Pharmaceutical three-dimensional printing (3DP) technology offers an automated platform that can be utilized to manufacture personalized medicine, improving pharmacotherapy. Although 3D-printed products have entered clinical trials, no costing studies have been performed yet. Cost insights can aid researchers and industry in making informed decisions about the feasibility and scalability of 3DP.
Objective
The aim of this research was therefore to develop a framework that can be utilized to estimate the manufacturing cost of one 3D tablet in a hospital pharmacy setting.
Methods
To develop the costing framework, general manufacturing phases were identified, consisting of (i) pre-printing, (ii) printing, and (iii) post-printing. For each phase, cost categories were defined, including personnel, materials, equipment, facility, and quality assurance. The three phases combined with the categories formed the base of the costing framework. An earlier developed 3D-printed hydrocortisone formulation (M3DICORT) was used as a case study. Costs were expressed in 2022 euros (€). The framework was applied to M3DICORT in four scenarios: a base case scenario, worst-case scenario, best-case scenario, and a scaling scenario. In the scaling scenario, we assumed that 3D inks were mass produced.
Results
Costs of manufacturing a single M3DICORT tablet were €1.97–3.11 (best-case–worst-case) and €1.58–2.26 for the scaling scenario.
Conclusion
Manufacturing costs of 3D-printed pharmaceuticals were thus far unknown. The framework is translated into an open-access costing tool to facilitate adoption by other parties, and is also applicable for other pharmaceutical 3DP techniques.
Pharmaceutical 3D printing allows for the personalization of medicines, by adapting shape, taste, dosage, and release profile. No formal costing studies for pharmaceutical 3D printing have been performed yet.
The aim was to provide insights in the manufacturing costs of 3D printed pharmaceuticals. A freely accessible costing framework has been developed to estimate manufacturing costs of 3D printed medication.
The costing framework was used to estimate manufacturing costs of M3DICORT, a 3D printed sustained release hydrocortisone product. The manufacturing cost of a single M3DICORT tablet is €1.58–3.11.
1 Introduction
Pharmaceutical products are often manufactured in bulk and generally effective for most patients. However, some individuals require personalized pharmaceutical products. Therefore, the emergence of three-dimensional printing (3DP) in pharmaceutical manufacturing has attracted significant attention in recent years [1, 2]. 3DP has been mainly used in academic research to manufacture personalized oral dosage forms, such as tablets. Several studies have shown that this technology has the potential to improve pharmacotherapy by personalizing the drug dose and, release profile, and release profile, and even adapting taste, appearance, or shape [3‐5]. The major advantage of 3DP is allowing for personalization of drug dose and release profiles, compared with conventional manufacturing of pharmaceuticals [2]. Currently in (hospital) pharmacies, drug formulations are compounded by using manual capsule filling machines or by manipulating existing dosage forms. Both approaches come with safety and quality concerns as these practices may lead to dosing errors, putting patients at risk [6‐9]. In contrast, studies on 3DP have demonstrated the feasibility of printing personalized medication with varying dose ranges and with high quality [10, 11]. For instance, Pietrzak et al. (2015) demonstrated that the tablet dose can be personalized by adjusted the 3D-printed tablet size [12]. Additionally, Macedo et al. (2022) demonstrated that 3D-printed tablets have intra-batch mass and drug content variabilities are within pharmacopeial limits, indicating high quality [13]. Although several studies have been published demonstrating the role of 3DP in drug manufacturing, no formal costing studies have been performed in this field yet [2, 14, 15]. However, to successfully move from proof-of-concept to more widespread implementation, insights into economic aspects related to manufacturing process of 3D-printed pharmaceuticals are needed, particularly as the first of such products have already entered clinical trials [11, 16]. Insight in economic aspects such as resource use and major cost drivers can help researchers and the industry make informed decisions about the feasibility and scalability of 3DP for drug manufacturing. Only with a thorough understanding of all cost items can the most cost-effective strategies for manufacturing and distribution be identified to facilitate patient access. Cost insights may also be useful for health technology assessment bodies in case of a reimbursement decision, as well as for clinicians, pharmacists, investors, and for policymakers to include economic considerations during guideline development [17, 18]. Therefore, the aim of this study was to develop a costing framework to assess manufacturing costs of pharmaceutical 3DP in a small-scale hospital pharmacy setting. The development of the framework, including the manufacturing process of 3D-printed products, are stated in the methods. The methodology underlying the costing framework is demonstrated through a case study of 3D-printed sustained-release hydrocortisone for patients with adrenal insufficiency (M3DICORT) [10].
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2 Methods
2.1 Framework Development
To develop the costing framework, we first identified the different phases of the 3DP process. The 3DP manufacturing phases were based on our previous experience in pharmaceutical 3DP and reflect the general manufacturing phases. Subsequently, we used the costing framework for a micro-costing study with several scenarios on M3DICORT. The formulation of M3DICORT was developed in previous research using fused deposition modeling (FDM) 3DP, and is described in detail elsewhere [10]. The study was conducted at the academic hospital pharmacy of the Erasmus Medical Center (MC), which has a total surface area of 2654 m2, 230 full-time equivalent (FTE) personnel, and is hence the largest academic hospital pharmacy in the Netherlands.
The costing framework includes three main phases in the 3DP process: (i) pre-printing, (ii) printing, and (iii) post-printing. For each phase, cost categories were identified including personnel, materials, equipment, facility, and quality assurance (QA). These cost categories are based on an existing manufacturing framework for Advanced Therapy Medicinal Products [19].
2.2 3D Printing Process
In phase 1, in the pre-printing phase, a digital 3D model is designed and converted to a readable file for the 3D printer to produce the desired shape. 3D models are designed using generic computer-aided design (CAD) software. These models can be directly accessed through ready-to-use digital designs, available for download in the .stl file format. Once obtained, an .stl file is converted into a geometric-code (g-code) by specialized 3DP software. This g-code entails the precise movements required by the printer, guiding it to accurately reproduce the 3D model layer by layer. The design of the final product is a crucial step in pharmaceutical 3DP as it influences the release profile and supports the manufacturing of specific formulation dosages [5, 10, 20, 21]. The detailed manufacturing steps, including the design of the M3DICORT used in this study are described elsewhere [10]. Once designed, the g-code can be used over and over.
During the pre-printing phase, drug-loaded filaments, which serve as the ink for the 3D printer, are manufactured. To this end, raw pharmaceutical powders are mixed and melted by means of hot melt extrusion, resulting in a printable drug-loaded filament. Currently, drug-loaded filaments are not commercially available and have to be manufactured in-house.
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In phase 2, the printing phase, the drug-loaded filament is manually fed into the 3D printer, after which the tablets are printed layer-by-layer until the final products are formed.
Finally, in phase 3, the post-printing phase, the printed tablets undergo rigorous quality checks and packaging. In pharmaceutical manufacturing lines, quality control (QC) and quality assurance (QA) systems play a crucial role to guarantee and maintain high-quality standards. In terms of QC, both pharmaceutical manufacturing lines, raw pharmaceutical products and final products, need to be validated to ensure consistent quality. Typically, this is realized by analyzing drug contents, stability, uniformity, homogeneity, and mechanical properties of the final product. Before distribution, batches need to be formally released by a qualified person. In addition, during this phase, any used equipment is cleaned, and the printed tablets are packaged, labeled, and stored before transportation. QA involves an active quality management system which proactively prevents product defects and deviations. For instance, by conducting risk assessments, developing standard operating procedures, and comprehensive documentation to ensure that final products meet with predefined quality parameters. As hospital pharmacies generally have QA systems in place, this study limits QA costs to costs related to QA personnel only.
2.3 Costing Definitions and Allocation
For each of the three printing phases, the framework further distinguishes between fixed and variable costs within the following five cost categories: personnel, materials, equipment, facility, and QA. Fixed costs are defined as all costs that are not correlated with a change in the number of printed products or services, while variable costs are costs that change in proportion to manufacturing output.
To quantify manufacturing costs per identified phase and category, we applied the costing framework following an activity-based costing methodology with which costs were estimated as a function of volume and price per volume [22]. We assumed a manufacturer perspective, meaning that only costs incurred by the developer, in this study the Erasmus MC hospital pharmacy, were considered. Consequently, costs for diagnosis, medical interventions, and logistics were not included [23].
Fixed costs are defined as the sum of the costs per year divided by the amount of tablets produced annually. For variable costs, we took an opportunity cost approach to allocate variable cost items. Hence, we valued all time and resources that were spent manufacturing the product of interest and therefore could not be used for other purposes. Historic prices or costs were converted and adjusted for inflation in adherence to the guideline of the Dutch National Healthcare institute (Zorginstituut Nederland; ZIN) on economic evaluations studies [24]. All costs stated here are expressed in 2022 euros (€).
All expenses associated with materials were identified as variable costs and included raw pharmaceutical ingredients, disposable items (such as face masks and gloves), packaging, and labelling materials. Resource use frequencies for these items were based on the M3DICORT development study, with detailed quantities used for this case study provided in the supplementary appendix [10]. All these items were valued using retail prices, derived from quotations received by the hospital pharmacy.
All expenses associated with equipment were identified as fixed costs. Equipment needed to manufacture M3DICORT includes an FDM 3D printer, a hot melt extruder to produce filaments, a scale for weighing, a rotor stator mixer for mixing, and a label printer. Costs for these items were based on their initial acquisition price and an annual depreciation. This depreciation was calculated by dividing the purchase price by an annuity factor that incorporated the lifespan of the respective equipment. The latter was uniformly assumed to be 10 years for all equipment items [25]. In addition, a standard interest rate of 4.2%, and an annual maintenance markup of 5% of the purchase price was considered for all equipment [19]. The annual expenditure for each device was further adjusted on the basis of the printing time per tablet.
For the case study, we assumed that manufacturing is performed by a pharmacy technician and batch release by a qualified person (QP). It is a legal requirement for pharmaceutical manufacturers in the Netherlands to have a QP [26]. This QP is responsible for certifying the release of every batch of a pharmaceutical product. By releasing a batch, a QP ensures that the batch complies to applicable laws, requirements of the marketing authorization, and with good manufacturing practices. QPs are typically pharmacists, with additional training on quality of pharmaceutical products. Time needed for weighing, mixing, extruding, printing, cleaning, labeling, and packaging was recorded with a stopwatch. Times for batch release were based on expert opinion and experience, as 3D-printed medication is not formally released yet. Batch release is a quality check performed by a qualified pharmacist after production. If the batch is formally signed and released by the qualified person, it can be distributed, and the batch is then “released.” Assumed working hours for personnel were 1558 h per year, based on a 36-h workweek, including holidays [27]. Personnel times were either valued with their respective salaries gathered from the collective labor agreement from The Dutch Federation of University Medical Centres (Nederlandse Federatie van Universitair Medische Centra; NFU) 2022–2023 for pharmacy staff or with references prices from the Dutch costing manual [28]. A correction of 39% was applied to salaries, which included holiday payments and social funds [29]. Personnel costs related to cleaning, loading ink, and QA were considered fixed costs, as they are not influenced by the manufacturing output. Other personnel costs were considered variable. Total FTEs of the 3DP team at our site consist of 3.04% compared with the total pharmacy’s FTEs. CAD software is available license-free and 3DP software are usually delivered together with a 3D printer. Simple shapes, such as tablet designs, are typically generated for pharmaceutical 3DP. We have not applied costs for designing since the final design is identified during formulation development. Revision control of modelling and slicing software were not considered. Once dimensions and slicing parameters are established and logged, they can be generated easily with other modelling and slicing software.
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For facility costs, estimates of surface areas needed for pre-printing, printing, and post-printing rooms were made, including non-production rooms. Internal financial data demonstrate general costs of production rooms of €1467.87 per m2/year, and for non-production rooms at €698.40 m2/year. Production room costs were classified as variable costs, and non-production rooms as fixed. For the facility, we assumed that a total of 26 m2 was needed for manufacturing and storage and 7.6 m2 for offices, on the basis of internal pharmacy area data. On the basis of the 3.04% FTE, the share in m2 for the non-manufacturing areas (e.g., office, hallway, bathrooms) of the 3D facility was assumed to be the same value in relation to the whole facility.
In the base-case analysis we assumed a manufacturing output of an arbitrary 75% but varied this in scenario analyses to acknowledge variability in manufacturing output. For a precise analysis, we employed a “follow the technician” approach to monitor the duration of all activities across the three phases. More specifically, we measured start and stop time of all activities using a stopwatch, following an experienced technician. The production of 250 cm filament, which can be used to print 164 tablets, took 105 min. This includes weighing, mixing, and extruding. Hot melt extrusion, used to produce the filaments, is also known as continuous manufacturing [30]. In theory, by continuously adding powder to the extruder, an endless length of filament can be produced, enabling tablet printing until the filament is exhausted. Once produced, the filament is fed to the printer, which becomes the production rate-limiting step of the production process with a rate limited to 120 tablets per h. Assuming a facility run time per year is equal to personnel working hours, (i.e., 1558 h per year), a maximum manufacturing output of 186,960 tablets per year could potentially be realized.
Cost of quality management software is not included as all hospital and compounding pharmacies already have a quality management system in place. QC is a component of QA and its incurred fixed costs were considered for validating the manufacturing process, starting material analysis, and mandatory pharmacopeial tests for oral dosage forms. The latter encompass assessments of content uniformity, dissolution, friability, hardness, impurity testing, and a stability test [31]. The FTE of the QA department reflect the QA department of the Erasmus MC hospital pharmacy.
Per category, QA costs were categorized on the basis of their association either with ink manufacturing or 3D printing the final product. QA expenses specific to ink production were allocated to ink costs, while other attributes were attributed to 3DP. For costs that were related to both categories (i.e., ink production and 3DP), such as some facility expenses, a 50/50% allocation was applied.
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Several input parameters for the M3DICORT case study are summarized in Table 1, and more detailed costs of personnel, materials, equipment, facility, and QA are provided in the supplementary material for all scenarios.
Table 1
General input parameters.
Input parameters
Quantity
Working hours personnel and facility run time
1558 per year
Manufacturing output facility and equipment
186,960 tablets per year
One batch of filament
250 cm
Filament batch manufacturing time
105 min
Amount of filament for 1 tablet
1.52 cm
Filament manufacturing time for 1 tablet
0.64 min
One batch of tablets
50 tablets
Maximum tablet printing rate
120 tablets/h
FTE QA department/total FTE pharmacy
5–10%
Total personnel costs pharmacy
€17,464,000
Yearly maintenance equipment
5%
Yearly interest rate
4.2%
Total surface area pharmacy
2654 m2
Overhead facility
29%
Production room cost
€1468 per m2
Non-production room costs
€699 per m2
2.4 Scenario analysis
In three scenario analyses we assessed how different assumptions on the operational factors from the base-case would affect M3DICORT manufacturing costs. We specifically varied loss of materials during printing, manufacturing output, batch size, and QA share dedicated to M3DICORT quality.
The worst-case scenario was conceptualized to reflect the challenging operational environment. Here, the material loss during the printing process was highest, set at 20%, indicating significant inefficiencies. The manufacturing output was set at 50%, reflecting potential constraints in demand or operational limitations. This scenario also assumed that the printer would be dedicated to a single product, highlighting limited resource adaptability. Moreover, the QA department’s engagement was extensive, with 10% of the total full-time staff focused on M3DICORT tablet testing.
Conversely, the best-case scenario assumed an ideal setting where operational processes are optimized for maximum efficiency. Material loss was reduced to just 1%, indicating highly effective resource use. The primary cause of material loss is residue in the extruder, but this is mitigated with better process control, leading to reduced waste. With higher production output, the relative material loss becomes negligible, supporting the assumption of a 1% loss rate. Manufacturing output was therefore set at 100% of the maximum printing capacity, assuming full utilization of the facility. As a result, 186,960 tablets can be produced annually. This scenario allowed for the printer to be used for two different products, showcasing an efficient allocation of equipment. In all but the best-case scenario, there is an excess capacity available on the 3D printing recourse, allowing for more products to be printed. However, in the best-case scenario, the equipment is fully utilized at 100%, which maximizes output. Consequently, fixed costs are spread across a larger number of units, reducing the per-tablet cost. Additionally, in a typical manufacturing setup, facilities are shared for the production of multiple products. By increasing the variety of products produced, economies of scale are achieved, further reducing costs per unit. In this best-case scenario, we assumed a 50% reduction in the cost per tablet for equipment, facility, and QA expenses. Furthermore, the involvement of the QA department was set at 5% of the total staff, implying a streamlined and effective quality assurance process. The total costs to produce a single M3DICORT tablet for each scenario, except the scaling scenario, was calculated by adding the costs of manufacturing the ink to the costs of 3D printing the M3DICORT tablets.
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Finally, in the scaling scenario we calculated manufacturing costs under the assumption that ready-to-use pharmaceutical ink becomes commercially available. The aim was to mirror a realistic, balanced operational model with strategic procurement of filaments that fulfill quality standards and can thus directly be used for printing. We maintained the material loss during printing at 0–20%. The manufacturing output was 75%, relative to the maximum printing rate of 120 tablets per h. This increased output was driven by the assumption that pharmacies would purchase ready-to-use pharmaceutical inks, instead of manufacturing the filament materials in-house. By acquiring these pre-filled inks, pharmacists could save considerable time. Since purchased filaments would already fulfill certain quality criteria, the QA department’s involvement in this scenario was set at 5%, similar to the best-case scenario assumption. Here, we assumed that the manufacturing site is shared by 2–4 products, translating to a 50–75% reduction in costs per product in categories of QA, facility, and equipment. We assumed that due to volume discount, materials costs are reduced by 30%. When producing larger amounts of ink, weighing and mixing cost more time, while extruding and cleaning times remain fixed. We therefore assumed that due to scaling effects, personnel costs are reduced by 50%, compared with the base case scenario. The total costs for a 3D printed tablet in this scenario were calculated by adding the ink manufacturing costs to the costs of printing one tablet of the worst-case and best-case scenario.
3 Results
On the basis of the developed framework, the pharmaceutical 3DP process is divided into the three phases (i.e., pre-printing, printing, and post-printing) and represented in Fig. 1. Within these phases, more intricate processing steps, such as filament manufacturing, are included. The framework is translated into a tool, which is included in the online appendix of this research. In the appendix, both an unpopulated and a populated version of the framework are provided. The unpopulated framework serves as a template for developers to conduct their own cost analyses of 3DP in a hospital pharmacy setting.
Fig. 1
Schematic visual of the framework, including the pharmaceutical 3DP process (left) and cost categories (right)
×
On the basis of the framework, input parameters, and assumption, the total cost for manufacturing one 3DP M3DICORT tablet was estimated to be €2.34 in the base-case scenario, €3.11 in the worst-case scenario, €1.97 in the best-case scenario, and between €1.58 and €2.26 in the scaling scenario (Table 2).
Table 2
Assumptions, cost per category, and total cost to produce one 3D-printed tablet, split in ink manufacturing costs and 3D printing costs, for all scenarios
Base case scenario
Worst-case scenario
Best-case scenario
Scaling scenario
75% manufacturing output
50% manufacturing output
100% manufacturing output
75% manufacturing output
10% QA department
10% QA department
5% QA department
5% QA department
10% material loss
20% material loss
1% material loss
0–20% material loss
Dedicated facility and equipment
Dedicated facility and equipment
Facility and equipment shared by 2 products
50% lower personnel costs due to scaling
Shared facility and equipment by 2–4 products
Category
Ink
(€)
Printing (€)
Ink (€)
Printing
(€)
Ink
(€)
Printing
(€)
Ink (€)
Printing
(€)
Personnel
0.760
0.593
1.071
0.904
0.721
0.554
0.534
0.554–0.904
Materials
0.141
–
0.154
–
0.130
–
0.091–0.154
–
Equipment
0.169
0.147
0.110
0.147
0.055
0.073
0.035–0.073
0.073–0.147
Facility
0.211
0.243
0.297
0.314
0.169
0.209
0.026–0.051
0.209–0.314
QA
0.037
0.037
0.055
0.055
0.028
0.028
0.028
0.028–0.055
Total
1.32
1.02
1.69
1.42
1.10
0.86
0.71–0.84
0.86–1.42
4 Discussion
The aim of this research was to provide more insights in manufacturing costs associated with pharmaceutical 3DP. A framework containing costing categories including personnel, materials, equipment, facility, and QA was therefore established and used to calculate the costs of a 3D-printed sustained release hydrocortisone product (M3DICORT) [10]. Following this framework and using price and cost estimates in 2022 euros in the Netherlands, the total cost of one 3DP SR hydrocortisone tablet was estimated to be between €1.58 and €3.11, depending on the scenario. In a setting where a third party manufactures ink in high volumes, cost estimates of the final products can be lower. The ink manufacturing costs in this scenario are between €0.71 and €0.84, which is lower compared with the ink manufacturing costs of all other scenarios. The order of magnitude of the manufacturing costs for 3D printed pharmaceuticals were unknown until now. This study demonstrates that the manufacturing costs of one 3D-printed sustained release hydrocortisone tablet is several euros, which may also be the case for other generic, off-patent drugs. However, costs per tablet as an outcome measure do not reflect reality, as it is unlikely that the process will be conducted to produce just one tablet. Here it rather served as a simple outcome measure, which can be used for comparison purposes. Cost per prescription for, e.g., 30 or 90 tablets, can be easily calculated on the basis of the costs per tablet. The developed costing framework can also facilitate a cost estimation for other products and 3DP techniques intended for manufacturing by 3DP. The pre-printing, printing, and post-printing process applies to all 3D-printing techniques and the hydrocortisone can be replaced by other active pharmaceutical substances.
The application of 3DP in fabricating personalized medicine has been researched extensively in the past years. It is a promising technology that allows for personalization of medicines in terms of drug dosage, release profile, drug combinations, shape, and taste [5, 10, 11, 32]. The first 3D-printed medicines have already been tested in clinical trials [11, 16]. This study focused on the manufacturing costs of M3DICORT, a 3D-printed sustained-release, personalizable hydrocortisone tablet. It was developed for patients with adrenal insufficiency, where the hydrocortisone need differs from patient to patient [10]. Currently, there are no sustained-release alternatives on the market, of which the dose can be personalized to the need of an individual patient. 3D printing seems a feasible method to make personalized sustained release hydrocortisone available for patients that cannot maintain disease control with alternative hydrocortisone formulations. The prevalence of primary adrenal insufficiency is estimated at between 82 and 144/million, translating to 1476–2592 cases in the Netherlands [33], which is a chronic disease. A total of 2592 patients treated with once daily hydrocortisone translates to 946,080 tablets administered per year in the Netherlands. It is unknown which percentage of patients do not have stable disease control and would need a personalized 3D treatment. However, the facility described in this study can produce enough for more than 19% of the patient population per year. Production costs per prescription per month, assuming 30 tablets, are €70 per patient in the base case scenario.
It seems very likely that academic university hospital pharmacies and/or large compounding pharmacies adopt 3DP technology first [34]. We therefore gathered data from the Erasmus MC hospital pharmacy for the general input parameters. If demand increases, pharmaceutical ink manufacturers may be willing to enter the market. Pharmacies could then purchase ready-to-print inks for manufacturing. Our scaling scenario presents a practical and feasible model for the manufacturing of 3D-printed SR hydrocortisone tablets when filaments are commercially available. It illustrates how the strategic procurement of materials, coupled with optimized resource allocation, can lead to efficient printing. Ink manufacturers may be able to offer inks against lower prices due to high volume manufacturing and scaling effects.
The Food and Drug Administration (FDA) has published a proposed rule containing drug products that are difficult to compound; among them are drug products produced using hot melt extrusion [35]. This is based on formulation complexity, and for instance, compounding process complexity. It is very unlikely that small community pharmacies will use hot melt extrusion to produce filaments that can be printed subsequently. The equipment costs are very high, and operating and validating an extruder requires significant training. Rather, large GMP-compliant compounding pharmacies that extrude the filaments on a wider scale is a more realistic scenario. Centralized larger compounding facilities have the knowledge and facility to set up complex compounding methods. Furthermore, the framework applies to other 3DP methods as well, such as semi-solid extrusion (SSE). This is a simpler technique without use of a hot melt extruder.
In this study, we used a “follow the technician” approach to record the duration of all activities within the manufacturing process and offer a detailed perspective on time allocation for each task. This method contributed to the precision of our analysis, highlighting opportunities for enhancing process efficiency. However, it is important to acknowledge the learning curve associated with 3DP technologies, suggesting that the time spent on specific activities can fluctuate on the basis of the technician’s and organizations’ experience. As such, the times measured in this may not be fully representative of those in other facilities with different levels of expertise. Costs for training personnel have not been included, which may also be a limitation of this study.
The main limitation of this study was that this framework only includes manufacturing cost. Of note, not all costing categories associated with the final retail price of a pharmaceutical product were included. These categories include, but are not limited to, research and development (R&D), regulatory, profit margins, taxes, marketing, and logistics [36]. Especially, R&D costs can have a significant influence on costs and may vary depending on which printing technique is used. In our experience, developing a product with FDM takes much more R&D efforts, and therefore brings higher costs compared with SSE 3DP. This is due to the nature of the inks, as the filaments manufactured for FDM printing are challenging to develop as they require a balance in strength, stiffness, hardness, flexibility, and thermorheological properties [37]. In the case of SSE, the development of the ink might take less time and may therefore be less costly compared with FDM, as the mechanical properties are not relevant with this technique [38]. Raw materials are mixed, filled in a syringe, and subsequently printed, which is simpler compared with FDM [38]. The advantage of FDM compared with SSE is that it is likely easier to manufacture and store in bulk. When comparing this to the current standard of manufacturing magistral medication, which is manual capsule filling, the R&D costs of 3D printed medication may be higher. In manual capsule filling, raw powders are mixed and directly inserted in empty capsules, and the R&D costs for this process are minimal [11]. Nevertheless, 3DP continues to be researched thoroughly in pharmaceutics and there may be standardized bases for printable inks in the future, in which any drug could be integrated. This would reduce R&D time and costs for developing 3D-printed medication.
Profit margins may only be relevant in case pharmaceutical inks are commercialized. The costs of procuring the pharmaceutical inks may in that case be higher than our estimations in this study. It would have been more realistic to add the costs of procuring pharmaceutical inks to the printing costs, instead of the manufacturing costs, in the scaling scenario. There are, however, no publications related to the procurement costs of pharmaceutical inks. We therefore chose to add the printing costs of the best-case and worst-case scenarios to the ink manufacturing costs of the scaling scenario. In the scaling scenario, costs for filing the pharmaceutical ink for regulatory approval has also not been included but is very relevant. These costs may also increase the price of pharmaceutical inks. Profit margins, mark-ups, and marketing costs are less relevant in case 3D-printed magistral formulations are manufactured by hospital pharmacies, which are public entities with no scaling interest. Also, some assumptions, for instance, the 30% reduction of materials costs due to scaling effect, may not reflect reality. The largest driver of savings may be, after all, the operator time, instead of materials. The framework was developed to give third parties the freedom to insert inputs that better reflect reality to calculate more accurate manufacturing costs.
Another limitation is in the cost calculation of equipment; the calculation is based on the time personnel uses the equipment. This may lead to an underestimation of the fixed costs, as the rest of the equipment costs are absorbed by the overhead when the equipment is not in use. Equipment costs can also be calculated by distributing the costs over the annually produced pills. In this case, the output in will greatly affect the unit cost where larger outputs lead to lower unit costs.
We assumed an excess capacity available of the 3D printing resource, allowing for multiple products to be printed using the same equipment, facility, and QA. This is a limitation as it may lead to an underestimation of costs. Producing another product with the same equipment and facility may still need investments, for instance of personnel. Although inefficiencies may be introduced by switching to another product, the increased utilization of the equipment will reduce cost per tablet.
Since 3DP makes it possible to adapt the dose and release profile to the individual patients’ needs, there is also a potential in reduction of macro healthcare costs. Adapting the dose and release profile may lead to better therapy control, less side effects, and therefore lower healthcare costs in adrenal insufficiency [39, 40]. However, this hypothesis has not yet been substantiated. Therefore, further clinical research is needed to investigate pharmacokinetics, effectiveness, and safety of 3DP tablets of M3DICORT and other formulations. The impact on healthcare spending can be further investigated with cost-effectiveness analyses. This study focused on one specific dosage, while the strength of 3D printing lies in manufacturing personalized medicine. Further costing studies are needed to understand the impact of personalization on manufacturing costs.
5 Conclusions
This study provides a solid framework for estimating manufacturing costs of printing 3D medication in a small scale or hospital setting. It can be used by compounding facilities to understand and optimize the economic aspects of (personalized) 3DP of medication, which is crucial for the wider adoption and success of 3DP technology in pharmaceutical practice. Manufacturing costs of pharmaceutical 3DP was unknown thus far. The developed framework was applied to M3DICORT, where manufacturing costs were estimated to be between €1.58 and €3.11. It seems to be a financially feasible technology to manufacture personalized generic medicines. 3DP enables personalization of medicine, which may in turn lead to a better therapy control and less adverse effects and therefore lower societal costs. More research is needed to confirm this potential.
Declarations
Funding
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Conflicts of interest
The authors declare that they have no competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Authorship Contribution Statement
Sejad Ayyoubi: conceptualization, data curation, formal analysis, and writing—original draft. Liesbeth Ruijgrok: conceptualization, review, and supervision. Hugo van der Kuy: review. Renske ten Ham: conceptualization, methods, review and editing. Frederick Thielen: conceptualization, methods, supervision, and writing—review and editing.
Ethics Approval
Not applicable.
Consent to Participate
Not applicable.
Consent for Publication (from patients/participants)
Not applicable.
Availability of Data and Material
Data will be provided upon request.
Code Availability
Not applicable.
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