For those in the pharmaceutical industry, the recent challenge has been in figuring out how to extend the digital capability of our everyday lives into pharma asset management. How do you bring all of a plant's activities and the data behind them into one place? Furthermore, if you could do that, what benefits would it bring to asset management? Karen Langhauser is joined by Ethan Smith, general manager of Life Sciences for Nuvolo, to get a better understanding of how pharma can bring its asset management into the digital age.
For those in the pharmaceutical industry, the recent challenge has been in figuring out how to extend that kind of capability into pharma asset management. How do you bring all of a plant's activities and the data behind them into one place? Furthermore, if you could do that, what benefits would it bring to asset management? And all of that is what we're here to talk about today.
I'm Karen Langhauser, and you're listening to a special Solutions Spotlight edition of all script Pharma Manufacturing's podcast that goes beyond the pages of our magazine to discuss the issues that matter most to the industry.
I'm joined today by Ethan Smith, who is the general manager of Life Sciences for Nuvolo. Ethan has spent the past 22 years of his career focused on technology for life sciences industries, and today he's going to help us get a better understanding of how pharma can bring its asset management into the digital age.
Ethan, thank you so much for joining me.
Ethan Smith: Hi, Karen. Thanks so much for having me. I look forward to the conversation.
Langhauser: So, I want to start today with the topic we've all heard a lot about across many different industries, and that's digitalization. So, how is digitalization specifically impacting pharma manufacturing?
Smith: Digitalization is massive for pharma across the life cycle and specifically for manufacturing. As many of your listeners probably know, this industry and particularly the manufacturing function has operated off of documents, AKA paper, for most of its existence. Regulators and inspectors from the health authorities have historically asked to see and review documents during inspections. Employees are trained using documents. And information has been “stored,” if you can call it that, in documents over the years. Just having a document in soft copy as opposed to printed out physically doesn't really change that just yet. But documents have essentially been a blessing, a curse and a handicap to progress for pharma manufacturing specifically.
Now, with advances in cloud technology, connectivity of everything the IoT movement and platforms that have enhanced integration capabilities are all driving the industry and manufacturing towards digitalization. Employees actually are often the ones that are pushing for it, given how much change has happened in the consumer world even before the pandemic, but accelerated with the pandemic, and how much we all just have come to expect to be able to do and take care of in our own personal lives digitally. It used to be talking about banking. Now, it's even getting your groceries delivered, getting health appointments happening that way, and pharma manufacturing really needs to catch up with that overall trend.
Langhauser: Right. But yeah, that all makes sense, and that employee buy-in is so important in this process I'd imagine.
So, what would you say is the ultimate goal of digitalization in the pharma industry?
Smith: It's a great question, and I'm sure many stakeholders in this space will have their own, somewhat different, answers to it. In my view, it's all about using digital technology to simplify work and secure sharing of information, not just data. And I'll come back to that. But sharing information securely across people, places and systems and information is different from data in that it's human centric and it's designed to support natural intelligence, AKA people, to ultimately empower employees to do their best work. They're going to need to have the right information at their fingertips. And historically, integrations have focused just on data, which is a precursor to it. But information allows employees, allows people, to translate what one system may have in it versus another system, maybe looking across departments at the kind of work that's happening. A classic comparison is always between the way that manufacturing looks at information and data versus the way quality looks at information and data.
So, simplifying that is a huge goal for it in my mind, and it's also important to recognize that digitalization is a journey, not a destination. There's not one goal or one thing or one solution and once we get there, we put a flag in it and we're there. It's a constant evolution, and I think we all know this. Personally, that technology really waits for no one. These advances are going to continue and accelerate. Ultimately, the industry is here to deliver safe and effective therapies to patients, and digitization, the goal of that is to make that simpler, make it faster while making it secure and ensuring the quality associated with it.
Langhauser: So that said, in speaking of manufacturing, where are there still inefficiencies in the manufacturing process?
Smith: Yeah, pharma manufacturing execution, the actual running of the machines and the equipment to make the products from API through intermediaries, intermediate products to finished products, that's all pretty highly efficient. I think of that and, kind of refer to that, as the industrialization of pharmaceutical manufacturing. It's a lean process. It has learned from many other process manufacturing industries like the automobile industry, the medical device industry, the high-tech industry. All of that has benefited from automation, with things like robots automating equipment usage. So, that's all pretty lean and efficient.
However, the processes that surround the actual manufacturing execution, both upstream of it and downstream of it, still have pretty high inefficiency across the board. So, if you look at it all the way back, pharmaceutical companies make products that meet demand, and you translating the market demand in terms of how many patients suffer from a particular disorder and how much of a particular medicine or therapy do we need while also managing its shelf life, translating that into manufacturing production schedules relies on information around manufacturing capacity, and that's not just the equipment, but the availability of ingredients and intermediaries and the like.
That is all a very highly manual process still, but it is directly tied to the revenue of any pharmaceutical product company. And the same is true of the mission-critical quality-review process of the produced batches of material at the end of manufacturing execution. And these areas which surround that automation or that industrialization as I called it before, these areas are really right for digitalization to ensure the manufactured batches can be safely released into inventory as quickly as practical, and that the production schedules can be optimized to ensure that all the equipment is well maintained and that the market needs are met so there aren't drug shortages or any of the other impacts from a revenue standpoint. So, the execution itself pretty highly efficient, the processes that surround it and drive it and support it still need a still have a long way to go in terms of efficiency.
Langhauser: So, perhaps the billion-dollar question is what solutions you see helping address these inefficiencies?
Smith: Yeah, very, very insightful question and a great follow-up to that because it's one thing to say it, it's another thing to then do something about it. And solutions to these kinds of complex challenges, they have to be flexible, they have to be interoperable and they also have to be, maybe most importantly, highly reliable to operate in the manufacturing space. And there's really no one right approach to manufacturing execution, let alone the capacity planning, the scheduling or the batch review processes.
Lots of companies do that different ways, and they're all getting products to market. Our approach at Nuvolo is, first and foremost, to work within the landscape of the existing mission critical applications that support manufacturing, like MES, manufacturing execution systems, and in our solution for that which we call digital alignment of manufacturing and quality depends on these other systems like MES and QMS to continue doing what they do best while taking additional information from the equipment and the assets into account to improve and enhance those processes. And here's what I mean a little more specifically, quality needs more than just the executed batch record or EBR, which is typically a document like we discussed at the at the top here, in order to certify that that batch is ready for release. They need more information than just a sheet of paper or a couple sheets of paper there. They need to know that all of the equipment that was used in the manufacture of that specific batch on that specific date of manufacture was up to date on all of its planned maintenance, had been calibrated within an acceptable calibration window, and the time frame that the equipment was all properly cleaned and properly set-up for the process, the manufacturing process that was happening. And this is information that's in our solution, our GXP asset management solution and it already contains that information. So, what we're looking to do is take the batch number and the product information from the MES or maybe from the ERP system or any other authoritative source, and we're able to provide quality then with a validated report that documents that all of the equipment used was in fact, “ready for use,” ready for its intended use and manufacturing. Think of it like a green light status at the asset level.
And for each batch, they're typically scores. Sometimes hundreds of assets that are involved. So, it might sound relatively simple on the surface that, yes, this machine was ready to work when we manufactured it. But when you have lots of batches being produced, you have multiple sites around the world that have multiple manufacturing lines within them, you're starting to talk about thousands, if not hundreds of thousands of pieces of equipment. And what this allows is for quality to get the same level of output without having to verify each piece of equipment going line by line through that executed batch record individually, but rather it's now sourced as a digital record to supplement that quality review package. So, there's a couple different ways that we're approaching it in order to bring these two closer together.
Langhauser: And did you, did Nuvolo, invent that term? Digital alignment? Is that a patented term?
Smith: It's not a patented term. It's one that I think several analysts who cover the space and maybe even more broadly than life sciences use. I'm a life sciences guy, so I'm not sure if it's been used in in other areas.
And I'm sure defining it is probably something that we wanna talk about a little bit, but it's not a term that nuvolo introduced or or has any has any rights to.
Langhauser: Yeah. So, can you talk a little bit more about what that term means?
Smith: Yeah, it's a great question. And simply put, digital alignment is bringing together processes and data to make them operate more efficiently. And those are some relatively generic terms and it's meant to be that way. So, think of digital alignment as a broader term than integration, which typically means point-to-point system connections, kind of piping and wiring between systems.
Digital alignment includes integrations. It's definitely a part of it as well as other ways to align information on topologies, which are typically used in the definition of products in life sciences taxonomies, another similar term are also forms of digital alignment in their purpose, and the reason they exist is to harmonize or match terminology and hierarchies so that one system or one department or even an entire company calls something the same thing and they know what the other party is calling it. Sounds relatively simple or maybe sounds a little bit academic, but the classic and best example is in pharma and in manufacturing. The definition of a product outside of life sciences can be very clear. We make cars. So, the product is a car. When it comes to drugs, and specifically the manufacturer of them, are you talking about the finished product, the marketed product, the packaged product, the API, the intermediate product? And it goes on and on and on. So, ontologies and taxonomies are a big part of digital alignment, so that a person with natural intelligence can look at information from multiple sources and not have to spend their time figuring out how does this term on one side align with on the other team on the other side. That's done for them and they can spend their time focusing on what's important.
And lastly, technology platforms are another form of digital alignment. And because they inherently bring processes and information together into alignment by virtue of the fact that this information and these processes coexist on the same platform, this is why we're seeing it more and more. It's almost standard, I would say, these days of larger pharma companies adopting an IT strategy that centered around enterprise platforms. And picking a smaller number of platforms to do more things on those platforms is a strategy that is being employed across the industry. You know, CIOs have learned, often the hard way, that aligning on and investing in a few strategic platforms pays big dividends over the long term and it also prevents the proliferation of point solutions that require integrations that are brittle.
And all of this points back to what I was saying before that it's really a journey and not a destination or a single solution. Starting to employ taxonomies to define terms well across your organization. Most pharma companies work with partners, whether it's manufacturing partners like CMOS Research Partners, Agency partners, so that we're not spending our time doing that translation of terminology, but rather we're spending our time on the real important business drivers that need to be addressed.
Langhauser: So, what would you say are some of the long-term benefits of digitally aligning quality and manufacturing for pharma manufacturers?
Smith: Yeah, bringing quality and manufacturing into closer alignment really has, I think of it as, three crucial benefits. The he first one is providing equipment information from a manufactured batch to the quality team streamlines the quality batch review process.
This it saves time while maintaining high quality, arguably enhancing the level of quality and let's quality focus on what they do best and what matters most, which is ensuring that all the process steps were followed. And it removes these additional manual layers of kind of forensic digging that they often have to do to find the information they need and allows them to focus on reviewing the quality of the produced product and getting that product into inventory as quickly as possible so that it can get to patients.
The second critical benefit is tracking batch numbers and products that each piece of equipment has been used to produce creates new information and insights for the manufacturing function, which owns these pieces of equipment. By including those batch numbers in the compliant audit trail of every asset, manufacturing now has the ability to analyze the equipment's performance based on their company’s products, and this is an entirely new dimension for equipment management or asset management, which is historically been managed just with downtime and runtime metrics. When was a machine being turned on and running versus when was it idle versus when was it offline. That was all the information that they had. These new insights will help manufacturing as well as finance and procurement to make better decisions around when to repair a device, when to replace it or when to maybe supplement it with a duplicate device for manufacturing efficiency.
And third alignment of digital alignment of quality manufacturing will prevent production delays by enabling the reservation of all the equipment that is needed for a production run in a single place where the maintenance plans and records for the equipment are also maintained. This ensures that a manufacturing site doesn't get ready to start a batch only to find out that one piece of equipment or a couple of pieces of equipment has an open maintenance order or is out of calibration, and then those challenges turn into delays to the actual manufacturing production, which is costly in terms of people's time, in terms of the ingredients that they have on hand to produce the material which all have shelf lives of their own, and ultimately lost time to market because that product isn't being produced while you're waiting on a manufacturing delay. And there's many more tentacles of benefits that you can start to see from this, but those are the three primary ones that I would expect anybody that's coming down this path can expect to see in quality and manufacturing.
Langhauser: Yeah, all three of those sound hugely beneficial to the industry.
Smith: Yeah, absolutely. And it's been a long time coming from that side, and we're still not there yet. It is a journey but absolutely it's something that the industry is ready for and it's time for.
Langhauser: Well, not to jump ahead on the journey, but are there opportunities to mature this alignment even further in the future?
Smith: Oh, absolutely. It's definitely a journey and companies involved in it, both the pharma manufacturers as well as technology providers like Nuvolo, we're all going to continue to evolve and mature processes and solutions to some of these challenges that have been there in the industry for quite a while. And for us, specifically, we see advancing and maturing the employment of machine learning and advanced analytics, using that data that I mentioned just before to enable really true asset performance management by the pharmaceutical companies. And what I mean is, does one brand of a piece of equipment like a tablet press or an HPLC, does it perform better when they're making a specific one of their products versus another product? Are there ways that we can use our equipment better? These are very expensive assets to produce our products at the end of the day, so turning this more into a focus on product intelligence, and I'm talking about the pharma companies, product intelligence is where I see this evolving in a big way and it will change the way the equipment is managed, maintained and ultimately purchased. And we're talking about lots of money here in terms of the equipment and another area in macro trend that will drive this further into the future is the advancement of cell therapy and gene therapy and other personalized areas of medicine immunotherapies where a single patient is the actual batch.
And we're talking about more continuous manufacturing versus batch or process manufacturing and what we can do with digital alignment here is help improve the yields and the timelines to get a patient's personalized therapy back to them as efficiently as possible. Of course, maintaining the highest quality because many of these therapies, as groundbreaking as they are, are reserved for patients that are really in a in a very, very bad state of health. And they need these therapies badly and the time to produce them from the patients’ own cells every day, the clock is ticking for the patient. So, being able to be more productive and more efficient here is massive. And you can really draw very direct lines between patient improved outcomes when you get into personalized medicine, again because the patient is the batch in that world. And this is where we really see the evolution towards product lifecycle intelligence enabling visibility of the product that personalized batch throughout its lifecycle to better understand all of the implications of it, not just the equipment, but the quality processes and everything that's involved with it to get that back to the patient as quickly as possible. And what's really exciting is this is early days, both for this idea of digital alignment between pharma and quality, it's also early days for these new types of therapies that are coming to market. And what's exciting is that technology really is in an amazing place to help, and ultimately, help patients here get their treatment sooner and faster, and we're super excited to have some involvement in that and work with our clients, work with the industry to help find things that we haven't thought of yet that we can continue to evolve this and expand it in even other ways to further help the industry and patients.
Langhauser: And I mean, that's great to see the technology stepping up to meet the industry where it's at and I'm excited to see where Nuvolo brings us in the future.
So, thank you so much Ethan, for joining us today and we appreciate your time and your input.
Smith: Yeah, absolutely, Karen. Thanks so much for having me. It's been it's been a great conversation. I really appreciate the insightful questions and getting this information out there. We're definitely open for hearing feedback and input. Anybody that's listening to this, that has some ideas for us, please don't hesitate to reach out and just thank you so much.
Langhauser: Thank you.
You've been listening to a special Solutions Spotlight episode of Off Script. Thanks so much for joining us. Stay safe and stay informed.