 Gweithio'r ffordd, mae'n fawr i'w gweithio'r fawr ar y cyfnodd, ac mae'n fawr i'w gweithio'r fawr. Mae'r mwyaf i'w Joyce O'Connor, ac mae'n gweithio'r fawr gyfwyr yn ymddangosol. Ac mae'n gweithio'r fawr i'w gweithio'r fawr yn ymddangosol bydd dr Barry Harvey yn ymdweud 4.0 o digitalisio a llifosu. Ac mae'n gweithio'r fawr i'w gweithio'r fawr yn ymddangosol. Mae'n ymwneud o gweithio hoddiwch amdangosol Barry i'w gweithio'r fawr. Mae'r cyfwyr hwywyng yn gweithio'r fawr. Mae'n ddau o gweithio'r fawr yn mynd i dddangosol. Ond mae'n gwneud i Barry a rheswm yn ymddangosol maen. Mae'r cyfwyr hwywyng yn gweithio'r fawr yn arlen yw yn 30,000 gweithio'r fawr i'w gweithio'r fawr, another 30,000 indirectly and there's been masses of investment over 10 billion over the last number of years so it is a major sector that we're looking at but just as say if we look at retail globally there's been major disruption saved by groups like Amazon and if you look at transport like Gruber and I think you know Dr Heavey now will explore how healthcare and life sciences are also at a tipping point where technology is driving change so I think this this presentation today I think will open our eyes to change that's happening there's you know a tipping point here and we're really very lucky to have Barry talk to us Barry has a very distinguished career started as a geneticist with PhD in Vienna he worked in pharma and biotech companies I think in the UK and in Ireland but then went to the IDA as a vice president in marketing technology in North America and then went to head up life sciences in the IDA and particularly and headed up the global side of that and then he left the idea and went to Accenture and was very interested to hear as head of life sciences and running the global team there as well but very interested to hear that he started with one person two years ago and there are now 200 people in Accenture working in that area which is you know quite amazing and did you say 10,000 globally so you can see how big that sector is so we're very lucky as I said to have Barry to speak to us today and we look forward to your presentation thank you very much Joyce and thank you to everybody for for attending today um and and to the organisers to Joyce and Jail and Deirdre for for for for welcoming me and to the to the group we we met earlier for for interesting discussions so so yeah I think today I'm really going to talk about um a theme that that's uh the IIA expressed a strong interest in the topic of industry 4.0 um which is a a buzzword it's around digitisation in in manufacturing and particularly how it's relevant to the life science sector which is a sector that I'm I'm very fond of and I think I'll also try and talk with us in the context of the overall mega trends in the life science sector and why why does digital trend in in the manufacturing space specifically is so important so um first of all um I'll show you some of the the cool eccentric slides so I hopefully if this works uh we'll um we'll be able to give you some statistics on the technology trends in the industry at the moment so yeah this is just again a little bit of perspective from Accenture on what's happening in the broader technology world and how that's impacting on industry on manufacturing so we talk about this this perfect storm that manufacturers are faced with at the moment um it's just this raft of change is happening very quickly so some of the key points are markets are you know the expectations of markets are are moving much faster than they were before so the expectation that new products will be brought to market more quickly that new waves of technology are are are coming faster and faster that there's completely disruptive business models Joyce touched on the uberisation of of of the transport industry and and the uh the air bnb isation of the um of the hospitality sector um and also the the product that that people are bringing to market is much more um you know much more complex so I was just thinking about this this morning and I'm the youngest of a big family and my my eldest brother back in the 70s was a bit of a a bit of a prototype of a yuppie and he had a little mg sports car um which was very impressive at the time um a convertible mg back into 70s in Ireland and then when he into the 80s he came a proper yuppie and he bought himself a bigger car and the the the um the mg had no technology at all it basically was four wheels a chassis and a a fell top but the um I think the Renault 25 that he had had buttons on the steering wheel that you could control the the the value and he had a car big one of these big blocky car phones but we take it for granted now that you know your your average car and you know will have you know centres all over the place and rear cameras all over the place and cruise control adaptive cruise control it may not be a smart car but it's damn near close to it and the amount of technology that's embedded in those products is is really massive but I'll give you an example in a in a few minutes about how actually life science is trumping that level of complexity quite significantly and in a much shorter space of time than than what happened over my my brother's car buying life cycle the workforce in the in these factories is going to have to change we had a conversation but this morning you know big old factories making large you know one product in large volumes with very little change over time is a thing of the past and the workforce has has new expectations about what their employer will do for them and we see it a lot in Accenture where we're kind of the ultimate kind of liquid organization where people's roles are constantly changing we have almost 500,000 people now in Accenture globally the life so half a million people in one company life science is only a tiny part of that the Irish practice is a tiny part of it the Irish life science practice is a tiny part of that but we all have to work and network in this massive organization and be entrepreneurs in a in a massive organization and avoid that organization becoming bureaucratic and the economy is changing so you know there's things like you know the digital platforms that are out there different sectors of the economy are interfacing we were talking earlier about healthcare interfacing with digital tech interfacing with pharmaceuticals and so on so the the old kind of rules of the economy don't seem to don't seem to necessarily stand anymore and then if you layer all of that on the changes in technology landscapes so these are actually this is an old slide so these are way out of date so this is you know the there's been a 119 exabytes of data that was in 2017 so it's it's probably triple that at this stage we've you know we've had more data collected in the last two years and in the history of mankind and a lot of that is frivolous data it's it's you know megapixel cameras that are posted on instagram or whatever um but but a lot of it's quite important data that isn't really mind very effectively massive amounts of processing power lots of devices collecting that data like the the sensors in your car and and huge spending on trying to make sense of all this data using artificial intelligence and then this is just the the waves of technology are getting are getting faster and steeper so the the first line here it's a little bit tricky for people to see but the first line here is the is the adoption of mainframe computing so you can see it started in the 50s and it kind of peaked not until like the mid 80s so so fully 35 years later and then you're getting into um you know the the the technology that's that's more kind of um familiar to us today like the iphone the adoption of the iphone happening from from from the late 90s and just growing exponentially and then a lot of new technology coming through much faster and quantum computing is the new artificial intelligence essentially it's a new buzzword that you'll be hearing a lot about in future but these waves of technology are becoming faster and faster now and if you layer that onto people's expectations it becomes difficult to to keep up um so so yeah this is kind of nice pretty slides and a lot of techno jargon about quantum computing and and so on so forth but but how is it really relevant to the sector that I'm not a technical person I don't have an IT background they have a biochemistry background and I join Accenture because I think this is really exciting in the context of the sector that we have here in Ireland so so why is industry 4.0 important for life science and first of all what is industry 4 I assume people have some sense of this but the idea is just in case anyone's not clear and if you have questions stop me the the first industrial revolution was steam powered you know equipment in in in in England then electrification came along then automation and the fourth is based on on really better better data capture using devices using sensors but more importantly actually analyzing that data and surfacing insights from that data using more advanced algorithms also better integrate interaction with the human and the machine so highly automated plants are great if you're making one product very efficiently with not much change but if you're if you're adapting to rapid changes in consumer expectations consumer needs that big old automated factory is actually can be a very difficult thing to deal with and and this idea that if you have that better interaction between you do need some automation but you don't want to take humans out of the loop completely that that that human machine interface enabled by industry 4.0 technology can can help companies adapted a rapid change and requirement for hyper personalisation that we talked about in the last few slides and and why is this relevant to life sciences as opposed to iphone manufacturers um well i'll talk about the fact that new drugs are becoming vastly more complex so keep in mind my brother's mg to renaw 25 kind of journey over about 20 years they're not only more complex but they're now emerging faster from r&d so so tom wleary from from icon will talk about the fact that you know the old adage was it takes 12 years to get the drug from from clinical trial start up to to the end on average i was at a conference recently and a guy from rush was saying that they they're now measuring their their timelines in days so they've set a target for a thousand days from discovering a drug to having it on the market it's still three years but they're trying to emphasise to their older employees we're not talking years anymore guys we have to be ready in days um and if you think about that a more complex product that's coming at you quicker if you're in a manufacturing site that's kind of intimidating um and because drugs are more personalized now one factory making one drug is not a viable factory anymore one factory has to make 20 drugs or 40 drugs or a thousand drugs and so it has to be able to gear up and gear down for different campaigns and batches of different products and what's always important is that the regulators expect flawless supply these companies are not making happy meal toys where they can accept you know one in a thousand happy meal toys doesn't work and the kid cries you know this is flawless supply zero defect every time um and the stakes are enormous if if you fail in that you're shut down and your 20 billion dollar franchise is gone so how can industry 4.0 help well um if you have a lot of complexity you're going to have a lot of variability if you've a lot of variability you better try and understand that variability so you can control that variability so you got to capture a lot of technology of data on your variables what's variable and what what could be variable and what is varying and how does one variable influence another variable that's the basis for for statistical analysis so you need to capture more and more data as we talked about earlier using iot you need to be able to do deep analysis and find correlations in that data to get to the root cause of your problem or take a proactive step to improve something and and you need to augment your human so they can be have a human machine interface so the human will be trained quicker they'll be they'll make less mistakes they'll have more agility they'll be able to adapt more quickly do more things and make better decisions faster and and and ultimately this industry is all about risk you know very often when you hear about industry 4.0 and other industries they emphasize the business case for investing in industry 4 we will get 20% more efficient we'll be able to push out 20% more widgets for the same cost in pharma they haven't really figured this out yet but they really their business case is based on risk it's like buying insurance against a major screw-up in your manufacturing facility if you understand your variables you understand what's happening there's a lower chance you're going to have a screw-up that will shut you down there's been you know there's been a couple of major cases of companies like genzyme of about 10 years ago who lost control of the manufacturing they were a darling of the of the street because they brought some amazing drugs to market for patients with with really bad diseases the brilliant r&d but they lost control of the manufacturing and their share price collapsed and synolfi acquired them and and synolfi has kind of turned them around and they've been a success but the shareholders kind of got got bitten by by loss of control of the manufacturing um so this is the point around the products becoming more complex so okay there's more sensors in a in a high on di i 40 now than there is in a in the in the really sexy mg that was driving around in the 70s but it's not this more complex so this is the best selling drug 10 years ago it's called lipitor and the chemical formula for lipitor i don't want to get too technical here but i like this way of explaining it you need to string together three c's 35 h's an f two ends and and five o's and that's how you make lipitor it's chemistry but the best selling drug in the you know at the moment is a drug called humira so you can see you got to string together a lot more things to make the best selling drug 10 years on from the so it's a lot more complex than going from a high on di 40 to from a from an mg um sorry i can't remember the name of the model that he drove um and fundamentally what that means is a lot can go a lot more can go wrong when you're making that product there's a lot more risk not to say it's easy to make those that product it is actually you need some pretty ninja chemistry to make that product but once you've figured it out the manufacturing process it's highly it's rinse and repeat it's turn the handle that's why um when that drug went off patent in 2008 or sorry what started off pattern i think around to tell it goes off pattern different countries different times i think around 2008 910 it was starting to drift off patent the generic companies pile in because it was easy for them to copy it and that the sales fell off a cliff and you heard about the patent cliff that drug there is already off patent since 2017 and it's been growing continuously since then it's still the best selling drug and it's continues to grow because it's really hard to copy but if it's really hard to copy it's also really easy for the company themselves to screw up the manufacturing so they need to be on top of their manufacturing or they lose their franchise so if you have more complexity you have you have more in the product you've more complexity in your processes and more complexity in showing um the regulators that you're in control this is just the point i'm not going to drain this but this is just the point around the fact that um things are moving more quickly um this is just some again some data from the british medical journal showing that in cancer in particular we talked about this briefly cancer is an area because medical oncologists have been very aggressive about adopting new drugs over 70 of of cancer drugs have been fast tracked through the approval process in the last few years so the FDA has said to the industry your drug is so exciting we're going to give you we're going to give you speed you through the process we're going to speed up we're going to get our regulators working fast which to get this to market because patients need this and we're seeing that across a number of different disease areas but a lot of cancer drugs are really complex you'll see in a minute and so you have this double whammy effect um this is the point about um the the whole area of low volume high mix so there's more and more um you used to hear about the blockbuster in in pharma and now it's all about the niche buster that you you focus on a much smaller patient population and you really cured that disease or get as near as damned close to to to curing it and you you charge more for that drug in a smaller patient population because you're having a bigger impact on the patient outcome and that was a kind of a mad idea back in the 90s and gensheim the company I mentioned earlier actually really went after that model and made a big success about and everyone copied them unfortunately for gensheim they screwed up the manufacturing and they they lost out but that model now has come through and most companies most facilities here in irland and elsewhere have gone from one product facilities to multi product facilities with lots of complexity and changeovers and so on and then we talked about this a little bit in in in the room downstairs this idea of looking also beyond the drug the drug itself is already quite complex but very often you'll see a lot of me too drugs coming out they're they're slightly different but they have maybe the same approach to treating a disease and a big thing now is how you differentiate your drug in the market add more complexity on top of of making the drug itself and making it flawlessly every time but wrap a device around it that that makes it easier for you to inject yourself that this is a an auto injector that instead of having a needle and glass it used to be the drugs that you have to inject yourself with they're so complex to make companies took the henry Ford approach to it you can have it in any format you want as long as it's in a gas file and you have to inject yourself and figure that out whereas now you know there's so many companies have figured out how to how to manage these these biologics or have these in a pipeline they're wrapping product and more more features so to speak around that that product and you can see here it's a an example of an inhaler where it's major it's it's obviously giving you your drug for your asthma or your COPD but it's also linked to a nap that might be linking into the smog or the weather or your Fitbit and say right you've been doing a lot of exercise and you're on a trip to to Shanghai so you might need an extra dose of your of your COPD medication or you may not and lots of interesting stuff happening in diabetes in the space as well so here you're intentionally adding complexity to your drug you're adding features like you do in the automotive industry but as I mentioned earlier there's a lot of unintentional complexity creeping in it's not unintentional but it's it's unavoidable complexity because the biology now is becoming so complex the companies have to make complex products and then intentionally add even more complexity so I keep coming back to complexity in in my in my um in my talk on this topic um this is just against probably difficult to read but this is just the kind of value chain in pharma so you know companies focus on discovering a drug pushing it into clinical development testing of humans getting regulatory approval and then doing lots of interesting things in the marketing space doing smart launches providing solutions to patients smart marketing solutions insights driven solution this is kind of where a lot of eccentric life science activity focuses we're known for this globally with big pharma companies in helping them digitally transform this value chain um but I don't focus on this at all because underneath this if you've if you've got this going on you also have an equivalent activity figuring out discovering a drug figuring out how to make it at small scale large scale for all of these to feed up into all of this value chain and then launching the drug and then maybe transferring it to a new facility in Ireland hopefully if uh if you've built a facility here or somewhere else maybe re-optimising the process and and maybe then um you know end of life in it and very often um this is kind of forgotten about because people still think well pharma has big margins manufacturing is easy you know it's not that but they forget that that that the manufacturing sector has been on this journey of complexity so um we often refer to the what we call the the kind of digital thread there's lots of data being collected around here often in silos in different groups in pharma so the r&d guys are understanding a bit about how the drug works and the manufacturing guys are figuring out the different variants of the drug but they might not think to join the dots between when we see this variant or when we saw this variant ten years ago during development we might see it again when we take transfer to a tech to a to a cmo and and there's no way of joining those dots so we're we're advocating for the idea that companies need to start breaking down the silos between their organizations sharing data and more importantly sharing insights and this idea of the digital thread to connect the dots between data silos and better understand your product your patient but also the the manufacturing processes that you you have to bring those products to the patients so as I mentioned oncology is at the cutting edge of innovation so I just look this is a recent story in a wall street journal of of a new drug it's a little bit difficult to remove cancer drugs offer the alternative to chemotherapy so traditionally you think of the kid in the hospital with getting chemo the hair is gone they're looking a bit pasty you're not looking too well this kid has been through an experiment clinical trial she was she was um a terminal cancer is her here's her dad given her a dose of of of the drug and completely cured her cancer she's she's cancer free now and she didn't have any of the side effects because the cancer was highly targeted to her particular drug um but I love about this is it you can't read it here but this is a you know a rock star medical oncologist in a research center in um in New York coming in to check on her how she's doing six months after trial is finished so she's asking them to check out her hangnail that's the biggest thing she's got worry she's that's worrying her at the moment is her hangnail so the medical oncologist has given her is checking that out for um and then uh did I skip this way there okay so this is again shout out to Novartis um so that's one example of of of um of innovation in in oncology this is a really cool one this is a a drug called kimrea treatment called kimrea which is a hyper personalized cancer treatment and you hear a lot of buzzwords about personalized medicine oh it's going to be we're in the age of personalized medicine and it's a bit of a it's a bit of an overused terminology so we've we've tried to break away from it or or be a bit more specific and we say hyper personalized because we're consultants and we come up with cool phrases like hyper personalized um but this is really like it's for you it's not kind of a niche buster it's not for a a sub population of patients with you know prostate cancer type 51629 which is like those thousands of people with that type is a prostate cancer it's about literally your treatment for your cancer um and this is done universe done by uh came came out of uh research from the university of pennsylvania emily whited if anyone wants to just google emily whited video on youtube it's really nice she was in with the hospital with the hair gone they tried everything else she was end of you know this was end of line treatment so she was enrolled in an experimental trial in 2012 which was run by a bunch of academics um wasn't really you know a kind of a pharma typical pharmaceutical clinical trial and essentially we've lost some of the slides here but but essentially what the process is is they took emily cells out of her blood so in your blood you have immune cells which i refer to them as the soldiers of your body and they're supposed to pick up cancer but usually they don't and they took those cells to a factory and they did some jiggery pokery on them which is genetically engineered their her immune cells and i describe it as like putting a pair of night vision goggles on a soldier and giving them a a kalashnikov and tell them right now you're going back to the front you're going back you know with your night vision goggles on they inject the cells back into into emily and the and the cells now will seek and destroy her um cancer much more effectively than they would normally and she was she's completely cancer free now this is you know eight years later and she's she's doing great and there's really nice videos over on on our parents have become kind of campaigners for this so that this is kind of the process here but effectively at this stage you're you're taking yet this is your your your world war one's soldier in the trenches not not getting very far not doing much you're turning them into a super soldier here and you're putting you're putting them back into the patient to to clear up the cancer and this all happens uh essentially in a factory so you're you're combining a kind of a clinical treatment with a factory and you're doing a batch for one person and you better not so this is the product um this is this is kim rhea and if you look at the label what's inside here what you've got inside here is you've got human t cells which is your immune cells they've been cultured and genetically modified they can only be used for the patient where they came from that's autologous they can't be used allegedly it contains about two million but it could be up to um 100 million or 200 million so it's not quite sure how many are in there but it's so it's a pretty complex product uh you have to store it minus 120 degrees Celsius when you're transporting it um and it's the label for this product come out of the factory has the name of the patient john dole in this case and their date of art and so on so you need to identify on the product which is pretty pretty amazing right um so continuing the theme of oncology these drugs i'm going to talk about briefly now are not as as fancy as kim rhea but they're actually making much more money than kim rhea at the moment because kim rhea is quite expensive so uh merc brought out a drug for ketrude a forwards magazine recently this is the other msd launched in 2014 and it's at 7 7.2 billion quite quick so kind of hockey stick growth so this similar to the last one but but not requiring the injected drug into your into your body that kind of activates the soldiers and the soldiers go a bit crazy and they they they kind of seek and destroy your cancer works very well and bms have a similar drug called obtivo um and that's heading towards their overall oncology franchise heading towards 12 11 billion um by next year so the implicate now we're getting to the irish implication so as i mentioned earlier we in when i was in idae i still say we um we went after these kind of companies and encouraged them to invest in our land and this is all our new drugs are these complex biologic drugs we need people who know how to make these so we set up a training centre to get them trained up to be able to make these drugs and the net result was when you have growth like this you typically need a new factory right so they got ahead of it and they're investing about half a billion in swords and they're investing almost a billion out in in uh blanchard stand um and it's a it's a massive jobs bonanza but but fundamentally this is a whole new way of manufacturing and this has been there's been several other of these um in recent years getting close to my time here now i'm going to give you a brief what's eccentric doing in this space i don't want to do this as an infomercial on eccentric um it's more to show you how our how we're approaching it and why arland is is is the irish part of eccentric is reacting to this so eccentric in the manufacturing supply chain space was typically focused just on playing up supply chain optimizing your supply chain not too focused on your detail of your manufacturing so what we're doing now is we're trying to diverse integrate diverse it tools um to go back into the more detail in the business process for all this complexity is and curate the data better that from all these different silos and actually unleash then the the insights a digital thread so we've if you look at the business process you you decide you need to make drug you buy all these raw materials from somewhere you have to really check that they're they're consistent because if they're not your product's going to be out of whack then you make them you have to make sure your process is in control or the product's going to be out of whack and then when your product comes out the door you better make sure to the regulator that your six thousand five hundred and thirty four carbon atoms are all in the right spot every time so there's a huge amount of data to be collected in this process that wasn't really as important before when the drugs were simpler so we've um acquired companies that spent niche companies who were specialized we bought a company called lab answer in the us that specialized in this data curation and we bought an irish company esp in cork that specialized in this data curation and we also had a big data analytics group in arland here who used to work in the financial services sector doing analytics for for the banks and we've moved them all over to the pharma to say there's lots of complexity here in pharma that needs needs analyzing so they've moved from actually into biotechnology um so this is the structure of our team now so we now have a hundred people in our but we had a hundred people already in our analytics team in arland uh before i started but a lot of those are pivoting towards live sciences now um we have the we made this acquisition in the us just when i joined and we we managed i kind of put my idea hat on again and got them to set up their e u hub um in in eccentric arland so they now have a 30 person team and that's growing rapidly and we bought esp this year and that's a hundred person team down in in cork so we're well over 200 people and then in addition we're lucky that eccentric is actually headquartered in arland so we have this big innovation center in in in dublin called the dock that opened in 2017 it's about 250 people that are working on innovation not life science focused but i've i'm getting them to to to work on a quite a few life science related activities and industry for related activities so we have a nice kind of capability around this whole area that we're we're building on but what the point of this slide is not as i say i'm not trying to just talk about what great eccentric is the point is this is a symbol of how eccentric of going on while something interesting is happening in arland we should be moving and buying companies in arland and doing interesting things in arland because the sector here is quite is quite um it's quite fertile and you know the when i was trying to make my case internally an eccentric to do this this is the kind of slide i showed them you know nine to top 10 the old the idea slides from um from my time sorry um yeah and a shout out to to idea and the relationships that they and the support they give to multinationals and the fact that you know it's not all about tax the the science and engineering capability is really key and the fact that idea is invested in things like nybert for biotech and i am ore for industry 4.0 is really important so i i guess my point in in this slide is really to make the point that it's eccentric now as a big or global organization but upward like industry 4.0 is seen as a kind of a german thing like a german's kind of patent that did the point but eccentric would see arland as being ahead of germany and industry 4.0 in the pharma sector maybe not an automotive but certainly in pharma and we have a unique capability here certainly way ahead of the UK but you know the UK again has a big manufacturing sector that's very loud and noisy but you know when you actually see the level of innovation that's happening here in arland that's much higher and the cluster of scale of capability that we have here so that's why eccentric is making these investments and and so on so that this is just again we talked about some of the investments earlier but but just a who's who of companies making major investments in in the sector like like J&J Dan O'Cork I see a couple of people from J&J here as well and uh and with that that kind of brings me a little bit a few minutes late but to to the end thank you very much no problem at all