Agnes Shanley is senior editor of BioPharm International.

Agnes Shanley

Like many business practices brought to the world by Japan in the 1980s, just in time (JIT) brought agility to many industries. For pharma, however, the term often triggers fear and loathing, given chronic and ongoing shortages of comparator drugs and investigational medicinal products (IMPs).

Since the COVID-19 pandemic began, however, more companies have been embracing JIT for clinical trial supply and distribution operations. Both the unique challenges posed by the pandemic and the European Union’s new Annex VI clinical trial labeling regulations have been driving this change. In the past, labels were only required on secondary packaging; however, the new regulation will require labels on both secondary and primary packaging (i.e., the vials, blisters, and metered dose inhalers containing the therapeutic), explains consultant Steven A. Jacobs, president of Global BioPharm Solutions.

Under the regulations, if new stability test data dictate the need to update a label for primary packaging, patient kits will need to be opened, which would be considered a manufacturing process requiring certification by a qualified person (QP), Jacobs explains. However, pharmaceutical QPs are not at clinical sites, so this impasse could potentially affect product quality and supply.

Meanwhile, pandemic-driven changes in clinical trial design, including greater use of pooled trials and direct-to-patient (DTP) distribution, have piqued interest in JIT. “Companies are shifting to smaller packaging runs and pooling supplies to get supply chains running as efficiently as possible,” Jacobs says.

Where, for some,JIT may conjure images of slashing inventories of urgently needed medications, in clinical trial operations, it signals the move to a less wasteful distribution model. Under the old “push” model, an innovator would announce that it was enrolling patients for trials at, say, 100 sites, and supplies would be sent to all of those sites, Jacobs explains. In the end, however, the Pareto principle would usually rule, and 20% of sites would end up enrolling 80% of the patients. “These days, especially with oncology trials and comparator drugs that cost millions of dollars, we can’t have materials sitting in depots or on sites and not being used. These are all key factors that continue to make JIT extremely advantageous,” he says.

With JIT, distribution is based on a “pull” approach. A master document is created in advance, and all packaging and labeling is standardized so that it can be made on demand before being shipped to the clinical site or patient’s home. The economic motivation for JIT is compelling. According to Frost and Sullivan, one third of global clinical trials were disrupted in 2020, affecting some $3 billion in new product revenue (1). Benefits of a “pull” approach include a 75% reduction in overall clinical trial timeframes and reduction in waste and rework, according to Natalie Balanovsky, JIT Solutions Manager at Almac Clinical Services (2). This is especially important in an environment in which each day of delay in a clinical trial costs $37,000 and between $600,000 and $8 million in lost opportunities (3). Research has shown that 85% of all clinical trials experience some kind of delay, 94% of them for a month or more (4).

On the logistics side, Marken has been applying pull concepts to maximize the flexibility of its clinical trial sourcing, increasing the number of supply options available to clients, according to Nina Vas, vice-president of clinical distribution for cell and gene therapies, who discussed trends in a February 2021 webcast (5). For direct-to-patient distribution, which has become much more important during the COVID-19 pandemic, the company relies on strategically placed regional and global networks of depots throughout the world.

Despite its benefits, JIT cannot work without early collaboration, communication, and planning. For one thing, Jacobs says, it’s crucial that all packaging to be used in any clinical trial be in the same configuration. He recalls one clinical trial that started with2-mL vials but then switched to 2-R vials. Even though the two types of vial are similar and R vials offer some improved capabilities, changing midstream added significant complexity because placebo vials had to be manufactured to match the new vials. “There are so many different configurations for drug delivery that it can be difficult to do JIT without standardizing. We need to get everyone to agree, early on, on what packaging will be used; how we get the new drug to the patient; and how patients will take the treatment once they receive it,” Jacobs says. Once agreement is there, he says, JIT principles can be applied to any operation from filling to labeling and kitting.

Risk assessment needs to be conducted as soon as possible in the planning stages, says Jacobs, which is much easier said than done when a company is under pressure to meet the types of clinical targets that have been set during the COVID-19 pandemic. He suggests following the principles outlined in the International Council for Harmonization’s (ICH’s) Q9 guidance on risk-based quality management and assessment (6), and gathering all stakeholder groups together for a brainstorming session to ask: What’s the worst that can happen; how likely is it to happen; and what can we put in place to prevent it from happening, or to mitigate the risk?

For the contract development and manufacturing organization (CDMO), Catalent, risk assessment and mitigation has been crucial to ongoing trial successes, says Stephanie Graham, director of clinical supply management. For ongoing studies, she says, the primary focus has been on whether it is safe for patients to continue to visit sites, especially those who might be at greater risk if they contract COVID-19. She also notes the importance of determining whether the frequency of planned visits is necessary.

Clearly, it became extremely difficult to conduct clinical trials after the pandemic’s impacts were first felt in the second quarter of 2020. The combination of uncertain patient visit scheduling and transportation disruption forced sponsors and their contract partners to perform a delicate balancing act: preventing supply wastage while ensuring that enough buffer supply was available in case of shipment delays or country lockdowns, says Graham. For trials that were still recruiting patients, enrollment slowed, driving the need for specialized packaging campaigns to extend the shelf-life of IMPs, she says.

Sponsors had to make hard decisions about which studies should continue and which should be delayed or canceled altogether. “For those studies that can progress, we have jointly had to answer how, why, and with what changes. Sometimes it has been necessary to explore alternative strategies, such as using decentralized trial designs to reduce risk and maintain continuity,” Graham says.

Raw material availability also posed problems, resulting in the need to manage shipment delays caused by disruption in raw material production or transportation disruption for normal routes, explains Mathias Dassel, storage and distribution manager for Catalent, based in Germany. “Distribution of pharmaceutical supplies could take longer than expected, and transportation costs may increase for high-risk regions when import/export restrictions are introduced because of the pandemic. In such cases, it has become extremely important to manage supplier and courier relationships effectively,” he says.

At the height of the COVID-19 pandemic in 2020, the number of daily commercial flights—which are used to ship 70% of the medicines used in clinical trials—was reduced to 10–15% of its pre-pandemic levels, says Jacobs. Fulfilling orders required more time, he says, typically two to four weeks, instead of the two-to-four-day pre-COVID norm. Some companies even booked chartered flights at a cost of over $100,000 each time, to ship their medications, Jacobs says. “We’re now at 25–30% of where [commercial] flights were before COVID-19, but gaining global acceptance for DTP was an amazing achievement,” he adds.

Sponsors and contract partners first began to see a major increase in delayed patient visits in China, from January through April 2020, says Sylvain Berthelot, global head of IRT (interactive response technology) and electronic data capture (EDC) solutions for Calyx. His company, an e-clinical and regulatory solutions provider, was spun off by Parexel and became an independent firm in January 2021. “In Italy and Spain, for example, we didn’t see the same number of delayed visits in the Spring of 2020, despite lockdowns, because sponsors focused efforts on ensuring that patients were supplied with medications directly,” Berthelot says.

Changes in trial methodology, in the context of the unfolding COVID-19 pandemic, also had a major impact on clinical trial operations. With some clinical testing being done in parallel, Berthelot says, sponsors were using more master protocols, which allow different compounds to be tested on the same group of patients or vice versa. “These protocols enable more program-level supply management, which reduces drug wastage, but make managing medications more complex, both for sponsors and for IRT systems, [used to manage clinical trial patients and supplies]” he says.

In the end, one of the most dramatic changes that occurred in clinical trials supplies and distribution during the pandemic was higher acceptance and demand for DTP shipments. The DTP model eliminates a major problem with clinical trials: getting patients on site consistently, without attrition, says Jacobs.

For years, many in the industry had discussed decentralizing trials, and regulators such as FDA and the European Medicines Agency supported the idea. The model was accepted in the United States, yet the pace of its adoption around the world was slow before the pandemic, says Jacobs. After the COVID-19 pandemic began, however, countries such as Italy and Russia, that were originally very resistant to the DTP concept turned around. Out of 195 countries, the number of those permitting DTP shipments doubled, to over 90 in 2020, he says. “This was amazing to see, and on the clinical operations side, we are all supporting this trend to make sure that we don’t go back to the old ways,” Jacobs adds.

Another achievement was increased acceptance of JIT and on-demand packaging, and more use of planning, forecasting, and simulation tools, says Jacobs.

For both sponsors and contract partners, flexibility has become key, as have proactive and clear communication and collaboration, Graham comments. Where possible, she says, DTP services can limit the need for patients to visit drug dispensing sites, allowing DTP and site-to-patient distribution strategies. For new trials, building such supply strategies within the protocol, the randomization and trial supply management, and the IRT design allow flexibility to minimize risk in the future, she says.

However, that flexibility should have some limits, Graham says. “Some sponsors are providing patients’ full treatment supply at the first visit. Although this approach can work, it is not optimal for an investigational product with a limited shelf life, or one that requires temperature monitoring. It is up to CDMOs and clinical supplies managers to work collaboratively with customers to determine the optimal solutions that work best for patients, sites, and the sponsor,” she adds

Since the start of the pandemic, Graham has seen more sponsors use adaptive designs in clinical trials. In addition, she remarks, many are exploring ways to provide healthcare remotely through DTP or site-to-patient distribution strategies of the clinical trial material/investigational drugs. For biologic drugs, she also sees greater use of autoinjectors for non-COVID-19 therapies, and IRTs built to handle the additional functionality required. In terms of small-scale manufacturing, Graham says, Catalent has developed manufacturing processes that permit switching to different batch sizes using the same manufacturing lines to meet the challenge to scale production up or down quickly.

For a risk-averse and often siloed industry, pharma made great progress in removing the barriers that can separate different stakeholders in clinical trials management and operation. In a typical scenario, Jacobs says, clinical operations used to be in one area, and chemistry, manufacturing, and control in another, with the clinical supply chain department functioning as the bridge to success. During the pandemic, says Berthelot, “vendors and sponsors are functioning more as part of a single team.”

That all this change could take place during a time when people didn’t meet face to face is significant, Jacobs says. “Before the pandemic, one could hear ‘weak signals’ of developing problems, just by overhearing snippets of conversation in the hallway or cafeteria. This gave teams more time to plan remediation. You can’t do that on Zoom,” he notes. There is also more acceptance of the concept of clinical operations as a work in progress, and an understanding that procedures may have to change. “A few years back, sponsors used to wait until they had the perfect protocol before starting a trial. Now they’ll start recruiting for a trial that they know that they will have to change,” Berthelot says.

On the technical side, better integration between IRT and EDC has seen substantial improvement, reducing errors and the need for data reconciliation between the two systems, and enabling more automation, says Berthelot.

In the future, he sees technology playing a more important role. “Real-world data are already becoming incorporated into more clinical trial designs. Use of machine learning will improve patient recruitment and site selection, and, from the supply chain perspective, will help reduce drug wastage and better identify risks that could have an impact on the supply chain,” he says.

Post-Pandemic Global Healthcare Market Outlook

,2020.
2. Almac, “Practical Application of JIT manufacturing in Clinical Operations,” an Almac webcast, August 19, 2000
3. O. Johnson, “An Evidence-based Approach to Conducting Clinical Trial Feasibility,” 

 (London) (2015).
4. A. Grignolo, “Managing Continuity in Clinical Trials in the Covid-19 Environment,” 

, May 20, 2020.
5. Marken, “Decentralized Trials: How to Develop a Flexible Supply Chain,” xtalks.com, Feb 2, 2021. 
6. EMA,“ICH Guidance on Quality Risk Management,” 

When citing this article, please refer to it as A. Shanley, “Necessity Drives Just-in-Time Approaches to Clinical Trials Supply," 

Articles

The COVID-19 pandemic is pushing more companies to adopt just-in-time practices, but success demands careful upfront risk assessment and planning.

Necessity Drives Just-in-Time Approaches to Clinical  Trials Supply 

	The past few years have brought great change to clinical trial logistics, particularly the move to direct-to-patient trial models. Increased development of personalized medicines, including gene and cell therapies, has required closer coordination and collaboration between distribution partners to ensure strict delivery timelines and end-to-end temperature controls. Cold-chain transportation specialists have adapted to these changes, investing in new technologies and programs (

).  But in 2020, the COVID-19 pandemic has presented new and unprecedented challenges. Given the strictures of social distancing, demand for direct-to-patient (DTP) shipments increased sharply, at a time when travel bans were in effect around the world, and commercial airlines had stopped a number of commercial shipping routes (

	This article highlights some of the approaches that cold-chain specialists are taking to the limits posed by the pandemic.  Sharing their insights with 

 are Sharon Courtney, logistics services manager for Almac Clinical Services; Alex Guite, vice-president of services and alliances for World Courier; Eric Valentine, vice-president of clinical supply services at Catalent, and Ariette Van Strien, president of Marken. 

:  What are the greatest challenges that the COVID-19 pandemic has posed for your programs?

): Internally, our first real challenge when the pandemic began was understanding what we would need, globally, in order for our team members to work remotely at all of our sites. We knew that some (e.g., site staffers, drivers, and warehouse workers) would need to continue to be on-site. We procured laptops and ensured that they were encrypted and made available, quickly. We also optimized scheduling and shifts for safety and efficiency. 

	Because domestic and international flights and air shipping lanes were interrupted or stopped, we needed to choose alternatives. In some cases, we rented our own charters; in other cases, we coordinated with UPS, our parent company, for alternative flight options for Marken shipments through their network.

	In addition, the immediate greater demand for DTP services required us to address important questions regarding our supply of temperature-controlled plastic shippers and GPS trackers, as well as staff training. We rolled out DTP training, which was already in place in approximately 57 countries in 2019, to over 80 countries, qualifying local transportation and supply-chain partners.

	We standardized processes to reduce the customization required for each shipment and customer. For instance, we selected one type of temperature monitoring technology, and one standard approach for handling any temperature excursions. 

	We also focused on key locations throughout the world. For example, in Asia, we chose Singapore as a central point from which to ship products.  The greatest challenge was ensuring constant communication with investigator sites. Sites often call in the morning requesting service and normally, we’d complete shipments by afternoon, but, when commercial airlines were down, we couldn’t always arrange things in just a few hours.

): Shipping products across international borders has created some logistical hurdles, particularly because certain countries have limited passage to prevent further spread of the virus. In some cases, these challenges have tripled the time it takes to manage a shipment, but we’ve been able to identify alternative routes to ensure that we’re meeting country-specific regulations and preventing delays and temperature excursions. Even as commercial flight availability has been reduced, we’ve been able to maintain air connectivity by booking space on airlines across a range of international carriers, which allows us to pivot based on the latest conditions and product needs. In fact, through our carrier-agnostic approach and contingency planning, we haven’t declined a single shipment, ensuring every patient has access to critically needed treatments.

(Catalent): The tightening of international borders, restrictions on travel, and a major reduction in airline capacity and frequency have presented the most significant challenges to the clinical supply chain. From a supply perspective, Catalent has been adding buffer stocks of critical materials and components to protect against the risk of stockouts. We have also seen the supply of some commercial drugs used as comparator products in clinical trials tighten up as manufacturers devote more production time to COVID-19 priorities, as well as individual countries designating existing medications as COVID-19 treatments. In these instances, we are working with our customers to alter their sourcing plans and to ensure that they have a robust strategy and sufficient material to support their ongoing trial needs.

	From a distribution perspective, social distancing requirements and significant work restrictions in some countries have impacted our facilities’ processes and workflows. To ensure worker safety, we have realigned several aspects of our operations so that we can be flexible to the changes in our clients’ clinical trials, while also being in a position to rapidly accommodate the needs of clients looking to develop products for the prevention and treatment of COVID-19. 

	For example, due to the restrictions on the number of employees allowed on-site, our Singapore facility has recently moved to a three-shift work force to ensure that we can process all work orders on time, without any impact on ongoing trials. 

: The pandemic threatens the continuity of supply for vital medications to patients enrolled in existing clinical trials around the world. Quarantines, travel restrictions, site closures and limited site personnel are some of the factors contributing to this increased level of risk.

	Changes in patient recruitment levels, study start-up activities, maintenance requirements, and possible changes to the timelines for key protocol milestones are all potential outcomes, as sponsors shift R&D priorities to accommodate the realities posed by the COVID-19 climate. Coupled with this is the level of urgency with which many sponsors are responding to the call to develop vaccines and treatments for the virus. 

: How are you working with partners to improve results?

): We’ve taken a number of steps (e.g., simplifying onboarding for new clients to allow faster program startup).  We have also worked closely with our clients as the guidelines changed in many countries to allow for adaptive trial models, permitting patient home deliveries and Marken’s nursing services to reach patients.

	In packaging, we re-forecasted the quantity and types of packaging that we would need to ship temperature-controlled drugs worldwide as the pandemic spread. Many reusable packaging options had to be moved to single use, but we also increased investment in reusable packaging and temperature monitors to ensure safe delivery in all regions around the world, and made sure that the necessary packaging was available in each country in which we operate. Our efforts so far have allowed 80% of staff to work virtually, and prevented any disruption in services.

): Recent studies (1) have found that nearly 80% of clinical research study sites have cancelled or put on hold at least one of their current clinical trials. However, we now find that many of our customers are continuing to collect data to support future therapy development.  Since the pandemic began, we’ve seen a five-fold increase in daily DTP shipments.In these cases, World Courier manages treatment deliveries to, and sample collection from patients’ homes. We have also supplied our drivers with personal protective equipment and implemented a contact-free pick-up and delivery process to protect the health of our associates. 

	Collaboration is key when mobilizing quickly during this fluid environment. That is why it is more important than ever for specialty manufacturers to stay in constant contact with their logistics partners. We are constantly looking at our existing systems to enhance the way we communicate and support customers. For instance, with worldwide flight suspensions, we’ve adapted the technology we use to monitor and manage travel to give our teams more line of sight into scheduling data. This change will allow World Courier’s teams to evaluate schedules from over 950 airlines and provide customers pro-active and accurate information about route mapping.

): One of the key changes in demand we have seen during this pandemic is an increase in requests from trial sponsors for clinical site-to-patient (STP) and DTP supply services. It appears that COVID-19 has accelerated the way that clinical trial sponsors, as well as some local regulatory authorities, think about STP and DTP as potential options to support patient needs. It will be interesting to see whether the industry and regulations ultimately change to facitate adoption of these models beyond the COVID-19 pandemic.

	Open communication with customers has helped ensure we reduce risk in the supply chain. As an example, we recently had a discussion with one of our suppliers, which needed to alter the processing of heavy shipments in order to safeguard its employees using social distancing. As a result, we are making more frequent shipments in smaller payloads so that multiple workers are no longer required to process an individual container.

	Early on in the outbreak, Catalent began an in-depth review of our operations and supply chains, working with our suppliers to consider their supply chains too. That has remained an ongoing process, and to date, we have not identified any significant risk, delay, or concern that may have a substantial effect on delivery of any product or clinical trial supplies. Catalent also formed a multi-disciplinary coronavirus response team made up of senior leaders that reports directly to our CEO. Reaching into all facets of the organization, and continuously monitoring the global situation, this team swiftly executes mitigation activities whenever and wherever they are required.

): One way in which we are helping sponsors streamline processes and improve ability is via Almac ONE, which aligns the digital (forecasting and interactive response technology) and physical (packaging and distribution) aspects of supply chain management, which have traditionally been managed in separate silos by separate vendors. Use of Almac ONE has reduced study set up time for several sponsors, with one COVID-19 trial sponsor up and running in just two weeks. In addition, Almac Adapt, our just-in-time manufacturing service, is helping sponsors package clinical supplies with increased agility. Site-support strategies such as remote drug monitoring have also been introduced to maintain blinding and dosing protocols without the need for the clinical research monitor to physically visit the site.

	1. Association of Clinical Research Professionals Survey, “Survey Shows One Third of Clinical Trial Study Sites Fear Total Closure; 77% Indicate at Least Some Ongoing Research Trials Have Been Impacted Due to COVID-19,”


	Vol. 44, No. 6
	June 2020
	Pages: 46-52

	When referring to this article, please cite as A. Shanley, "Finding New Efficiencies in Clinical Trial Logistics," 

The COVID-19 pandemic has led to increased demand for direct-to-patient shipments, challenging cold-chain specialists to become more agile and to strengthen their global distribution networks.

Finding New Efficiencies in Clinical Trial Logistics

	Public pressure to reduce drug costs has led to a number of proposals to reduce drug prices.  Among the alternatives discussed so far have been 

 price controls and synching prices to those in other global markets. In December 2019, the United States Department of Health and Human Services introduced a Safe Importation Action Plan outlining two pathways for allowing the safe reimportation of lower cost drugs from Canada (1).

	Although these proposals have not yet become law, biopharmaceutical company executives are reacting to regulatory uncertainty by focusing more intensely on reducing operating costs, according to John Boyd, CEO of the Boyd Company, a site selection advisory company. “Operating costs have always been important for life sciences site selection, but they’ve never been as important as they are now, as the industry focuses on price reduction. Many of our pharma clients see site selection as a preferred market-based way to reduce operating costs,” he told 

	Operating costs vary highly among major life sciences sites (Figure 1), and labor costs (Figure 2) make up roughly 60% of those costs, says Boyd. In the US, Austin, TX and Raleigh, NC are currently among the fastest growing metropolitan areas, and both are attracting biopharma investment. So far, the Raleigh-Durham area in North Carolina offers the lowest operating costs of any US location, Boyd says, and boasts the presence of some leading universities such as Duke, University of North Carolina, and North Carolina State. Eli Lilly recently selected Raleigh as the location for a new $474-million, 462-employee facility to manufacture injectable and other diabetes therapies (2). The Austin area, meanwhile, is seeing increased investment in biopharma, due to life sciences developments such as the University of Texas’ Dell Medical Campus and facilities affiliated with nearby Texas A&M.

	Boyd’s latest analysis compared major operating costs in 2019 for a representative 300,000- square-foot biomanufacturing facility employing 300 hourly staffers. Examining costs for 25 US, European, and Asian locations research found that they ranged from $58.7 million in Copenhagen to $13.7 million in Bangalore. In the US, costs ranged from $55.4 million in New York to $37.2 million in Raleigh/Durham, NC.

	“In the US, there has already been a mass exodus of human capital to states that have right-to-work laws,” says Boyd. These laws establish “at will” employment and make membership in labor unions voluntary, reducing union power as well as labor costs for employers (3).  There has also been a trend to “reshore” some operations and bring them back to the US in lower-cost labor states, he says.  “For areas such as Bangalore in India, the initial numbers may be compelling, but investors have found additional hidden costs,” he says, including training and, in the US, boosting corporate participation in federal procurement programs has become a political issue that has both Republican and Democratic party support, he says. Boyd notes that new life science regional hubs may be on the horizon, depending on how new regulations take shape in the US.  Amgen, for example, is building a new 1600-employee facility in Greenwich, RI.  Oher potential areas for future development could include Southern Florida, Phoenix, AZ, Las Vegas, NV, and the Winston-Salem area of North Carolina near Wake Forest University.

	In the meantime, many municipalities are getting the message loud and clear, to hold the line on new corporate taxes, says Boyd. New Jersey, which is the nation’s largest biopharmaceutical and pharmaceutical development and manufacturing center, may offer a cautionary tale.

	The state recently increased corporate and personal income taxes, on top of high property taxes, making it more difficult for companies located in the state to remain competitive and reducing disposable income for working professionals, says Boyd.  Over the past 15 years, he noted in a December 2019 interview (4), higher taxes in the state have resulted in $30 billion in personal income moving to lower cost, more corporate friendly locations. New Jersey officials have also proposed a millionaire’s tax that would impose 10.75% in income tax on individuals earning $1 million per year or more. The proposed regulations could affect 20,000 state residents, many of them business owners, and could decrease investment in the state. New York, California, and Massachusetts already have similar laws in place.

	1. "HHS Announces New Action Plan to Lay Foundation for Safe Importation of Certain Prescription Drugs,” Press Release, July 31, 2019.
	2. North Carolina Biotechnology Center, “Lilly Building $474M Pharma Factory in RTP, Hiring 462 Workers,” Press Release, Feb. 11, 2020.
	3. Vittana, “20 Pros and Cons of Right To Work,” vitanna.org, Feb. 11, 2020.
	4. New Jersey News Network, “Murphy Renews Hope For Millionaires Tax,” newjerseynewsnetwork.com, Feb. 11, 2020.

As politicians focus on drug cost reduction, biopharmaceutical companies in the US are moving to states with lower taxes, and relocating some facilities that had been offshore.

Lower Taxes, More Flexibility Crucial to Retaining Pharma Employment

In less than four decades, biopharmaceutical manufacturing has traveled light years from its origins in facilities such as Amgen’s Building Six in Thousand Oaks, California, which manufactured 200 grams of recombinant human erythropoietin per year with two stainless steel tanks and 3000 roller bottles (1). As increasingly sophisticated equipment was developed for upstream and downstream processing, standardization allowed for the engineering of new processes and platforms and faster development and scale-up.

	Cell therapies, genetically modified cell therapies, gene therapies, and tissue engineering now stand where biotech was in the late 1980s; the first products have been commercialized and manufacturing them has become a question of doing whatever works. 

	“The greatest success so far has been the fact that the industry has even launched the cell and gene therapy products that it has introduced. Regulators have accepted them, and developers have figured out how to get them to the market,” says Phil Vanek, general manager of cell and gene therapy strategy, GE Healthcare. 

	The next phases of industrial development, Vanek says, will focus on streamlining the supply chain and the creation of increased therapeutic value; engineering new therapeutic value into the cells to achieve the highest potency per amount of production time and cost; and connecting both of these efforts, via an intricate pathway, directly to patients.

	“We must draw on the valuable experience that we acquired in biologics manufacturing, where we evolved from small to large volumes and from stainless-steel to single-use platforms for flexibility,” says Lisa Krallis, head of business development, cell and gene technologies at Lonza Pharma & Biotech.

	As the cell and gene therapy market grows, substantial pressure is on developers to meet commercial demand and supply clinical quantities of material. By the end of 2018, 1028 global clinical trials were underway for cell and gene therapies, 58% of them for oncology therapies; 57% of them in Phase II, and nearly 9% in Phase III, according to the Alliance for Regenerative Medicine’s 2018 Regenerative Medicine Data Report (2). That year, more than 906 companies focused on cell and gene therapies, generating $19 billion in merger and acquisition activity and $13.3 billion in corporate financing for research and development, up 73% from 2017.

	Meeting increased demand will require a one-to-two-orders-of-magnitude improvement in gene therapy vector manufacturing, and a similar reduction in cost, as Peter Marks, director of FDA’s Center for Biologics Evaluation and Research noted at the 2018 Galien Foundation’s Forum (3). “Platforms need to become standardized, industrialized for yield, and then optimized for complexity,” says Krallis.

	Today, efforts focus on improving existing manufacturing platforms for both patient-specific, or autologous therapies, and allogeneic treatments designed for many patients (4). They include 

 adeno-associated viral vector (AVV) technology, which enabled the commercialization of Spark Therapeutics’ retinal blindness therapy, Luxturna, which FDA approved in December 2017. Roche plans to acquire the company (pending approval by the US Federal Trade Commission) (5). 

 Lentivirus vectors, which modify cells that have been removed from a patient, then are combined with T or stem cells and injected back into the patient, an approach that Bluebird Bio is using for chimeric antigen receptor (CAR)-T cell therapies (3). 

	Novartis and Kite have developed faster autologous CAR-T processes, while ZIOPharm is refining its Sleeping Beauty non-viral gene transfer platform, which FDA approved for use in T-cell receptor cell therapy in June 2019 (6). That same month, FDA approved the first clinical trials using UCART123, an off-the-shelf, allogeneic cell therapy approach developed by the French company, Cellectis (7) that uses Talen, a proprietary gene editing technology. Trials are already underway for UCART19 and UCART123, other therapies that utilize the technology. 

	“With queues for new vector production frequently around 12 months, the industry isn’t where it needs to be in terms of production capacity,” says Andrew Bulpin, head of process systems at MilliporeSigma. “As a result, innovation focuses on improving scalability to enhance the amount of material produced per run.” Upstream, the best way to improve scalability is to move cell culture into suspension. “Current vector production is disproportionately done in adherent culture, which is only conducive to scaling out, not scaling up. There is also significant use of serum in cell culture media, which increases regulatory burden and creates a potential supply bottleneck,” says Bulpin. Moving culture into single-use bioreactors improves scalability and enables a shift to chemically defined media, solving a number of problems at once, he says. 

	For downstream processing, Bulpin explains, the picture is more complex because of the number of steps required in the workflow. “In addition to process complexity, there is a need to increase the scale that current unit operations can handle as well as to minimize the loss of vector in each unit operation. Innovations in chromatography and filtration will be important to achieving those goals,” he says. 

	Platforms specifically designed for viral gene therapy applications could address more of these challenges at once and will be essential for ongoing growth in the industry, says Bulpin. At this point, innovative therapies are still being developed in equipment that was designed for traditional biopharmaceuticals, and there is a disconnect. “In biologics, the cell is a byproduct, and material is purified by removing that byproduct,” explains Vanek. “In cell therapy, however, the cell is the final product, so we must be very careful to develop platforms and approaches that do not fundamentally change the biology of the cell. That’s a tall order,” he says.

	As more is learned about innovative therapies in the clinic, equipment will eventually be customized for use with cell and gene therapies, Vanek says.  “Every cell type will have a set of specific conditions that it thrives under, and those conditions will ultimately be developed into next-generation equipment, whether bioreactors, cell processing platforms, and ancillary materials, upstream and downstream methodologies, including everything from reagents to hardware, to consumables and software,” he says. 

	“In patient-specific therapies, you may not need more than a billion cells per batch, but if you start to scale up in allogeneic you might need hundreds of billions of cells per batch,” Vanek says. In order to scale up and increase the volumes of allogeneic cell therapies, manufacturers will need to be able to move seamlessly from adherent to suspension cell culture, says Krallis, and ultimately 2000 L single-use bioreactors of the type now used for viral vectors may be needed for allogeneic applications to achieve the required cell volumes. 

	“Suspension processes for allogeneic manufacturing have been established for some time, so there has been more work adapting processes for these needs than there has been for vector production,” says Bulpin. Closed, automated technology platforms will be critical in the future, he says.

	Autologous therapy development will not be one size fits all, says Krallis, who emphasizes the need for “mass customization,” which she defines as “automating processes while remaining flexible from the clinical-to-commercial phase and adapting to the quality of the raw material.” Lonza launched its closed, automated Cocoon platform (acquired via its purchase of Octane Biotech in 2018), which aims to help developers achieve this goal and is currently being used by Sheba Medical Center to produce autologous therapies (8). 

	Although most biopharmaceutical companies are adopting automation, cell and gene therapies pose challenges, says Bulpin. “Unlike monoclonal antibodies that utilize robust and predictable immortalized cell lines, CAR-T therapy requires the patient’s own cells for further processing. Incoming cell composition from patient to patient is exceedingly variable. Automation and process control for CAR-T manufacturing will require a high degree of flexibility for variable cell inputs while also providing robust and predictive processing,” Bulpin says.

	Data management will also be crucial for autologous manufacturing, which will require patient tracking to ensure that the product makes its way back to the intended recipient. “It is also extremely important, given that many of these patients have not responded to chemotherapy and radiation therapy, that the manufacturing process be short and patient scheduling seamless,” Bulpin says. 

	As he notes, the typical CAR-T manufacturing process can take anywhere from 20–30 days, with a significant portion of this time dedicated to release testing. Bulpin suggests that using in-line sensors for real-time quality control release testing could improve overall efficiency. 

	“To support this new type of manufacturing, we are going to need to replace as many manual processes as possible with closed and automated processes, so the labs will look very different as a result,” Krallis says. In addition, she sees the need for a new digital approach to managing manufacturing systems. “Especially as we increase the number of patients treated per week with autologous cell and gene therapies, it is key to have the right data-management systems in your manufacturing setup to track and trace all patient material in real-time, before, during, and after manufacturing,” she says. 

	Vanek agrees that digitalizing the overall process will be crucial to development of personalized medicine. “If you’re translating from a clinic and you have a therapeutic that’s progressing through clinical trials, there is a need for better data management and integration. Even at the unit operation level or the individual step of a larger process, just being able to connect data in a cohesive fashion is crucial,” he says. 

	Although many pharmaceutical companies are at a very early stage of digitalization, Vanek believes that capabilities can be adopted sequentially. The first step would involve connecting data with batch records and standard operating procedures (SOPs) so that the information becomes part of the manufacturing record. GE launched a platform called Chronicle in May 2019 (9) to enable e-notebook and e-SOP connection in a more streamlined way, he says.

	“Entering data incorrectly at the production stage poses a very high risk to the manufacturing process, particularly for autologous therapies,” he says. “So, our goal is to get the devices used across the process, independent of vendor, to have a consistent way of reporting out data and having data available to operators, to the quality assurance and regulatory affairs teams that are ultimately responsible for the quality of that product.”  

	But he acknowledges that this is only the first level of integration. Data must flow from the patient through the manufacturing process and then back to the patient, and all the elements of the complex supply chain must be coordinated, he explains, so the second level of digital integration will connect digital patient records, the materials flowing in, as well as the production process into one manufacturing workflow.  

	“Ultimately, you want to escalate that integration to the point where it’s part of a manufacturing execution system (MES), to start to schedule, coordinate, and orchestrate all the moving parts. This will require a much more sophisticated capability than the industry has today,” Vanek says.

	Beyond digitization and automation, developers face a number of other challenges as they scale-up cell and gene therapies. One concern that Krallis notes is requirements for and availability of the complex raw materials (e.g., plasmids and lentivirus) required for manufacturing. In addition, she says, as the field evolves, developers must be careful about investing too-much too-soon in technologies that may soon be outdated, before they recover their capital expenditures, she says.

	Ultimately, she says, developers face reimbursement challenges and the need to balance cost effectiveness in the scaled-up process with demands to reduce drug cost to patients. She believes that contract development and manufacturing organizations (CDMOs) can offer developers a way to control operating and capital costs, allowing them to focus on pipeline development.

	Bulpin sees the shift toward personalized, point-of-care medicine as a challenge for the delivery of finished therapies. Another hurdle is the long timeline from development through manufacturing, he says. 

	As more companies get involved in personalized medicine development, all stakeholders including operating companies, CDMOs, technology vendors, and research organizations are forming alliances to stay ahead of challenges and share different perspectives. One example is the Centre for Advanced Therapeutic Cell Technologies in Toronto, Canada, whose members include GE Healthcare and the NJII Cell and Gene Therapy Development Center, which works with Pall Corp.  

	The dynamics of collaborations in this field may differ from those in traditional biopharmaceutical development. One reason is the complexity of the supply chain, especially for autologous therapies, because the starting material is the patient’s own cells, says Bulpin. “Closed and automated systems offer the potential for manufacturing sites to be located closer to the patient, regionally or even at the hospital. In this context, CDMOs may require satellite facilities, or academic medical centers may take on more of a CDMO role,” he says. 

	Another difference from traditional biopharma is the fact that many of the therapies originated from research and discovery conducted by the doctors and academics at hospitals and research institutes, says Krallis. “Institutes can manufacture therapies for clinical trials but most of them don’t have the expertise or the capacity to make product at commercial scale. Instead, the therapies get spun off to new companies and are usually tech-transferred to a CDMO,” she says, noting that CDMOs may have an advantage in being able to scale up or down, to adapt to changes in demand. 

	“People have succeeded with therapeutic production at small scale, but we don’t have industrial experience yet. All stakeholder groups must come together to share experiences and identify ways to retire risk, reduce costs, keep up with regulatory pace, and make safe and effective products available to patients who need them,” Vanek says. “The pace of change and approvals is faster in this sector than we’ve ever seen before. Everyone is figuring this out as we go,” he says.

Manufacturing Excellence That’s Decades in the Making

.
	2. The Alliance for Regenerative Medicine, “

Annual Regenerative Medicine Data Report, 2018

, Nov. 14, 2018.
	4. W. Colasante et al., “

The Link Between Manufacturing and Commercialization in Gene and Cell Therapy

Pharmaceutical Technology Biologics and Sterile Drug Manufacturing

eBook (May 2019).
	5. Roche, “Roche and Spark Therapeutics Receive Request for Additional Information from FTC,” Press Release, June 10, 2019.
	6. Ziopharm, “Ziopharm Announces FDA Clearance,” Press Release, June 11, 2019.
	7. Cellectis, “FDA Grants Cellectis IND Approval for UCART 22,” Press Release, June 4, 2019.
	8. V. Barba, “

, June 11, 2019.
	9. BioPharm International, “

Software Automates Cell Therapy Manufacturing


	Supplement: Outsourcing Resources
	August 2019
	Pages: s32–s35

	When referring to this article, please cite it as A. Shanley, “Industrializing Cell and Gene Therapies," 

Pharmaceutical Technology Outsourcing Resources

Now that the first genetically modified cell therapies are being manufactured, the industry must move beyond “whatever works” to meet growing demand.

Industrializing Cell and Gene Therapies

Biopharmaceutical manufacturers have often described operations as data rich but information poor. While advanced analytics and sensors collect more data than ever before, much of it may not be used or shared with the operations that need it most to prevent lost batches and quality or compliance problems. The rise in outsourcing has only intensified the challenge. 

	IDC Health Insights surveyed 126 biopharmaceutical and pharmaceutical executives in the United States and the United Kingdom and found a significant gap between their need and their strategies for harnessing data (1). More than 98% of respondents said that cross-functional data access was important or very important to their business strategies, and 94% described the ability to apply advanced analytics and/or artificial intelligence the same way. Respondents believed that data access would be crucial to improving overall quality and productivity as well as the return on investment of their R&D investments.

	However, 51% of those surveyed said that they did not have a clear strategy in place to help them reach either of those goals, citing regulatory uncertainty, budget prioritization, and the need for more action from functional operational groups. As Kevin Julian, senior managing director in Accenture’s Life Sciences practice, the survey’s sponsor, commented, “Important insights that could lead to the discovery, development, and delivery of promising new treatments are too often trapped within the functional silos of ... biotechnology companies” (2). 

	While some pharmaceutical manufacturers are still using paper-based record systems, a growing number are digitizing processes and making more data accessible in the right context. On a fundamental level, open control systems and a common data structure have helped allow this to happen, according to Rockwell Automation, resulting in distributed control systems (DCS) that enable integration using unmodified Ethernet, and allowing two-way communication between enterprise resource planning (ERP) and manufacturing execution systems (MES) (3).

	Work is underway to improve collaboration in preclinical and quality labs, where good laboratory practices (GLPs), rather than good manufacturing practices (GMPs), drive operations. Much progress is being made in the area of batch records, and expanding connections between electronic lab notebooks, laboratory information management systems, MES, and ERP to increase access to information. Augmented reality offers one way to do this at the basic data recording and recovery level. 

	In addition, according to Emerson Process Management’s consultant Johan Zebib, quality review management and review by exception are being used with MES (4). Data historians can also be developed as a point of access, a concept that Eli Lilly has leveraged with its contract manufacturers in medical devices (5). Vendors are offering tools that make this task easier, with applications that use machine learning and other facets of artificial intelligence, allowing users to make connections between data points that might otherwise have seemed unrelated.

	Apprentice.io has developed augmented reality and database applications that allow users to get feedback as they perform their jobs and to compare equipment performance and different batch runs (6). Contract development and manufacturing organizations (CDMOs) are becoming a more important market for the technology, says CEO Angelo Stracquatanio, using it not only to share data, but for training and troubleshooting in real time. “There are so many silos within manufacturing, and data are not being leveraged at different levels,” he says.

	In 2019, the company has made improvements to its augmented reality products with augmented batch recordkeeping products that extend batch connectivity to laboratory information systems (LIMS) and electronic lab notebooks (ELNs), allowing inputs to be captured for every batch. Users can analyze process data to compare batch runs and implement continuous improvement programs and analyze specific runs to isolate deviations, Stracquatanio says, leaving an audit train of data that can be mined to decrease variability.

	A growing number of CDMOs are using Apprentice.io’s Tandem remote telepresence tool to collaborate with their clients. The Apprentice System also collects voice, picture, and other types of data to create a rich audit trail. “For example, for a single-use filter, one can scan its bar code. Users now know what filter that is and can create an audit trail for it … and put data together in real time, using a hierarchy of importance to present data in a way that doesn’t overwhelm the user.” says Stracquatanio.

	Machine learning and artificial intelligence are also moving into pharmaceutical manufacturing applications. The technology is farther along in clinical trials and in discovery. Accenture launched INTIENT in May 2019 to focus on discovery, clinical, and pharmacovigilance applications. Amgen has been working with Tata Consultancy Services on a Holistic Lab digital platform using Dassault Systemes’ BIOVIA, for process development (7). 

	However, some vendors are focusing on pharmaceutical manufacturing. Quartic.ai, for example, has launched an AI-driven platform to provide feedback to operators and to monitor and improve processes (8). The platform, which includes a data engine, designed to extract data from DCS, quality management systems (QMS), and data historians, as well as a connector that allows disparate software systems to communicate with each other, was designed to be integrated into existing plants and equipment, but Quartic is also working with a pharma company to embed the platform into a new facility.

	Quartic.ai cofounder and CEO Rajiv Anand has an extensive automation and reliability background and previously worked at Emerson.The company’s management team members all come from pharmaceutical and automation backgrounds. “We didn’t want pharma users to feel that they needed to be coders or data scientists,” says vice-president of life sciences Larry Taber. 

	The platform is geared to the fact that every potential user will have a different level of digital maturity, says Anand. Once legacy data sources have been connected, the artificial intelligence engine can be used to solve a specific problem (e.g., monitoring an asset’s performance for deviations), he adds. Some clients are using it for complex predictive work (

, above, shows the platform in use at a biopharm facility).

	The company has applied the platform in a number of situations, including an effort to monitor and improve fermentation yield in a highly variable process where all critical quality attributes were under control. Quartic extracted data and identified a few key batches, Anand explains, and then built an algorithm to study relationships between the batches, clarifying eight years’ worth of data and fingerprinting each phase of the process. Ultimately previously unknown sources of variation were discovered. Work will now focus on learning more about them.

	The company has also done work with predictive maintenance. Anand recalls one project designed to baseline the performance of an autoclave. The equipment was modeled and industrial Internet of Things (IIoT) sensors used to get additional vibrational and ultrasound information. Once deployed, machine learning models could then predict potential failures with the ability to trace the source of the failure down to an individual component (i.e., a damaged valve).

	There are many other applications where artificial intelligence could be applied to pharmaceutical manufacturing operations, particularly in visualizing end-to-end processes. As data analyst Jonathan Lowe (9) found at one company, more than 100 quality events were being investigated at any one time, stretching staff capacity. A machine learning model was designed to predict which events would take the longest to resolve. The model predicted more than 85% of the severe delays weeks before they happened, allowing quality managers to prioritize tasks more equitably. 

The Case for Connectivity in the Life Sciences

, May 22, 2019.
	2. Accenture, “Accenture Introduces Intient,” Press Release, 

, May 16, 2019.
	3. B. Sisk, “Analytics Informs Decisions in the Facility of the Future,” a Rockwell Automation white paper to be published in July 2019 on 

.
	4. J. Zebib, “Review by Exception: Connecting the Dots,” an Emerson Process Management white paper to be published in July 2019 on 

Data Sharing in a Contract Manufacturing Environment

,” a presentation at the OSI Soft Users Conference, 2017, 

Mixed Reality Gains a Foothold in the Lab

Empowering 21st Century Science in Life Sciences

,” an IDC Perspectives Paper, Document VS43749317, 

Quartic Introduces AI Platform for Process Manufacturing Operations at INTERPHEX 2019

Why Biopharma Manufacturing Needs to Leverage Network Optimization Techniques via Data Science

The means to continually improving and enabling the use of artificial intelligence in manufacturing lies in the ability to make data accessible across functions and to contract partners.

Translating Rich Data to Useful Information

Analytical method transfer suffers from many of the same problems that plague technology transfer in general. All too often, a method may work well in the R&D lab as a characterization test, but fails when taken to a wider stage, where reproducibility is key.

	In addition, incomplete information may be shared between the two organizations working on the transfer, and details on how to carry out standard operating procedures may be given short shrift. Partners may also fail to consider critical points (e.g., whether data interpretation software meets FDA regulations). As Berangere Tissot, general manager with SGS Life Sciences says, “The devil is in the details.” Tissot, who is a subject matter expert on protein and glycoprotein characterization and complex method validations, recently shared best practices with 

: What mistakes do people typically make with regard to analytical method transfer for biologics?

: The most common mistake people make is underestimating the complexity of analytical method transfer, particularly for biologics. The problem that will jeopardize any analytical method transfer, whether at very early or late stages, is the failure to convey the ‘know how’ in documentation that is sent to the transfer partner. Often, instructions are very detailed on some aspects of the method yet key information is missing because it is not considered critically relevant. It’s important to remember that the manipulation of a biologic is very different from that of a small molecule. For some assays, sample preparation is key to the method, yet it is often the least described part of the methodology. Even in cases where it is well described, important elements are often missing. This can undermine the difficult challenge of reproducing an assay with consistency and robustness.

	Another area where insufficient knowledge transfer often occurs is when a company has to validate, or ask its contract development and manufacturing organization (CDMO) partner to validate, what was developed as an early phase characterization assay. In many cases, 50–90% of the information that is needed in order to validate the method is simply not there, which makes the next step of transferring that method from development to a quality control (QC) environment, a real challenge.

: How and what kind of information must be conveyed, and what kind of mindset is needed to ensure that key issues are not left out?

: Thinking in terms of developing what will later be validated allows one to have more control over the analytical development stage. When you develop an R&D method with the idea that it could be a QC test at some point in the future, you will do it differently from the way you would develop a characterization test that will remain an R&D characterization test.

	When you develop a method that will be transferred to QC or to another lab, you would want to focus on simplifying sample preparation and data acquisition-for example, you would not want to have a 60-step process for sample preparation. You may also consider, whenever possible, to make the method unbiased to any specific type or brand of instrumentation. 

: Do R&D scientists have to think like QC technicians?

: These two categories have different skillsets and mindsets. It does not mean they are incompatible, but it requires some training to move from one to the other. When you work in QC, you have to deal with many restrictions on what you can change. Scientists who are developing analytical methods in R&D typically do not have to consider these restrictions. However, if the method has any chance of being part of a release panel, they should at least know what these restrictions are and conceive of an assay that takes them into account. 

	For example, they shouldn’t specify the use of exotic enzymes, however more specific or appropriate they might be, because those materials might pose availability and quality consistency problems that will affect the method’s continuity and robustness. For any enzyme used in testing, consistency in quality and multiple sources of supply would be paramount. Early phase analytical teams are developing a new method because they are after either new or more precise information, but what will work best for moving the method along in R&D is unlikely to work in the QC environment. Thus, it is very important to think about that translation at the very beginning of assay development. 

	We always ask clients, when we are developing methods for them, whether they envision the method being used as a release assay at some point in the future, or whether they see it as having to be validated. Even if no one can be certain, just the possibility that it might is important for devising the appropriate strategy around the method development.

: But how can one know this at early R&D stages?

: You don’t, at least not with absolute conviction. It is very difficult to know at this stage, but you may have some sense of whether this approach will be needed, and that sense needs to be communicated to whoever is working on developing the assay so that the method is built on a solid basis and with the appropriate mindset.

	This is the major difficulty with transferring analytical methods. Creativity is valued and imagining the best possible way to approach the method is very important. However, analytical developers should also consider the most reliable way of performing the assay, if it is to be implemented in GMP environments and QC labs later. Situations will come up where these two priorities cannot be matched, and some compromises will be needed.

: It is essential to developing a good risk management strategy around the method itself and its lifecycle. Imagine you are working on the development of a characterization assay for N-glycan structure elucidation that will be used for a drug that has a very complex glycosylation (e.g. for a replacement enzyme, where you know that some form of derivatization or glycosylation will be key to the product’s functionality). In this situation, the method, which should normally belong to the characterization panel only, will probably end up being the best approach for monitoring and controlling a critical quality attribute (CQA) of the product. 

	For the purpose of the characterization assay, you are trying to fully understand the complexity of the N-glycan structures. In order to get detailed results, the method might be complex and convoluted. Repeatability or robustness will not be evaluated and rightly so, if this method is just for characterization. The method efficiency will be as good as the scientist carrying out the assay, which is very common in R&D environment. However, if you haven’t considered the future use of the assay and built some preliminary risk management (e.g., having some specificity, repeatability, and evaluation of the critical parameters to control in the sample preparation done at the R&D phase), you will need to put a remediation plan in place, and then develop a translation phase for that method, to demonstrate that the assay can be brought into QC and eliminate most of the risks that would be linked to a complex procedure.

: Do you need to staff these projects in a special way? 

: In very small companies, there may not even be a QC or an R&D department. At many of the medium-size biopharma companies, these groups may not be actively working together. However, a growing number of large biopharmaceutical companies now have groups in between R&D and QC that focus on bridging these two groups and assisting them with the transition of R&D methods in the QC environment. These ‘translation’ groups generally include people who are educated in QC and understand all the restrictions of QC work, yet who are well versed in R&D, to find that middle ground.

: We started to see it a few years ago, and this trend is likely to continue to grow.

: You mentioned the importance of describing all steps in detail. Why should that be necessary?

	Tissot: This is the key reason why these transfer or transition projects fail. Let me describe one situation which we encountered where we received an R&D method to transfer in our lab and validate to cGMP. The protocol had many details around the sample preparation but failed to mention the fact that the protein of interest was adsorbed on plastic surfaces, and therefore was adsorbed on plastic microtubes. It took us some time to pin the difference observed in recovery to this very basic fact. Nowhere in the protocol were glass containers mentioned, because it had been so engrained in the minds of the scientists who worked with this protein that ‘it went without saying.’ 

: How do you ensure that clients provide this information?   

: We spend a lot of time talking with the client, the scientists who developed the assay, and reviewing the method before we even take the work in. We need to understand each of the steps of the method and evaluate how much of undisclosed details are at each of these steps. It may sound tedious and we may ask questions that seem unimportant, but all of this is essential to understanding what is critical to the method and what is not.

	In general, the more we know upfront, the less we have to ask later. We need to be proactive about the transfer and clients generally understand that a lot of preliminary work is required in order to maximize the efficiency of the transition and the chance of validating a robust and reliable assay.

: Yes, it is a crucial factor. The requirement for compliance to 21 

Part 11 for R&D methods is not as critical as it is for cGMP methods.

	For some high-end methods, it is still very possible that the software used to analyze data is not yet Part 11 compliant. When such a method needs to be validated, the risk management has also to account for the workarounds to be implemented around the data acquisition and interpretation. This is not trivial and requires close collaboration between the scientific staff, quality assurance and computerized system validation groups, and sometimes, the instrument manufacturer. This consideration needs to be more apparent to R&D scientists, with the understanding that the method might eventually be pushed to the QC lab.

: Mostly by opening up lines of communication and work around the language barrier between R&D and QC. In any circumstance, take a stepwise approach while evaluating whether the method can be transferred to GMP. Our first phase of evaluation is performed on our instrumentation, leveraging our ability to do R&D in a regulated environment. Based on that first evaluation, we define critical checkpoints (i.e., what may pose problem to specificity, repeatability or any other critical validation requirement) and parameters which may require optimization or adjustments. We evaluate critical reagents and work our way through defining multiple suppliers to briefly assess robustness , whenever necessary. The method is now in a “state” where it can be evaluated more in depth for its applicability to release.

	What will be investigated next will depend on the use of the assay: whether it is for an identity test, the monitoring of CQA, or for quantitative residual testing. Each application will have a set of parameters for which specifications would need to be defined. Based on these, we will either optimize further or go straight to a pre-validation or pre-qualification study to see how the method fares and what could be the targeted acceptance criteria. What is needed here will also depend on the clinical phase for which the method needs to be validated. Stringency on acceptance criteria and extent of the study will be different depending on whether the product is in Phase I or III. Once everything has been empirically assessed, we can then work on a validation protocol.

: Have you ever had to ‘just say no’ to a project?

: It is always difficult to say no because most of the time, it is not that the method is impossible to work with, but rather the requirements that are coming with the transfer. For example, when companies want to validate one of their R&D methods, but then ask for it to be validated within a week, they need to understand that this is not likely to be achievable. Rushing to such a critical step in their analytical development is likely to result in them shooting themselves in the foot and incurring the risk of running into extensive and expensive remediation work.

	Success requires a lot of homework and careful, educated evaluation of method from a preparation, analytical and software/IT standpoint. The focus cannot be only on the instrument acquiring the data, but must include the software analyzing those data and the way the data are being recorded. Everything must be considered.

: How can you do the work and comply when the software isn’t Part 11 compliant?

: It requires creativity and a good handle on the compliance and regulatory requirements. Analytical instrument manufacturers are working on solutions. One can assume that there will be fewer and fewer of these gaps in the very near future.

Often, transferring an analytical method from R&D to quality control fails; success depends on determining where “the best” and “the most reliable” intersect.