WEBVTT 00:00:00.208 --> 00:00:01.167 Franck, welcome. 00:00:01.626 --> 00:00:05.588 Franck, tell me what impact of recent digital AI innovations 00:00:05.588 --> 00:00:07.966 have had on the ophthalmic industry. 00:00:08.758 --> 00:00:12.971 Yeah, I would say that I would consider two types of impact. 00:00:13.179 --> 00:00:18.226 One is towards the patients and the surgeons or the doctors, but 00:00:18.226 --> 00:00:23.314 the other one is on the industry itself in terms of the way we do 00:00:23.314 --> 00:00:24.983 R&D, for example. 00:00:25.233 --> 00:00:27.193 So I will start with the first one. 00:00:28.069 --> 00:00:32.866 I think the biggest impact of digitization and AI has been, 00:00:32.866 --> 00:00:36.745 you know, with the development of connectivity. 00:00:37.746 --> 00:00:41.916 Everybody now is trying to connect everything, from the 00:00:41.916 --> 00:00:46.296 time a patient, for example, arrives in a clinic, they of 00:00:46.296 --> 00:00:50.717 course, their coordinates are entered, their visit is even 00:00:50.717 --> 00:00:52.218 scheduled digitally. 00:00:52.510 --> 00:00:56.347 And then there's a direct connection made to the EHR 00:00:56.347 --> 00:00:59.893 system to retrieve all kinds of medical records. 00:01:00.769 --> 00:01:04.647 And then some surveys are done on the patient, including their 00:01:04.647 --> 00:01:08.568 lifestyle, which might have an impact on what the surgeon might 00:01:08.568 --> 00:01:10.653 recommend as a solution later on. 00:01:11.112 --> 00:01:14.616 And all this is used for the planning of the surgery. 00:01:14.866 --> 00:01:18.536 Once the planning is approved—again, all this 00:01:18.536 --> 00:01:23.291 digitally—then of course the data can be used to guide the 00:01:23.291 --> 00:01:27.462 surgeon during the procedure in the operating room. 00:01:27.837 --> 00:01:33.176 And of course, this doesn't stop until there is the post-op visit 00:01:33.176 --> 00:01:38.306 of the patient, where the doctor can again collect new data to 00:01:38.306 --> 00:01:43.645 measure of the clinical outcomes and envisage further refinements 00:01:43.645 --> 00:01:45.021 with the patient. 00:01:45.021 --> 00:01:45.980 Or stop there. 00:01:46.189 --> 00:01:48.650 And what impact will this have on the industry as a whole? 00:01:49.901 --> 00:01:53.571 Connecting instruments via a cloud and enabling the 00:01:53.571 --> 00:01:57.909 collection of data and moving data around is very important, 00:01:57.909 --> 00:02:00.787 and it's going to transform health care. 00:02:01.246 --> 00:02:05.083 What it means for the patient is definitely a better experience 00:02:05.083 --> 00:02:05.667 all along. 00:02:06.167 --> 00:02:09.212 It means also better clinical outcomes at the end. 00:02:09.629 --> 00:02:13.174 And for the surgeon in terms of practice, I think it's going to 00:02:13.174 --> 00:02:17.762 improve the efficiency terribly, you know, and it will avoid, you 00:02:17.762 --> 00:02:21.266 know, human transcription errors, which were done manually 00:02:21.266 --> 00:02:26.479 so far, everything being transported digitally from the 00:02:26.479 --> 00:02:30.692 instruments to the cloud and then back to the instruments or 00:02:30.692 --> 00:02:32.193 back to an EHR system. 00:02:32.735 --> 00:02:35.321 In terms of the way we 00:02:35.321 --> 00:02:38.116 do R&D, I will give a few examples. 00:02:38.116 --> 00:02:42.620 AI comes like something that is going to really transform the 00:02:42.620 --> 00:02:47.542 way R&D professionals will be performing their job in the future. 00:02:48.042 --> 00:02:49.002 Few examples. 00:02:49.127 --> 00:02:55.258 You can now use generative AI to help you first of all plan your 00:02:55.258 --> 00:03:00.180 work in terms of software development, for example, 00:03:00.180 --> 00:03:06.227 looking at the requirements and the inputs and outputs, the way 00:03:06.227 --> 00:03:10.773 you design your software, the architecture. And then of course 00:03:10.773 --> 00:03:17.655 the coding itself can be highly sped up via the use of 00:03:17.655 --> 00:03:18.990 generative AI. 00:03:18.990 --> 00:03:22.869 And it goes even beyond that with the verification and 00:03:22.869 --> 00:03:26.789 validation and even the reporting of what has been done 00:03:26.789 --> 00:03:29.334 in view of a regulatory submission. 00:03:29.334 --> 00:03:34.464 So it's an end-to-end process that can be really accelerated 00:03:34.464 --> 00:03:36.549 with the use of of GenAI. 00:03:36.549 --> 00:03:39.344 Clinical trials management. 00:03:39.552 --> 00:03:42.472 You know, how can we leverage GenAI 00:03:42.472 --> 00:03:47.143 to draft protocols, trial protocols? 00:03:47.352 --> 00:03:48.853 How can we use GenAI 00:03:48.853 --> 00:03:52.565 to search into health records and knowing already the 00:03:52.565 --> 00:03:56.986 inclusion/exclusion criteria we are looking for, try to look in 00:03:56.986 --> 00:04:01.199 the database of patients which ones would meet this criteria 00:04:01.199 --> 00:04:04.244 and could be readily enrolled into a trial. 00:04:04.827 --> 00:04:08.164 The third example I would give is for example in the Medtech 00:04:08.164 --> 00:04:13.628 industry, how you can leverage AI to do generative design by 00:04:13.628 --> 00:04:19.676 combining the power of physics-based simulations with 00:04:19.676 --> 00:04:21.803 deep learning capability. 00:04:22.637 --> 00:04:27.016 So this is starting to be developed and the advantage, the 00:04:27.016 --> 00:04:31.646 benefit, is that the engineers using that will be most likely 00:04:31.646 --> 00:04:37.026 able to explore a bigger space of possibilities and do it much faster. 00:04:37.026 --> 00:04:38.695 And in some projects 00:04:38.695 --> 00:04:41.990 we've been reducing the cycle time for prototyping 00:04:41.990 --> 00:04:44.742 dramatically thanks to these technologies. 00:04:45.118 --> 00:04:49.080 Where do you see the next wave of innovation coming from in 00:04:49.080 --> 00:04:49.831 this space? 00:04:50.331 --> 00:04:53.126 One of them is, for example, surgical robotics. 00:04:54.419 --> 00:04:58.464 Robotics is on the rise because now, for example, for 00:04:58.464 --> 00:05:02.802 ophthalmology, you can develop robotic arms that have the 00:05:02.802 --> 00:05:05.513 needed precision to do a procedure. 00:05:05.847 --> 00:05:09.267 But on top of that, you can combine it with, again, 00:05:09.267 --> 00:05:10.184 generative AI. 00:05:10.601 --> 00:05:15.106 And by doing that, you could develop fully automated, fully 00:05:15.106 --> 00:05:17.108 autonomous robotic systems. 00:05:17.400 --> 00:05:20.278 There's a lot of robotic-assisted procedures as 00:05:20.278 --> 00:05:21.738 well that are being done. 00:05:21.946 --> 00:05:25.700 I think within the next ten years we're going to see more of that. 00:05:25.950 --> 00:05:30.246 Another big thing for patients is screening and diagnostics. 00:05:30.997 --> 00:05:37.211 You know, here again, AI can really help develop new methods 00:05:37.211 --> 00:05:43.509 that are really providing very high specificity and very high 00:05:43.509 --> 00:05:44.761 sensitivity. 00:05:45.428 --> 00:05:47.472 And of course in pharma, 00:05:47.472 --> 00:05:52.518 I think we're going to see also a lot of more new development 00:05:52.518 --> 00:05:57.023 thanks to AI in terms of drug discovery. Talking about 00:05:57.023 --> 00:06:02.070 ophthalmology in particular, new types of therapies like cell 00:06:02.070 --> 00:06:03.780 therapies are coming. 00:06:03.780 --> 00:06:07.408 Some of them are even approved in some countries. 00:06:08.284 --> 00:06:09.994 This could be the next gen 00:06:10.161 --> 00:06:14.874 of products before even we get more gene therapy treatment 00:06:14.874 --> 00:06:16.709 available for patients. 00:06:17.085 --> 00:06:20.588 There are so many things that are happening that it's actually 00:06:20.588 --> 00:06:22.507 quite exciting when you see that. 00:06:22.924 --> 00:06:24.675 Franck, thank you so much for your time. 00:06:25.093 --> 00:06:25.760 You're welcome. 00:06:25.760 --> 00:06:26.677 It's my pleasure. 00:06:26.677 --> 00:06:27.095 Thank you.