:32.560 --> 00:07:35.600 shouldn't be able to browse raw clinical trial 00:07:35.600 --> 00:07:38.660 patient data, for example. Roles and responsibilities 00:07:38.660 --> 00:07:41.550 have to dictate access. OK, encryption access 00:07:41.550 --> 00:07:43.589 controls. Is that enough? Just set it up and 00:07:43.589 --> 00:07:45.629 forget it. Definitely not. You need continuous 00:07:45.629 --> 00:07:48.029 security monitoring and regular audits. It's 00:07:48.029 --> 00:07:50.209 absolutely vital. Why continuous? Because the 00:07:50.209 --> 00:07:52.290 threats are always changing. New vulnerabilities 00:07:52.290 --> 00:07:55.170 pop up. Attackers develop new techniques. You 00:07:55.170 --> 00:07:57.310 have to be constantly watching your cloud environment 00:07:57.310 --> 00:07:59.610 for any suspicious activity. And then you need 00:07:59.610 --> 00:08:02.709 periodic, thorough security audits to proactively 00:08:02.709 --> 00:08:05.069 look for weaknesses and make sure your defenses 00:08:05.069 --> 00:08:07.089 are still up to scratch against the latest threats. 00:08:07.279 --> 00:08:09.500 Right. It's an ongoing battle, not a one -time 00:08:09.500 --> 00:08:13.560 fix. Exactly. And regulations. Pharma is so heavily 00:08:13.560 --> 00:08:15.680 regulated, there must be specific roles about 00:08:15.680 --> 00:08:18.139 cloud data security. Oh, absolutely. Companies 00:08:18.139 --> 00:08:21.420 using the cloud. have to navigate this complex 00:08:21.420 --> 00:08:24.819 web of regulations, things like IP in the US 00:08:24.819 --> 00:08:28.100 for health information, GDPR in Europe for personal 00:08:28.100 --> 00:08:31.660 data, plus specific pharma guidelines like GXP, 00:08:31.660 --> 00:08:34.460 which relate to data integrity. Now, your source 00:08:34.460 --> 00:08:37.840 materials didn't explicitly detail, say, GXP 00:08:37.840 --> 00:08:40.980 cloud validation specifics, but the overall regulatory 00:08:40.980 --> 00:08:44.220 focus on data integrity and patient privacy makes 00:08:44.220 --> 00:08:47.620 it crystal clear. So regulators expect proof. 00:08:47.840 --> 00:08:50.899 that data is safe in the cloud. They do. You 00:08:50.899 --> 00:08:52.720 need to demonstrate you have the right technical 00:08:52.720 --> 00:08:54.720 measures, the right organizational policies, 00:08:55.039 --> 00:08:57.259 the right documentation to show your cloud setup 00:08:57.259 --> 00:09:00.309 meets those stringent requirements. OK, so it 00:09:00.309 --> 00:09:02.049 sounds like using the cloud isn't just about 00:09:02.049 --> 00:09:04.210 the tech. It forces you to be really disciplined 00:09:04.210 --> 00:09:06.210 about data management overall. That's a great 00:09:06.210 --> 00:09:08.789 way to put it. You can't have strong cloud security 00:09:08.789 --> 00:09:11.350 without a solid foundation of good data governance. 00:09:11.889 --> 00:09:13.610 That means things like ensuring data integrity 00:09:13.610 --> 00:09:16.750 is the data accurate, complete, reliable, maintaining 00:09:16.750 --> 00:09:18.789 high data quality from the start, and having 00:09:18.789 --> 00:09:21.529 really clear policies and procedures for everything. 00:09:22.269 --> 00:09:25.389 How data gets collected how it's stored, processed, 00:09:25.669 --> 00:09:27.870 backed up, archived, who's responsible for it. 00:09:28.169 --> 00:09:31.149 That data stewardship piece is key. Right. And 00:09:31.149 --> 00:09:33.230 practically speaking, what about things like 00:09:33.230 --> 00:09:36.750 backups, disaster recovery? What if a cloud provider 00:09:36.750 --> 00:09:40.610 has an outage or worse? Essential planning. You 00:09:40.610 --> 00:09:43.990 absolutely need robust, regularly tested backup 00:09:43.990 --> 00:09:47.179 procedures for cloud data. and a clear disaster 00:09:47.179 --> 00:09:49.539 recovery plan. What happens if there's a major 00:09:49.539 --> 00:09:51.519 disruption? Could be technical, could be a cyber 00:09:51.519 --> 00:09:53.940 attack, could even be a physical event at a data 00:09:53.940 --> 00:09:55.940 center. How do you get critical systems back 00:09:55.940 --> 00:09:59.159 online quickly and minimize data loss? That has 00:09:59.159 --> 00:10:01.639 to be mapped out. Okay. Let's try and connect 00:10:01.639 --> 00:10:03.639 this back to some of the actual research mentioned 00:10:03.639 --> 00:10:05.740 in your OPR and DSource materials, even if they 00:10:05.740 --> 00:10:08.700 don't explicitly say, we used the cloud. It feels 00:10:08.700 --> 00:10:11.360 like these principles must apply. That source 00:10:11.360 --> 00:10:12.960 and structure activity relationship study is 00:10:12.960 --> 00:10:15.659 using NMR spectroscopy that sounds like it generates 00:10:15.659 --> 00:10:17.960 incredibly complex data. It certainly would. 00:10:18.500 --> 00:10:20.620 And while a research paper might not detail the 00:10:20.620 --> 00:10:22.679 IT infrastructure, the kind of sophisticated 00:10:22.679 --> 00:10:25.120 analysis involved there, it almost certainly 00:10:25.120 --> 00:10:28.340 relies on significant computing power and storage. 00:10:28.840 --> 00:10:31.980 It's highly probable that cloud resources are 00:10:31.980 --> 00:10:34.179 providing that scalability behind the scenes. 00:10:34.669 --> 00:10:37.110 And of course, the security of those novel research 00:10:37.110 --> 00:10:39.429 findings would be paramount wherever the number 00:10:39.429 --> 00:10:41.970 crunching actually happens. And what about collaboration? 00:10:42.090 --> 00:10:44.629 We saw that Nature article excerpt in the Handbook 00:10:44.629 --> 00:10:47.309 of Medicinal Chemistry with a huge list of authors. 00:10:47.490 --> 00:10:50.629 Yeah, that suggests a large, likely multi -institutional 00:10:50.629 --> 00:10:54.690 effort, maybe involving complex data sets like 00:10:54.690 --> 00:10:58.149 genomics, perhaps. Possibly. Well, in that kind 00:10:58.149 --> 00:11:01.210 of scenario, multiple teams, maybe in different 00:11:01.210 --> 00:11:04.450 places, working on shared data. A secure cloud 00:11:04.450 --> 00:11:06.389 environment is often the most practical way to 00:11:06.389 --> 00:11:09.029 provide that central accessible platform. It 00:11:09.029 --> 00:11:11.470 can streamline collaboration compared to, you 00:11:11.470 --> 00:11:14.009 know, emailing massive data sets around provided 00:11:14.009 --> 00:11:15.809 those strict security and access controls we 00:11:15.809 --> 00:11:18.029 talked about are in place. Even for developing 00:11:18.029 --> 00:11:20.870 a single drug candidate like that cysteine protease 00:11:20.870 --> 00:11:23.460 inhibitor case study you had. Think about all 00:11:23.460 --> 00:11:26.320 the data accumulating over time. In vitro tests, 00:11:26.580 --> 00:11:28.860 animal studies, formulation data, eventually 00:11:28.860 --> 00:11:31.279 clinical trials. It adds up. It really adds up. 00:11:31.419 --> 00:11:33.419 You need a system to manage all that securely 00:11:33.419 --> 00:11:35.779 and ensure its integrity over the long haul. 00:11:36.440 --> 00:11:39.120 The cloud, if implemented properly with strong 00:11:39.120 --> 00:11:42.289 security and governance, can provide that. So 00:11:42.289 --> 00:11:44.629 it's kind of like the hidden enabler. The science 00:11:44.629 --> 00:11:47.389 gets the spotlight, but secure, scalable data 00:11:47.389 --> 00:11:49.710 management, often via the cloud, is what makes 00:11:49.710 --> 00:11:51.549 a lot of it possible. I think that's fair to 00:11:51.549 --> 00:11:53.769 say. The cutting edge science detailed in your 00:11:53.769 --> 00:11:57.110 sources, it's increasingly fueled by complex 00:11:57.110 --> 00:12:00.049 data analysis. And that analysis often relies, 00:12:00.409 --> 00:12:02.649 practically speaking, on cloud capabilities. 00:12:03.360 --> 00:12:05.919 But the absolute bedrock has to be that commitment 00:12:05.919 --> 00:12:08.440 to security and good data practices. That's what 00:12:08.440 --> 00:12:11.799 allows the innovation to happen safely and ethically. 00:12:12.220 --> 00:12:14.720 This has been really, really insightful, a crucial 00:12:14.720 --> 00:12:18.419 area for sure. So for you, our listener, wrapping 00:12:18.419 --> 00:12:22.179 this up. The main takeaways seem pretty clear, 00:12:22.460 --> 00:12:25.179 right? Cloud computing offers some really significant 00:12:25.179 --> 00:12:27.580 advantages for pharma handling data, analyzing 00:12:27.580 --> 00:12:29.940 it, maybe speeding up development. Huge potential. 00:12:30.039 --> 00:12:33.919 Huge potential, yes. But realizing that potential 00:12:33.919 --> 00:12:36.139 hinges completely on getting the security right. 00:12:36.279 --> 00:12:39.840 robust cybersecurity measures, really solid data 00:12:39.840 --> 00:12:42.220 management habits, and playing by the regulatory 00:12:42.220 --> 00:12:45.019 rules, they're not optional. No, they're absolutely 00:12:45.019 --> 00:12:47.320 essential. Getting this right isn't just, you 00:12:47.320 --> 00:12:49.539 know, good IT practice. It's fundamental. Yeah. 00:12:49.659 --> 00:12:51.340 It's about protecting that valuable research, 00:12:51.759 --> 00:12:53.820 safeguarding patient privacy, and ultimately 00:12:53.820 --> 00:12:55.970 maintaining trust. in the whole pharmaceutical 00:12:55.970 --> 00:12:58.429 R &D process. The choices companies make now 00:12:58.429 --> 00:13:00.889 about cloud and security, they'll echo for years. 00:13:01.649 --> 00:13:02.990 Definitely. OK, so here's a final thought to 00:13:02.990 --> 00:13:05.070 leave you with. As pharma keeps generating more 00:13:05.070 --> 00:13:07.690 and more complex data, just staggering amounts 00:13:07.690 --> 00:13:10.289 of it, how is this balancing act going to evolve? 00:13:10.409 --> 00:13:12.970 How do you keep harnessing the power and flexibility 00:13:12.970 --> 00:13:16.029 of the cloud while guarantee truly guaranteeing 00:13:16.029 --> 00:13:18.669 the security of that incredibly sensitive data? 00:13:19.129 --> 00:13:21.570 What new challenges or maybe new innovations 00:13:21.570 --> 00:13:23.669 are we going to see at this critical intersection 00:13:23.669 --> 00:13:25.779 in the next few? years. Something to chew on. 00:13:26.039 --> 00:13:27.320 Thanks for joining us on the Deep Dive.