by Kelsey H | Sep 10, 2024 | Supply Chain
For years, many of the leaders in the biopharmaceutical industry focused on vertical integration in their supply chain. These industry giants built an internal network of manufacturing plants to keep the production of drug substance and drug product under their control. However, those internal networks have become difficult to sustain given the increasing rate of development of pharmaceutical products. According to the Congressional Budget Office, between 2010 and 2019, an average of 38 new drugs were developed each year, representing a 60% increase over the previous ten years.
To keep up with their quick pace of development, some biologics companies have utilized CDMOs to take over production on new products when their internal capacity is limited. According to Grand View Research, the global market for large molecule drug substance CDMOs is expected to achieve a compound annual growth rate of 9.3% between 2023 and 2030. At the same time, other companies have chosen to keep production in-house by expanding and optimizing their internal manufacturing sites.
There are advantages for both strategies of biopharma production. Internal manufacturing sites retain more long-term profit and control, while CDMOs help create a more dynamic and adaptable supply chain. For either production route, the benefits are most pronounced when the site can maximize capacity and resource utilization by deploying digital twin technology. Follow along with us as we explore the pros and cons of relying on in-house and contract manufacturing to produce new biologics products.
The Case for In-House Manufacturing Plants
Pros
For biopharma organizations that already have a network of internal production sites, utilizing existing facilities is often the most cost-effective way to accomplish commercial manufacturing when they develop new products. CDMOs work on a contract basis, charging their clients per batch or weight of product produced, in addition to raw material and other consumable costs. Those costs can add up quickly, and if demand for the new product increases, production costs will increase concurrently. Alternatively, if the biopharma developer can utilize an internal site, additional costs beyond materials can be minimized, resulting in more retained profit from the sales of the new product.
Keeping production in-house also gives biopharma companies more control over the manufacturing process. Working with an external partner introduces risk of mistakes or decisions the developer may not agree with, even if the CDMO has experience in the industry. Utilizing internal facilities ensures that production meets company standards for product quality, working conditions, and regulatory compliance.
To continue manufacturing new products at internal manufacturing sites, biologics companies will need to optimize their schedule to accommodate the production of both new and existing drugs. For organizations with a robust product lineup, finding available capacity for new projects is often difficult and time-consuming, eventually forcing them to work with a contract partner. However, digital twin software like VirtECS is designed to help plants optimize their processes and reorganize their schedule to maximize production capacity. A digital twin also allows in-house sites to refine their processes over time, adding worthwhile investments and layout changes to create competitive advantages your organization can benefit from long-term.
Cons
Pharmaceutical companies that don’t utilize digital twin technology may find it challenging and costly to fit their growing portfolio of products into their internal plants. It requires extensive time and resources to retrofit an old plant with new product lines. Then, when circumstances change and production needs to be scaled up or down in response to fluctuations in demand, sites with inflexible schedules and processes struggle to keep up. In these situations, utilizing a CDMO may be ideal – unless the company invests in digital twin technology. A digital twin can help manufacturing sites overcome many of these production challenges, analyzing data to recommend the most ideal schedule that will fit new projects into the plant schedule without disrupting current demands. Digital twins can also test future scenarios, such as scaling output for one product up or down, to analyze the trade-offs and find the production plan that maximizes revenue for the company.
In some cases, even a digital twin can’t overcome the reality that a company’s internal manufacturing plants are maxed out of capacity. Keeping production of a new product in-house will then require constructing a new facility, which costs millions or even billions of dollars and can take five to ten to complete. For some companies, this cost and time will still be worthwhile, if they have enough projects in the pipeline to fill the new plant’s capacity. A digital twin will be helpful in these future planning scenarios, ensuring the new site is designed to optimize production by maximizing potential output and creating flexible processes that can adjust around future product changes.
The Case for CDMOs
Pros
Unlike pharmaceutical giants, which are not only involved in manufacturing, but also discovery, development, research, and market approval, CDMOs are specifically focused on key areas of commercial production. This narrow focus means that contract facilities can often dedicate more significant investments into perfecting its production processes. These sites are more likely to be kept up to date with leading technology and use leading tactics to optimize output, helping their clients produce more batches in less time. CDMOs can also offer biopharma companies examples of success from past product batches, providing much-needed assurance during high-stakes projects, as well as their proven knowledge of key industry regulations.
Additionally, CDMOs have the advantage of speed. Because CDMOs are project-based, their schedules tend to be more flexible, and most biopharma companies can quickly find and reserve space at a CDMO for new production needs. Companies that don’t utilize a digital twin at existing sites may find themselves short on capacity and spend years waiting to start production at a new internal site. If they instead partner with a CDMO, they could begin production within weeks and bring the product to market on an efficient timeline. CDMOs also offer the flexibility to scale production up or down as needed, without the internal scramble to reset the production schedule, which is complicated and time-consuming for plants operating without a digital twin.
The benefits of working with a CDMO can be enhanced if the site uses a digital twin for analysis, planning and scheduling. Using the digital twin’s virtual model of their facility, the CDMO can test scenarios incorporating new products into their schedule to find the optimal sequence of events that will satisfy all their deadlines. This technology can help CDMOs be even more accommodating for biopharma developers and take on their projects more quickly, further improving the product’s time to market. Biopharma companies looking for a CDMO partner should prioritize facilities utilizing a digital twin to gain the greatest advantage from their fast, reliable production.
Cons
Any time a company engages with a third-party partner, they run the risk of being responsible for their contractor’s mistakes. In a complicated manufacturing process, there will inevitably be errors made. If the CDMO is not well-prepared to produce a new product, they may face delays securing raw materials or mistakes that waste products, resulting in higher costs and slower run rates. Even if the biopharma company didn’t make the mistakes themselves, they will still have to deal with the fallout. To avoid these scenarios, it’s important for biologics developers to thoroughly vet their chosen CDMO to ensure they have experience in their industry and comply with Good Manufacturing Practices. Some companies also choose to create a quality agreement, which thoroughly outline expectations for production.
Coordinating the tech transfer for drugs between the drug developer and CDMO can be a particularly complicated process – especially if the CDMO or biopharma company does not use a digital twin. Without a tool that can analyze and incorporate the data for the product’s specifications early in the transfer process, CDMOs may have to spend time once the product arrives to prepare their equipment to run the batch. If there are misunderstandings or details lost in translation, it can lead to costly mistakes or wasted product that could have been avoided. To create an easier tech transfer process, biologics companies can utilize a digital twin to deliver specific production data to their CDMO partner. You can learn more about the unique advantages of VirtECS digital twin technology for biologics processes in our short guide.
by Kelsey H | Aug 13, 2024 | Industry News, Planning & Scheduling
During the heights of the Covid-19 pandemic, contract development and manufacturing organizations, or CDMOs, experienced a historic surge in demand. Large pharmaceutical companies had raced to create vaccines and treatments, but once they were approved, those biopharma giants were unable to immediately fit mass production for such a high-demand product into their existing footprint. Instead, leading CDMOs like Catalent and Emergent BioSolutions strategically partnered with Johnson & Johnson, AstraZeneca, and Pfizer to provide drug substance production and fill-finish work to produce the first Covid-19 vaccines as quickly as possible.
With these CDMOs’ help, major drugmakers were able to bring these lifechanging products to market more efficiently and begin controlling the spread of the disease. By 2022, CDMOs had expanded their production capacity so much that they were collectively capable of producing more than 20 billion Covid-19 vaccine doses each year, according to MedCity News.
Years later, the surge in demand for Covid-19 vaccines and treatments has slowed. As a result, CDMOs have seen a slow decline in work after experiencing all-time high production demands. However, due to their flexible and adaptable business model, the CDMO industry is ripe for growth and innovation. According to analytics firm Evaluate, the CDMO market is projected to outpace the overall pharmaceutical industry’s growth through 2028.
As CDMOs find themselves at a crossroads on how to build on their work during the pandemic, many are investing in digital twin technology. A digital twin can help CDMOs navigate the most optimal ways to allocate their resources and priorities to best position themselves for the post-pandemic future. Let’s take a look at how CDMOs can best utilize a digital twin to generate new business growth.
Taking on Newly Developed Drugs
Over the past several years, large biologics companies have invested heavily in research & development to create new, patented drugs that treat more illnesses plaguing people around the world. As more new products get approved, these large organizations must suddenly find available capacity to coordinate production for their new drugs ready to come to market. Many pharmaceutical companies’ internal production sites are already near capacity with their current product lines and fitting in a brand-new drug may require more resources to accommodate than they have available.
In these situations, a CDMO is well-positioned to take over production for these drugs. CDMOs are especially effective at speeding up the time between a product’s clinical manufacturing stage and commercial stage. According to Lonza, working with a single-source CDMO can speed up time to market by an average of 14 weeks. For pharma companies, those 14 weeks represent less idle time and a faster return on their R&D investment.
In order to adapt their plant operations to take on projects for newly developed drugs, CDMOs will need a tool like a digital twin. With a virtual model of their site’s specific setup and constraints, these facilities can quickly identify slots in their schedule with available capacity. The plant can also use the digital twin to optimize their upstream and downstream processes to create more space. As an added benefit, optimizing processes can also further improve CDMOs’ time-to-market, which will help cement their competitive advantage as a production partner for drug developers.
Speeding Up Tech Transfers
CDMOs hoping to jumpstart growth and form partnerships with major pharmaceutical developers through the coming years must prioritize creating a smooth and comprehensive tech transfer process. A digital twin can help both the pharma partner and CDMO speed up the time devoted to tech transfer. Digital twins can first study the technology provided by the drug developer and recommend the best site for production based on the product’s unique specifications. With an optimal site selected, the tech transfer can be implemented smoothly with the fewest possible process modifications.
Several CDMOs have also found success approaching partner pharma companies while they’re still in development to begin the tech transfer process earlier. This approach gives CDMOs more control over the transfer process and provides more time to ensure their chosen site is prepared to start the new project. It can then simulate an ideal plan and schedule for the new project to ensure there are minimal disruptions and scheduling trade-offs. With less time needed to implement the new product’s technology once development is completed, the CDMO can bring the drug to market more quickly and meet more clients’ production goals.
Flexibly Switching Between Products
The nature of contract manufacturing means that plants must often switch between products without much notice. Managing a varied and revolving lineup of products effectively requires CDMOs to have a responsive and adaptable production plan. According to EY, many of the most successful CDMOs have been the ones that are able to account for flexibility and alter their production lines to meet the demands of a diverse range of projects. If CDMOs want to increase their capacity and take on more new projects, production flexibility becomes even more critical.
Using a digital twin, CDMOs can test any potential layout or plan for their manufacturing site. Operators can move equipment, product lines, employees, and other variables until they final the most optimal combination to achieve their desired flexibility. The digital twin will also account for the plant’s specific constraints and priorities, which helps schedulers find the most simple and cost-effective way to rearrange their production plan or take on a new project without disrupting current demands.
When speaking on a webinar for Evaluate earlier this year, Charles River Laboratories Vice President Matthew Hewitt said, “We need to continue to [embrace manufacturing technologies] if this field is going to reach its full potential.” Our digital twin software VirtECS is an ideal technology to help CDMOs achieve these growth goals. VirtECS provides flexibility, shared resource coordination, capacity analysis and many other features that address the specific needs of contract manufacturers. To learn more about how pharmaceutical manufacturers use VirtECS to schedule new products into existing production plants, watch our founder Dr. Pekny’s keynote presentation.
by Kelsey H | Jul 9, 2024 | Planning & Scheduling
When we talk to biologics companies about implementing VirtECS at their manufacturing sites, we always ask about the planning challenges they face. In those conversations, we hear frequently about issues with facility fit and tech transfer. Many hope to cut weeks or even months out of their lengthy tech transfer processes, which will help them save resources and speed up time to market. They also often struggle to determine how to fit a new, in-demand product into the schedule of an existing production facility without requiring costly adjustments or major disruptions.
Biopharmaceutical companies are experiencing these problems even more frequently and urgently as more therapies get approved. Building a new facility is extremely time-consuming and expensive, so it’s not always an option when a new product is approved for production, especially because delaying a product launch can negatively impact patient care. Given these stakes, it’s critical to execute an accurate facility fit analysis to quickly determine the ideal site for production.
Facility Fit Analysis with a Digital Twin
Highly regulated production steps and complex sub-systems make manufacturing biopharmaceuticals a particularly complicated process. Analyzing the plant’s many activities, constraints, and details to identify opportunities for new product production is nearly impossible to accomplish manually. When companies try to rely only on manual programs like Excel for facility fit, we often hear that it results in errors, delays, and further adjustments needed after the tech transfer begins. Manual programs simply cannot account for the level of critical detail present in biologics manufacturing environments.
Manufacturers that utilize a digital twin in the tech transfer process can avoid many of these pitfalls. By creating a highly detailed and precise process model, they can more accurately calculate the total capacity available, while also accounting for potentially deal-breaking constraints, such as hold or changeover times. A digital twin can also finish its analysis in just hours or days, while more manual processes may take months or even years.
How Sanofi Uses VirtECS to Fit New Products into Older Plants
As one of the largest biopharmaceutical companies in the world, Sanofi regularly introduces new products. Years ago, they needed to implement one of those new biologics products into an existing manufacturing site. Sanofi evaluated several software providers to assist in their tech transfer process, but they were either unable to the handle the site’s complexity or took too much time to complete the analysis. Then, they discovered VirtECS.
With VirtECS, Sanofi was able to turn around the facility fit analysis quickly. “By having this digital twin, we can rapidly simulate scenarios where we fit new products into old plants,” said Jon Forstrom, Director of Manufacturing Science and Technology at Sanofi. “Where it would normally take weeks or months to do a full analysis, we’ve turned around some of these analyses with VirtECS in a day or two.”
Real-World Implementation with VirtECS
Given its advanced analysis capabilities, VirtECS stood apart as the only tool that could meet the needs of a leading biologics company. With the tool in place, Sanofi could easily select the site with the most available capacity and most adaptable conditions to accommodate their new product. They then used VirtECS to test different ways to integrate their new product into the selected site. With each potential scenario, their team could measure the impact of the change and identify the best ways to add revenue from new products without jeopardizing the revenue earned from existing products. These details ensure that the tech transfer is completed as smoothly as possible with minimal disruptions.
The VirtECS digital twin also guaranteed that the resulting plan and schedule for Sanofi’s new product would work in the site’s real day-to-day operations and wasn’t limited to a hypothetical scenario. According to Forstrom, “With the power of [VirtECS], we could model variability to get a real-world answer and not an over-simplified computer answer, which is what you get with most tools.” The realistic plan helped employees on the plant floor accurately execute the schedule, minimizing the discrepancies and questions that often arise when implementing new processes into the real plant environment.
In addition to speeding up time-to-market and avoiding costly construction of a new plant, fitting a new product into an existing facility also helps maximize capacity at the site. As Forstrom explained, “I call it building a capacity roadmap – a roadmap from where we are today to achieving maximum theoretical capacity.” With VirtECS, Sanofi can make sure they’re getting the most possible output and profitability from their current resources.
Tech transfer and facility fit analysis represent just a small snapshot of VirtECS’ digital twin capabilities. The benefits of utilizing a digital twin for manufacturing planning are far-reaching, including optimized design of new facilities, debottlenecking, and smarter long-term decision-making. You can hear more from Jon Forstrom about how VirtECS has impacted Sanofi’s smart manufacturing initiatives by listening to his presentation with our co-founder, Dr. Joe Pekny, at the 2023 BioProcess International Conference.
by Kelsey H | May 14, 2024 | Debottlenecking, Process Improvement
Bringing these new products to the commercial market creates a wide range of challenges for leading biopharma manufacturing facilities. Plants operations can often look drastically different once a new commercial manufacturing run is added to production. Our colleague from Sanofi, Jon Forstrom, noted in a recent keynote presentation at the BioProcess International Conference that four in five biopharma plants no longer manufacture the products they were designed for. Instead, they now manufacture other, newer products.
In the second part of our new product development series, we examine ways the manufacturing environment must evolve to accommodate the transition from clinical to commercial manufacturing. We’ll also showcase the way digital twins can provide valuable time and cost saving support to facilities. According to McKinsey analysis, companies who utilize these digital resources to scale up production can see a 25 to 40 percent increase in plant capacity among other improvements in the most critical performance metrics.
Evaluating Supply Chain and Inventory Processes
When it comes time for a site to scale up manufacturing a new biopharma drug, it will be necessary to re-evaluate all elements of the existing supply chain. This could require using an alternate raw material supplier rather than the one used during the clinical phase if they cannot meet the expanded requirements. Depending on the ingredients of the new product, a facility may be able to identify a current supplier able to provide all the necessary materials for existing and new product lines. If a new supplier needs to be sourced, complexities could arise in receiving schedules compounding the initial uncertainty that comes with acquiring a new vendor.
If the vendor list does need to expand and raw materials start to arrive on different timelines, this could also require overhauling the inventory management system to account for the changes. Will supplies for the new drug arrive just as inventory levels for an existing product are at their peak? Does the facility possess the necessary equipment to accommodate the necessary hold times or temperature storage requirements?
With an advanced process modeling tool, planners can easily troubleshoot ways to account for changes in raw material deliveries and unforeseen storage bottlenecks. Planners can adjust the production schedule to relieve inventory pressure or expand the existing storage footprint to accommodate the new influx of materials. The site will also be able to evaluate improvements to their inventory system to handle changing ingredient storage requirements, such as longer hold times or temperature restrictions.
Reallocating Resources for Commercial Production
In addition to acquiring and storing raw materials, it can also be difficult for plants to adapt their processes to optimize the allocation of resources needed for scaling-up new products. Site leaders are often uncertain about how to best adjust labor and equipment schedules to meet the needs of an expanded range of products. If the new product demands a more skilled labor force, human resources may have to invest time to reskill or upskill the existing workforce. Operations leadership might also look to invest in automation to reduce the burden on HR. If the site lacks adequate labor or equipment resources, the plant will need to determine the most optimal production compromise until the shortage can be corrected.
Leveraging a highly accurate, virtual model of a real-world manufacturing plant will provide a greater understanding of main line activities and underlying detailed process dynamics. Because it’s an exact replica of the real site, planners can use the digital twin to test possible changes to best suit the new products. Running experiments with different allocations of labor and equipment can determine the optimal configuration to accommodate the new product. An advanced tool like VirtECS will also identify the most efficient production path to maximize output if critical resources are limited and cannot be addressed immediately.
Adjusting the Production Schedule
Even with all the correct materials and resources in place, facilities often face a lot of uncertainty determining the optimal times to start the various production runs. Planners may try to slate the new product into the various openings presented by the current production schedule. This approach can create unnecessary bottlenecks or challenging changeovers in the overall production schedule. Further, this could decrease run rates, hurt overall plant production output and increase product lead times.
Planners may not immediately recognize the facility is running at suboptimal production because there is a lack of historic data to show what the plant is capable of producing with the new product included. This could force leadership to underestimate how much product can be delivered to market.
Digital twins take the guess work out of production scheduling, even with a new product. Planners will always know the true maximum capacity of their plant’s resources, making it easier to find opportunities to improve the current manufacturing yield and debottleneck production. Consistently identifying and taking advantage of efficiencies in the manufacturing process will lower the overall cost of producing the new drug. Every additional cost-saving effort can often mean the difference between profitability or loss.
VirtECS has been implemented in sites for several global manufacturers to solve their challenges in scaling-up production of new products. In his keynote presentation, Forstrom noted that with the VirtECS digital twin, “We can rapidly simulate scenarios where we fit new products into old plants. Where it would normally take weeks or months to do a full analysis, we’ve turned around some of these analyses with VirtECS in a day or two.” To hear more about Forstrom’s experience using a VirtECS model at Sanofi, you can watch his full presentation here.
by Kelsey H | Apr 16, 2024 | Planning & Scheduling, Process Improvement
The past several years have been a time of accelerated innovation in the biopharmaceutical industry and new drugs are being developed at a rapid rate. According to Deloitte’s 13th Annual Pharmaceutical Innovation Report, the top 20 global pharmaceutical companies spent a combined $139 billion on research & development in 2022.
However, an observation coined “Eroom’s Law” shows a declining efficiency in bringing new drugs to market. The trend, named because it is the inverse of Moore’s Law in microelectronics, shows the cost of developing a new drug has doubled every 9 years. According to a 2016 report published in the Journal of Health Economics, it cost approximately $1 billion to bring 30 new drugs to market in 1950. Today, it costs nearly $3 billion to develop and successfully launch one new drug.
In the following series, we’ll break the life cycle of a new product into two distinct stages: clinical manufacturing and production scale manufacturing. We’ll analyze the critical components of each phase and how a process modeling tool can optimize your facility for success. To begin, let’s look at a new product ready to move from the lab into the manufacturing environment for clinical trials.
Transferring Tech to the Manufacturing Team
One of the most crucial stages in the development of a new drug is the shift from lab-scale to clinical manufacturing. Central to this transition is the tech transfer process. During this phase, all the product information and procedures created by the development team in the lab must be shared with the manufacturing team. This knowledge will be combined with equipment data and production practices to develop a process capable of meeting the supply needs of the upcoming clinical trials.
A significant amount of documentation and knowledge must be organized and transitioned for the transfer to be successful. A process modeling tool or digital twin can be a valuable tool for logging process data and supporting the collaboration between the development and manufacturing teams. A failure at this stage could create a loss of relevant technical knowledge, allowing previously solved problems to reemerge. These setbacks hinder the ability to begin manufacturing the necessary supply of product for clinical trials, delaying one of the most time-consuming parts of a drug’s journey to market.
Unfortunately, industry estimates show these delays are all too common – nearly 85% of all clinical trials experience delays. According to a 2022 report from Statista, the average clinical trial already lasts over 7 years and costs nearly $19 million to complete. Additional delays to the start of a clinical trial program will only compound the problem and jeopardize the journey to recoup the billions invested during development.
Selecting the Optimal Clinical Manufacturing Facility
Once the tech transfer is complete, the manufacturing team should begin a facility fit assessment to ensure the plant can complete the manufacturing process. This might entail evaluating multiple facilities to determine the optimal location. Leadership will look at the availability of all necessary equipment for production and material storage. The site’s current production schedule and overall capacity will also need to be taken into consideration.
Often these assessments can be supported by a digital twin. These virtual models can quickly identify the optimal facility already prepared for the clinical manufacturing needs. If potential gaps or risks present in all facility options, the digital twin can run experiments adding equipment or modifying the plant’s footprint to produce the optimal solution. Since this analysis can be performed in a matter of hours, facility fit evaluations can be completed early in the transition to clinical manufacturing. If these gaps are not discovered until later, they could lead to lengthy design and construction delays.
Mastering Process Design and Qualification
It has been said that clinical trials showcase a new drug’s efficacy, while the clinical manufacturing process determines its ability to succeed in the market. A great deal of scrutiny is placed on the manufacturing process as a new drug seeks approval, and regulators need to be convinced a facility can deliver a consistent product that meets the necessary quality standards. This entails minimizing variations in product batches that could compromise drug quality and risk process failure.
Digital twins become a useful tool during the process design phase because they allow developers an opportunity to test how different components of the manufacturing process will impact product variability and yield. Running these experiments in a digital environment could save an organization a significant amount of time and reduce the amount of costly process qualification runs needed from a test facility. This digital model will lead to a better understanding of the entire manufacturing process and allow for the implementation of stronger control strategies to keep every batch within specifications. A McKinsey analysis in conjunction with the World Economic Forum found that leading biopharma companies who utilized these digital tools saw up to a 50% reduction in deviations, and an 80% reduction in recurring deviations.
Designing for Flexibility
Manufacturing during the clinical stage of product development requires a great deal of flexibility. As data begins to emerge from phase I and phase II trials, formulation issues might be identified, and batches may begin to vary in both composition and size. If a facility is not prepared to adapt to these changes quickly, the entire clinical phase of development could suffer from significant delays and increased costs.
Without access to a digital twin, production decisions are often made that overcompensate for the new demands of the clinical trial and generate excessive waste. This excessive waste could reduce the budget available to expand the trials to new sites, slowing the progression toward drug approval. It could also place increased demands on the equipment within the facility and create cascade disruptions for other products in the plant’s portfolio.
Preparing For Scale-Up
While addressing the demands of clinical development, it is essential keep commercialization in mind. Much of the process design stage requires focus on data collection and regulatory compliance, leaving little room for long-term process optimization. Many facilities will focus on getting clinical studies underway quickly and delay consideration for scale-up needs until late into Phase II trials. They might arrive at a validated manufacturing process which meets the needs of the clinical stage, but it is often overly complex and lacks efficiency.
Faced with an urgent need to scale-up, facilities will often resort to simply stretching the small-scale clinical manufacturing operation to the new commercial scale demands. Many of the components in the process quickly become inefficient with this approach to expansion and increased quality-control issues risk the integrity of your new product. Making changes to the existing manufacturing process can be extremely costly, especially if a comparability bridging study is required to approve the new process.
Developers should utilize a digital twin during the process design phase to plan for long-term commercialization. Allocating time to this planning effort might slow down the early stages of process development, but it could avoid costly inefficiencies and time-consuming setbacks when demands of scale-up production arise later. A virtual model can quickly identify risks for product deviations or production bottlenecks when the existing processes are scaled up. Planners can troubleshoot solutions and identify any necessary capital investments early before they can lead to production delays. Despite the initial investment of time, this step ultimately speeds up a new product’s time to market.
Maximizing Revenue Potential
Digital twins are a critical tool for navigating new products through the clinical development phase towards registration. They also can have significant implications for company revenue. It has been estimated that leading pharma companies can lose up to 80% of revenue when a patent expires. EY reports over the next 5 years, an astounding $356 billion in worldwide sales are at risk from patent expiration. Utilizing powerful modeling tools like VirtECS to identify avoidable setbacks in the early stages of product and process development can add up to millions, or billions, of dollars in additional revenue when the clock is ticking.
If you’re interested in learning more about how VirtECS can improve your new product development process, download our short overview guide and check back for part two of this series next month.
