Flexibility in pharmaceutical manufacturing is becoming an increasingly pertinent requirement. Various industry trends, such as the development of increasingly complex and novel therapies, a greater focus on orphan drug designation, and the use of more highly potent ingredients, are leading to demand for adaptable and versatile processing equipment.

“For decades, large-scale drug production was the industry standard. However, the rise of rare diseases now demands increasingly expensive medications, which, in turn, require greater research and development efforts, including innovations in machine design,” remarks Andreas Mattern, vice-president Strategy and Global Product Management Pharma at Syntegon. “For example, there is now a need for machines capable of processing small and micro batches with greater flexibility. At the same time, new drugs like anti-obesity medication are sustaining the demand for high-performance equipment that can handle large batch volumes.”

“There have been significant advances in flexible manufacturing to accommodate the rapidly changing therapeutic landscape, particularly in response to the rise of personalized medicine, biologics, gene and cell therapies, and the need for rapid responses to health crises (like the COVID-19 pandemic),” specifies Caterina Funaro, Competence Center manager at IMA Active. “These advances are helping the pharmaceutical and biotech industries adapt to smaller batch sizes, varied production processes, and the need for faster, more adaptable production cycles. Key innovations in processing equipment, facility design, and digital technologies are enabling greater flexibility in manufacturing.”

Specialized treatments are certainly driving new equipment developments, confirms Mattern, who points out that personalized therapies are becoming a focus for future treatment breakthroughs. “Many types of cancer and genetic disorders can only be treated with highly specialized drugs,” he says. “These [drugs], in turn, require production in ever smaller batch sizes.”

New therapeutic modalities, such as cell and gene therapies, require flexible equipment that can handle fast changeovers from one product batch to the next, Mattern continues. “A wide variety of products must be filled into different container sizes and types such as vials, syringes, or cartridges. Hence, it comes as no surprise that the market for ready-to-use (RTU) containers has been growing at a rapid pace over the past years,” he says.

Benefits of RTU containers include reduced time-to-market, lower cost of ownership, increased flexibility, and greater integrity of the drug product, explains Mattern. “While RTU containers have been the de-facto standard for pre-filled syringes for some time, they are now also increasingly being used for vials and cartridges in both bulk and small batch applications,” he states.

A general move away from traditional approaches to manufacturing has been trending for a while, comments Funaro. “Continuous manufacturing (CM) has gained traction as an alternative to traditional batch production,” she adds. “[CM] provides greater flexibility by allowing production to run continuously, without the need for lengthy shutdowns between batches, which is especially beneficial for both small- and large-scale manufacturing.”

“The industry has made significant progress in adopting continuous processes, which are progressively replacing traditional batch processes, particularly in the pharmaceutical, chemical, and food processing sectors,” explains Funaro. “Continuous processes offer enhanced efficiency, higher throughput, better product consistency, and improved energy use, driving their adoption across industries.”

For pharmaceuticals, manufacturers are employing continuous processes to API production, granulation, mixing, tableting, and coating, remarks Funaro. Through using continuous processes for these tasks, companies are being able to reduce lead times, improve product consistency, and facilitate any potential scale changes that may be required to meet therapeutic demand, such as increased production of vaccines or biologics, she confirms.

Within the oral solid dosage (OSD) space, CM has been trending for a few years, Mattern adds. “Higher flexibility, shorter development times with minimum API usage, and a direct transfer from development to production without scale-up are among the primary requirements of pharmaceutical manufacturers,” he says. “The main challenge with traditional solutions is the precise dosing of the starting materials in a constant mass flow rate of milligrams per second.” However, as the pharmaceutical industry is highly regulated, adopting newer processes can take time, Mattern specifies.

“FDA has endorsed continuous processes, recognizing their potential for faster production and more consistent product quality,” asserts Funaro. “As a result, manufacturers are investing in equipment such as continuous coaters and continuous mixers.”

Additionally, while investment in continuous processes grows, advances are also being seen in real-time data monitoring tools, which are vital in helping to control variables in CM, such as temperature, pressure, and product quality, continues Funaro. “Real-time analytics are increasingly being integrated with machine learning (ML) algorithms to allow for self-regulating systems that automatically adjust process parameters to maintain optimal efficiency and output quality,” she says.

“The shift from batch to continuous processes is well underway, but ongoing advances in processing equipment will further accelerate the transition,” asserts Funaro. “As technologies such as real-time monitoring, modular designs, AI [artificial intelligence] integration, and energy-efficient systems mature, industries will be able to harness the full potential of continuous processes, resulting in lower costs, higher productivity, and improved sustainability.”

“Automation is playing an increasingly critical role in processing equipment across industries such as pharmaceuticals, food and beverage, chemicals, and biotechnology,” explains Funaro. “The current trends in automation are transforming manufacturing processes by enhancing productivity, improving consistency, ensuring quality, and reducing human error.”

Through the use of automation, manufacturers can achieve a multitude of benefits. For example, Funaro points out that automated material handling, packaging, and processing reduces human intervention and speeds up cycle times. Additionally, she alludes to the fact that automation reduces variability in production processes, which ensures consistent quality.

For Funaro, the use of digital twins, which are virtual replicas of physical processes or equipment, will become more widespread within industry over time. “Digital twins allow manufacturers to simulate process changes, predict how equipment will behave under different conditions, and optimize production before making physical adjustments,” she says.

“Predictive maintenance is becoming a standard practice, leveraging AI, IoT [Internet of Things], and analytics to predict when equipment will fail, and schedule maintenance before a breakdown occurs. This reduces unplanned downtime and extends the lifespan of processing equipment,” adds Funaro. “As predictive maintenance becomes more advanced, it will shift toward prescriptive maintenance, where AI not only predicts failures but also suggests the optimal maintenance actions to take, further minimizing disruption and cost.”

While digitalization is producing large amounts of data in production every day, it will mean nothing if it cannot be viewed or used, Mattern warns. “New cloud-based software solutions, such as Synexio from Syntegon, provide a remedy by enabling the acquisition, evaluation, and visualization of equipment and production data,” he says. “[These solutions] allow for real-time monitoring of machine conditions, helping manufacturers make data-based decisions and optimize operations.”

“In sectors like pharmaceuticals, where regulatory compliance and precision are critical, automation ensures that products meet exacting standards,” continues Funaro. “Automated quality control systems, including automated visual inspection and process analytical technology (PAT), are reducing the risk of human error and ensuring that processes stay within defined limits.”

Reducing human intervention in processes is particularly helpful in high-risk environments, such as dealing with hazardous chemicals or highly potent ingredients, asserts Funaro.

“The use of robotics is taking the industry a huge step further towards even higher product protection and quality, as it eliminates the main cause for contamination (i.e., human intervention),” Mattern remarks. “This is further fueled by [the European Union’s] Annex 1 [guidance].”

In August 2023, the updated EU good manufacturing practice (GMP) Annex 1 guidance (1) came into operation (except for point 8.123), which has profound implications for sterile manufacturing across the global pharmaceutical sector, Mattern specifies. “One of the key challenges presented by the new Annex 1 is the requirement to separate the aseptic processing area from the operator’s environment. As a result, pharmaceutical manufacturers now need at least restricted access barrier systems (RABS) to gain approval for new products,” he says.

After the updated guidance was published, industry saw a surge in upgrades to existing cleanroom lines to incorporate RABS, Mattern notes. “Manufacturers must choose whether to upgrade their current cleanroom line for a new product or invest in new filling equipment with isolator technology or RABS,” he specifies.

“It is expected that isolator technology will become the new standard, given the added safety provided by automatic bio-decontamination processes and the pressure differential from the operator environment,” Mattern notes. “[Whereas], RABS will likely remain a preferred option for more frequent product changes and experienced operators.”

The second chapter of the revised Annex 1 guidance places a focus on automation and robotic systems, highlighting these as “Appropriate Technologies” (1), Mattern reveals. “These technologies aim to reduce, or even eliminate, the need for gloves and human intervention in barrier systems,” he says.

“Gloves pose several challenges, which are addressed in dedicated paragraphs of the [Annex 1] document,” Mattern continues. “For instance, during longer production campaigns, [gloves] must be tested in operation—a process that is difficult to achieve with current glove testing equipment without compromising the sterile environment. The shift toward gloveless systems, utilizing robotics for these tasks, is viewed as the ideal solution.”

There are several potential future trends that are set to impact processing equipment and pharmaceutical manufacturing in general, asserts
Funaro. “These trends are being driven by technological innovation, sustainability goals, and the need for enhanced efficiency, safety, and compliance,” she says.

Notably, automation and Industry 4.0 are set to shape the future, explains Funaro. For example, employing predictive maintenance to anticipate equipment failures before they happen, utilizing AI and robotics for fully autonomous processing systems, integrating advanced sensors and machine vision systems for greater precision and control, and analyzing vast amounts of data with ML and AI, she summarizes

“Future equipment will increasingly incorporate self-learning systems that can adjust their operation based on past performance data. This will enable greater flexibility and adaptability in production lines, particularly in industries that need to switch between different products or processes frequently,” says Funaro. “As demand for customization and flexibility grows, processing equipment will increasingly be designed with modularity in mind.”

“A persistent concern within the pharmaceutical industry and its suppliers is the need for more sustainable equipment and processes. Unfortunately, resource consumption in the sector continues to surpass that of many other industries,” stresses Mattern. “In response, drug manufacturers are intensifying efforts to reduce their carbon footprint, with the support of manufacturing companies offering services such as lifecycle assessments for their equipment.”

Adoption of more energy-efficient equipment and an overall reduction of environmental footprint is becoming a greater focus for manufacturers, confirms Funaro. “Recyclable and reusable components in machinery, as well as the use of environmentally friendly materials, are becoming more widespread,” she says.

“Given its longevity, equipment usually contributes to overall emissions over several decades,” remarks Mattern. “By continuously optimizing their machines and developing new, more energy-efficient solutions, equipment providers can help pharmaceutical manufacturing companies achieve their sustainability goals.”

“These future advances will fundamentally change how industries approach processing equipment, offering greater flexibility, efficiency, and sustainability while adapting to the needs of a rapidly evolving marketplace,” concludes Funaro.

1. EC. Annex 1 Manufacture of Sterile Medicinal Products. 

Felicity Thomas is associate editorial director for 

®
Vol. 48, No. 11
November 2024
Pages: 9–11

When referring to this article, please cite it as Thomas, F. Increasing Processing Flexibility to Meet Demand. 

Articles

Cover Story

Evolving industry demands are driving the need for greater flexibility and innovation in processing equipment for pharmaceutical manufacturing.

Increasing Processing Flexibility to Meet Demand

The training function in a pharmaceutical facility is vital to site operations. The objective of training is straightforward; training is responsible for employee learning. Site training programs must be effective to accomplish employee learning. Effective training is difficult; the broad scope of topics, trainer communication skills, trainee motivation, logistics, documentation, maintenance of training quality, and other considerations may challenge effective training. Training is a cost; training in some organizations may be restricted by budget, time, facilities, conflicting priorities and criticalities, or other limitations. Identifying problematic aspects in training and appropriately addressing these considerations is crucial to accomplishing effective employee learning. 

This manuscript discusses the application of quality risk management (QRM) concepts within a site training program. QRM application helps to identify potential problematic aspects in training; these potential issues may then be addressed by following the QRM process. ICH Q9(R1) is the fundamental document describing QRM (1). Hazard identification (i.e., potential problem identification) is the first step in the QRM process. This paper focuses on problem identification within a comprehensive training process. Specific application of QRM to training and education is identified in ICH Q9(R1).

QRM application in training provides a systematic approach that complements traditional training—a thought process distinct from usual training. Typical training involves information, actions, and procedures (i.e., how to do things); training should also address understanding (i.e., why are things done). QRM identifies potential problems during training—QRM addresses what might go wrong. QRM thus improves training and makes training content more relevant. QRM application facilitates poka-yoke, mistake-proofing, defensive design, or other approaches intended to prevent problems—QRM proactively facilitates problem prevention. Adult learners in pharma are practical in orientation; QRM problem identification is harmonious with adult learning (2). Examples of potential training problems are presented throughout the following discussion:

 Training functions within pharma may be organized in different ways. Training may be the responsibility of each technical function (e.g., engineers train other engineers, chemists train other chemists, etc., within function departments); each function accomplishes their individual personnel training. Centralized training with varying levels of activities is also possible; some centralized functions may be responsible for minimal administrative activities (e.g., personnel training records); others may manage training requests, training content documents, schedule sessions, and periodically monitor training quality—a much more comprehensive responsibility. Some training organizations may be linked to corporate human resource (HR) systems to integrate government-mandated training within employee files. The following discussion addressing QRM in training utilizes a centralized function with responsibility for individualized training and administrative activities. The point of this discussion is the identification of potential problems adjunctive to typical training regardless of organizational structure.

 The role of training management is critical to training program success. Training management is responsible for actual training as well as training function management. Quality systems guidance documents (3–5) identify expectations of management; QRM considerations are also mentioned in these documents. Training management may need to mediate conflicting training time/costs vs. site criticalities with other site functions. Other management training responsibilities are also crucial for success. Site training programs often rely on personnel in other departments to accomplish training objectives; training management must ensure that these individuals know and understand their responsibilities supporting training. Training management also provides an unspoken message to trainees during training; conscientious effort in training with thorough and well-designed training content conveys a message of quality and compliance to employees. A common thread in deficient training is a lack of visible management involvement; one cannot demonstrate commitment by staying in the office and going to meetings. Training management must be “on the floor” when and where training happens (i.e., management by walking around [MBWA]) (6). Current workplace trends in Zoom management exacerbate management lack of visibility. An ongoing commitment to training excellence demonstrated by management visibility helps to develop a quality culture in the organization.

 This discussion is structured according to the FDA lifecycle approach to process validation (7). The process validation model provides a comprehensive approach to training. Process validation is designed, executed, and continually maintained; training activities can likewise follow this same approach. 

 describes three stages in a training lifecycle akin to three stages in process validation. Training stage 1 describes the design of the training topic including content, presentation, and associated elements; stage 2 comprises actual training performance by trainers and trainees; stage 3 addresses the ongoing maintenance of training (i.e., effectiveness, content accuracy, and compliant performance). A basic tenet of process validation is the identification and control of variation; training problems may include performance variation by trainers, uncontrolled logistics, and other causes. Training management should develop a training master plan akin to a validation master plan containing training strategies, approaches, procedures, documentation, and commitments. The following continues previous discussions correlating training with process validation including validation application overview, training content development, trainer qualification, trainee prerequisites, the training process, performance monitoring, management overview, and documentation (8–15). 

QRM terminology may often confuse readers based on common language within their pharma settings—specifically the words ‘hazard’ and ‘risk’. Hazard and risk are often assumed to describe dangerous workplace situations (e.g., fall, slipping, electric shock, overhead machinery, others). Per ICH Q9(R1), ‘hazard’ and ‘risk’ are not synonymous (16,17). Hazard is a source of harm; after a hazard is identified, its risk of causing harm (high, medium, low, or descriptive numeric) is assessed using risk assessment tools or subjective methods. Risk assessment describes the probability of harm occurrence and the level of harm severity; some common risk analysis methods include failure mode and effect analysis (FMEA), preliminary hazard assessment (PHA), and fault tree analysis (FTA); these tools are identified in ICH Q9(R1) Annex I. FMEA integrates frequency, severity, and detection in its Risk Priority Number (RPN), which quantifies risk. 

 more completely defines terminology as explained in Q9(R1) training modules and used in the following discussion. Q9(R1) changed the initial step in the risk assessment process to ‘hazard identification’ from ‘risk identification’. Although this change enabled consistency with the definition of hazard in other regulatory documents, it may cause confusion in common word usage. Hazard identification in training is the primary objective of the following discussion. 

Stage 1 comprises the design, planning, and development of training to be executed in actual employee training. Training design must comprehensively address the topic to be trained. Stage 1 design addresses new training as well as evaluating and integrating training changes identified during subsequent training stages. When the training process is designed, conscious thought about what might go wrong is integrated with the how and why being trained. Training design is the most important activity in the training process and may be complex depending on the subject topic. The following briefly describes elements of training designed in stage 1:

Content, presentation, testing, and process

. Numerous content categories (e.g., policies, procedures, equipment operation, analytical, etc.) are required for pharma employee training. Content presentation describes the method of delivering content; computer delivery (e.g., one-way delivery), virtual reality, Zoom interactions, classroom training, and skill delivery (i.e., on-the-job [OJT] training with a subject matter expert [SME]) are general categories. Testing to verify effective training is related to content complexity; “read and sign,” multiple choice, and skills demonstration to an SME are options.

 Supporting elements in training design include the trainer, trainee, and logistics. Background, technical expertise, and communication skills of trainers must be consistent with training complexity. Trainees must be capable of competent performance post-training. Training logistic considerations such as facilities and equipment, number of trainees per session, scheduling, internet access, and other relevant elements are specified in training design.

 All of the above must be recorded in an approved controlled document for use in future actual training. This document serves as an ongoing record of training subject matter. Document changes are controlled via change management; content is modified as experience is gained, and risks are evaluated. Supplementary information used in training to emphasize key content is appended.

 Training management is ultimately responsible for training design and related elements. Establishment of training standards for content, presentation, testing, trainers, trainees, logistics, and related elements is required. Standards must be documented. Standards are the backbone of the training effort that helps to establish a quality culture in the organization. Training compliance with standards should provide a quality message to trainees. A Training Master Plan listing training standards, approved Training Content Records, and other function information is recommended.

 Stage 1 hazards are identified during the design and development of the training content by the training author. Hazards are identified concurrently with the ‘what’ and ‘why’ of training; authors address ‘what might go wrong’ along with the what and why in subject matter. Addressing potential hazards within training leads to more effective content, presentation, and testing. Design personnel must anticipate potential problems during training design. Illustrations, videos, checklists, and other aids addressing problems should be incorporated into training design. Trainers must verbally emphasize critical content in their training presentation. Testing should emphasize questions on critical content. Addressing training problems through different types of learning (e.g., visual, auditory, reading/writing, kinesthetic, etc.) is recommended; employees learn in different ways. The greater the anticipated risk to product, process, or organization, the greater the potential problems, and the greater the effort that is required in training—a principle of ICH QRM. 

 provides examples of stage 1 hazards based on experiences and observations. 

Case study #1: deficient training design—machine setup.

 Customer complaints and returned product were received on a new prescription sedative product. Distinct white spots on the blue tablet surface were observed. Recall letters were sent and product was back-ordered with availability, financial, and regulatory ramifications. Engineers determined that milling equipment was incorrectly set up causing large white-spot particulate. Performance by manufacturing technicians was the hazard in this case; incorrect machine-part assembly was directly correlated to ineffective training. Improvements in training content and illustrations highlighting correct setup were developed. Trainees were required to demonstrate correct equipment assembly to an SME to successfully pass training.

Stage 2 training performance comprises the executed training of a trainee by a trainer and review of the training process. Stage 2 activities confirm the stage 1 design and identify necessary modifications—actual stage 2 training experiences between trainer and trainee may differ from stage 1 expectations. Stage 2 observation also affords opportunity to confirm trainer–trainee focus on critical aspects of the training subject matter:

 The actual training process executes the planned training designed in stage 1.

 Stage 2 training is evaluated; trainer, trainee, training management, training designer, and other interested individuals are involved. Overlooked or unanticipated problems are noted. Trainer emphasis on critical parameters is reviewed. Trainee engagement is evaluated.

Documentation—Personnel Training Record.

 The Personnel Training Record documents completion of training for employees. When an auditor asks to see the training record for a specific employee, this document will be provided. Training documentation contains dates and times of training sessions; these must be consistent with training design. If training is not clearly documented, it didn’t happen.

 Observation and evaluation of the training process by management provides an opportunity to enhance training design and performance. If changes are needed, the stage 1 Training Content Record is modified through the site change management process.

 Stage 2 hazards that were not anticipated in stage 1 design but become apparent during actual training are identified. New hazards noted in stage 2 are evaluated per ICH Q9(R1) methods and integrated per change management. Actual performance variation in trainers and trainees not anticipated in stage 1 design is noted. Training content, testing, logistics, and other considerations are modified in the Training Content Record via change management. 

 and case studies provide examples of potential stage 2 hazards. 

Case study #2a: training logistics—training in the auditorium. 

GMP) training for more than 200 site employees was conducted in response to a regulatory audit observation. The site auditorium was reserved, and a two-hour session was scheduled for 3 pm to include first and second shift employees. The session discussed data integrity, original data recording, error corrections, signature/date verification, “white-out” use, “post-dating,” and numerous other documentation topics. A few days after the training was completed, a site engineer was observed recording original data on scrap paper for later transfer to his notebook. Other technicians were observed writing data on “Post-it” notes instead of batch records. Continuing “white-out” use was also observed. Many key topics addressed in the training were not understood—training was an obvious failure. Poor training logistics was the fundamental hazard that caused ineffective training. Failure modes included too many people in the same room, a lengthy session at the end of the workday (i.e., sleeping employees), uncomfortable room temperature, smartphone distractions, and too many topics without adequate discussion. Trainer communication was also identified as a hazard; supplementary illustrations, lack of hardcopy handouts; and no Q&A with trainer were deficiencies. Training was poorly designed—-an efficient training session became more important than employee learning. Training was disingenuous; management just wanted it done to claim accomplishment of the regulatory commitment. Training was not given appropriate time, effort, and priority to accomplish employee learning. New sessions with smaller groups and improved presentation of content were developed and rescheduled. Large group auditorium training sessions were eliminated in future training.

Case study #2b: training logistics—computer fatigue. 

A site training program for “read and sign” training was managed through a training computer system. Employees were assigned training materials to be read; computer links were provided. Employees were allowed a 30-day time limit to complete the training; completion was self-paced. Employees would routinely give training a low priority and delay training until the deadline. This approach was not acceptable for new employees assigned an excessive number of training modules; more than 50 documents were often “read and sign” in one day—training was ineffective. Trained performance was the hazard identified in this case. The training computer system was modified to allow completion of not more than five training modules in one day.

A senior SME operator was the designated training person for a non-sterile manufacturing area. He always accomplished training of new personnel in one demonstration session. Some procedures required several hours of demonstration. The trainee and trainer then signed documentation that the trainee was qualified to perform the task without actual trainee demonstration of competency. When the newly qualified trainee was assigned manufacturing tasks, the senior person would be nearby to help as needed. Training deficiencies became apparent when the trainee was working alone. When the trainer was asked about his training methods, he responded that his manager told him to complete training as quickly as possible so that the trainee can begin working. Deficient technician performance was the hazard in this case. The trainer should have adjusted training repetition and emphasis based on trainee understanding and complexity of training content. After adequate repetition, the trainee should have been required to independently demonstrate trained skills. Training could not be firmly standardized due to the variation in trainee skills; experienced operators could be adequately trained by observation; inexperienced operators required additional repetition. Management did not give the priority to training due to production criticalities; production criticalities were more important than training. The manager had no incentive to make training a priority vs. his manufacturing responsibility; what the manager did undermined or undercut training. Future training required complete skills demonstration to an independent SME.

Continued training verification comprises the periodic review of training content and performance. Activities in stage 3 enable continuous improvement in training and maintenance of training quality. Training periodic reviews are specified in a Training Master Plan or other scheduling commitments:

 Training effectiveness is evaluated by review of experiential documents (e.g., deviations, non-conformances, investigations, corrective and preventive action [CAPA]), stakeholder interviews, trainer/trainee discussions, and other reviews that critically evaluate training performance. Investigations citing training deficiencies as causes of process deficiencies indicate the need for training improvements. Problem trends should be noted and addressed.

 Training content in the Training Content Record is reviewed for accuracy. Changes in equipment, processes, cleaning methods, and other variables may have occurred without concurrent changes in training. Supportive documents (e.g., flow diagrams, piping and instrumentation diagram [P&ID], sampling protocols, etc.) relevant to training may also be obsolete, inaccurate, or incomplete.

 Performance of trained procedures may also have been modified in response to equipment changes or improved efficiency without concurrent changes in training. Employee shortcuts in performing trained procedures are a common occurrence. Non-compliance with procedures are among the highest frequency of FDA-483 citations (18)

Documentation—Training Periodic Review.

 Performance of the Training Periodic Review must be documented.

 Completion of periodic training reviews as identified in the Training Master Plan or other commitment is the responsibility of management. If new hazards are identified, these must be submitted for evaluation through the QRM process and change management for implementation if appropriate.

 Stage 3 hazards may be identified in periodic review activities for a variety of reasons. New hazard identification may occur years after training was successfully completed. Stage 3 periodic review provides the opportunity to review ongoing routine performance of trained activities vs. approved training content, supporting materials, and procedures. Changes may have occurred in any of the above, making training inconsistent with aforementioned materials. For example, utilities may have been modified, supporting sampling diagrams may have changed, procedures may have changed, or practices may have changed without concurrent changes in training. Stage 3 hazards are also evaluated and integrated in stage 1 design per change management. 

 and case studies provide examples, experiences, and observations of potential stage 3 problems. 

Case study #4: low tablet target potency. 

Periodic review of a tablet compressing process was conducted. The manufacturing technician was an excellent machine operator (“Best Technician Award”). His manufactured products always met acceptance specifications and product yields were always above average. Further evaluation of product potency data made under his responsibility indicated a slightly low average potency (97–98%) compared to lots made by other personnel. The manufacturing supervisor observed his machine setup and operation; tablet weight setup was within specifications, but always at a theoretical weight of less than 100%. When questioned why tablet weight was not adjusted to 100%, the technician responded that he always set a slightly low weight so that he would have a high product yield—management wants high yield and more profit—this is why he was “Best Technician.” Technician performance was the hazard in this case. GMP allows product release within specification (usually 95-105%), but product must be formulated to contain 100% unless otherwise justified. The technician was retrained on GMP requirements. Training documentation was revised to emphasize 100% formulation target requirements. Recognition procedures were modified to eliminate product yield as criterion for employee performance.

Case study #5: supporting documentation. 

Periodic review of site utility systems was conducted. Documents reviewed included procedures, supporting documents, and associated training. Supportive drawings and training documents were incomplete and not updated. Hazard in this case was inaccurate documentation. Investigation of discrepancies between documents indicated that final changes on drawings and training were not completed due to competing work priorities; responsible personnel were assigned other projects with higher priority. Review of other systems (e.g., compressed air, ethanol, and other utilities that had been recently modified) had similar inconsistencies—engineers were never allowed to completely finish a project before being reassigned by management to higher priority work.

Case study #6a: training culture—cleaning process review. 

Internal review of a product cleaning process was conducted in advance of a regulatory audit. Technical, Manufacturing, and quality assurance (QA) supervisors observed technician performance. Several discrepancies compared to approved procedures were noted. The amount of cleaning agent was modified; specific steps were changed to increase efficiency; an unspecified organic solvent was used to remove stains. When questioned about discrepancies, the manufacturing technician expressed site reality—the approved cleaning procedure was ineffective. Management advised to fix the cleaning problems without involving the technical group. The site culture was identified as the hazard in this case. The above occurrence demonstrated problems with interpersonal relationships, interactions between groups, function silos, and general disrespect for approved policies and procedures; technicians proudly stated, “We do whatever it takes to get the job done.” Management leadership and attitude were also identified as contributing to this hazard. The site quality culture begins with management (19). Several corrective actions were initiated within various functions at the site. Personnel learned to follow procedures and not “to do whatever it takes”.

Case study #6b: training culture—aseptic compounding. 

A sterile compounding facility required technician training and annual re-qualification on aseptic techniques. Testing required handwashing, garbing, work area sanitization, technique demonstrations, aseptic transfer of sterile media between vials, finger impressions testing, and related activities. Personnel observing testing noted unusually high frequencies of hand sanitization and surface sanitization by technicians; supervisors were continually reminding trainees to sanitize their hands. Most troubling was hand sanitization immediately prior to finger impression testing. The donning of new sterile gloves or spraying 70% alcohol immediately before finger-impression testing does not challenge aseptic technique and does not represent actual work performance. The site culture was identified as the hazard in this case. Technicians explained that the department manager told them, “There shall be no problems with qualification testing—do whatever necessary to prevent failures.” A deficient quality culture at the site translated into substandard employee behavior..

This paper discusses applications of QRM principles in a site training quality system. QRM applications enable several significant benefits to training.

 QRM in training focuses on identification of training problems. QRM application provides a distinct and comprehensive approach that complements traditional training. Training fundamentally comprises prospective activities (i.e., how to do things and why things are done). QRM provides additional relevant considerations to training—what can go wrong. QRM thus helps to describe training reality in the workplace. Hazard identification facilitates problem evaluation and subsequent action as needed.

 This discussion is structured according to the lifecycle approach as used in process validation. A lifecycle approach to training is described that affords opportunities to review and continually improve the training process. Three stages of QRM activities are identified, and QRM hazards are identified in each stage:

Stage 1 training design comprises planning and relates to hazards that are associated with training content, trainers, trainees, and the training process; stage 1 hazards are identified when new training is originally developed.

Stage 2 training performance relates to hazards associated with actual training activities when trainers present content to trainees; observation of stage 2 training may identify new hazards and necessitate modifications to content, trainer, or other designed elements.

Stage 3 continuous training monitoring (i.e., training periodic review) relates to hazards associated with the ongoing performance of trained procedures—training effectiveness, content accuracy, employee performance, consistency with related documentation, and compliance with approved procedures. Observation of training content and/or performance in stage 3 may also necessitate modifications to training content.

 illustrates the respective stages of the training lifecycle. Stages of the training lifecycle (black print) anchor the overall training process; hazards are originally identified in stage 1 when training is developed. If new hazards are identified in stage 2 or stage 3 (red print), these are forwarded to stage 1 for evaluation and integration with training content, presentation, testing, and other elements; training quality is maintained and continually improved by this process. 

 Training management has significant responsibility and influence on performance of site training as follows:

 Training management is responsible for all training activities in all stages as well as for the general training function administration. Training is a cost; training management must balance accomplishing training objectives within site budgetary constraints. Numerous QRM hazards may be associated with management responsibilities. Management must integrate QRM considerations to maintain and improve training content. Management in this context includes training management as well as other site function management involved in training.

 A site training program often utilizes individuals from other site functions as trainers, SMEs, training content authors, or other contributors. These individuals also have direct responsibility for employee training. Training management must ensure these contributors know and understand their responsibilities, including QRM considerations, and that they are accountable for successful employee learning.

 Training management significantly influences the attitudes and performance of trained employees. Employee training is among the first activities of new employees; this relationship continues throughout the employee career with additional training, re-training, and other interactions. Management commitment to training excellence, including QRM considerations, must be visible and sets the tone for employee performance. Management actions influence the development of a quality culture in the organization.

Helpful discussions with Kevin O’Donnell, PhD, Health Products Regulatory Authority (HPRA) Ireland; Alan M. Mancini, RPh; and Richard Poska, RPh, managing director, Flexo CMC Consulting, Nokomis, Fla., are greatly appreciated.

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Paul L. Pluta, PhD, RPh, is a pharmaceutical scientist with experience in pharma industry, university academia, pharmaceutical journal editorship, and community and hospital pharmacy practice.

®
Vol. 48, No. 11
November 2024
Pages: 20–26

When referring to this article, please cite it as Pluta, P. L. Application of Validation Principles to the Training Quality System: Part 9, Quality Risk Management Hazard Identification. 

Special Report

Pharmaceutical training programs are enhanced by integrating ICH quality risk management considerations.

Application of Validation Principles to the Training Quality System: Part 9, Quality Risk Management Hazard Identification

High-throughput screening (HTS) enables the rapid testing of numerous compounds against biological targets. By automating and miniaturizing assays, HTS significantly accelerates the identification of potential drug candidates or optimal process conditions and can be applied throughout the entire development path of a potential drug, from discovery to process development. In the discovery phase, HTS is one of several hit-identification (Hit-ID) paradigms and involves the use of sensitive and miniaturized methods for screening large libraries of small molecules in a practical and efficient manner. During process development, HTS helps researchers rapidly establish an optimal synthetic route and conditions for each process step that reliably produce sufficient material quickly.

The most widely used HTS technologies for identification of small-molecule API candidates include fluorescence-based, luminescence-based, and absorbance-based assays, according to Sachin Mahale, research leader, Discovery Sciences at Charles River. He adds that methods for detection of unlabeled biomolecules, such as those based on mass spectrometry, have also become more widely used at an HTS-scale in recent years, allowing the screening of compounds in both biochemical and cellular settings and thus expanding the breadth of targets to those that would otherwise be unscreenable. High-content imaging and automated electrophysiology are additional techniques providing multi-parametric cellular data that are becoming more widespread in high-throughput formats for discovery research, Mahale observes.

“Considering the vast number of technologies, each one of them serving a different purpose to address the scientific question, naturally different attributes, including binding affinities, reaction kinetics, enzymatic activity, functional activity, target engagement, selectivity, and specificity, are often analyzed. These attributes are critical because they provide early insights into the potential efficacy and selectivity of drug candidates, which is essential for optimizing pharmacological profiles,” says Mahale. Given the wide range of technologies available, he also emphasizes the importance of selecting a fit-for-purpose technology to address each biological question.

Numerous advantages for process development

During the early stages of candidate development, the synthetic pathway is still flexible, making HTS particularly valuable, according to Jens Schmidt, associate director of manufacturing, science, and technology at Lonza. “HTS can help process development scientists rapidly evaluate the feasibility of different synthetic routes or optimal chemical combinations, such as solvents, catalysts, and bases,” he explains. As the project advances through clinical phases, the flexibility in process steps decreases, but HTS remains useful for expanding the understanding of the process, such as its reaction kinetics.

Overall, using HTS during process development can, contends Schmidt, “help in the optimization and simplification of established workflows, integration of emerging technologies such as photochemistry and electrochemistry, and leveraging of rapidly evolving computational tools like artificial intelligence (AI) and machine learning (ML).”

One of the key advances in HTS for drug discovery and development is the adoption of a wider array of state-of-the-art analytical techniques for this application. The most notable technologies introduced recently as high-throughput platforms include affinity selection mass spectrometry (ASMS)-based screening platforms such as self-assembled monolayer desorption ionization (SAMDI), target protein degradation (TPD), and molecular glue platforms; and CRISPR (clustered regularly interspaced short palindromic repeats)-based functional screening platforms, notes Luke Alderwick, senior group leader, Discovery Sciences with Charles River.

ASMS screening is increasingly used to discover small molecules that engage a specific target, says Alderwick. “Highly advanced ASMS platforms that use rapid workflows to quickly generate high-quality data are getting traction as HTS methods. The platform is amenable to a broad spectrum of targets, including proteins, complexes, and oligonucleotides such as RNA, and can be a leading assay to initiate drug discovery programs,” he comments. Unlike traditional label-free approaches, which are often slow, restrictive, and not optimal for large screening campaigns, Alderwick adds that new solutions such as Charles River’s SAMDI ASMS platform allow efficient investigation of protein-protein interactions, TPD, molecular glues, RNA binders, etc. in a high-throughput format.

CRISPR-based functional screening, meanwhile, is employed to elucidate the biological pathways involved in disease processes, according to Alderwick. CRISPR editing of genes for knock-out and knock-in experiments have greatly advanced assay designs for cell-based phenotypic HTS approaches, he explains. In addition, by selectively tagging proteins of interest, CRISPR is advancing the understanding of target engagement and functional effects of drug treatments. “By screening small molecules alongside CRISPR-modified cells, researchers can better understand drug-target interactions at a genomic level, enabling the selection of candidates with higher precision,” says Alderwick.

Overall, Alderwick summarizes, these various innovations have improved the scalability, specificity, and throughput of HTS, enabling researchers to screen more diverse compound libraries and discover novel molecular mechanisms of action.

Automation and miniaturization technologies having an impact

Some of the biggest advances improving and expanding HTS for drug discovery and development relate to automation and miniaturization of laboratory systems. “Automation is transforming the landscape of API development and manufacturing,” Schmidt states.

Automated liquid-handling robots, says Mahale, have become faster, more accurate, and capable of working with extremely low volumes of reagents, enabling more cost-effective screening. “Advances in pipetting precision, multi-plate handling, and integration with other systems (like incubators, centrifuges, and imagers) have significantly reduced human error and improved reproducibility. Automated workflows for complex cell assays and readouts based on imaging analysis, meanwhile, allow multiple assays to be performed with minimal consumable cost and keeping sustainability in mind. Use of multimode plate readers in the automation workflow also allows for multiplex assays to maximize data collection,” he details.

By automating process development tasks, researchers can significantly accelerate the identification of optimal synthetic pathways and fine-tune processes for maximum efficiency, according to Schmidt. “This translates to faster development times, reduced errors, and more consistent API production. For drug developers, this means reduced risk and uncertainty in API development, enabling a greater focus on clinical trials and regulatory approvals,” he contends.

More specifically, automation accelerates workflows by allowing researchers to complete multiple tasks at once. “This kind of parallelization is especially helpful for processes like catalyst screening, ligand screening, or solvent selection. Automation also allows chemists to conduct experiments in high-pressure and high-temperature conditions, which are difficult to complete manually. With these features, automation makes experimentation in the lab more targeted and efficient, saving valuable time, energy, and cost,” Schmidt notes.

In addition to advances in automation, innovation in miniaturization technologies is helping to improve HTS performance. “By shrinking assay volumes, miniaturized platforms like microfluidics and nanodispensing have allowed for higher throughput while reducing reagent consumption,” Mahale remarks. Access to smaller-volume assays, he says, is especially useful in fragment-based drug discovery and the screening of complex biological samples, as it allows for cost-effective experiments with even larger libraries.

Data analysis and sharing solutions making a difference

In addition to innovation in the analytical methods and laboratory equipment used for HTS, significant advances have also occurred in the software arena, most notably the integration of AI and ML for data analysis and improvements in cloud-based platforms for collaborative research.

New AI algorithms can, observes Schmidt, analyze data from high-content screening systems, detecting complex patterns and trends that would otherwise be challenging for humans to identify. AI/ML algorithms can identify patterns and predict the activity of small-molecule candidates, even when the data are noisy or incomplete, Mahale adds. In addition to significantly speeding up the analysis of screening results and identifying promising leads faster and with higher accuracy, integration of AI into HTS processes can also improve assay optimization, he comments. Another key advantage of AI-driven HTS, according to Mahale, is its ability to adapt to new data in real time when compared to traditional HTS relying on pre-determined conditions.

“These advances in AI and ML have been pivotal in accelerating drug discovery by improving both the quality of data and the efficiency of experimental processes. In the early stages of development, meanwhile, using these advanced solutions provides a holistic view that streamlines route scouting and accelerates the transition from research and development to robust manufacturing processes,” Schmidt says. As an example, he points to Lonza’s AI Route Scouting Service, which integrates proprietary commercial data with cutting-edge synthesis planning technology. “This innovation allows for more accurate and comprehensive analysis of cellular phenotypes, providing deeper insights into the efficacy and safety of drug candidates,” he notes.

Cloud technology, meanwhile, has enhanced the ability to store, share, and analyze HTS data across multiple sites in real time, says Mahale. “The result is improved collaboration between research teams globally, reduced data redundancy, and increased application of machine learning models on large datasets,” he explains.

Combined, Mahale believes the various software innovations incorporated into HTS systems are enabling the handling of more complex datasets, improving prediction accuracy and streamlining the drug discovery pipeline.

Implementing HTS for drug discovery and development is not a simple matter. The systems are both complex and costly. Fortunately, minimizing these issues has also been a focus of technology providers and end users.

Schmidt points to significant advancements in standardization and simplification of workflows as helping to accelerate HTE experimentation timelines and reduce costs. Examples include the development of standardized protocols and data formats, which has simplified the implementation and operation of HTE assays, specifically improving their accessibility and accuracy. He also notes that software tools powered by AI have made it easier for researchers to design, execute, and analyze HTE experiments.

Another effective approach, according to Alderwick, is to leverage tailored compound libraries such as Charles River’s Lead-Like Compound Library, which include compounds with lead-like properties and diversity and excludes problem chemotypes. The company’s Fast-Track HTS offerings leverages this library to provide rapid hit discovery and lead identification while maintaining high-quality data outputs, he adds. “With a fixed-cost and streamlined program, this service is ideal for proof-of-concept studies and suits research groups or companies with limited funding because it allows for high-quality, early-stage screening without the need for extensive internal resources or infrastructure,” Alderwick says.

Alderwick also notes that modular systems in development offer the potential to customize HTS systems to the specific needs of a lab, which will further lower the initial capital investment required. “All of these advances are making HTS more cost-effective, scalable, and user-friendly, reducing barriers to entry for smaller research organizations,” he concludes.

Despite the many remarkable advances made in HTS technologies for drug discovery and process development, significant challenges impacting both the efficiency of identifying optimal small-molecule candidates and processes, and their downstream success in clinical trials, remain.

One important issue, according to Schmidt, is the need to analyze large HTE datasets that require significant computational resources. “This can be a bottleneck for many drug developers, which is why partnering with a contract development and manufacturing organization (CDMO) like Lonza can be helpful. CDMOs have the tools and technology, such as AI algorithms, to help drug developers analyze data and progress through development stages quickly,” he says.

There are also challenges to handling very small amounts of solids, Schmidt notes. “Although this may seem like a minor technical detail, understanding and accepting these limitations is crucial,” he says. One potential solution highlighted by Schmidt is the use of solid supports such as ChemBeads (MilliporeSigma), small, chemical-coated glass beads created specifically for use in HTS applications.

A primary challenge in HTS for drug discovery is identifying assays that are physiologically relevant to the disease state despite the need for simplification to ensure scalability and robustness, according to Mahale. Model systems do not always translate well. In addition, biochemical assays, while simpler, often fail to capture the nuances of cellular contexts, such as the impact of membrane permeability, metabolite production, or protein-protein interactions, while cell-based assays are closer to physiological reality but are more complex, expensive, and challenging to miniaturize.

“The complexity of human diseases, particularly multifactorial diseases like cancer or neurodegenerative disorders, makes it difficult to develop assays that can recapitulate the true pathophysiology of the disease,” Alderwick observes. “Poor assay choice,” he continues, “leads to the identification of hits that might show promise in early testing but later fail due to lack of efficacy or off-target effects in more complex disease models or clinical settings. The incorrect assay not only risks identifying false positives but also misses out on potential therapeutic candidates that could have better real-world efficacy. This limitation significantly contributes to the high attrition rates in drug development.”

Another challenge is the development of a robust screening cascade (primary, secondary, and tertiary screenings) that helps to identify, confirm, validate, and refine viable candidates and reduce the attrition rate during later stages of drug development. Further assays are then employed during lead optimization to assess toxicity, selectivity, functional activity, bioavailability, and pharmacokinetics for further hit validation. “Failures in designing an appropriate HTS cascade occur when these different stages are not sufficiently de-risked,” contends Alderwick.

While incorporating more predictive absorption, distribution, metabolism, excretion, and toxicity screens early in the process has helped de-risk candidate selection to some degree, the challenge still lies in balancing the need for throughput and speed with the inclusion of more complex, multi-parametric data, according to Alderwick. “Early prediction of 

 efficacy and safety in HTS remains a weak point, contributing to high failure rates in the transition from hit-to-lead and lead-to-clinical candidate stages,” he concludes.

Finally, Mahale notes that the selection of chemically diverse and high-quality libraries for HTS is pivotal in the success of small-molecule candidate identification, because even with the best assays, if the chemical library lacks diversity or contains unsuitable and non-drug-like compounds, the likelihood of finding optimal candidates diminishes. “Many historical compound libraries are biased toward certain chemical scaffolds that have been repeatedly screened over decades, thus reducing the chances of discovering novel small molecules with new mechanisms of action,” he observes. Charles River, Mahale adds, has tackled this issue by developing an expertly curated small-molecule compound library that covers a wide range of structural and functional diversity, thereby maximizing the probability of finding useful hits.

Several emerging strategies aim to improve the efficiency, reliability, and outcomes of HTS by leveraging advancements in technology, biology, and chemistry, according to Alderwick. Advances in organoid and 3D-cell culture technologies are helping to bridge the gap between simple 

 assays and complex human disease biology, and thus address the need for more physiologically relevant assays, he observes. “These models better mimic the physiological conditions of tissues and organs, providing a more relevant system for screening potential drug candidates,” Alderwick explains. Organoids derived from patient tissues, for example, can offer insights into how drugs might work in specific disease contexts, improving the predictive power of assays.

To shrink the gap between biochemical, cell-free assays and phenotypic, cell-based screens and thus better understand the on-target activity of identified hit molecules, including binding assays such as for target engagement and protein-protein interaction analysis in the HTS screening cascade, would greatly advance the ability to select optimal compounds for further development, believes Alderwick. He also notes that the use of advanced cellular models, such as CRISPR/Cas (

-associated protein) knockouts and induced pluripotent stem cells, for early screening is likely to improve HTS outcomes.

Continued advances in automation and the use of AI and ML will further enable HTS platforms to handle more complex assays with higher precision, reproducibility, and throughput, according to Mahale. “Fully automated HTS systems can reduce human error, improve the consistency of assay conditions, and allow for more sophisticated workflows that balance throughput with data quality, while incorporation of AI/ML algorithms can reduce the rates of false readouts, making HTS more reliable and reducing the time spent following up on false positives,” he says.

Ultimately, concludes Mahale, these emerging solutions aim to reduce the high attrition rates in drug discovery by improving the relevance and quality of the screening process, optimizing candidate selection, and expanding the chemical diversity available for exploration. “While challenges remain, these developments promise to significantly enhance the utility of HTS in the drug development pipeline,” he contends.

Looking beyond these strategies, Alderwick is excited about the trend toward integration of multi-omics approaches into HTS, which he says represent a major leap forward in the ability to identify optimal small-molecule API candidates. “Multi-omics approaches leverage data from various molecular levels, including genomics, proteomics, transcriptomics, metabolomics, and even epigenomics, providing a more comprehensive and holistic understanding of how small molecules interact with entire biological networks and pathways rather than isolated targets,” he explains. “Complex diseases such as cancer, neurodegenerative disorders, and metabolic syndromes often involve multiple, interconnected biological systems, and thus multi-omics approaches have a greater likelihood of identifying effective new drug candidates,” he states.

In today’s fast-paced drug manufacturing environment, HTS has become an indispensable tool. However, Schmidt emphasizes that advances in technology are not sufficient by themselves to enhance the performance of these platforms. “Looking ahead, we can expect continued improvements in both reliability and simplicity, but the key to success lies in having a motivated, dedicated, and technically skilled team that is ready to embrace challenges and open to adopting innovative techniques,” he insists. 

Cynthia A. Challener, PhD, is a contributing editor for 


Vol. 48, No. 11
November 2024
Pages: 12–16

When referring to this article, please cite it as Challener, C. Accelerating Discovery and Development with Advances in High-Throughput Screening. 

Development

Automation, miniaturization, and new software algorithms are improving throughput and accuracy.

Accelerating Discovery and Development with Advances in High-Throughput Screening

In the course of the significant transformation of the biopharmaceutical industry, modular manufacturing emerges as a game-changing approach to fluid management. This innovative methodology is reshaping how pharmaceutical companies and contract development and manufacturing organizations (CDMOs) produce and handle biopharmaceuticals, offering unprecedented flexibility, efficiency, and scalability.

Modular manufacturing in biopharmaceutical fluid management (

It allows for rapid adaptation that is due to either changing market demands or product specifications.

It enables manufacturers to optimize their production processes, reducing costs and improving product quality.

It facilitates easier compliance with regulatory requirements.

The latter is true when technologies provide better control and traceability throughout the manufacturing process. The integration of modular systems with manufacturing execution systems (MES) helps ensure seamless operations, real-time monitoring, and data-driven decision-making.

Overall, the approach to add modularity is particularly valuable when dealing with diverse product portfolios, varying batch sizes, and the potential need for quick scale-up or scale-out capabilities.

Process flexibility: a necessity in modern biomanufacturing

In today’s dynamic biopharmaceutical landscape, process flexibility is not just an advantage—it’s a necessity. CDMOs, in particular, face the challenge of producing a wide array of products with different specifications, volumes, and handling requirements.

One of the primary drivers for process flexibility is the diverse nature of biopharmaceutical products. From monoclonal antibodies (mAbs) to cell and gene therapies, each product may require unique processing conditions, volumes, and handling protocols. Such a volatile demand necessitates rapid scalability.

Will the COVID-19 pandemic remain unique? Uncertain. However, it has prompted manufacturers to be more prepared for potential further outbreaks, such as monkeypox. With pandemic preparedness comes the importance of being able to scale up production swiftly. Modular manufacturing systems provide the agility needed to respond to such sudden surges in demand. They also allow CDMOs to quickly reconfigure their production lines to accommodate these varying needs without significant downtime or retooling or alternatively piling equipment for all possible events and scales.

Why would CDMOs invest in a full set of multiple technologies when they can have one modular system for many scenarios?

Fluid management in manufacturing: the shift to automated closed systems

Fluid management is all about transferring liquids in biopharmaceutical manufacturing between different process steps. This can be the case in upstream, downstream, fill/finish, or in between. The industry is witnessing a transition from manual, open handling to automated closed systems, in large part due to Annex 1 of the European Commission’s guidelines, which favors closed systems. This regulatory requirement has been effective in shifting the interest of manufacturers and CDMOs to automated closed systems (1). The shift in attitude is primarily driven by the need for increased sterility, reduced contamination risks, and improved process control. Even for aliquoting small volumes into single-use bags, closed systems are increasingly being used (see 

Why would a manufacturer or CDMO want to close the fluid path system? Responses to this question include the following:

Enhanced sterility: by minimizing human intervention and exposure to the environment, closed systems significantly reduce the risk of contamination.

Improved process control: automated systems allow for precise control over filling parameters, ensuring consistency across batches.

Increased efficiency: automation reduces manual handling, leading to faster processing times and reduced labor costs.

Better traceability: closed systems integrated with MES provide comprehensive data logging, facilitating easier compliance with regulatory requirements.

Six most current pain points and challenges in fluid management

Despite the advancements in fluid management processes, several challenges persist in the biopharmaceutical industry.

 Many current systems struggle to accommodate varying production volumes efficiently. So many aspects can change, be it the batch volume or the size of the primary packaging. Does the manufacturer fill 100 L of antibody-drug conjugates into five single-use bags of 20 L? Or does the manufacturer dispense 20 L of viral vectors into 40 single-use bags of 500 mL? Do mAbs even need to be filled into 20 1-L bottles?Scaling up, down, or out often requires significant changes to equipment or processes, leading to increased costs and downtime.

 There is one closed system that CDMOs do not like—the closed ecosystem of technologies. A vendor lock-in and the resulting incompatibilities can restrict flexibility and increase costs for manufacturers. If Solution Provider A only accepts its own single-use assemblies, single-use bags, and sometimes even platform systems and not those of Vendor B or C, it limits both the drive for optimization and productivity and simply prevents CDMOs from following suit with their customers’ mandatory equipment.

 The need for different systems to handle various scales of production leads to increased capital expenditure, larger footprints, and more complex training requirements for operators, even more when platform systems are not modular. Adding a number of technologies does not necessarily equal scalability. More equipment is just a problem with regards to footprint in manufacturing suites.

 As the industry moves toward advanced therapy medicinal products (ATMPs) and personalized medicines, the need for precise handling of small volumes becomes critical. Many existing systems lack the required accuracy for these applications into single-use bags. In most cases, scales are integrated to measure larger filling quantities, while flow sensors are used to aliquot smaller volumes.

 Some biopharmaceuticals, particularly cell-based products, always require precise temperature control. Otherwise, inaccurate temperatures reduce cell viability, such as when cells are held too warm for too long. Most current systems struggle to maintain optimal temperatures in process steps before the cooling process.

 Most existing systems often leave significant residual volumes in tubing and containers, leading to product waste and reduced yield. This waste can be limited by draining single-use assemblies post filling with negative pressure.

Streamlining requirements: a (liquid) path forward

All of the mentioned pain points are issues that every manufacturer would want to be solved. But do all these pain points make sense for a specific manufacturer’s production? These points are of importance when biopharmaceutical manufacturers and CDMOs carefully consider their project criteria and priorities when selecting or designing fluid management systems.

What are the key project criteria, and in what order should these criteria be prioritized?

Shifting to automated, closed modular manufacturing systems is growing increasingly crucial for biopharmaceutical production.

Pharmaceutical Technology, November 2024

Increasing Processing Flexibility to Meet Demand

Application of Validation Principles to the Training Quality System: Part 9, Quality Risk Management Hazard Identification

Accelerating Discovery and Development with Advances in High-Throughput Screening

Automate Aseptic Filling: Closing the System at Full Modularity

Untethered Data: Unifying and Contextualizing Drug Discovery Data

Strategies for Overcoming Common Challenges in Tech Transfer

Weathering the Storms

The Importance of Appropriate Supplier Oversight