# From conception to consumption: Applications of semi-solid extrusion 3D printing in oral drug delivery

Morenikeji Aina, Fabien Baillon, Romain Sescousse, Noelia M. Sanchez-Ballester, Sylvie Begu, Ian Soulairol, Martial Sauceau

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## To cite this version:

Morenikeji Aina, Fabien Baillon, Romain Sescousse, Noelia M. Sanchez-Ballester, Sylvie Begu, et al. From conception to consumption: Applications of semi-solid extrusion 3D printing in oral drug delivery. International Journal of Pharmaceutics, 2025, 674, pp.125436. 10.1016/j.ijpharm.2025.125436. hal-05000806

HAL Id: hal-05000806

https://imt-mines-albi.hal.science/hal-05000806v1

Submitted on 21 Mar 2025

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Review

From conception to consumption: Applications of semi-solid extrusion 3D
printing in oral drug delivery

Morenikeji Aina<sup>a,●,*</sup>, Fabien Baillon<sup>a</sup>, Romain Sescousse<sup>a</sup>, Noelia M. Sanchez-Ballester<sup>b,c</sup>, Sylvie Begu<sup>b</sup>, Ian Soulaïrol<sup>b,c</sup>, Martial Sauceau<sup>a</sup>

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ARTICLE INFO

Keywords:

3D printing (3DP)

Semi-solid extrusion (SSE)

Oral drug delivery

Rheology

Printability testing

Personalized medicine

A B S T R A C T

Semi-Solid Extrusion 3D printing (SSE 3DP) has emerged as a promising technology for fabricating oral drug formulations, offering significant opportunities for personalized medicine and tailored therapeutic outcomes. SSE 3DP is particularly advantageous for producing soft and chewable drug products and is well-suited for formulations containing thermosensitive drugs due to its low-temperature printing process. Among various 3D printing techniques, SSE 3DP holds considerable potential for point-of-care applications, enabling the on-demand production of patient-specific dosage forms. Despite these advantages, SSE 3DP faces certain limitations that affect its overall development and widespread adoption. This review provides a comprehensive overview of SSE 3DP's fundamental principles, current applications, and future prospects in oral drug delivery. It also addresses the challenges and limitations associated with SSE 3DP and examines the current outlook of this technique in oral drug delivery applications. An example of such a challenge is the lack of a harmonized method for evaluating rheological properties. To address this issue, the review describes a methodology for obtaining information related to extrudability and shape fidelity from rheological properties. Overall, this review aims to highlight the transformative potential of SSE 3DP in the pharmaceutical landscape, paving the way for tailored, and patient-centric therapies.

Contents

<table><tr><td>1.</td><td>Introduction</td><td>2</td></tr><tr><td>2.</td><td>Principle and printing process</td><td>3</td></tr><tr><td>2.1.</td><td>Preparation of the drug-loaded formulation</td><td>3</td></tr><tr><td>2.2.</td><td>Extrusion</td><td>4</td></tr><tr><td>2.2.1.</td><td>Piston-driven extrusion</td><td>4</td></tr><tr><td>2.2.2.</td><td>Screw-driven extrusion</td><td>5</td></tr><tr><td>2.3.</td><td>Printing parameters</td><td>5</td></tr><tr><td>2.4.</td><td>Post-treatment techniques</td><td>6</td></tr><tr><td>3.</td><td>Characterization techniques</td><td>6</td></tr><tr><td>3.1.</td><td>Printability assessment</td><td>6</td></tr><tr><td>3.2.</td><td>Rheological characterization</td><td>7</td></tr><tr><td>3.2.1.</td><td>Temperature sweep: Determining melting or gelling temperatures for optimal printing or drying</td><td>8</td></tr><tr><td>3.2.2.</td><td>Three interval thixotropy test (3ITT): evaluating viscosity changes across printing stages</td><td>8</td></tr><tr><td>3.2.3.</td><td>Amplitude ramp test: assessing response to increasing deformation</td><td>8</td></tr><tr><td>3.2.4.</td><td>Frequency sweep test: assessing shape fidelity and for improved print quality</td><td>8</td></tr><tr><td>3.2.5.</td><td>Yield stress: assessing resistance to deformation</td><td>9</td></tr><tr><td>3.2.6.</td><td>Viscosity measurement and flow behaviour: evaluating consistency and extrudability</td><td>9</td></tr><tr><td>3.2.7.</td><td>Practical guide to rheological characterization for 3D printing</td><td>9</td></tr><tr><td>3.3.</td><td>Texture profile analysis (TPA)</td><td>10</td></tr></table>

<footnote><sup>a</sup> RAPSODEE, D'IMines Albi, CNRS, University of Toulouse, 81013, Albi, France</footnote>

<footnote><sup>b</sup> ICGM, University of Montpellier, CNRS, ENSCM, Montpellier, France</footnote>

<footnote><sup>c</sup> Department of Pharmacy, Nîmes University Hospital, Nîmes, France</footnote>

<footnote>* Corresponding author.</footnote>

<footnote>E-mail address: morenikeji.aina@mines-albi.fr (M. Aina).</footnote>
<table><tr><td>3.4.</td><td>Physicochemical characterizations</td><td>12</td></tr><tr><td>4.</td><td>Applications of SSE in oral drug delivery</td><td>12</td></tr><tr><td>5.</td><td>SWOT analysis of SSE 3D printing in oral drug delivery applications</td><td>13</td></tr><tr><td></td><td>5.1. Strength (Advantages)</td><td>13</td></tr><tr><td></td><td>5.2. Weakness (Limitations)</td><td>16</td></tr><tr><td></td><td>5.3. Opportunity (Outlook)</td><td>18</td></tr><tr><td></td><td>5.4. Threats (Barriers)</td><td>18</td></tr><tr><td>6.</td><td>Conclusion</td><td>19</td></tr><tr><td></td><td>CRediT authorship contribution statement</td><td>19</td></tr><tr><td></td><td>Declaration of competing interest</td><td>19</td></tr><tr><td></td><td>Acknowledgment</td><td>19</td></tr><tr><td></td><td>Data availability</td><td>19</td></tr><tr><td></td><td>References</td><td>19</td></tr></table>

# 1. Introduction

Oral drug delivery has long been favoured for its ease of use and patient compliance. However, the prevalent *one size fits all* manufacturing model often falls short in addressing the diverse needs of patients, particularly in paediatric medicine. The heterogeneity of the paediatric population—ranging from infants and toddlers to adolescents—necessitates constant adjustments in drug therapy and dosing flexibility to cater to their unique physiological conditions and rapid developmental changes (El Aita et al., 2020). Moreover, children are not merely smaller versions of adults, and the traditional method of dosing by tablet splitting is fraught with issues, leading to imprecise and potentially unsafe doses. This problem is compounded by the fact that many paediatric medications are prescribed off-label and often require manual compounding, as tailored, individualized formulations are not widely available (Liang et al., 2023). In addition to dosage accuracy, palatability and ease of swallowing are also critical for ensuring medication adherence among children. As a result, paediatric medications are often administered as liquid dosage forms or split tablets dispersed in food, water, or milk to make them more palatable and easier to ingest (Karavasili et al., 2020). However, these methods are not without their drawbacks. For instance, the stability of the medication, when mixed with different substances, can vary, potentially affecting efficacy (Januskaite et al., 2020) and achieving consistent dosing can be challenging, particularly with split tablets (Karavasili et al., 2020).

Advancements in pharmaceutical technology are beginning to address these challenges, and one promising avenue is the use of three-dimensional (3D) printing. This technology enables precise customization of drug formulations through digital modelling, facilitating diverse modifications of dosage forms and tailoring medications to the specific needs of individual patients with limited manual manipulation (Siyawamwaya et al., 2019; Li et al., 2021; Goh et al., 2021). With 3D printing (3DP), tablets can be created containing the exact dosage required for the patient, considering factors like age, weight, and health condition. Moreover, 3DP allows medications to be produced in various shapes, sizes, and flavours, significantly improving palatability and ease of swallowing for paediatric patients (Herrada-Manchón et al., 2020; Tagami et al., 2021). This level of customization can also be extended to drug release profiles, ensuring optimal therapeutic effectiveness.

Recently, a form of additive manufacturing, SSE has been gaining attention due to its low-temperature printing requirement for the extrusion of formulations containing thermosensitive drugs (Liang et al., 2023; González et al., 2022; Johannesson et al., 2021). SSE 3DP employs layer-by-layer deposition of a gel or paste-like formulation to build three-dimensional structures. The gelation mechanism of the formulation which could be by physical, chemical, or radiation crosslinking allows it to cure rapidly at low or room temperature and with or without post-processing (Liang et al., 2023; Lopez-Vidal et al., 2022; Korelc et al., 2024). Furthermore, the nature of the feedstocks affords the technique a wide availability of printing materials including

pharmaceutical or food-grade polymers (Panraksa et al., 2021). Notably, hydrogel-based polymers like gelatine allow the fabrication of chewable formulations thereby improving palatability and swallowability (Herrada-Manchón et al., 2020; Tagami et al., 2021). In addition, as it allows customization at the point of demand and modification without the need for additional tooling or moulding, this technique offers a potentially cost-effective and decentralized manufacturing method for tablet production (Siyawamwaya et al., 2019; Kamlow et al., 2021; Zhang et al., 2022).

Another notable advantage of SSE 3DP is the use of pre-filled and/or disposable syringes. This approach ensures high purity and quality of drug products, facilitates regulatory compliance, and supports the use of SSE in decentralized clinical environments, such as hospitals and pharmacies (Goyanes et al., 2019; Díaz-Torres et al., 2022; Denis et al., 2024; Rodríguez-Maciñeiras et al., 2025). Also, the use of spectroscopic techniques, such as Raman spectroscopy and near-infrared spectroscopy allows non-destructive inline quality control of the production process (Johannesson et al., 2023a; O'Reilly et al., 2021). Applications of SSE 3DP in oral drug delivery includes the fabrication of immediate release tablets (Yang et al., 2020; Khaled et al., 2018a; Aina et al., 2024b; Khaled et al., 2018b), controlled release tablets (Olmos-Juste et al., 2021; Ou et al., 2023; Leão et al., 2024), poly pills (Zhang et al., 2022; Wang et al., 2023; Alayoubi et al., 2022), chewable printlets and gummies (Herrada-Manchón et al., 2020; Tagami et al., 2021; Rouaz-El Hajoui et al., 2023; Zhou et al., 2023), and oral films (Panraksa et al., 2021, 2023; Elbl et al., 2020). Studies have also been done to use this technique in developing personalized dosage forms with high drug loading (Khaled et al., 2018a,b; Cui et al., 2020) and multiple drug release profiles from different printed compartments (Li et al., 2021).

While the advantages of SSE 3DP are evident, it however remains in the research and development stage and faces limitations such as the need to identify critical process parameters and understand the behaviour of printable materials. This often necessitates analysing the rheological and textural properties of different formulations (Liang et al., 2023) to ensure a final product with reproducible dimensions and shape, desired mechanical properties, and controlled drug release (Viidik et al., 2019). Moreover, a material is said to have good printability if it has good extrudability and supportability, but these two behaviours are usually contradictory (Zhou et al., 2023). For instance, the feedstock should be viscous enough to prevent the printed structure from collapsing, but not too viscous to impede extrusion through the nozzle (Eduardo et al., 2021; Zhang et al., 2024). In addition, despite the critical importance of understanding the rheological properties of feedstocks, a clear and quantitative understanding of these requirements, as well as the necessary characterization methods, is yet to emerge (Smith et al., 2018; Aina et al., 2024c). Moreover, to date, no standardized guidelines exist to produce these personalized dosage forms using 3D printing (Johannesson et al., 2023a).

Nevertheless, SSE 3DP remains an innovative tool that could revolutionize the pharmaceutical industry. Therefore, in this review, we aim to provide a comprehensive overview of how SSE 3D printing is transforming the landscape of oral pharmaceuticals. We will delve into
the essential aspects of the process, including the selection of printable materials, the optimization of printing parameters, and the evaluation of final product performance. Additionally, we investigate the current state of research, highlighting key advancements, existing challenges, and future directions in this innovative field. Ultimately, this review aims to elucidate the transformational potential of this technology and its implications for the future of personalized medicine.

## 2. Principle and printing process

SSE 3DP is a 3D printing technique used for fabricating objects using materials (inks) that possess a semi-solid or paste-like consistency. This technique involves extruding substances with suitable rheological properties, such as semi-solids (e.g., pastes or gels) or semi-molten forms, through a nozzle, typically at room temperature. The extruded material is then shaped into the desired form, generally designed beforehand using computer-aided design (CAD) software. After the printing process, the object is allowed to solidify or undergo additional post-treatments, such as freeze-drying or chemical cross-linking, to enhance its structural integrity or functional properties (Korelc et al., 2024; Panraksa et al., 2023; Mathiyalagan et al., 2023).

The technique has been described using various names, including paste extrusion printing (PEP), pressure assisted microsyringe (PAM) (El Aita et al., 2020; Callede et al., 2022; Mohammed et al., 2021; Tagami et al., 2022), extrusion 3D Printing (Karavasili et al., 2020; Khaled et al., 2018b; Ganatra et al., 2024), syringe extrusion 3D printing (Zhang et al., 2022; Chaiwarit et al., 2022; Panraksa et al., 2020), among others. Indeed, each of these alternative names for the technique sheds light on specific attributes or aspects of SSE. For example, PAM highlights the significance of pressure in enabling the continuous extrusion of printing material from a syringe-like printing head at a predefined speed (Koshovyi et al., 2023a). Consequently, these various names serve to not only emphasize different facets of the process but also provide valuable insights into its operational principles and requirements.

Typically, the production of oral formulations using SSE follows these steps: (i) preparation of the drug-loaded formulation, (ii) extrusion of a uniform paste, (iii) deposition of the material into a 3D structure based on the model design, and (iv) solidification into the final dosage form or post-processing for solvent evaporation (optional). Further details on this process are provided below.

### 2.1. Preparation of the drug-loaded formulation

The distinctive attribute of SSE 3D printing is possibly the feedstock (Bhawale et al., 2023). The feedstock typically comprises the model drugs, carrier polymers, solvents, and/or other excipients with properties suitable for the intended printed formulation. The combination of all these components usually results in a paste or semi-solid formulation suitable for extrusion. Among these components, the selection of the carrier polymer holds paramount importance, as it directly influences the printability, mechanical properties, drug stability, and release profile of the final dosage form (Anderspuk et al., 2021). The most commonly used class of polymers in SSE are hydrogels due to their biocompatibility, non-toxicity, low cost, wide availability, and ease of use (Bashir et al., 2020). These polymers can retain large amounts of water, providing good drug-loading capacity (Cheng et al., 2020). Examples frequently employed in SSE include alginate (Kondiah et al., 2022; Falcone et al., 2023), gelatine (Liang et al., 2023; Herrada-Manchón et al., 2020; Jovanović et al., 2021), and cellulose derivatives (Germini and Peltonen, 2021; Zheng et al., 2020). Other carrier polymers include lipids (Lafeber et al., 2021; Bendicho-Lavilla et al., 2024), food-grade additives such as chocolate (Karavasili et al., 2020; Chachlioutaki et al., 2022), and synthetic polymers like poly(ethylene glycol) (PEG) (Algahtani et al., 2020; van Kampen et al.,

2023) and poly(ethylene oxide) (PEO) (Viidik et al., 2019; Sjöholm et al., 2020).

However, the use of single-carrier polymers can often lead to poor mechanical properties and limited material stability, resulting in low structural integrity and reduced printing accuracy (Liang et al., 2023). To overcome these challenges, polymer blends are frequently employed. For example, combining alginate with gelatin Li et al. (2021), Kondiah et al. (2022) or cellulose derivatives (Olmos-Juste et al., 2021; Falcone et al., 2022) has been shown to improve mechanical strength. Additionally, some polymers possess thermogelation properties, which allow transitions between solid and liquid states in response to temperature changes. While these properties can be beneficial for modulating drug release rates or altering mechanical characteristics, they can also present challenges during printing. For instance, gelatin undergoes a sol-gel transition above 30 °C, which can alter its viscosity and potentially compromise both shape fidelity and printing accuracy (Li et al., 2021; Yang et al., 2020; Zhou et al., 2023). Therefore, the choice of polymer must not only match the intended drug release profile—whether immediate, sustained, or targeted—but also possess the appropriate rheological properties to ensure consistent extrusion and optimal shape retention.

In immediate-release formulations, disintegrants such as croscarmellose sodium (CCS) (Zhang et al., 2022; Conceição et al., 2019), crospovidone (Kollidon CL) (Sjöholm et al., 2022b,a), and sodium starch glycolate (SSG) (Alayoubi et al., 2022; Panraksa et al., 2022) are commonly incorporated to facilitate disintegration and promote rapid drug release. Water-soluble or swellable polymers, including hydroxypropyl cellulose (HPC) (Cui et al., 2020) and polyvinylpyrrolidone (PVP) (Eduardo et al., 2021; Suárez-González et al., 2021), are also often added to enhance wetting and ensure the rapid dispersion of the drug in the dissolution medium (Funk et al., 2022; Muehlenfeld et al., 2024). In contrast, sustained-release formulations rely on hydrophobic or swellable polymers like hydroxypropyl methylcellulose (HPMC) which control drug diffusion and extend therapeutic effects (Muehlenfeld et al., 2024). For site-specific drug delivery systems, bioadhesive polymers such as sodium alginate and gelatin, enhance retention on mucosal surfaces, making them ideal for fabricating orodispersible films (Turac et al., 2024). Similarly, gastroretentive systems, designed to prolong drug presence in the stomach, utilize polymers with high swelling and floating capacities, such as HPMC and alginate (Abdella et al., 2021; Vemula et al., 2024; Turac et al., 2024).

In addition to their impact on drug release, the rheological properties of the polymer are crucial for successful extrusion and maintaining the structural integrity of the printed material. Polymers must exhibit suitable flow behaviour to ensure smooth processing and to preserve the desired physical properties of the final formulation. To optimize the mechanical properties and extrudability of the feedstock, excipients like polyvinylpyrrolidone (PVP) (Jovanović et al., 2021; Suárez-González et al., 2021), microcrystalline cellulose (MCC) (Yang et al., 2020; Li et al., 2018; Yang and Kim, 2023), and lactose monohydrate (Eduardo et al., 2021) are frequently added. These excipients improve the flowability and consistency of the polymer mixture, ensuring smooth extrusion and retention of the material's shape and integrity after deposition (Zhang et al., 2022; Suárez-González et al., 2021).

The interactions between the carrier polymer(s) and the drug is another crucial factor influencing the selection of feedstock components (Vemula et al., 2024). For example, incorporating swellable excipients such as Avicel® and Polyplasdone® into carbopol-based pastes modified the drug release profile of diclofenac sodium. However, this also increased paste viscosity, leading to lump formation, which negatively affected flowability and caused extrusion issues such as deformed filaments and nozzle blockages (Zidan et al., 2019a).

Additionally, polymer-polymer interactions can either enhance or hinder formulation performance. Hydrogen bonding between gelatin and PVP creates a highly cross-linked network (Jovanović et al., 2021), which may influence drug release kinetics. In contrast, the interaction
between PVP and HPMC acts as a plasticizer, modifying the formulation's rheological behaviour (Zhang et al., 2024). Similarly, kappacarrageenan interacts with thiamine to form a cross-linked network. However, at higher drug concentrations, charge cancellation saturates the gel-forming polymer, reducing cross-linking density. In contrast, agar, an uncharged polymer, does not exhibit such concentration-dependent changes (Kamlow et al., 2021).

Drug-polymer compatibility is another critical factor in preventing phase separation, crystallization, or chemical degradation, all of which can compromise product efficacy and printing performance (Abaci et al., 2021; Abdulhussain et al., 2023; Kumari et al., 2023). For instance, in paracetamol-containing formulations, increasing drug loading enhanced mechanical strength due to hydrogen bonding with PVP, improving shape fidelity (Teoh et al., 2022). However, exceeding the drug's solubility limits in the feedstock resulted in undissolved particles, which altered rheological properties and impaired liquid flow characteristics (Teoh et al., 2022). Similarly, high concentrations of tranexamic acid reduced viscosity but led to nozzle blockages due to the accumulation of undissolved drug particles (Zhang et al., 2024).

Beyond polymer selection, polymer content and cross-linking density play a crucial role in the printability and stability of SSE formulations. Inadequate polymer concentration can lead to poor shape retention or even structural collapse of printed constructs (Viidik et al., 2019; Jiang et al., 2020). For example, the printability and shape fidelity of PEO-based formulations have been shown to be highly dependent on polymer concentration, with insufficient amounts leading to structural instability and poor definition in printed constructs (Viidik et al., 2019). However, modifying the excipient composition to enhance printability may inadvertently alter drug release kinetics. A more flexible approach is to adjust the solvent content, allowing for fine-tuning of rheological properties without significantly changing the polymer content. Since the solvent can be partially or entirely removed post-processing, this strategy optimizes printability while maintaining the intended application (Goh et al., 2021).

While water-based formulations are commonly used in SSE, non-aqueous solvents provide a valuable alternative, particularly for poorly water-soluble drugs. These non-aqueous systems enhance solubility, reduce hydrolytic degradation, and minimize microbial contamination. For instance, mesoporous magnesium carbonate (MMC) combined with polyethylene glycol (PEG 400) has been used to develop stable, water-free tablets and suppositories, preventing weight loss and structural deformation during curing (Katsiotis et al., 2024). Additionally, lipid-based carriers such as Gelucire® have been explored as semi-solid inks, eliminating the need for post-printing drying while maintaining drug stability (Lafeber et al., 2021; Barberis et al., 2022; Real et al., 2020, 2023; Lyousoufi et al., 2023). Moreover, organic solvents like acetone and ethanol can be utilized to enhance paste fluidity and accelerate deposition during printing. However, due to their rapid evaporation, achieving a homogeneous paste with consistent viscosity can be challenging (Yang et al., 2020).

After selecting the excipients based on the intended use, they are mixed with the drug in an aqueous or non-aqueous solvent, with or without heating, to achieve the desired rheological properties while preserving drug stability. While some studies recommend rigorous mixing to ensure thorough homogenization (Li et al., 2021; Lafeber et al., 2021), others suggest slower, manual mixing to minimize air incorporation, which could affect formulation consistency (Herrada-Manchón et al., 2020). In certain cases, physical or chemical cross-linking is employed to stabilize the formulation or induce gel formation (Falcone et al., 2023, 2021). With the homogeneous paste or semi-solid formed, the formulation is either loaded directly into the printing syringe for immediate use (El Aita et al., 2020) or left to rest at ambient temperature or under refrigeration to optimize its properties before printing (Tagami et al., 2021; Kondiah et al., 2022; Real et al., 2023; Ahmed et al., 2022).

## 2.2. Extrusion

In this step of the printing process, the prepared feedstock is pushed through the nozzle to create the desired shape. This can be accom-

plished in two primary ways. The first method is piston-driven extrusion, where a piston applies pressure to force the feedstock through the nozzle. The piston can be moved either by air pressure or by a motor that converts rotational motion into linear motion to advance the piston. Alternatively, extrusion can be achieved using screw-driven extrusion, where a rotating screw shears and pushes the feedstock through the nozzle. The printer's capacity has been reported to be associated with the extrusion mechanism, and both this mechanism and the properties of the prepared formulation collectively determine the extrusion outcome (Aina et al., 2024c). The outline of the different extrusion mechanisms is shown in Fig. 1, followed by a brief description of each mechanism.

### 2.2.1. Piston-driven extrusion

Most piston-driven SSE 3D printers (Díaz-Torres et al., 2022; Johansson et al., 2023a; Mohammed et al., 2021; Roche et al., 2023; Abdella et al., 2024; Derakhshanfar et al., 2018; Ozbolat and Hospodiuk, 2016) use pressurized air to drive the extrusion process. As shown in Fig. 1(a), the direct application of pneumatic pressure ensures consistent and controlled extrusion of the material, even with highly viscous formulations. Derakhshanfar et al. (2018), Ozbolat and Hospodiuk (2016). This method offers several advantages over valve-based systems, which control material release by opening or closing a valve at the nozzle (Seoane-Viaño et al., 2021a). Since valve-based systems are typically used for bioprinting applications, they are not included in this classification. The valve-free piston-based system is preferred here for its simplicity, ease of maintenance and cleaning, and reduced risk of mechanical failure (Ozbolat and Hospodiuk, 2016).

The air pressure required for the printing process is usually determined by gradually increasing the pressure until a consistent and uniform extrusion of continuous filaments is achieved (Ganatra et al., 2024). It is crucial to avoid both excessively high and low pressures, as they can adversely affect the quality of the extruded material, causing issues such as inconsistent filament diameter or material defects. Typical extrusion pressures reported in the literature range from 0.2 to 6 bars (Tagami et al., 2021; Ou et al., 2023; Aina et al., 2024c; Kondiah et al., 2022; Zidan et al., 2019a; Tagami et al., 2019). This range highlights the need to adjust pressure according to factors such as material properties and print parameters. Additionally, extrusion pressure is influenced by the viscosity of the material; higher viscosity materials generally require higher pressures for proper flow (Panraksa et al., 2023; Koshovyi et al., 2023a; Cheng et al., 2021). Thus, precise adjustment of extrusion pressure based on the material formulation and printing parameters is essential for maintaining print quality, as emphasized by previous studies (Siyawamwaya et al., 2019; Smith et al., 2018).

In motor-based piston-driven extrusion systems, printing begins with vertical mechanical forces applied to the piston. This is achieved using a motor—typically a stepper or servo motor—that drives the piston (Fig. 1(b)). The motor's rotational motion is converted into linear motion via mechanical linkages, such as a lead screw or rack and pinion system (Panraksa et al., 2020; Barberis et al., 2022). This setup is valued for its precision, ease of control, and cost-effectiveness compared to pneumatic systems (Díaz-Torres et al., 2022). Notably, the use of a motor allows for straightforward modifications to adjust the extrusion force, offering significant flexibility over pneumatic systems, which have more rigid specifications and can be more expensive to modify or replace. As a result, many customized 3D printers utilize this form of extrusion (Panraksa et al., 2021, 2023). Additionally, some FDM 3D printers are adapted to accommodate liquid or semi-solid dispensing systems (Rycerz et al., 2019; Janigová et al., 2022), with the extrusion mechanism becoming based on the movement of the piston. These modifications enable the printers to handle a broader range of materials beyond traditional thermoplastic filaments, allowing for the deposition of various liquid or semi-solid feedstocks. Moreover, the quick and easy replacement of printing cartridges in piston-driven printers contributes to a faster and cleaner printing process.
<figure><img src="image_4.png" /><figcaption>**Fig. 1.** Outline of the different extrusion mechanisms: Piston-driven extrusion using air (a), motor-based piston-driven extrusion (b), screw-driven extrusion (c), and a combination of screw-driven and pneumatic extrusion (d).</figcaption></figure>

### 2.2.2. Screw-driven extrusion

In screw-driven extrusion mechanisms (Fig. 1(c)), material is pushed through the nozzle by the rotational forces of the screw, which shears and extrudes the feedstock. While air pressure may be used to feed the material into the screw in some cases (Fig. 1(d)), it does not drive the extrusion process itself. Instead, the extrusion is achieved through the screw's movement, which directly pushes the material through the nozzle.

Both piston-driven and screw-driven mechanisms offer distinct advantages. Piston-driven systems provide precise control over the flow of the feedstock, allowing for accurate deposition and the printing of complex structures with high precision (Díaz-Torres et al., 2022; Ozbolat and Hospodiuk, 2016). However, these systems may struggle with very viscous materials due to constraints in the design of the driving mechanism, such as motor torque or air pump specifications. In contrast, screw-driven mechanisms are particularly effective at handling feedstocks with higher viscosities (Díaz-Torres et al., 2022; Callede et al., 2022; Ozbolat and Hospodiuk, 2016). The rotating screw generates sufficient force to shear even very viscous materials and push them through the nozzle. Additionally, when air supply is used to assist the flow of material into the dispensing system, it works in conjunction with the screw's motion to increase the shear rate, thereby reducing the material's viscosity as it moves through the nozzle (Aina et al., 2024c).

In summary, the choice between piston-driven and screw-driven extrusion depends on the specific requirements of the printing application, such as the viscosity of the feedstock and the desired level of flow control (Díaz-Torres et al., 2022; Aina et al., 2024c; Derakhshanfar et al., 2018).

## 2.3. Printing parameters

Once continuous extrusion of the feedstock is confirmed, critical printing parameters such as layer height, print speed, and deposition

method are optimized, as they play a pivotal role in achieving high-resolution prints (Ganatra et al., 2024). The gap between the nozzle head and the print platform (layer height) is particularly important, as an excessively large gap can lead to poor material deposition, while a gap that is too small may compromise printing resolution (Bhawale et al., 2023; Suryavanshi et al., 2023). Additionally, parameters such as feed rate, line spacing, and layer thickness have been identified as crucial factors influencing the printing process (Khaled et al., 2015b). However, other studies suggest that key optimization parameters include travel speed, nozzle diameter, and extrusion rate (Korelc et al., 2024). Notably, high-resolution and mass-uniform dosage forms can be achieved by fine-tuning printing parameters to match the feedstock and using nozzles with diameters smaller than 1 mm (Eduardo et al., 2021).

Despite some variations in the parameters considered critical across studies, there is a broad consensus regarding their influence on printing outcomes. For instance, printing speed, infill rate, and travel speed are widely recognized as key factors affecting the extrusion of feedstock from the nozzle (de Oliveira et al., 2022). Consequently, adjustments to these parameters should be accompanied by modifications in printing pressure to maintain consistent material extrusion (Mohammed et al., 2021; Ganatra et al., 2024; Kavimughil et al., 2022). Likewise, the resolution of printed shapes is influenced by factors such as infill pattern and weaving angle (Conceição et al., 2019; Zidan et al., 2019a; de Oliveira et al., 2022). Infill patterns that conform to the shape of the object, such as concentric patterns, or a weaving angle greater than 45° are preferable for printing cylindrical forms. Layer height is another critical parameter affecting resolution and surface smoothness, as lower layer heights can produce smoother surfaces (Herrada-Manchón et al., 2020) but may also lead to poor layer alignment depending on the formulation (Yang et al., 2020).

Furthermore, varying certain printing parameters can modify the mechanical properties, drug release rate, and disintegration time of
dosage forms. For instance, by adjusting the filling pattern and density, the mechanical properties, porosity and release characteristics of the drug can be modified to suit the specific requirements of the application and the needs of the patient. Several studies have demonstrated the capability of SSE to fabricate dosage forms with diverse release properties by manipulating the infill density of the printed object (Wang et al., 2023; Aina et al., 2023). Likewise, reducing the infill density has been shown to decrease disintegration time (Johannesson et al., 2023a; Eduardo et al., 2021). Consequently, some researchers have developed highly porous dosage forms with rapid disintegration (O'Reilly et al., 2021; Panraksa et al., 2022) or floating dosage forms (Li et al., 2018; Yang and Kim, 2023) by decreasing the infill density. Conversely, other studies (Karavasili et al., 2020; Goh et al., 2021; Sjöholm et al., 2022b) have printed objects with higher infill densities to ensure adequate mechanical strength.

However, it is important to note that the understanding of the optimal range for these parameters remains somewhat limited, as they are often influenced by various formulation properties. For instance, the behaviour of these parameters can vary significantly depending on the viscosity of the feedstock. Low-viscosity materials typically require faster printing speeds and smaller nozzle diameters to achieve optimal print resolution (Alayoubi et al., 2022). Conversely, highly viscous materials may require slower printing speeds and larger nozzle diameters. Ultimately, the quality of the print can only be reliably evaluated through the actual 3D printing process, with parameters adjusted and optimized accordingly to achieve the desired results (de Oliveira et al., 2022).

## 2.4. Post-treatment techniques

In SSE 3D printing, the feedstock typically contains liquid solvents along with other components. After the printing process, post-print treatment steps such as drying or cross-linking are often conducted (Teoh et al., 2022). During these post-treatment processes, the printed paste undergoes transformations as the liquid components evaporate or undergo chemical reactions. For instance, cross-linking involves the formation of covalent bonds between polymer chains, leading to the development of a more robust network within the printed material (Wang et al., 2023; Anderspuk et al., 2021). Similarly, drying involves the removal of liquid solvents through evaporation, resulting in the consolidation of the printed structure. This consolidation process contributes to the enhancement of physical strength and the attainment of the final form of the printed object (Korelc et al., 2024; Zidan et al., 2019b). In addition to enhancing the microbial stability of the dosage form (Sjöholm et al., 2022b) by reducing moisture content through drying, the chosen post-treatment technique can significantly affect drug release properties. For instance, studies have revealed that the release of curcumin is accelerated in freeze-dried objects compared to cross-linked or air-dried ones (Olmos-Juste et al., 2021). In contrast, ultraviolet (UV) cross-linked tablets, due to their reticulated and more porous structure, demonstrated faster drug release compared to non cross-linked counterparts (Anderspuk et al., 2021). Therefore, the choice of post-treatment method—or the decision to forgo post-treatment—has a significant impact on the mechanical properties, stability, and functionality of SSE-printed objects.

However, the post-treatment step in SSE 3D printing presents notable challenges, as highlighted by previous research findings (Eduardo et al., 2021; Falcone et al., 2021). While this approach enables the optimization of material integrity, it introduces process complexities and time constraints. Some pastes necessitate extensive post-processing, involving time-consuming procedures such as freeze drying (Kavimughil et al., 2022; Chatzitaki et al., 2023), vacuum drying (Ahmed et al., 2022; Johannesson et al., 2023b), air drying (Eduardo et al., 2021), and others. These processes, aimed at facilitating solvent evaporation, can extend for up to 12 h or more, significantly prolonging the overall printing process. Moreover, in a comparative study (Falcone et al., 2021),

air drying emerged as the preferred method over microwave-assisted and oven drying. The latter methods resulted in deformed and wrinkled structures or brown, fragile textures, respectively. Additionally, concerns arise regarding the safety of certain cross-linking agents used in the post-treatment phase. If residual agents remain within the dosage form, there is a potential risk of compromising patient safety (Knowlton et al., 2017; Chan et al., 2020). It is also worth noting that drying may lead to supersaturation of the active pharmaceutical ingredient (API) in the dosage forms. This can ultimately reduce handleability and result in poor content uniformity, as the drug crystals may detach from the dried objects during handling (Sjöholm et al., 2020).

One might think the post-treatment time could be reduced by using highly evaporative solvents, but this could ultimately result in nozzle blockage (Algahtani et al., 2020). Furthermore, cross-linking is advised to be done during or after printing as if done before, this could also result in nozzle blockage. However, a successful strategy employed to reduce the time spent on post-printing processes is in-process drying. For example, drying during printing has been demonstrated to be as effective as post-drying in enhancing the mechanical strength of orally disintegrating films (ODFs) (Janigová et al., 2022). Another successful strategy is the in-situ gelification of the printed object by increasing (Elbl et al., 2020; Jiang et al., 2020) or reducing (Herrada-Manchón et al., 2020) the temperature of the printing plate. Also, printing on a glass surface could be used to improve the handling of printed objects (Herrada-Manchón et al., 2020). In addition, a form of SSE, melting solidification printing process (MESO-PP) could be conducted. In this method, solvent-free feedstocks with low melting points are used for printing thus eliminating the post-treatment step (Real et al., 2020).

## 3. Characterization techniques

Collapsing and shape fidelity present recurring hurdles in 3D printing. Collapsing, a phenomenon frequently observed in hydrogels formed from natural polymers, is often due to insufficient polymer content. Conversely, shape fidelity is linked to the viscoelastic characteristics of the printing paste. Ideally, the paste should smoothly flow through the nozzle during printing and maintain its intended shape post-printing and after curing (Viidik et al., 2019). Characterization techniques for SSE 3DP, thus encompass various methods aimed at evaluating the properties of both the feedstock material before printing and the printed dosage forms, either directly after printing or following post-treatment processes.

### 3.1. Printability assessment

In the development of printed pharmaceuticals, ensuring consistent dimensions and shapes in the final product is critical. Variations and defects in the geometry and structure of printed drug delivery systems (DDSs) can significantly impact drug dosing and delivery efficacy. For instance, inconsistencies in the dimensions and shape of printed tablets or other dosage forms can lead to inaccuracies in drug dosage (Elbl et al., 2020). Such discrepancies, whether resulting in overdosing or underdosing, pose risks to therapeutic outcomes and patient safety. Additionally, variations in shape can influence the dissolution profile of the drug, thereby altering its release kinetics and bioavailability (Siyawamwaya et al., 2019). Moreover, irregularities in the geometry of printed DDSs can affect drug distribution within the dosage form and subsequent release behaviour. Non-uniform distribution may cause localized concentrations of the drug, resulting in uneven drug release and potentially ineffective treatment. Furthermore, variations in shape can impact the mechanical properties of the dosage form, affecting its handling, packaging, and administration. Therefore, meticulous diligence in ensuring reproducible dimensions and shape during the development and manufacturing of printed pharmaceuticals is essential.
<figure><img src="image_5.png" /><figcaption>Fig. 2. Illustration of the semi-quantification of printability.</figcaption></figure>

In this context, the term “printability” assumes paramount significance, denoting the intrinsic capability of a 3D printer to accurately replicate a model created by computer-aided design (CAD) (Johannesson et al., 2023a; Viidik et al., 2019). Notably, assessments of printability encompass multifaceted considerations such as shape or structural integrity, and extrudability, thereby underscoring its pivotal role in the characterization process (Bom et al., 2022). One example of printability assessment is the 1D test, also known as the filament collapse test. In this test, a line of material is extruded onto a surface, and its ability to retain shape without collapsing is evaluated (Nelson et al., 2021; Ribeiro et al., 2017). Similarly, 2D tests involve extruding square grids and comparing the printed areas with the original design, or assessing the roundness of pores to evaluate extrudability (Aina et al., 2024c; Bom et al., 2022). Finally, 3D tests focus on printing three-dimensional shapes to determine the maximum height achievable without collapse and to assess how closely the printed shapes resemble the original 3D models (Kavimughil et al., 2022; Zheng et al., 2021; Rodríguez-Herrera et al., 2024). While some researchers favour qualitative descriptions of printability through visual inspections, others advocate for the establishment of semi-quantitative or quantitative metrics (Bom et al., 2022; Ribeiro et al., 2017). For instance, the visual appearance of printed figures has been assessed to gauge their shape fidelity and extrudability (printability) (Kamlow et al., 2021; Johanneson et al., 2023a; Rouaz-El Hajoui et al., 2023; Chaiwarit et al., 2022; Kavimughil et al., 2022). Conversely, a semi-quantitative method was used to evaluate the printability of caffeine-loaded formulations (Aina et al., 2024c).

The semi-quantitative method, which assesses pore circularity, suggests that optimally gelled feedstock extrudes filaments with consistent width and a smooth surface, thereby resulting in regular grids and square channels in the printed constructs (Ouyang et al., 2016). Consequently, printability (Pr) was defined as shown in Eq. (1) (Ouyang et al., 2016). Under ideal conditions, perfect printability yields square-shaped structures with interconnected pores, resulting in a Pr value close to 1 (Fig. 2).

$$Pr = \frac{L^2}{16A} \qquad (1)$$

where L and A are the perimeter and area of a printed square grid, respectively.

Deviations from this ideal state, such as over gelled or under gelled feedstocks, lead to higher (> 1.1) or lower (< 0.9) Pr values, respectively. Additionally, Pr values obtained from a manual syringe extrusion test, which is faster and easier to perform, has been shown to display similar tendencies to those obtained from a 3D printer (Aina et al., 2025). This highlights the utility of this semi-quantitative method for quickly comparing the printability of formulations. However, despite the significance of calculating Pr, this test does not account for all factors influencing printability. Moreover, its reliance on two-dimensional measurements may inadequately evaluate layer stacking in multilayer printing scenarios.

As a result of this limitation, alternative concepts and indices have garnered attention, such as the shape fidelity factor (SFF) (Panraksa et al., 2023; Chaiwarit et al., 2022). SFF is the ratio of any side of the printed area of a cube, $A_p$ to the area of the CAD model, $A_m$ (Polamapllly et al., 2019). The test, shown in Eq. (2), quantitatively evaluates the physical deformation of the printed geometries. A higher SFF indicates a lower ability of the material to stack up in layers (Fig. 3(a)), while a

<figure><img src="image_6.png" /><figcaption>Fig. 3. Formulation with (a) poor shape fidelity and formulation with (b) good shape fidelity.</figcaption></figure>

<figure><img src="image_7.png" /><figcaption>Fig. 4. Illustration of a material with poor pore interconnection.</figcaption></figure>

lower SFF suggests that the material can stack more layers (Fig. 3(b)). There are alternative definitions of the parameters in Eq. (2). For example, $A_p$ and $A_m$ has been described as the experimental or printed pore area and theoretical lattice or designed pore area, respectively (Viidik et al., 2019; Kim et al., 2020).

$$SFF = \frac{A_p}{A_m} \qquad (2)$$

In recent papers (Zhang et al., 2024; Panraksa et al., 2022), another quantitative method has emerged to assess the printability of formulations. This method, like the collapse area factor (Habib and Khoda, 2018), is based on a diffusion rate variable (He et al., 2016) and is calculated using Eq. (3). Both studies observed that in cases where the material is under-gelled or in liquid state, there is no interconnection (due to gravity-driven diffusion, shown in Fig. 4), resulting in $A_p$, equal to 0, indicating a $\phi$ of 100%. In contrast, under ideal conditions, the filaments exhibit interconnection, and $A_p$ matches its theoretical area, $A_m$. Consequently, $\phi$ equals 0%.

$$\phi = \frac{A_m - A_p}{A_m} * 100 \qquad (3)$$

## 3.2. Rheological characterization

Printability in extrusion-based 3D printing is intricately linked to the rheological properties of the feedstocks, encompassing factors such as viscosity, shear-thinning behaviour, yield stress, and viscoelastic properties. Achieving the right balance of these properties is essential for producing high-quality prints. For example, the viscosity of a material must be low enough to facilitate flow through the nozzle yet high enough to ensure that deposited layers hold their shape and support subsequent layers. Striking this balance is a significant challenge in the field of SSE 3D printing (Zhou et al., 2023). Moreover, ensuring that the feedstocks exhibit both liquid-like (extrudability) and solid-like (shape fidelity) properties is crucial for successful printing outcomes (Liang et al., 2023; Zhou et al., 2023).
Rheological measurements using most commercial rheometers generally employ two main modes of deformation: oscillatory and rotational. The oscillatory deformation mode provides insight into the viscoelastic properties of a material. In these tests, a material is subjected to small, oscillatory deformations where the applied strain or stress is sinusoidal. By measuring the resulting stress or strain, key parameters such as the storage modulus (G'), loss modulus (G''), and phase angle (δ) or tangent of phase angle (tan δ) are determined. On the other hand, the rotational deformation mode focuses on the material's flow behaviour under continuous shear, providing crucial information on its viscosity profile and shear-thinning behaviour.

However, due to the complexities involved in these deformation modes, classifying rheological characterizations strictly under these two categories can be challenging. Therefore, we have classified the characterizations below based on the specific information or parameter to be measured, allowing for a more straightforward understanding of the rheological properties relevant to 3D printing.

### 3.2.1. Temperature sweep: Determining melting or gelling temperatures for optimal printing or drying

In the formulation and preparation of printing materials, researchers conduct temperature sweep experiments to analyse the thermo-responsive characteristics of the feedstock. This reversible temperature response facilitates the seamless integration of additives, particularly at the melting temperature ($T_{melt}$) of the gel-forming polymer, where the highly viscous mixtures behave like solutions (Smith et al., 2018). $T_{melt}$ also denotes the temperature at which the material attains sufficient viscosity to flow through the nozzle without obstruction, it therefore helps in determining the optimal printing temperature. For instance, the dependence of the viscosity of chocolate-based feedstocks on temperature was assessed to determine the point at which their viscosity decreased sufficiently to be extruded. As a result, the melting temperature of 32 °C was selected as the printing temperature, which allowed for smooth extrusion of the feedstock through the nozzle (Chachlioutaki et al., 2022).

Another information that can be derived from a temperature ramp test is the gelation temperature, $T_{gel}$. In contrast to $T_{melt}$, $T_{gel}$ is defined as the point where the G', which signifies the material's elastic or gel-like properties becomes higher than G", which denotes its viscous nature. Sometimes, the $T_{gel}$ can be modified by adding additives to reduce or increase the thermosensitivity of the formulation. For example, the addition of excipients such as carboxymethyl starch sodium and carrageenan increased the gelation temperature ($T_{gel}$) of gelatine, which consequently raised the melting temperature ($T_{melt}$) and improved the overall printability of the gelatine-based feedstock (Liang et al., 2023).

In addition, $T_{gel}$ helps identify the temperature at which viscoelasticity intensifies, thereby aiding in the selection of the temperature required for solidification (Li et al., 2021). Moreover, in cases where the printing or drying temperature needs to be modified, the addition of certain excipients can be used. For instance, by testing various formulations in a controlled shear rate temperature ramp, it was reported that the addition of HPMC to a gelatine matrix increased the required printing temperature from 32.7 °C to 45 °C (Yang et al., 2020). A temperature ramp test thus allows for greater understanding of the thermal requirements of feedstocks, ensuring that the material maintains its functionality and integrity throughout the printing and post-processing stages.

### 3.2.2. Three interval thixotropy test (3ITT): evaluating viscosity changes across printing stages

Another characterization technique in rotational or oscillatory mode is the three interval thixotropy test (3ITT). The first interval simulates behaviour at rest and the material is evaluated at low shear or strain. The second one includes high strain or shear (beyond the linear viscoelastic region, LVER or yield stress), to simulate the structural

breakdown during extrusion. Finally, the third stage returns to the low strain or shear and simulates structural regeneration at rest. However, for samples that undergo curing, a fourth stage exists in which the rheological property of the feedstock is evaluated after the intended post-treatment is performed (Real et al., 2023). Generally, materials with high shear recovery (strong thixotropic behaviour) are desirable since they keep the layer-by-layer deposition without collapsing (Ganatra et al., 2024; Cheng et al., 2020; Sjöholm et al., 2020). Additionally, the viscosity recovery is crucial in preventing unintended changes to the printed shape both during rest and upon solvent removal (Goh et al., 2021).

### 3.2.3. Amplitude ramp test: assessing response to increasing deformation

In an oscillatory amplitude ramp, the response of rheological parameters such as the G', G", δ or tan δ are evaluated in response to either a strain (γ) or stress (τ) amplitude. For instance, a graphical presentation of G' and G" versus shear stress (τ) was used to determine the LVER (Olmos-Juste et al., 2021). Whereas a graphical presentation of G' and G" versus γ was used to determine the LVER (Rouaz-El Hajoui et al., 2023). In the LVER, the viscoelastic properties of a material (such as G', G" and tan δ) are independent of the strain or stress amplitude. The LVER, thus exists at the stress or strain where oscillatory measurements can be conducted without destroying the internal structure of the sample.

Furthermore, the shorter the length of the LVER, the greater the solid behaviour (Rouaz-El Hajoui et al., 2023; Herrada-Manchón et al., 2023). In addition, materials whose G" drops constantly after leaving the LVER region have been demonstrated to display good extrudability. This is possibly because of the slow breakdown of the gels which facilitates its continuous extrusion (Aina et al., 2024c; Suryavanshi et al., 2023). Furthermore, feedstocks with higher G', typically have better self-supporting ability and higher mechanical strength whereas higher G" signifies better extrudability or more viscous flow of the feedstock (Aina et al., 2024c; Ganatra et al., 2024). In the same way, the material is said to be more elastic (better shape fidelity) or more viscous (better extrudability) when δ (or tan δ) is lower or higher, respectively (Zhou et al., 2023; Kavimughil et al., 2022).

### 3.2.4. Frequency sweep test: assessing shape fidelity and for improved print quality

The Cox-Merz rule typically links the frequency dependence of complex viscosity (η *) to the shear rate dependence of shear viscosity in non-Newtonian fluids. However, it was observed that HPMC-based feedstocks deviate from this rule, indicating that it may not apply to all non-Newtonian fluids, particularly those containing gel-forming polymers (Teoh et al., 2022). This deviation is likely due to the complex microstructure and phase transitions of these polymers, which lead to non-linear viscoelastic behaviour that contradicts the assumptions of the Cox-Merz rule (Rathinaraj et al., 2022). Other factors, such as wall slip, thixotropy, polymer concentration, and molecular weight distribution, may also contribute to these deviations (Rathner et al., 2021).

Despite the deviation from the Cox-Merz rule, feedstocks that show a decrease in η * during a frequency sweep still demonstrate shear-thinning behaviour, which is advantageous for 3D printing (Kavimughil et al., 2022). At lower frequencies, the material behaves elastically, while at higher frequencies, it becomes more viscous. The crossover frequency of G' and G" represents the polymer relaxation time, beyond which the polymer chains cannot rearrange, leading to potential flow or structural collapse (Ramli et al., 2022). Understanding this behaviour is, thus crucial for optimizing the printing process, as it helps maintain shape fidelity by minimizing the risk of viscosity changes. For example, a starch-based feedstock exhibited a relaxation time of 7 ms (corresponding to 150 Hz), indicating that exceeding this frequency could lead to structural collapse (Chatzitaki et al., 2022).
However conventional rheometers are constrained by torque limitations, making it difficult to reach frequencies beyond 50 Hz (Schroyen et al., 2020), alternative strategies such as the time-temperature superposition of frequency curves may provide means to determine relaxation times. However, unlike polymers, generating master curves for gelled systems poses challenges similar to those encountered with the Cox-Merz rule (Ramli et al., 2022). Consequently, researchers often compare the power law exponent of the frequency dependence of G' within the linear viscoelastic region (Aina et al., 2024c; Gholamipour-Shirazi et al., 2019). The higher the relaxation exponent, the softer the gel, whereas a lower exponent indicates a stiffer gel (Henning Winter et al., 1994). Moreover, samples with a relaxation exponent (referred to as $m_{index}$) below 0.06 exhibited poor extrudability due to excessive stiffness or an over-gelled state, resulting in high Pr (Aina et al., 2024c).

### 3.2.5. Yield stress: assessing resistance to deformation

In an oscillatory shear ramp, the yield point ($\tau_y$) is identified where G' loses its linearity, while the flow stress ($\tau_f$) is determined either at the cross-over point between G' and G'' (González et al., 2022). In rotational shear rate ramps, two yield stresses are observed: static yield stress ($\tau_{stat}$), measured from the change in the slope of the stress during an upward shear rate ramp, and dynamic yield stress ($\tau_{dyn}$), measured from the y-intercept during a downward shear rate ramp (Smith et al., 2018). It is crucial to note that, while some studies define both $\tau_y$ and $\tau_{dyn}$ as the stress required to initiate flow, they represent different concepts (Qian and Kawashima, 2018; Liu et al., 2023). Specifically, $\tau_y$ denotes the minimum stress needed to initiate irreversible plastic flow or deformation in a material (Liu et al., 2023), whereas $\tau_{dyn}$ refers to the minimum stress required to sustain or terminate flow (Qian and Kawashima, 2018). Similarly, yield stress determined using rheological models typically corresponds to $\tau_{dyn}$ and not $\tau_{stat}$.

In addition, these yield stresses are not fixed material properties; they fluctuate depending on several factors such as test conditions, the specific device employed, and the type of regression models used (Paar, 2025). Nonetheless, given that yield stress signifies the stress necessary to either sustain or initiate flow, it holds significant importance in assessing printability and is thus subject to more frequent investigation. Furthermore, when compared against the maximum stress exerted on the feedstock by the 3D printer, yield stress serves as a pivotal metric to ascertain whether this force is adequate to initiate or maintain material flow through the nozzle (Baniasadi et al., 2021). Furthermore, for a paste to retain its shape and resist deformation, its yield stress, $\tau_{dyn}$, must surpass or at least equal the stress induced by the weight of the layers above it, i.e., the hydrostatic pressure (M'Barki et al., 2017). Consequently, the maximum height ($h_{max}$) that can be stacked is determined by Eq. (4). For instance, considering a feedstock with a density of 1000 kg.m⁻³ and a yield stress of 1000 Pa, the maximum stackable height is approximately 10 cm. Thus, it highlights the importance of optimizing the formulation to attain the required yield stress for printing the desired layers, reducing the risk of structure collapse.

$$h_{max} = \frac{\tau_{dyn}}{\rho g} \qquad (4)$$

where $\rho$ represents the density of the paste and g the acceleration due to gravity.

### 3.2.6. Viscosity measurement and flow behaviour: evaluating consistency and extrudability

The viscosity measurement and flow behaviour of the feedstock is crucial as it directly impacts the printability of samples. For instance, when the viscosity is too low, the feedstock may leak out from the nozzle, leading to poor shape fidelity. Conversely, when the viscosity is too high, excessive pressure is required to extrude the material, resulting in poor extrudability (Tagami et al., 2021). Furthermore, fluids whose viscosity decreases in response to shear stress are highly

desirable in SSE 3DP (Herrada-Manchón et al., 2020). These fluids, known as pseudoplastic or shear-thinning fluids, exhibit a unique property where their viscosity significantly drops when subjected to shear. This characteristic facilitates smoother and more efficient flow through the nozzles during printing.

When analysing the rheological behaviour of feedstocks for SSE, it is advisable to obtain flow curves within the specific conditions encountered during the SSE process, such as printing speed or shear rate. This necessitates viscosity measurements at higher shear rates (>100 s⁻¹) where the material behaves differently. In instances where traditional rheometers are unable to perform measurements at such shear rates, employing a makeshift capillary rheometer via a texturometer, can provide viable solutions (Aina et al., 2024a). Equally important is the selection of an appropriate rheological model to ensure accurate interpretation and comparison of results. While several models exist, including the Herschel-Bulkley equation and Casson model, the Ostwald-de Waele or power-law model emerges as particularly well-suited for SSE feedstocks. This preference stems from the challenges posed by the complex nature of these materials, which exhibit properties of both solids and liquids. Furthermore, the Herschel-Bulkley equation, though prevalent, presents challenges in determining yield stress for such complex materials, which might not even exhibit a well-defined yield stress. This ambiguity often results in the over or underestimation of yield stress values, complicating inter-study comparisons and hindering the identification of printable range of this parameter. Moreover, higher shear rates typically correspond to the power-law region, where the Ostwald-de Waele model excels in accurately determining parameters like the consistency index (K) and flow index (n).

Notably, higher K, defined as the viscosity at a shear rate ($\dot{\gamma}$) equals to 1 s⁻¹, translates to feedstocks requiring more energy and higher extrusion force (Panraksa et al., 2021; Sjöholm et al., 2022b). In addition, for pseudoplastic fluids, n is less than 1, and the smaller the value, the greater the viscosity drop in response to shear, which translates to better extrudability (Liang et al., 2023). Moreover, successful printing of low-viscosity gels has been attributed to the shear-thinning properties of the samples (O'Reilly et al., 2021; Leão et al., 2024). Additionally, the shear-thinning behaviour helps prevent nozzle clogging and overfilling of the formulation, particularly at instances where there is a rapid (smaller nozzle sizes) or gradual (larger nozzle sizes) change in direction during the printing process. Therefore, n would have more influence on the choice of nozzle size than K (Ahmed et al., 2021).

### 3.2.7. Practical guide to rheological characterization for 3D printing

As discussed above, rheological properties are crucial to the 3D printing process, significantly influencing material behaviour during extrusion and layer deposition. Despite their importance, there is still limited consensus on the specific rheological ranges universally considered optimal for printability. To address this gap, the printable ranges for key rheological parameters identified in the literature are detailed in Table 1.

However, the knowledge of these optimal ranges is just one piece of the puzzle. In addition, differences in printing equipment, extrusion mechanisms, and printing parameters may require different material specifications, which might not always fall within the range identified in Table 1. The challenge thus lies in how to effectively assess the rheological properties of SSE-based feedstocks using consistent and reliable methods. While some researchers employ both oscillatory and rotational measurements to capture a comprehensive rheological profile, others may use only one type of measurement, which can lead to discrepancies in data interpretation. For example, rotational tests often measure viscosity and flow behaviour under steady shear conditions, providing insights into how a material will extrude, whereas oscillatory tests assess viscoelastic properties like storage and loss moduli, which are crucial for understanding how a material will maintain its shape post-extrusion.
<table><caption>**Table 1**
Identified printable range of some rheological parameters of drug-loaded formulations.</caption><thead><tr><th>G' (kPa)</th><th>tan δ (°)</th><th>τ<sub>y</sub> (Pa)</th><th>τ<sub>f</sub> (Pa)</th><th>K (Pa.s<sup>n</sup>)</th><th>n (-)</th><th>τ<sub>dvn</sub> (Pa)</th><th>Ref</th></tr></thead><tbody><tr><td>–</td><td>–</td><td>47.60–97.40</td><td>468.40–795.10</td><td>400.80–417.20</td><td>0.10–0.11</td><td>–</td><td>González et al. (2022)</td></tr><tr><td>–</td><td>–</td><td>–</td><td>993.48</td><td>1 109.81</td><td>0.12</td><td>–</td><td>Liang et al. (2023)</td></tr><tr><td>13.1–26.9</td><td>–</td><td>–</td><td>–</td><td>1 221.30–1 681.80</td><td>0.23–0.37</td><td>–</td><td>Yang et al. (2020)</td></tr><tr><td>–</td><td>–</td><td>–</td><td>–</td><td>723.44</td><td>0.13</td><td>–</td><td>Panraksa et al. (2021)</td></tr><tr><td>2.8–3.0</td><td>–</td><td>–</td><td>–</td><td>380.68–568.63</td><td>0.24–0.30</td><td>–</td><td>Olmos-Juste et al. (2021)</td></tr><tr><td>–</td><td>–</td><td>200–1 400</td><td>–</td><td>940–1 580</td><td>0.29–0.33</td><td>–</td><td>Cheng et al. (2021)</td></tr><tr><td>–</td><td>–</td><td>–</td><td>2 000.00</td><td>–</td><td>–</td><td>–</td><td>Schmidt et al. (2022)</td></tr><tr><td>19.1–169.6</td><td>0.16–0.43</td><td>29.2–197.40</td><td>–</td><td>1 126.9–2760.7<sup>b</sup></td><td>0.08–0.14</td><td>702.91</td><td>Aina et al. (2024c)</td></tr><tr><td>–</td><td>–</td><td>–</td><td>–</td><td>59.38<sup>a</sup></td><td>0.67<sup>a</sup></td><td>–</td><td>Chaiwarit et al. (2022)</td></tr><tr><td>1.6</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>Suryavanshi et al. (2023)</td></tr><tr><td>–</td><td>–</td><td>–</td><td>–</td><td>96–240<sup>c</sup></td><td>–</td><td>–</td><td>Karavasili et al. (2020)</td></tr><tr><td>–</td><td>–</td><td>–</td><td>–</td><td>1 019–2 825<sup>b</sup></td><td>0.09–0.21</td><td>–</td><td>Aina et al. (2024a)</td></tr><tr><td>–</td><td>–</td><td>534.6</td><td>–</td><td>–</td><td>–</td><td>–</td><td>Leão et al. (2024)</td></tr><tr><td>–</td><td>–</td><td>188–1 681.6</td><td>–</td><td>–</td><td>–</td><td>–</td><td>Johannesson et al. (2023a)</td></tr><tr><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>Johannesson et al. (2023b)</td></tr><tr><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>2 271.0</td><td>de Oliveira et al. (2022)</td></tr><tr><td>>1</td><td>–</td><td>–</td><td>–</td><td>100.40<sup>a</sup></td><td>0.41<sup>a</sup></td><td>–</td><td>Panraksa et al. (2023)</td></tr><tr><td>–</td><td>–</td><td>–</td><td>–</td><td>1 621.95</td><td>0.06</td><td>–</td><td>Panraksa et al. (2022)</td></tr><tr><td>5.1–6.3</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>Teoh et al. (2022)</td></tr><tr><td>–</td><td>0.2–0.7</td><td>&lt;4 000</td><td>–</td><td>–</td><td>–</td><td>–</td><td>Cheng et al. (2020)</td></tr><tr><td>28.0<sup>b</sup></td><td>0.19</td><td>26.7</td><td>–</td><td>–</td><td>–</td><td>–</td><td>Aina et al. (2025)</td></tr></tbody></table>

This lack of a standardized approach across studies makes it difficult to directly compare results, further complicating the selection of materials for specific applications. Moreover, the variability in rheological characterization methods underscores the need for a consistent testing framework that can be widely adopted. Such a framework would not only enhance the predictability and reliability of material performance but also facilitate more accurate comparisons across different studies. In our previous studies (Aina et al., 2024c, 2025), we successfully demonstrated that similar rheological insights can be derived from both rotational (viscosity data) and oscillatory (viscoelastic data) measurements. Specifically, we showed that comparable information could be obtained using either viscosity data alone or viscoelastic data alone. These correlations were identified through principal component analysis (PCA), where three principal components (PCs) consistently accounted for over 90% of the total variance of the rheological data across all three studies. These components were correlated with key aspects of the 3D printing process: PC 1 with the extrusion force required, PC 2 with the extrudability of the material, and PC 3 with the shape fidelity of the printed structure. Importantly, these findings suggest that three key rheological parameters could provide information equivalent to what would typically require the measurement of eleven different parameters (Aina et al., 2024c).

Building on these insights, the parameter $m_{index}$ (or relaxation time) emerged as a crucial indicator of printability, as it correlates strongly with both PC 2 (extrudability) and PC 3 (shape fidelity). This correlation is likely due to $m_{index}$ reflecting the balance between the viscous and elastic components of the material, which directly influences its behaviour during and after extrusion. Additionally, $τ_{dyn}$ offers critical insights into shape fidelity, as it can be used to estimate the maximum layers ($h_{max}$) that can be stacked before collapse. Moreover, K and n, measured at shear rates relevant to the 3D printing process (at the shear rate equivalent to the printing speed, $γ_p$), provide valuable information about extrudability since they describe the material's viscosity and shear-thinning behaviour during printing. Integrating all this information, a simplified characterization workflow is proposed in Fig. 5, emphasizing the importance of selecting rheological parameters tailored to the specific information required for optimizing the 3D printing process.

### 3.3. Texture profile analysis (TPA)

Materials suitable for SSE 3DP must be continuously and homogeneously extruded through the nozzle without fracturing or developing a lumpy texture (Cheng et al., 2021). Therefore, another commonly performed characterization for both feedstocks and final objects is Texture Profile Analysis (TPA). In TPA, a sample is compressed twice to simulate the action of chewing, and the resulting force-time curve is analysed. As such, this method is particularly useful for evaluating chewable or gummy formulations. Key parameters derived from TPA include hardness, springiness, cohesiveness, adhesiveness, chewiness, and gumminess (Liang et al., 2023).

A typical TPA curve and some key parameters evaluated for semi-solid formulations is shown in Fig. 6. Hardness indicates the maximum force occurring during the first compression. Cohesiveness measures the sample's ability to withstand deformation, such as during mastication. This parameter is measured by dividing the area of work during the second compression cycle by the area of work during first compression. Springiness assesses the elasticity or recovery of semisolids after compression and is the ratio of the distance of the detected height during the second compression divided by the first compression distance (Derossi et al., 2020). Adhesiveness represents the energy required to overcome the attractive forces between the sample's surface and the probe and corresponds to the area under the curve during the first withdrawal or unloading (Jonkers et al., 2022). Gumminess reflects the energy needed for the sample's disintegration and is calculated by multiplying hardness by the cohesiveness (Chatzitaki et al., 2022; Carranza et al., 2023).

Typically, higher hardness indicates formulations with a more compact structure, thereby requiring a higher extrusion force (Zhou et al., 2023). Formulations with high adhesiveness are generally sticky to touch, but handleability can be improved if the formulations also possess a high G', indicating a more solid-like texture. Conversely, lower cohesiveness and springiness indicate formulations that deform easily and have lower elastic recovery, respectively (Cheng et al., 2021). Depending on the composition of the feedstock, these TPA parameters can be increased or decreased. For instance, it was reported that the hardness of an HPMC-based formulation increased with polymer concentration (Cheng et al., 2020). A similar effect was observed for yield stress and G', attributed to the increased amount of total polymer

<footnote>a Formulations destined for fabricating oral films.</footnote>

<footnote>b Printing pressure: 4–5 bars.</footnote>

<footnote>c Printing pressure ≈ 2 bars.</footnote>
<figure><img src="image_8.png" /><figcaption>Fig. 5. An example of a process flow for characterizing the rheological properties of drug-loaded feedstocks printable at room temperature (RT).</figcaption></figure>

content. However, it was noted that the information obtained from texture and rheological analyses cannot be directly compared, as the principles of these techniques differ significantly (de Oliveira et al., 2022). The authors suggested that samples should be discriminated by comparing results obtained from the same technique, thus necessitating the use of both a rheometer and a texturometer for comprehensive sample characterization.

Moreover, texture profile analysers fitted with a syringe share similarities with SSE 3DP. However, to date, researchers primarily focus on the texture analysis of formulations using TPA. Instead of utilizing TPA to monitor flow behaviour and detect the presence or

absence of air bubbles—factors that could predict printing outcomes— researchers typically correlate printability with parameters obtained from a rheometer (Anderspuk et al., 2021). These rheological tests might not be suitable for characterizing feedstocks for SSE due to their higher powder-to-liquid ratio, higher viscosity, and lower fluidity (Zi-dan et al., 2019b). The authors, therefore, used data obtained from a texture analyser to develop constitutive and analytical models that quantify intrinsic rheological parameters such as τ<sub>dyn</sub>, K, and n.

Recently, a texture analyser was used as a capillary rheometer (Aina et al., 2024a). The authors compared parameters obtained from this makeshift rheometer to those from a rotational rheometer and observed
<figure><img src="image_9.png" /><figcaption>Fig. 6. Example of a TPA curve with the definition of some typical parameters.</figcaption></figure>

insignificant differences (p-value >0.05) between both techniques. This finding demonstrates the potential for evaluating both textural and rheological properties using a single piece of equipment. Although one limitation of this method is the difference in flow velocity of materials from the syringe of a texture analyser compared to that from a 3D printer (Anderspuk et al., 2021), it has however been observed that the high shear rate regime of the flow curves generated using the texture analyser improved the prediction of printability (Aina et al., 2024a). This is because the shear rate regime included the shear rate calculated for the 3D printer used, thereby simulating the true printing process and ultimately improving the accuracy of the printability predictions (Aina et al., 2023).

### 3.4. Physicochemical characterizations

Physicochemical characterizations play a crucial role in evaluating the quality, safety, and efficacy of printed dosage forms. These characterizations encompass a variety of techniques aimed at assessing various aspects of the formulations and printed objects (Table 2).

## 4. Applications of SSE in oral drug delivery

SSE 3D printing, which shares similarities with bioprinting but excludes cells from the bioink, has emerged as a promising technology for the development of innovative oral dosage forms in pharmaceutical applications (Mathiyalagan et al., 2023). This technology enables the fabrication of various drug delivery systems, including 3D-printed tablets (Printlets™), cereal-based tablets, solid lipid tablets, chewable tablets, and orodispersible films. One of SSE's key advantages is its ability to produce these drug products in a single-step process within minutes, making it a promising candidate for clinical research and point-of-care applications (Sjöholm et al., 2022a).

The application of SSE 3D printing has been demonstrated in both hospitals and pharmacies, with a notable example from a community pharmacy in Spain. Here, a 3D printer was used to auto-fill minoxidil capsules for nine patients as part of routine dispensing. The capsules, available containing 2.5 mg and 5 mg doses, met rigorous quality standards for mass uniformity, drug content, and dissolution rates. The automation led to a 55% reduction in operator involvement, a 20%–35% decrease in production costs, and a 10% faster preparation time. Furthermore, in-line automated quality control enhanced patient

safety (Rodríguez-Maciñeiras et al., 2025). This example highlights the significant potential of SSE 3D printing to improve efficiency, precision, and cost-effectiveness, offering pharmacists a powerful tool to streamline medication compounding while maintaining high standards of quality.

Beyond applications in pharmacies, SSE 3D printing has also demonstrated significant potential in hospital settings. A notable example comes from a study conducted at the Clinic University Hospital in Santiago de Compostela, Spain, where the focus was on developing customized tablets for children with Maple Syrup Urine Disease (MSUD) using SSE 3D printing technology. This approach involved creating tablets with individualized shapes, flavours, and dosages specifically designed to improve compliance in children aged 6 to 14 (Goyanes et al., 2019). The study therefore not only highlighted the feasibility of using SSE to customize treatments for a vulnerable patient population but also underscored the broader potential of SSE 3D printing in various hospital-based applications.

Similarly, the OPERA clinical trial showcased the successful integration of SSE 3D printing into hospital workflows for personalized polypill formulations (Denis et al., 2024). Immediate-release tamoxifen was combined with either extended-release venlafaxine or delayed-release duloxetine using SSE 3D printing and a novel pellet dispensing system. The process adhered to French compounding regulations, met USP dissolution specifications, and ensured stability for up to one year, covering the full duration of the clinical study. Additionally, 200 dosage units were produced in under an hour—from pharmaceutical preparation to final testing—while maintaining high quality and precision. By simplifying treatment regimens and enabling rapid, on-site production of personalized medications, this approach helps reduce side effects, improve adherence, and reinforces the role of SSE 3D printing in streamlining pharmaceutical compounding and ensuring timely access to tailored therapies.

In a separate study conducted at Leiden Medical Centre in the Netherlands, SSE 3D printing was explored to develop sildenafil 3D-printed tablets. This clinical trial involved 12 healthy volunteers who received either the 3D-printed tablets or a marketed sildenafil product. The pharmacokinetic results showed that the 3D-printed tablets met the required bioequivalence criteria, with parameters like area under the plasma concentration curve (AUC) and maximum plasma concentration (Cmax) falling within the acceptable regulatory range (80.00–125.00%) (Lyousoufi et al., 2023). The study thus confirmed
<table><caption>**Table 2**
Physicochemical characterization techniques.</caption><thead><tr><td>Technique</td><td>Description</td><td>Relevance</td><td>Reference</td></tr></thead><tbody><tr><td>Surface morphology and internal structure</td><td>Analysis using scanning electron microscopy (SEM) and/or X-ray micro-computed tomography (micro-CT) to assess surface morphology, porosity, and internal structure of printed dosage forms.</td><td>Provides insights into microstructure of the final dosage form, crucial for assessing printability (structural integrity and extrudability).</td><td>Chatzitaki et al. (2022), Chen et al. (2021), Algahtani et al. (2021)</td></tr><tr><td>Mechanical strength</td><td>Evaluation of mechanical properties and structural integrity of printed objects (especially printed films) using tensile and compression testing.</td><td>Ensures printed objects meet required standards for handling and administration by assessing parameters like young's modulus, tensile strength and fracture resistance.</td><td>Goh et al. (2021), Alayoubi et al. (2022), Elbl et al. (2020), Sjöholm et al. (2020), Janigová et al. (2022)</td></tr><tr><td>Drug release kinetics</td><td>Study of drug release kinetics using dissolution testing apparatus to evaluate the drug release properties of printed formulations.</td><td>Critical for ensuring that the printed formulation releases the drug at the intended rate and duration.</td><td>Wang et al. (2023), Real et al. (2023), Baniasadi et al. (2021), Gholamipour-Shirazi et al. (2021)</td></tr><tr><td>Stability and microbial testing</td><td>Conducting stability tests under various environmental conditions to assess physical, chemical, and microbiological stability of printed dosage forms.</td><td>Guides formulation optimization, packaging design, and storage conditions to ensure product quality and patient safety throughout shelf life.</td><td>Johannesson et al. (2023a), Aina et al. (2024b), Mathiyalagan et al. (2023), Ganatra et al. (2024), Zheng et al. (2020), Liu et al. (2023), Aita et al. (2020)</td></tr><tr><td>Thermal analysis</td><td>Utilization of techniques such as differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) to evaluate thermal properties and stability of materials.</td><td>Provides information about phase transitions, thermal degradation behaviour, and composition, crucial for evaluating the compatibility of drugs with excipients and for assessing the stability of the formulation.</td><td>Olmos-Juste et al. (2021), Katsiotis et al. (2024), Hu et al. (2023), Protopapa et al. (2024)</td></tr><tr><td>Chemical composition and structure analysis</td><td>Identification of chemical bonds and functional groups in materials used in formulations. Commonly performed using fourier transform infrared spectroscopy (FTIR).</td><td>Reveals information about chemical composition, purity, and structural integrity of materials, ensuring none of the printing steps (e.g. paste preparation, printing and drying) nor storage conditions interferes with the state of the API in the final dosage form</td><td>Ou et al. (2023), Cui et al. (2020), Chachlioutaki et al. (2022), Teoh et al. (2022), Yan et al. (2024)</td></tr></tbody></table>

that 3D-printed medications can be manufactured at the point-of-care while maintaining high-quality standards suitable for clinical use.

These case studies highlight the growing applications of SSE 3D printing in oral drug delivery. Additional examples are discussed in Table 3, which covers the APIs studied, excipients used, and specific printing conditions.

## 5. SWOT analysis of SSE 3D printing in oral drug delivery applications

The application of SSE 3D printing in the fabrication of oral dosage forms brings unique advantages, including personalized medicine, low-temperature processing, and point-of-care manufacturing. As research and development in this field continue to progress, it is essential to critically assess both the benefits and challenges that may affect its broader adoption. As summarized in Fig. 7, this section presents a SWOT analysis of SSE 3D printing, categorizing its strengths, weaknesses, opportunities, and threats in the context of pharmaceutical manufacturing. The subsequent subsections provide a detailed examination of each of these aspects, offering a comprehensive evaluation of the factors that influence its feasibility, scalability, and regulatory acceptance.

### 5.1. Strength (Advantages)

One of the primary benefits of SSE compared to other 3D printing techniques is its ability to operate without the need for hot temperatures or UV radiation. This characteristic makes SSE particularly well-suited for printing temperature- or light-sensitive compounds (Bhawale et al., 2023). These mild conditions of operation also affords SSE a wide choice of excipients that are often listed as food-grade or generally recognized as safe (GRAS) (Johannesson et al., 2023a). Furthermore, unlike other 3D printing techniques, SSE involves simpler preparation steps and requires little to no prior processing, such as hot melt extrusion, which is needed for producing drug-loaded filaments in FDM (Panraksa et al., 2023; Bhawale et al., 2023). Moreover, the paste extrusion and preparation process are generally well-understood and have been used in pharmaceutical and other industries (Khaled et al., 2018b). In addition, the feedstock can be easily prepared in hospitals or pharmacies, making this technology particularly useful for decentralized manufacturing approaches (El Aita et al., 2020) and small-lot production to meet the dispensing needs of pharmacies (Liang et al., 2023; Roulon, 2023). Moreover, the utilization of disposable and pre-loaded syringes guarantees the high quality and purity of the final product, meeting the rigorous quality standards essential for pharmaceutical applications (Lopez-Vidal et al., 2022; Díaz-Torres et al., 2022).
<table><caption>**Table 3**
Different dosage forms prepared using the SSE 3DP, as well as the composition of the feedstock used.</caption><thead><tr><th>Gel or paste-forming polymer</th><th>Other excipients</th><th>Printing temperature</th><th>Post-treatment</th><th>API</th><th>Ref.</th></tr></thead><tbody><tr><td colspan="6"><strong>Subdivided dosage forms or compounded medicine</strong></td></tr><tr><td>HPC<sup>a</sup> (2%)</td><td>CCS<sup>a</sup> (2%)</td><td>RT<sup>a</sup></td><td>RT<sup>a</sup> (48 h)</td><td>Levetiracetam (96%)</td><td>Cui et al. (2020)</td></tr><tr><td>HPMC<sup>a</sup> (5%)</td><td></td><td>ND<sup>a</sup></td><td>ND<sup>a</sup></td><td>Levothyroxine sodium (0.061%)</td><td>Liu et al. (2023)</td></tr><tr><td>PVP<sup>a</sup> K30 (5%)</td><td>SSG<sup>a</sup> (40%)<br>Lactose (50%)<br>Sucralose (5%)</td><td>RT<sup>a</sup></td><td>RT<sup>a</sup> (overnight)</td><td>Carbamazepine (ND<sup>a</sup>)</td><td>Hu et al. (2023)</td></tr><tr><td>Gelucire 44/14 (50 – 70%)<br>Precirol ATO 5 (30 – 50%)</td><td></td><td>60 – 70°C</td><td>9°C (ND<sup>a</sup>)</td><td>Hydrocortisone (ND<sup>a</sup>)</td><td>Protopapa et al. (2024)</td></tr><tr><td>HPMC<sup>a</sup> (35%)</td><td>Mannitol (27%)<br>Crospovidone (6%)<br>Glycerol (8%)</td><td>RT<sup>a</sup></td><td>RT<sup>a</sup> (overnight)</td><td>Theophylline (20%)</td><td>Sjöholm et al. (2022b)</td></tr><tr><td>HPMC<sup>a</sup> (15%)</td><td></td><td>RT<sup>a</sup></td><td>RT<sup>a</sup> (24 h)<br>Freeze-drying (15 h)</td><td>nano-Piroxicam (3%)</td><td>Mathiyalagan et al. (2023)</td></tr><tr><td colspan="6"><strong>Chewable dosage forms</strong></td></tr><tr><td>Corn starch (5%)<br>Carrageenan (2%)<br>Xanthan gum (0.25%)<br>Gelatine (8%)</td><td></td><td>37°C</td><td>15°C (ND<sup>a</sup>)</td><td>Ranitidine HCl (3.3%)</td><td>Herrada-Manchón et al. (2020)</td></tr><tr><td>HPMC<sup>a</sup> (ND<sup>a</sup>)<br>Gelatine (ND<sup>a</sup>)</td><td>Reduced starch syrup (ND<sup>a</sup>)</td><td>RT<sup>a</sup></td><td>RT<sup>a</sup> (24 h)</td><td>Lamotrigine (ND<sup>a</sup>)</td><td>Tagami et al. (2021)</td></tr><tr><td>Pectin (4%)<br>Maltitol (60%)</td><td>Citric acid (1%)<br>Sorbitol (2%)</td><td>RT<sup>a</sup></td><td></td><td>Simethicone (20%)</td><td>Ganatra et al. (2024)</td></tr><tr><td>CMC<sup>a</sup> (3%)<br>Gelatine (8%)<br>Carrageenan (2%)<br>Xanthan gum (0.5%)</td><td></td><td>RT<sup>a</sup></td><td>15°C (ND<sup>a</sup>)</td><td>Omeprazole (1% & 22.5%)</td><td>Rouaz-El Hajoui et al. (2023)</td></tr><tr><td colspan="6"><strong>Poly and combi-pills</strong></td></tr><tr><td>Humic acid (38.3%)<br>Cellulose acetate phthalate (2.04%)</td><td>Polyquaternium 10 (12.8%)</td><td>RT<sup>a</sup></td><td>20°C (12 h)</td><td>Efavirenz (25.5%)<br>Tenofovir disoproxil fumarate (12.8%)<br>Emtricitabine (8.52%)</td><td>Siyawamwaya et al. (2019)</td></tr><tr><td>HPMC<sup>a</sup> 2208 (3.5 – 14.2%)<br>PEG<sup>a</sup> 6000 (13 – 53.5%)<br>PVP<sup>a</sup> K30 (6%)<br>Cellulose acetate (55%)</td><td>Lactose (25.1 – 51%)<br>MCC<sup>a</sup> (18.5%)<br>SSG<sup>a</sup> (14%)<br>CCS<sup>a</sup> (7%)<br>Mannitol (32 – 73%)</td><td>RT<sup>a</sup></td><td>40°C (24 h)</td><td>Captopril (18.5%)<br>Nifedipine (10.7%)<br>Glipizide (3.5%)</td><td>Khaled et al. (2015b)</td></tr><tr><td>HPMC<sup>a</sup> 2208 (15%)<br>Cellulose acetate (22.64%)<br>PEG 6000 (15.10%)<br>PVP K30 (10.3%)</td><td>Mannitol (62.26%)<br>Lactose (55 – 70%)<br>SSG<sup>a</sup> (55.18%)</td><td>RT<sup>a</sup></td><td>40°C (24 h)</td><td>Atenolol (30%)<br>Pravastatin (20%)<br>Ramipril (15%)<br>Aspirin (28.62%)<br>Hydrochlorothiazide (5.86%)</td><td>Khaled et al. (2015a)</td></tr><tr><td>PVP<sup>a</sup> K30 (20%)</td><td>CCS<sup>a</sup> (15%)</td><td>RT<sup>a</sup></td><td>25°C, 37°C and 60°C (ND<sup>a</sup>)</td><td>Tranexamic acid (45%)</td><td>Zhang et al. (2022)</td></tr><tr><td>Starch (25%)<br>Carbopol (1 – 5%)<br>HPMC<sup>a</sup> (10 – 40%)</td><td>SSG<sup>a</sup> (6%)<br>Mannitol (10%)<br>Lactose (26%)</td><td>RT<sup>a</sup></td><td>40°C (overnight)</td><td>Atorvastatin (55%)<br>Metoprolol succinate (48%)</td><td>Alayoubi et al. (2022)</td></tr><tr><td colspan="6"><strong>Nutraceuticals</strong></td></tr><tr><td>Gelatine (6%)<br>Peach gum polysaccharide (6%)</td><td>Fructose corn syrup (10%)</td><td>RT<sup>a</sup></td><td></td><td>Cucurmin (0.05%)</td><td>Zhou et al. (2023)</td></tr></tbody></table>

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<table><caption>**Table 3 (continued).**</caption><thead><tr><th></th><th></th><th></th><th></th><th></th><th></th></tr></thead><tbody><tr><td>Gel or paste-forming polymer</td><td>Other excipients</td><td>Printing temperature</td><td>Post-treatment</td><td>API</td><td>Ref.</td></tr><tr><td>Gelatine (10%)<br>Gellan gum (1.5%)</td><td>O/W emulsion<br>(30:70)</td><td>RT<sup>a</sup></td><td>Freeze-dried<br>(ND<sup>a</sup>)</td><td>Curcumin (5%)<br>Resveratrol (5%)</td><td>Kavimughil et al.<br>(2022)</td></tr><tr><td>κ-Carrageenan (3%)</td><td></td><td>RT<sup>a</sup></td><td></td><td>Thiamine (2%)</td><td>Kamlow et al.<br>(2021)</td></tr><tr><td>PEO<sup>a</sup> (20%)</td><td>Eumulgin (30%)</td><td>RT<sup>a</sup></td><td>40 °C (ND<sup>a</sup>)</td><td>Eucalypt<br>extract (10%)<br>Ascorbic<br>acid (20%)</td><td>Koshovyi et al.<br>(2023a)</td></tr><tr><td>PEO<sup>a</sup> (12%)</td><td>Eumulgin (15%)</td><td>RT<sup>a</sup></td><td>30 °C (ND<sup>a</sup>)</td><td>Cranberry<br>extract (10%)</td><td>Koshovyi et al.<br>(2023c)</td></tr><tr><td>PEO<sup>a</sup> (12%)</td><td>Eumulgin (3%)</td><td>RT<sup>a</sup></td><td>40 °C (ND<sup>a</sup>)</td><td>Eucalypt<br>extract (1%)<br>Ascorbic acid (2%)</td><td>Koshovyi et al.<br>(2023b)</td></tr><tr><td colspan="6"><strong>Oral films or fast disintegrating tablets</strong></td></tr><tr><td>Gelatine (10%)<br>PVP<sup>a</sup> K30 (5%)<br>PVA<sup>a</sup> (5%)</td><td>Glycerol (1%)</td><td>RT<sup>a</sup></td><td>RT<sup>a</sup> (24 h)</td><td>Propranolol<br>hydrochloride (2.5%)</td><td>Jovanović et al.<br>(2021)</td></tr><tr><td>HPC<sup>a</sup> (16%)</td><td></td><td>RT<sup>a</sup></td><td>RT<sup>a</sup> (24 h)</td><td>Warfarin (1.3%)</td><td>Sjöholm and Sandler<br>(2019)</td></tr><tr><td>HPMC<sup>a</sup> E15 (10%)</td><td>Glycerin (10%)<br>Propylene Glycol<br>(15%)</td><td>RT<sup>a</sup></td><td>RT<sup>a</sup> (15–30 min)</td><td>Phenytoin (10%)</td><td>Panraksa et al.<br>(2020)</td></tr><tr><td>HPMC<sup>a</sup> F4M (1.4%)<br>Hydroxypropyl-β<br>-cyclodextrin (72.1%)</td><td>CCS<sup>a</sup> (2.5%)</td><td>RT<sup>a</sup></td><td>40 °C (12 h)</td><td>Carbamazepine<br>(24%)</td><td>Conceição et al.<br>(2019)</td></tr><tr><td>PVP<sup>a</sup> (8.1%)</td><td>CCS<sup>a</sup> (30.3%)<br>Lactose (18.2%)<br>Banana flavour (3%)</td><td>RT<sup>a</sup></td><td>RT<sup>a</sup> (6 h)</td><td>Hydrochloro-<br>thiazide<br>(40.4%)</td><td>Eduardo et al.<br>(2021),<br>Suárez-González et al.<br>(2021)</td></tr><tr><td>HPMC<sup>a</sup> (5.5%)<br>Sodium alginate<br>(9.5%)</td><td>CCS<sup>a</sup> (60%)</td><td>RT<sup>a</sup></td><td>40 °C (12 h)</td><td>Caffeine (35%)</td><td>Roche et al.<br>(2023)</td></tr><tr><td colspan="6"><strong>Immediate release</strong></td></tr><tr><td>Techna 20 SF™<br>(98.3%)<br>PEG<sup>a</sup> 4000 (97.8%)<br>Xanthan gum<br>(0.5,%)</td><td></td><td>70 °C</td><td></td><td>Minoxidil<br>(1.7%)</td><td>Rodríguez-Maciñeiras<br>et al.<br>(2025)</td></tr><tr><td>PEG<sup>a</sup> 4000<br>(70,%)</td><td></td><td>75 °C</td><td></td><td>Tamoxifen citrate<br>(30%)</td><td>Denis et al.<br>(2024)</td></tr><tr><td>Gelatin<br>(CuraBlend®,<br>94.6–94.8%)</td><td>Polysorbate 80<br>(2%)<br>Citric acid<br>(1.2–2.4%)</td><td>RT<sup>a</sup></td><td></td><td>Clopidogrel<br>bisulphate<br>(1–2%)</td><td>Shokraneh et al.<br>(2025)</td></tr><tr><td>Gelatin (7.56%)<br>Carrageenan (0,50%)</td><td>Xylitol (21%)<br>Butylated<br>Hydroxy Anisole<br>(0.70%)<br>Butylated<br>Hydroxytoluene<br>(0.07%)</td><td>30 °C</td><td></td><td>Isoniazid (4.53%)<br>Pyridoxine<br>Hydrochloride<br>(0.15%)</td><td>Holkunde et al.<br>(2025)</td></tr><tr><td>HPMC<sup>a</sup> E5 (2%)</td><td>Lactose (18%)</td><td>RT<sup>a</sup></td><td>RT<sup>a</sup> (24 h)</td><td>Ofloxacin (80%)</td><td>Fang et al.<br>(2024)</td></tr><tr><td>PVA<sup>a</sup>-PEG<sup>a</sup> (31%)</td><td></td><td>27 °C</td><td>40 °C<br>(0.5 – 1 h)</td><td>Levetiracetam<br>(≈ 28%)</td><td>El Aita et al.<br>(2020)</td></tr><tr><td>PVP<sup>a</sup> (10%)<br>Starch (8.33%)</td><td>CCS<sup>a</sup> (0.63%)</td><td>27 °C</td><td>80 °C<br>(overnight)</td><td>Paracetamol<br>(81.04%)</td><td>Khaled et al.<br>(2018a)</td></tr><tr><td>PVP<sup>a</sup> (11.25%)</td><td>CCS<sup>a</sup> (8.75%)</td><td>23 °C</td><td>80 °C (3 h)</td><td>Paracetamol<br>(80%)</td><td>Khaled et al.<br>(2018b)</td></tr></tbody></table>

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SSE 3DP also offers a broader range of flexibility in adjusting formulation properties like drug release rate, texture, and drug loading compared to many other printing technologies (Korelc et al., 2024). The encapsulation of the drug within the feedstock matrix used in SSE is particularly noteworthy, as it facilitates high drug loading and potential taste masking (Yang et al., 2020; Cheng et al., 2020). Furthermore, due to the ability to prepare the feedstock with a significant amount of water, SSE reduces the requirement for large quantities of

excipients (Cheng et al., 2020). Therefore, SSE 3DP presents potential solutions to the challenges associated with inkjet printing, particularly those related to drug or binder oversaturation (Alayoubi et al., 2022). Moreover, the feedstocks utilized in SSE have the capability to load both highly water-soluble and poorly water-soluble APIs, offering a broad spectrum of drug compatibility. This flexibility allows for the formulation of a wide range of pharmaceutical products, catering to diverse therapeutic needs and patient populations. In addition, chewable
<table><caption>**Table 3 (continued).**</caption><thead><tr><th>Gel or paste-forming polymer</th><th>Other excipients</th><th>Printing temperature</th><th>Post-treatment</th><th>API</th><th>Ref.</th></tr></thead><tbody><tr><td>Agar (3%)<br>HPMC<sup>a</sup> (2%)</td><td>Sucrose (10%)</td><td>RT<sup>a</sup></td><td></td><td>Caffeine (2%)</td><td>Aina et al. (2024b)</td></tr><tr><td>Agar (3%)</td><td>Crospovidone (5%)<br>SSG<sup>a</sup> (10%)<br>Sucrose (10%)</td><td>RT<sup>a</sup></td><td></td><td>Caffeine (2%)</td><td>Aina et al. (2025)</td></tr><tr><td colspan="6"><strong>Modified release</strong></td></tr><tr><td>HPMC<sup>a</sup> (4–5%)</td><td>PEGDA<sup>a</sup> (35%)<br>DPPO<sup>a</sup> (0.1–1%)</td><td>RT<sup>a</sup></td><td>RT<sup>a</sup><br>(overnight)</td><td>Hydrochlorothiazide (10%)</td><td>Tasevska et al. (2025)</td></tr><tr><td>Guar gum (8%)</td><td>Glycerin (5%)<br>Citric acid (2.4%)</td><td>RT<sup>a</sup></td><td>RT<sup>a</sup> (48 h)</td><td>Pimobendan (0.24%)</td><td>Leão et al. (2024)</td></tr><tr><td>HPMC<sup>a</sup> K100 M (15%)<br>HPMC<sup>a</sup> E5 (15%)<br>Sodium alginate (10%)</td><td>Lactose (5%)<br>MCC<sup>a</sup> (5%)</td><td>RT<sup>a</sup></td><td>40 °C (24 h)</td><td>Ofloxacin (50%)</td><td>Fang et al. (2022)</td></tr><tr><td>HPMC<sup>a</sup> K100 M (20%)<br>HPMC<sup>a</sup> E5 (15%)</td><td>Lactose (10%)<br>MCC<sup>a</sup> (5%)</td><td>RT<sup>a</sup></td><td>RT<sup>a</sup> (12 h)</td><td>Ofloxacin (50%)</td><td>Fang et al. (2024)</td></tr><tr><td>Sodium alginate (4%)<br>Cellulose nanofibers (3%)</td><td></td><td>RT<sup>a</sup></td><td>Cross-linked with Ca<sup>2+</sup> (4 h) and air-dried (1 week)</td><td>Curcumin (15%)<br>Chloramphenicol (50%)</td><td>Olmos-Juste et al. (2021)</td></tr><tr><td>HPMC<sup>a</sup> K4M (12%)</td><td></td><td>RT<sup>a</sup></td><td></td><td>Theophylline (5 – 9%)</td><td>Cheng et al. (2020)</td></tr><tr><td>MC K4M (10%)</td><td></td><td>RT<sup>a</sup></td><td></td><td>Theophylline (5 – 9%)</td><td>Cheng et al. (2021)</td></tr><tr><td>PVP<sup>a</sup> K30 (8.8%)</td><td>CCS<sup>a</sup> (11.2%)</td><td>RT<sup>a</sup></td><td>RT<sup>a</sup> (12 h)</td><td>Artesunate (80%)</td><td>Fang et al. (2024)</td></tr><tr><td colspan="6"><strong>Lipid tablets</strong></td></tr><tr><td>Gelucire 48/16 (23.3%)<br>Gelucire 44/14 (46.5%)</td><td>Kolliphor® (23.2%)</td><td>65 °C</td><td>4 °C (24 h)</td><td>Fenofibrate (7%)<br>Cinnarizine (7%)</td><td>Vithani et al. (2019)</td></tr><tr><td>Gelucire 50/13 (75%)</td><td></td><td>49 °C</td><td>RT<sup>a</sup> (during printing)</td><td>Ricobendazole (25%)</td><td>Real et al. (2020)</td></tr><tr><td>Gelucire 50/13 (75%)</td><td>Poloxamer 188 (12.5%)</td><td>47 °C</td><td>RT<sup>a</sup> (during printing)</td><td>nano-Niclosamide (12.5%)</td><td>Real et al. (2023)</td></tr><tr><td>PEG<sup>a</sup> 1500 (45%)<br>PPG<sup>a</sup> (5%)</td><td>Poloxamer 188 (25%)</td><td>42 °C</td><td>RT<sup>a</sup> (during printing)</td><td>nano-Albendazole (25%)</td><td>Lopez-Vidal et al. (2022)</td></tr></tbody></table>

printlets or gummies manufactured using SSE have garnered significant attention in paediatric drug delivery, emerging as the preferred dosage form among this patient group (Januskaite et al., 2020).

Besides the specific advantages offered by SSE, the technique shares several benefits with other 3DP methods. Like other 3DP techniques, SSE enables the customization of geometry and drug release properties according to individual patient requirements (Leão et al., 2024; Algah-tani et al., 2020). Additionally, SSE enables the fabrication of unique geometries and functionalities that are challenging or even impossible to produce using conventional methods. For example, it allows for the spatial arrangement of excipients and materials to separate incompati-ble ingredients or achieve desirable release rates (Zidan et al., 2019a; Vithani et al., 2019). Moreover, drug screening and prototyping can be accelerated as various compositions and properties can be tested simply by adjusting printing parameters or formulation compositions (Vithani et al., 2019).

Also, the 3D printers are portable, cost-effective and relatively simple to operate, which makes them eligible for on-demand manufac-turing. In addition, the same tool can be used for different operations without the need to change the entire production line (Real et al.,

2020). Furthermore, compared to traditional manufacturing, the use of a 3D printer allows the fabrication of personalized dosage forms at a lower cost (Zhang et al., 2022). Moreover, SSE 3DP facilitates the fabrication of dosage forms with precise drug content by correlating material consumption or geometry volume with the desired dose (Goh et al., 2021). Therefore, avoiding human errors typically associated with manual subdivision of tablets. This feature is also particularly appealing for drugs with a relatively narrow therapeutic index and for the production of personalized medicines (Chaiwarit et al., 2022). Finally, with a 3D printer, it is possible to fabricate highly porous structures that rapidly disintegrate by fine-tuning infill settings and other parameters. This feature holds significant potential for improving medication adherence among patients facing swallowing difficulties, including paediatric and geriatric populations (Panraksa et al., 2022).

## 5.2. Weakness (Limitations)

Despite the capabilities of SSE 3DP, achieving optimal printing processes often remains reliant on a trial-and-error approach (Bhawale

<footnote><sup>a</sup> Notes: CCS = Croscarmellose sodium, CMC = Carboxymethyl cellulose, DPPO = Diphenyl (2,4,6-trimethylbenzoyl) phosphine oxide, HPMC = Hydroxypropyl methylcellulose, HPC = Hydroxypropyl cellulose, MCC = Microcrystalline cellulose, ND = Not disclosed, PEG = Polyethylene glycol, PEGDA = Polyethylene glycol diacrylate, PEO = Polyethylene oxide, PPG = Polypropylene glycol, PVA = Polyvinyl alcohol, PVP = Polyvinylpyrrolidone, RT = Room temperature, SSG = Sodium starch glycolate.</footnote>
<figure><img src="image_10.png" /><figcaption>Fig. 7. SWOT Analysis of SSE 3D Printing in Oral Drug Delivery Applications.</figcaption></figure>

et al., 2023). Rheological characterization, which is essential for controlling various aspects of the printing process, is one of the most challenging and time-consuming tasks, particularly for those with limited experience (Aina et al., 2024c; Elbadawi et al., 2020a). The lack of detailed information on critical feedstock characteristics (Díaz-Torres et al., 2022; Zidan et al., 2019a) and the limited availability of materials with suitable printability and rheological properties add further complexity (Ganatra et al., 2024), often necessitating the preparation of multiple formulations and extensive rheological testing. Although efforts in this study have aimed to reduce the number of required rheological tests (Fig. 5), variations in printing equipment, extrusion mechanisms, and processing parameters mean that optimal rheological properties identified in one study may not always be directly applicable to another (Aina et al., 2024c). Additionally, in high-dose formulations and nanoparticle-based materials, the inclusion of solid drug particles and nanoparticles further complicates the rheological properties of the feedstock, challenging the extrusion process (Ganatra et al., 2024; Germini and Peltonen, 2021).

The absence of universally accepted print-ready materials that can accommodate any API further limits the scalability and versatility of SSE 3DP in pharmaceutical manufacturing (Smith et al., 2018). To enhance printability, formulations often require additional excipients, which may affect drug diffusivity or increase the size of the printed dosage form (Zhang et al., 2024; Muehlenfeld et al., 2024; Aina et al., 2025). This poses challenges for patients, particularly for solid oral formulations that must be swallowed whole, potentially impacting compliance and medication adherence (Siyawamwaya et al., 2019). Additionally, larger printed dosage forms, especially those exceeding 10 mm in diameter, may be unsuitable for certain patient populations, such as neonates or infants, due to swallowing difficulties. The physical stability of the API also remains a concern, potentially limiting drug loading in the feedstock (Smith et al., 2018). This issue becomes even more pronounced during drying, where dislodged drug crystals can compromise dose homogeneity and content uniformity (Sjöholm et al., 2020; Aina et al., 2025). Moreover, factors such as weighing errors during feedstock preparation, the presence of air bubbles in the paste, and paste leakage during printing can affect drug content in the final product, thereby compromising dose personalization (Goh et al., 2021).

Furthermore, current research on the development of immediate-release dosage forms often relies on highly water-soluble excipients or large amounts of disintegrants (Conceição et al., 2019; Aina et al., 2025). Moreover, despite the prevalence of poorly water-soluble drug

candidates in pharmaceutical development, most 3D printing studies have focused on water-based formulations, which can accelerate the degradation of hydrolytically sensitive drugs, compromising shelf life and efficacy (Johannesson et al., 2023a,b). The presence of water also increases the risk of microbial growth during formulation preparation, storage, and handling (Aina et al., 2024b; Elbl et al., 2020; Mathiyalagan et al., 2023; Sjöholm et al., 2022b). While aseptic processing, antimicrobial excipients, and single-use, pre-sterilized cartridges can help mitigate contamination risks, maintaining stability and sterility remains a concern. Solutions such as refrigeration, desiccation, or post-processing techniques like freeze-drying and oven drying may be necessary to enhance stability (Khaled et al., 2018a; Mathiyalagan et al., 2023; Khaled et al., 2015b; Kavimughil et al., 2022). However, further research is needed to define optimal storage conditions and assess long-term stability to ensure the reliability of 3D-printed pharmaceuticals (Sjöholm and Sandler, 2019).

Moreover, the use of water or organic solvents for excipient solubilization may necessitate post-printing steps, and the amount of organic solvent required for solubilization may exceed safe limits for human use (Denis et al., 2024). Post-processing treatments also often require long durations and can compromise the quality of the printed object, leading to issues such as shrinkage (Siyawamwaya et al., 2019; Wang et al., 2023). Also, SSE 3DP has relatively low spatial resolution compared to other 3D printing techniques, likely due to its reliance on nozzle-based layer-by-layer construction (Khaled et al., 2018b). This limitation can result in visible surface imperfections, affecting the overall quality of the printed dosage form. Despite this, research suggests that neither shrinkage nor printing resolution significantly affects the overall quality or drug release characteristics of the final product and in some cases, shrinkage may even enhance swallowability (Goh et al., 2021). Nevertheless, challenges remain in maintaining consistent and reproducible material flow during the start-stop-start phases of the print head, as interruptions in flow can lead to dosage inaccuracies, especially in formulations requiring precise dosing (Seoane-Viaño et al., 2021a; de Oliveira et al., 2022). The absence of standardized calibration models for accurate dose dispensing further complicates the clinical implementation of SSE 3DP, making it difficult to achieve consistent and reliable dose accuracy (El Aita et al., 2020).

Furthermore, SSE is inherently slower than traditional pharmaceutical manufacturing methods primarily due to its layer-by-layer deposition process (Rahman and Quodbach, 2021). This process, while precise, limits the ability to produce large quantities in a short time
frame, which is a significant barrier to scaling up production (Milliken et al., 2024). To increase throughput, advanced multi-nozzle systems or parallelized setups are needed, but these add significant complexity to equipment design, introducing new challenges in terms of consistency, reliability, and cost (Tracy et al., 2023). Furthermore, the extrusion process itself demands careful control over flow rates, extrusion speed, and layer deposition, all of which can slow down production when scaling up (Tracy et al., 2023; Guidetti et al., 2024). Industrial-scale SSE also faces the challenge of integrating with existing pharmaceutical workflows, such as blending, granulation, and packaging. This integration requires either significant modifications to current infrastructure or the development of hybrid systems that combine traditional manufacturing techniques with additive technologies (Domokos et al., 2021). Such a transition involves not only technical challenges but also potential disruptions to established processes, making it a complex and resource-intensive undertaking.

### 5.3. Opportunity (Outlook)

One of the most significant opportunities for SSE 3D printing is its scalability for industrial production. While traditionally considered a small-scale manufacturing technique, SSE has evolved to support high-throughput production. Companies such as Laxxon Medical have pioneered SSE-based technologies capable of rivalling conventional pharmaceutical manufacturing in both efficiency and output (Tracy et al., 2023). Their Screen Printing Innovative Drug (SPID®) Technology allows for the precise deposition of drug-loaded pastes through distinct screen openings onto a substrate, enabling large-scale pharmaceutical production with a reported capacity of up to 1.5 million units per day (Tracy et al., 2023; Moldenhauer et al., 2021; Medical, 2022; Enke et al., 2023). This advancement positions SSE as a viable alternative to traditional tableting methods, offering increased flexibility in drug formulation and production.

Beyond its potential for large-scale production, SSE's most transformative opportunity lies in its ability to facilitate on-demand, decentralized manufacturing, which can increase flexibility, reduce supply chain dependencies, and improve access to medications in remote locations (Díaz-Torres et al., 2022; Abdella et al., 2021; Seoane-Viaño et al., 2021b). Unlike centralized pharmaceutical production, which depends on extensive logistics and distribution networks, small-scale SSE 3D printers can be deployed in pharmacies, hospitals, long-term care facilities, military field hospitals, rural clinics, space, or even patient homes (Seoane-Viaño et al., 2021b). This approach is especially valuable where limited access to essential medications and frequent shortages make timely, customized medicines crucial (Englezos et al., 2023; Aronson et al., 2023b,a).

SSE 3DP offers unprecedented opportunities for personalized medicine by addressing the limitations of traditional pharmaceutical manufacturing, which is constrained by fixed dosages and formulations (Englezos et al., 2023; Seoane-Viaño et al., 2021a). By enabling on-demand production and real-time dose adjustments based on patient response, SSE not only minimizes medication waste but also enhances treatment personalization. This capability is particularly advantageous in paediatric, geriatric, and veterinary medicine, where precise dosing and alternative formulations—such as chewable tablets, gummies, or rapidly disintegrating dosage forms—can significantly enhance treatment adherence (Sjöholm et al., 2022b,a; Gkaragkounis and Fatouros, 2023; Suárez-González et al., 2024). Furthermore, SSE provides precise control over drug release kinetics, enabling advanced delivery mechanisms such as pulsatile and zero-order release systems, which are critical for managing complex medical conditions (Yan et al., 2024; Milliken et al., 2024).

Alongside industrial adoption, material innovation plays a crucial role in SSE's advancement. Novel polymers and excipients are expanding the range of printable materials, improving drug stability, bioavailability, and controlled release. Companies such as CuirifyLabs and FabRx are developing GMP-compliant 3D printers and

pre-formulated excipient bases, streamlining pharmaceutical production workflows (CurifyLabs, 2024, 2023; FABRX, 2025). Moreover, the well-established use of gels in pharmaceuticals reinforces SSE's potential for drug development (Smagina et al., 2023; Bahú et al., 2022; Mohd Shahrizan et al., 2022). However, developing universal feedstocks capable of accommodating diverse APIs could further optimize formulation processes and reduce the current trial and error approach (Elbadawi et al., 2020b). Additionally, the integration of predictive modelling tools will enhance formulation efficiency, reducing material testing demands and accelerating the drug development pipeline (Elbadawi et al., 2024).

Advancements in Quality-by-Design (QbD) principles and Process Analytical Technology (PAT) in SSE manufacturing are improving dose accuracy, strengthening quality control, and enabling real-time monitoring. In-line quality control techniques, such as spectroscopy, enable non-destructive, continuous assessments of feedstock printability, drug content, and distribution (Johannesson et al., 2023a). Additionally, inline analytical balances enhance dose uniformity through real-time weight monitoring, minimizing variability in printed drug products (Bendicho-Lavilla et al., 2024; Korelc et al., 2024; O'Reilly et al., 2021). The integration of machine learning (ML) algorithms with these real-time monitoring tools further optimizes manufacturing processes, enabling dynamic adjustments to maintain consistent product quality (O'Reilly et al., 2021; Jiang et al., 2022; Rojek et al., 2025). Furthermore, the automation of SSE systems will reduce human error, increase manufacturing throughput, and further streamline large-scale production (Díaz-Torres et al., 2022; Bendicho-Lavilla et al., 2024). Additional innovations, such as QR codes and data matrices on dosage forms, could enhance traceability and product safety (Seoane-Viaño et al., 2021a).

However, for these advancements to achieve widespread adoption, regulatory progress is essential. Agencies like the FDA and EMA are actively working to establish Good Manufacturing Practice (GMP)—compliant guidelines for 3D-printed pharmaceuticals, ensuring standardized quality control and accelerating industry acceptance (Eduardo et al., 2021). Notably, in the UK, the Medicines and Healthcare products Regulatory Agency (MHRA) has established a new regulatory framework to support the decentralized production of medicines, including 3D-printed drugs, at the point-of-care. Following strong stakeholder support in a 2021 consultation (MHRA, 2021), a Statutory Instrument under the Medicines and Medical Devices Act 2021 has been introduced (MHRA, 2023; U.K. Statutory Instruments, 2025). The legislation includes a six-month implementation period after the completion of Parliamentary processes and is expected to come into effect by Summer 2025 (U.K. Statutory Instruments, 2025; MHRA, 2024). As the regulatory landscape for 3D-printed drugs continues to evolve, standardized quality assurance protocols ensuring the safety, efficacy, and consistency of SSE 3D-printed drug products will become more widely available, thereby facilitating their integration into mainstream pharmaceutical manufacturing.

### 5.4. Threats (Barriers)

SSE 3D printing offers significant potential for pharmaceutical manufacturing, yet several external barriers hinder its widespread adoption. One such barrier is scaling up production volumes to meet demand. While Spritam® remains the only 3D-printed drug approved for commercialization, its manufacturing process was specifically optimized for large-scale production (Seoane-Viaño et al., 2021a). In contrast, achieving sufficient production capacity using other 3D printing techniques, including SSE, remains a critical issue. To prevent production disruptions, manufacturers may need to deploy multiple printers as well as establish facilities in various locations (Tracy et al., 2023). Although 3D printing allows for the creation of customized drug release profiles and pharmacokinetics that traditional methods cannot achieve, manufacturers will likely prioritize minimizing per-tablet production
costs to maximize profitability (Tracy et al., 2023; Andreadis et al., 2022). This cost-driven approach by pharmaceutical manufacturers could ultimately restrict the full potential of 3D printing in delivering truly personalized medications.

In addition to scalability concerns, intellectual property protection presents another major challenge. The ability of other manufacturers to mass-produce 3D-printed drugs increases the risk of unauthorized reproduction and patent circumvention, potentially undermining pharmaceutical innovation and discouraging investment in novel drug formulations (Araújo et al., 2019; Elkasabgy et al., 2020; Simon et al., 2024). Furthermore, compliance with Good Manufacturing Practice (GMP) standards adds another layer of complexity. To ensure product quality and consistency, 3D printers and their associated software must meet GMP requirements; however, only a limited number of SSE 3D printers currently comply, including CraftMake™ by Craft Health (Craft Health, 2023), M3DIMAKER by FabRx (FABRX, 2025), MED-U Modular by MB Therapeutics in collaboration with Lynxter (M.B. Therapeutics, 2025), and DoseRx1 by Doser (Doser, 2025). The scarcity of GMP-compliant printers restricts scalability, while securing GMP-certified materials further complicates manufacturing (Smith et al., 2018).

Regulatory classification further complicates the path to commercialization. A key issue is whether 3D-printed drugs will be regulated as compounded medicines or conventional pharmaceutical products. Compounded drugs are subject to stricter oversight due to past safety concerns, such as the 2012 fungal meningitis outbreak (Alhnan et al., 2016; Shehab et al., 2018; CDC, 2019). If 3D-printed pharmaceuticals fall under this category, they could face additional regulatory burdens, further complicating production and distribution. At the same time, it is unclear which components—such as the pharmaceutical feedstock (ink), the 3D printer, or the final drug product—will be subject to regulation, complicating the approval process and slowing the integration of 3D printing into pharmaceutical manufacturing. Moreover, traditional pharmacopoeia tests, designed for conventionally manufactured tablets, may not be directly applicable to 3D-printed drugs, requiring the development of new or modified testing methods (Lafeber et al., 2021). Without standardized protocols, ensuring the safety, efficacy, and quality of 3D-printed pharmaceuticals becomes increasingly difficult.

All these challenges are further complicated by the intricate ecosystem in which SSE 3D printing operates, encompassing pharmaceutical companies, contract manufacturers, and compounding pharmacies. This complex network creates multiple ambiguities, particularly in terms of legal and regulatory compliance, that must be resolved to ensure the safety, efficacy, and quality of 3D-printed pharmaceuticals. Addressing these issues is crucial for unlocking the full potential of SSE 3D printing.

## 6. Conclusion

This review thoroughly examined semi-solid extrusion (SSE) 3D printing as a tool for fabricating oral drug formulations, elucidating its fundamental principles, distinctive characteristics, and current applications through a synthesis of existing literature. It highlights SSE's unique ability to load thermosensitive drugs and produce complex as well as customizable dosage forms with precise control over drug release kinetics, positioning it as a promising tool for enhancing therapeutic efficacy and patient adherence. The review discusses SSE's versatility in creating a wide range of dosage forms, including chewable, immediate-release, and sustained-release tablets. Also, it explores the innovative use of SSE to tailor drug release profiles through manipulation of tablet geometry and composition, demonstrating its potential to revolutionize personalized medicine and improve patient outcomes. Furthermore, the paper delves into the characterization methods crucial for selecting materials with optimal printability and performance, emphasizing the importance of rheological properties and printing parameters. It addresses the technical challenges, such as the optimization

of the printing process and the requirement for solvent evaporation, and the regulatory hurdles that currently impede SSE's commercialization. The review also highlights pioneering research efforts aimed at overcoming these obstacles, including advancements in formulation studies, process optimization, and the development of quality control frameworks tailored to these 3D-printed pharmaceuticals. By presenting significant achievements in SSE's application to oral drug delivery, this review not only underscores the technology's current capabilities but also envisions its future potential in personalized medicine. It suggests that SSE could revolutionize the production of patient-specific medications, allowing for on-demand fabrication of tailored therapies with precise dosages and release profiles. This synthesis aims to inform and inspire researchers, clinicians, and industry professionals, providing a comprehensive reference to guide the ongoing development and adoption of SSE for next-generation oral drug formulations, ultimately paving the way for more effective and individualized patient care.

## CRediT authorship contribution statement

**Morenikeji Aina:** Writing – original draft, Visualization, Methodology, Investigation, Formal analysis, Conceptualization. **Fabien Baillon:** Supervision, Software. **Romain Sescousse:** Writing – review & editing, Supervision, Resources. **Noelia M. Sanchez-Ballester:** Writing – review & editing, Supervision. **Sylvie Begu:** Writing – original draft, Supervision, Project administration. **Ian Soulairi:** Writing – review & editing, Validation, Supervision, Methodology, Conceptualization. **Martial Sauceau:** Writing – review & editing, Validation, Supervision, Resources, Project administration, Methodology, Funding acquisition, Conceptualization.

## Declaration of competing interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Martial Sauceau reports financial support was provided by Occitanie Region. Martial Sauceau reports financial support was provided by French National Research Agency. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Acknowledgment

The authors are grateful to the Occitanie Region and ANR "Investissements d'Avenir" program, ANR-18-EURE-0021 project, for funding.

## Data availability

No data was used for the research described in the article.

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