Factors affecting response variables with emphasis on drug release and loading for optimization of liposomes

Abstract

Drug delivery through Liposomes has shown tremendous potential in terms of the therapeutic application of nanoparticles. There are several drug-loaded liposomal formulations approved for clinical use that help mitigate harmful effects of life-threatening diseases. Developments in the field of liposomal formulations and drug delivery have made it possible for clinicians and researchers to find therapeutic solutions for complicated medical conditions. A key aspect in the development of drug-loaded liposomes is a careful review of optimization techniques to improve the overall formulation stability and efficacy. Optimization studies help in improving/modulating the various properties of drug-loaded liposomes and are vital for the development of this class of delivery systems. A comprehensive overview of the various process variables and factors involved in the optimization of drug-loaded liposomes is presented in this review. The influence of different independent variables on drug release and loading properties with the application of a statistical experimental design is also explained in this article.

HIGHLIGHT POINTS

Periodically, liposomes have shown tremendous potential as drug carriers as they are multifunctional nanoparticles with a unique ability to deliver drugs and other therapeutic moieties to target sites in the body. The use of statistical experimental designs and optimization models to develop drug-loaded liposomes is considered the most effective step in formulation development. A careful consideration of various factors and variables in optimizing liposome formulations has been specifically described in this review article. Thorough understanding of different factors that affect drug loading and release in liposomes provides deeper insights in achieving a stable, efficacious drug formulation. There are several new aspects and concepts which need to be explored as part of formulation development and optimization of drug-loaded liposomes and this article hopes to shed light on some important aspects in this scientific journey.

Keywords:

• Nanoparticles
• liposomes
• optimization
• drug loading
• experimental design

Introduction to drug delivery through liposomes

Among the different types of nanoparticles for drug delivery, liposomes are the most developed and established clinically available drug delivery systems available clinically [1]. A typical liposome structure is depicted in a review of dual-functional drug liposomes for the treatment of drug-resistant cancers (Figure 1) [2].

Figure 1. General structure of Liposomes [2].

Liposomes are spherical vesicles comprising lipid bilayer shells surrounding aqueous interior cores that are spontaneously formed when amphiphilic lipids are dispersed in water [3]. Moreover, they are non-toxic, biocompatible, and biodegradable and have been approved by the Food and Drug Administration (FDA) for the delivery of various anticancer agents [4, 5]. Different types of liposomes exist based on their composition and applications such as conventional liposomes, charged liposomes, stealth stable liposomes, actively targeted liposomes, stimuli-responsive liposomes, and bubble liposomes [6]. Among various drug delivery systems, liposomes represent versatile and advanced Nano delivery systems for a wide range of biologically active compounds [7]. PEGylated liposomes are effective drug delivery vehicles because they facilitate high drug-loading capabilities, improved biocompatibility, and long-circulating properties, with improved stability [8, 9]. Various potent drugs have been incorporated into liposomes with remarkable clinical success [8, 10]. Some FDA-approved liposome formulations include Ambisome (amphotericin B), Dioxil (doxorubicin), and Marquibo (vincristine), thereby emphasizing the advantages of using liposomes as drug delivery systems [11].

Advantages of Liposomes over other nanoparticles [12, 13]

• Liposomes are known to increase drug efficacy and stability due to encapsulation in bilayer and aqueous compartments.

• They can encapsulate hydrophilic and hydrophobic drugs/moieties.

• Liposomes are non-toxic, flexible, biocompatible, completely biodegradable, and non-immunogenic for systemic and non-systemic administrations.

• Flexibility to couple with site-specific ligands to achieve active targeting.

• Commercially available clinically approved products for treating various disease conditions.

The entrapment of anticancer agents and delivery through liposomes is a promising strategy that has gained tremendous potential for the treatment of cancers [2]. Numerous studies have been conducted on the ability of liposomes to be loaded with single or multiple drugs [1] especially for the treatment of cancer. A study describing the formulation of gemcitabine-loaded thermosensitive liposomes for antitumor activity explained the feasibility of loading and improving the release of gemcitabine into tumour cells and emphasized the potential of liposomes as drug delivery vehicles [4]. Paclitaxel, a highly potent anticancer drug for breast and ovarian cancers, was delivered through liposomes to increase the total drug content in a stable formulation [14]. Doxorubicin (DOX), a widely used anticancer drug for prostate cancer is known for its severe side effects including tissue cytotoxicity and cardiotoxicity was formulated into a thermosensitive liposomal formulation [15]. The results showed that there was stable and controlled drug release from thermo-responsive liposomes with enhanced cell uptake owing to formulation modification and suitable release conditions [15]. Thus, liposomes with their successful and versatile abilities need to be explored as delivery systems for single and dual drug-loaded formulations.

Literature review of factors for optimization using statistical experimental design

Several studies have described the specific properties and applications of drug-loaded liposomes by controlling and modifying process parameters, methods of formulation, varying drug, and lipid contents, changing the volume of the aqueous phase during formulation, and modifying liposome surface for active or passive drug loading mechanisms [11, 16]. A general illustration showing liposome formation and structure capabilities can be seen in Figure 2 [17].

Figure 2. General formation and structural capabilities of liposomes [17].

These studies also explain the outcomes of formulation modifications that typically improve the pharmacokinetics and therapeutic potential of drug-loaded liposomes. The entire process of conducting trials or experiments with predicted variations to achieve the desired outcome is known as optimization of the formulation. The design of the experiment is an important and efficient step in identifying the important factors that affect the outcome variable [18]. A statistical experimental design allows the use of different statistical models to obtain the most competent results that require minimum experimental trials [18]. To establish significance, it is necessary to explain the impact of each factor on the outcome variable. Therefore, an overview of these factors and their impact on drug loading and release, along with other response variables, is provided in this review.

Optimization with phospholipid to cholesterol ratio

The composition of lipids in liposome formulations has been well characterized and documented. Phospholipids and cholesterol constitute the lipid compartments of liposomal structures [19]. The phospholipid: cholesterol ratio affects various properties of liposomes, including size, zeta potential, stability, drug loading, and drug release [19, 20]. It is observed that among various phospholipids available, phosphatidylcholine and phosphatidylethanolamine are most used in liposome preparation [21]. Cholesterol, which is also an important component of the lipid compartment, confers rigidity to the lipid bilayer, reduces the permeability of water-soluble molecules through the liposomal membrane, and imparts stability to the liposome [12, 21]. High drug-loading capacity and sustained drug release from liposomes are desirable and beneficial for the development of drug-loaded liposomes for clinical applications [22]. Several studies have reported the effect of optimizing phospholipid: cholesterol to improve (%) drug loading and stable drug release properties.

There have been various studies that have explained the effects of varying phospholipid: cholesterol ratio on liposome stability. A study explaining the formulation of liposomes using three phospholipids: DMPC, DPPC, DSPC with different molar ratios of cholesterol was evaluated for formulation stability, drug encapsulation and in vitro drug release [23]. The study tested encapsulation of Atenolol and Quinine in liposome formulations composed of 5 ratios of phospholipid: cholesterol (100%, 80:20, 70:30, 60:40 and 50:50). The study also utilized a simulation model to validate the testing of formulation stability, drug encapsulation and in vitro drug release. Results indicated that among the various ratio’s tested, the formulation with phospholipid: cholesterol of 70:30 showed the most stable and controlled drug release.

A study on docetaxel-loaded liposomes with respect to the effect of lipid composition and purification on drug encapsulation was performed [22]. Specifically, this study focused on the effect of varying the lipid composition on the drug loading and physicochemical properties of docetaxel-loaded liposomes [22]. Liposomes were prepared using a thin-film hydration method, followed by extrusion and size-exclusion chromatography to remove the free un encapsulated drug. Liposomes were prepared with different phospholipid and cholesterol compositions and variable drug-to-lipid ratios. The results showed that with increasing lipid content, the drug loading and encapsulation efficiency obtained was around 95%. When the lipid content was low and the drug content was high, there was a decrease in the drug loading and encapsulation of approximately 40%. The effect of lipid composition on drug-trapping efficiency and vesicle stability has been studied in dexamethasone-incorporated liposomes [24]. Liposomes were formulated with different amounts of phosphatidylcholine (PC) and distearoyloglycero-PC (DSPC), along with two different cholesterol: lipid ratios (2:1 and 1:1). The results showed that DSPC + Cholesterol liposomes with high cholesterol content had a stable displacement of dexamethasone compared to PC + Cholesterol liposomes. The combination of PC and DSPC liposomes with cholesterol caused steady release of dexamethasone over 48 h. Based on the results obtained in this study, lipid composition had a significant effect on drug incorporation efficiency. Additionally, the study also revealed that release kinetics of drugs can be modified by varying and optimizing lipid composition. The Co-encapsulation of quercetin and resveratrol into elastic liposomes was achieved by optimizing the drug-loaded formulation [25]. Dual-drug-loaded liposomes were prepared using the thin lipid film method. The experimental design of this study consistedof two parts. The first part included a two-level fractional factorial design to evaluate the effects of phospholipid and cholesterol concentrations and drug inclusion complexes on the size, polydispersity index, zeta potential, and (%) drug encapsulation efficiency of liposomes. The second part of the experimental design was a two-level full factorial design to study the effects of drug concentration and 1:1 co-encapsulation of quercetin and resveratrol on the same outcome variables as the first part. The results of the optimization studies showed that (%) encapsulation efficiency of 97% was achieved in the optimized formulation with a slightly negative zeta potential (–13.3 mV) and particle size of 149 nm with a polydispersity index of 0.3. Liposomes loaded with the antiviral agent nevirapine have been developed using three different lipid components: PLPC, POPE, and cholesterol [26]. Liposomes were prepared using a thin-film hydration technique followed by extrusion and freeze-drying. Drug loading was performed using different ratios of drug to phospholipid. A phospholipid: cholesterol ratio of 9:1 showed maximum drug encapsulation and was influenced by the presence of cholesterol in the formulation. High cholesterol levels resulted in low drug loading and encapsulation. Lornoxicam-loaded liposomes were prepared and optimized using a central composite design [27]. Drug-loaded liposomes were prepared using the thin-film hydration method with pH-induced vesiculation. Optimization was performed using a central composite design with phospholipid and cholesterol contents as the two independent variables. The dependent variables in this study were the drug entrapment efficiency and in vitro drug release. A polynomial equation was used to relate the effects of the independent variables on the outcome of this study. The results showed that the maximum entrapment of lornoxicam was 98% at 45% cholesterol and 80% phospholipid contents. The optimized formulation showed steady drug release for 8h with a particle size of 156 nm. Hence, variation in the phospholipid: cholesterol ratio is an important factor in liposome optimization studies.

Some studies have demonstrated the use of different drug loading or encapsulation techniques with different lipid compositions to assess the formulation with the best lipid composition and loading conditions. Carboplatin was loaded into preformed liposomes with different lipid compositions using a passive equilibration method [28]. This method is applicable to liposomes prepared with high (45 mol%) or low (<20 mol%) cholesterol levels. The main goal of this study was to assess the role of ethanol in stable liposome formation and the effect of cholesterol content on ethanol-induced destabilization of liposomes. The lipid compositions used to formulate liposomes in this study were DSPC:Chol (55:45 mol ratio), DSPC:DSPG:Chol (70:20:10 mol ratio), DSPC:DSPE-PEG₂₀₀₀ (95:5 mol ratio), and DSPC:Chol:DSPE-PEG₂₀₀₀ (65:30:5 mol ratio). All liposomes were prepared using the thin-film hydration and extrusion method. The loading efficiency of carboplatin was the highest in DSPC:DSPG:Chol (70:20:10 mol ratio) compared to other combinations in the presence of ethanol as an encapsulation enhancer. Quercetin-loaded liposomes were optimized with respect to variations in lipid composition to evaluate the in vitro cytotoxic effects of quercetin [29]. Liposomes were prepared using a thin-film hydration method, followed by sonication. Three combinations of lipids were used to prepare the liposomes. Liposomes containing 3% PEG had a phosphatidylcholine: cholesterol (67:30), liposomes with 5% PEG had a phosphatidylcholine: cholesterol (65:30) and liposomes with 7% PEG had a phosphatidylcholine: cholesterol (63:30). Results showed that among the three combinations of formulations, the highest drug encapsulation of 90% was observed in the formulation with 3% PEG and Phosphatidylcholine: Cholesterol (67:30). Thus, variations in the phospholipid: cholesterol ratio contributed to the improved drug loading and release ­characteristics. Therefore, optimization of the lipid ratio is essential for achieving improved drug-loading and release properties.

Effect of volume of aqueous phase on drug loading and release characteristics

In the preparation of liposomes, the aqueous phase usually consists of buffers of varying pH depending on the requirement and method of preparation. Some studies that indicated the importance of optimizing the volume of the aqueous phase for drug loading and release properties are explained in this section. The effect of phosphate buffer (pH 7.4) on in vitro drug release from pilocarpine nitrate-loaded liposomes was evaluated using the thin film hydration method [30]. Drug-loaded liposomes hydrated using phosphate buffer (pH 7.4) showed prolonged release for over 8 h. Additionally, optimization was performed for the volume of buffer (5 ml) used during hydration. Large volumes of buffer result in poor drug loading and subsequently affect release properties [30, 31]. A major reason for this has been attributed to the loading capacity of the vesicles. Specifically, the aqueous core as larger buffer volumes would dilute the drug concentration to be loaded and the overall loading would be limited due to breach of maximum vesicle loading capacity [32]. Another study explaining formulation of Ketorolac-loaded liposomes was optimized by considering the molar ratio of phospholipid: cholesterol, pH value of the hydration medium, volume of the aqueous hydration phase, and concentration of surfactant used [33]. Liposomes were prepared using a thin-film hydration method and their entrapment efficiency was evaluated. The results showed that among the tested formulations, the highest (%) entrapment efficiency was observed in the formulation with a hydration volume of 2.5 ml and pH of 4.2 at 50% cholesterol concentration. Thus, optimization of the aqueous phase volume could be an important factor in improving the drug release and loading properties of liposomes. The optimized volume would ensure that the accurate amount of drug is loaded in the individual compartment of liposomes thereby ensuring optimal drug release.

Optimization with lipid type and drug to lipid ratio

The drug: lipid ratio is an important characteristic in the formulation of liposomes that expresses the capacity of liposomes to accommodate the drug and can thereby play a key role in the optimization process of liposome formulation [34]. The selection of specific lipid types in liposome preparation is rationalized based on their impact on membrane fluidity, stability, and drug encapsulation efficiency. Lipids with varying acyl chain lengths, saturation levels, and headgroup properties offer diverse physicochemical characteristics, influencing liposome size, drug release kinetics, and biocompatibility [35, 36]. Tailoring lipid composition allows for fine-tuning liposome characteristics to optimize drug delivery efficacy and therapeutic outcomes. A novel study explaining the production of methotrexate (MTX) loaded liposomes by double flow focusing microfluidic device focused on optimizing encapsulation efficiency, drug loading and stability parameters of the formulated liposomes [37]. The formulation optimization was achieved by adjusting the operational and formulation parameters flow rate ratio (FRR), total flow rate (TFR), total lipid concentration and MTX concentration. Similar studies describing the variations in the drug:lipid ratio and their effects on drug loading and release characteristics are discussed below.

Clodronate, an active bisphosphonate compound used in the treatment of osteoporosis and several cancers, was loaded into liposomes using an optimized lipid to drug ratio (4:1) that gave maximum drug loading compared to the other ratios used in the study [38].

A study describing the formulation of primaquine- and chloroquine-loaded liposomes was performed using varying amounts of hydrogenated soy phosphatidylcholine (hspc), cholesterol and DSPE-PEG₂₀₀₀ [39]. Primaquine and chloroquine were the antimalarial drugs of choice. Liposomes were prepared using the thin-film hydration and extrusion method. Drug loading was determined using the transmembrane gradient method. In vitro drug release experiments were performed using dialysis. The results showed that the optimal drug-to-lipid ratios for loading primaquine and chloroquine were 1:10 and 1:3, respectively. Drug release data for dual-drug-loaded liposomes showed steady drug release of 63% for primaquine and 44% for chloroquine at 48 h. Another study describing the formulation of liposomal vincristine was performed by varying the drug-to-lipid ratio to optimize the rate of drug release [40]. Vincristine was loaded into the liposomes using the ionophore-loading technique. Results showed that the formulation with slowest rate of drug release at 24 h consisted of lipid: cholesterol (55:45 mol ratio) had a t_1/2 of 15.6h in vivo. The study also stated that this formulation has undergone advanced clinical trials for the treatment of non-Hodgkin’s, which shows the potential of considering phospholipid: cholesterol and drug: lipid ratios as factors for optimization.

Some studies have optimized liposome formulations using different types of lipids, varying amounts of cholesterol, and polyethylene glycol, along with different drug-to-lipid ratios. Topotecan-loaded PEGylated liposomes were prepared and characterized according to the thin-film hydration-extrusion method, and optimized using a factorial design [41]. This study used a fractional factorial experimental design. The independent variables included the type of lipid, molar ratio of phosphatidylglycerol to the main lipid, mole percentage of DSPE-PEG₂₀₀₀ and drug to lipid molar ratio. The results showed that the entrapment of hydrophilic drugs prepared by the thin-film hydration method is affected by lipid composition, the percentage of each lipid, and the drug-to-lipid molar ratio. Additionally, PEGylated liposomes showed prolonged drug release for over 48h. The study concluded by describing the role of the type of lipid, amount of DSPG, drug-to-lipid molar ratio, and interactions between these factors for improved drug encapsulation. Berberine-containing liposomes were optimized using a 3² full factorial design and evaluated for in vitro drug release [42]. Liposomes were prepared by thin-film hydration and were optimized using a full factorial design. The independent variables for this study were the drug-to-lipid and (SPC) ratios. The dependent variables were liposome size (nm) and EE (%). According to this study, a three-level two-factor design was effective in achieving the desired outcomes with a limited number of experiments. The results of the study were visually observed using a response surface (3D) and contour plots. Among all the prepared formulations, the formulation with drug: lipid (1:9.56) and SPC: Cholesterol (50:50) provided the optimum values for vesicle size and (%) entrapment efficiency. Finally, sustained in vitro drug release (24 h) was observed for the selected formulation.

Optimization using response surface methodology was performed to develop folic acid-conjugated liposomes for the delivery of 5-Fluorouracil in the treatment of colon cancer [43]. Liposomes were prepared using a thin-film hydration technique followed by size reduction using sonication to evaluate the encapsulation efficiency. A central composite design was used to evaluate the influence of the amounts of phospholipids (DPPC) and 5-FU on the encapsulation efficiency and particle size of the liposomes. The optimized formulation had an encapsulation efficiency of 39.71% and particle size of 174 nm. Liposomes co-encapsulated with cabazitaxel and silibinin for targeted delivery to CD44 receptors have been optimized to improving (%) drug loading [44]. Dual drug-loaded liposomes were prepared using the ethanol injection method and were characterized for particle size, entrapment efficiency, and cytotoxicity against prostate cancer cells. The independent variables were lipid weight, phase volume ratio, and concentration of hyaluronic acid (HA). Drug loading (%) was the dependent variable. The results showed that the optimized formulation had a particle size of < 100 nm with > 90% entrapment efficiency at 10% w/w drug loading. The influence of liposomal lipid composition on vesicle size, zeta potential and liposome induced dendritic cell maturation was evaluated using design of experiment approach in peptide-containing liposomes [45]. This study used four lipid types to assess the effect of lipid composition on the physicochemical properties of liposomes. A linear mixture model was used as a part of the statistical experimental design of this study. The values for every parameter were set, and a D-optimal design containing 18 runs and one central point was predicted to evaluate size, zeta potential, and dendritic cell maturation. The optimized formulation had a size of 181.1 ± 8.7 nm, polydispersity index of 0.12 ± 0.01 and zeta potential 30.3 ± 6.2. Thus, the experimental design used in this study helped predict the optimized formulation with respect to the outcome variable. Finally, a besifloxacin hydrochloride-loaded liposomal gel was prepared and optimized using a 3² full factorial design [46]. Drug-loaded liposomes were prepared using a thin-film hydration technique and optimized with two independent variables: soy lecithin-to-cholesterol ratio and lipid-to-drug ratio. The outcome variables were entrapment efficiency, drug loading, and particle size. As seen earlier, a quadratic polynomial equation helps predict the relationship between independent and outcome variables. The optimized formulation had particle size of 436.8 ± 23.4 nm; (%) drug loading of 10.84 ± 0.46% and encapsulation efficiency of 41.01 ± 1.22%. Thus, the use of statistical experimental designs for the optimization of liposome formulations is useful for the development of stable and effective formulations for transition into clinical practice.

Studies with optimization of process parameters for improved drug release, loading and entrapment efficiencies

Some formulation studies have used process parameters/steps for liposome optimization.

The preparation and optimization of quercetin-loaded liposomes evaluated the effect of the temperature of the water bath and rotation speed of the rotary evaporator on (%) encapsulation efficiency (%), drug release, and mean particle size [47]. Liposomes were prepared using a thin-film hydration method and optimized using response surface methodology. Optimization results showed that a rotational speed of 75 rpm and a water bath temperature of 46 °C yielded the best particle size (146 nm), (%) encapsulation efficiency (86.5%), and in vitro drug release of 75.09% at 24 h. Similarly, the preparation of liposomes containing hydroxytyrosol (HT) for evaluation of antioxidant activity was optimized using response surface methodology [48]. The factors used for optimization were temperature, phospholipid: cholesterol ratio, Tween 80 volume, and HT mass. Liposomes were prepared using the film dispersion method. This study describes the stability problems associated with hydroxytyrosol and the need to improve its encapsulation efficiency in liposomes. Preliminary data from this study showed that among the four factors, Tween 80 volume had no effect on the encapsulation efficiency of HT. Hence, the remaining three factors were used to optimize the formulation. The results showed that the formulation with phospholipid: cholesterol ratio of 4.5:1, HT mass of 5 mg, and water bath temperature of 63 °C had the highest EE (%). Moreover, HT liposomes had better stability and sustained in vitro release than free HT. Liposomes containing madecassoside were prepared and optimized using the response surface methodology to evaluate in vitro dermal permeation [49]. The liposomes were prepared using a two-step emulsification procedure. The factors used for optimization were the concentration of madecassoside (mg/mL), the ratio of egg yolk lecithin to cholesterol (w/w), and the stirring speed (rpm). The statistical design predicted 15 experimental runs that were part of the central composite design. A second-order polynomial equation was used to describe the effect of each factor on the outcome variable. The results showed that among the three factors, the ratio of egg yolk lecithin to cholesterol and the concentration of madecassoside were significant in achieving high drug-loading efficiency and sustained release rate of the drug. Doxycycline-, albendazole-, and diethylcarbamazepine-loaded solid lipid nanoparticles were prepared and optimized to evaluate the effects of independent variables on the size, polydispersity index, zeta potential, and encapsulation efficiency [50]. Dox-loaded liposomes were prepared using a hot emulsification-ultrasonication method. Albendazole- and diethylcarbamazepine-loaded liposomes were prepared using a double emulsion technique. Different lipids, stabilizers, and surfactants have been screened for liposome preparation. The particle size and encapsulation efficiency of the liposomes were measured. Based on the results obtained from the screening studies, glycerol monostearate and Tween 80 were used in the optimization process with a central composite design. The measured values for both dependent variables were very close to the predicted values from the statistical design, indicating the accuracy of the design of the experiment. The liposomal formulation of the cytotoxic agent capecitabine was surface-modified with a tumour-homing peptide (THP) to achieve site-specific delivery to breast cancer cells [51]. The formulation was optimized using a central composite design with three independent variables: amount of THP-cholesterol conjugate, amount of capecitabine, and sonication time (min). The dependent variables were particle size and encapsulation efficiency. The predicted values of the adapted design had a particle size of 114.036 nm and an encapsulation efficiency of 80.87%, which were very close to the measured values obtained in this study. Depending on the desired outcome, variations in process parameters, along with formulation content, could be beneficial in the development of drug-loaded liposomes.

Studies with multiple factors for optimization of liposomes

Multiple studies on liposome formulations have demonstrated the use of three or more factors for optimization. The development and optimization of G-1 polymeric nanoliposomes were performed using different volumes of T-80 solution, stir bar sizes, surfactant types, and sonication regimes [52]. The effects of each of these independent variables on the size, poly­dispersity, and zeta potential of the nanoparticles were eva­luated. Similarly, a study describing the development of co-encapsulating curcumin and doxorubicin liposomes selected four factors as independent variables to optimize the formulation for evaluating anticancer effects [53]. The four factors chosen for optimization were lipid concentration, drug concentration, buffer pH, and the phospholipid: cholesterol ratio. This study utilized variations in these factors to obtain liposomes with predefined specifications by running a set of experiments predicted by the statistical experimental design. The quality-by-design approach of this study was successful in identifying the factors that significantly contributed to the outcome variable. Optimization of docetaxel loading conditions in liposomes was studied using variable cholesterol content and different phospholipids to develop stable formulations with high encapsulation efficiency [54]. There were two sets of three formulations, each with variations in phospholipid and cholesterol content, loaded using active and passive loading methods. For both the active and passive loading sets, formulation with HSPC/mPEG2000-DSPE/DSPG/Chol (85/5/5/10) showed the highest encapsulation efficiency and a steady rate of drug release at 72h. The drug loading of paclitaxel-long circulating liposomes was optimized to improve the physical stability of the formulated liposomes by varying process parameters, such as the number of extrusion cycles, drug-lipid ratio, and total lipid and cholesterol content [55]. The goal of this study was to optimize the liposome formulation by testing the effect of variations in process parameters and drug-lipid content on (%) drug loading. Paclitaxel-loaded liposomes were prepared using the thin-film hydration-extrusion method and were characterized for particle size and morphology. The results showed that an increase in total phospholipid content caused an increase in the amount of paclitaxel in the formulation. However, formulations with a high total phospholipid content reduced drug entrapment. Cholesterol improved the overall stability of liposomes and a subsequent decrease in cholesterol content caused an increase in paclitaxel loading. Different drugs and lipids were tested to increase drug-loading capacity. Maximum drug loading was observed at a drug: lipid ratio of 1:30, with poor formulation stability. The optimum stability was observed at a drug: lipid ratio of 1:60. Finally, 10 extrusion cycles were used to prepare the liposomes. Liposomes containing methotrexate for enhanced skin permeation were optimized using the following factors: lipid: drug ratio, proportion of lipids used, and concentration of polymer [56]. Liposomes were prepared using a thin-film hydration method and were optimized using the Box-Behnken design. The dependent variables were the particle size, entrapment efficiency, and transdermal flux. This study utilized a three-factor, three-level Box-Behnken statistical design experiment involving 15 trials. The results showed that the optimized formulation had a drug: lipid ratio of 1:6, the proportion of lipids used was PC: OA:LAB (9:1:1), and the polymer concentration was 1.5%. Vancomycin-loaded liposomes have been characterized and optimized to improve encapsulation efficiency [57]. Liposomes were prepared using the reverse-phase evaporation-rehydration method. Optimization studies included the ratio of cholesterol to lecithin, the ratio of drug to lipid (w/w), the ratio of the water phase to the oil phase, and the hydration temperature as independent variables. Encapsulation efficiency was selected as the dependent variable. The orthogonal experimental design used in this study predicted nine formulations as a part of the screening process. The formulation with the highest EE (%) was selected as the optimized formulation. Additionally, the in vitro release of vancomycin was sustained for 48 h. Amphotericin B-loaded liposomes have been prepared, characterized, and optimized for ocular drug delivery [58]. Drug-loaded liposomes were prepared by hot-melt emulsification, followed by high-pressure homogenization. Liposome optimization was performed using the Box-Behnken design. The independent variables chosen for the study were the amount of amphotericin B, castor oil content, amount of mPEG-2k-DSPE, and the number of high-pressure homogenization cycles. The response variables were the particle size, zeta potential, PDI, entrapment efficiency, and loading efficiency. Results showed that the optimized formulation was prepared with 30 homogenization cycles with particle size 218 ± 5 nm; PDI 0.3 ± 0.02; (%) drug loading 4.6 ± 0.1% w/w and entrapment efficiency 92.7 ± 2.5% w/w. The use of statistical experimental design has indeed improved the optimization of liposomal formulations and is therefore described in the articles cited in this review.

Optimization of drug-loaded liposomes using various statistical experimental designs

The optimization of drug-loaded liposome formulations is a critical process in pharmaceutical development, requiring precise control over various parameters to achieve the desired therapeutic effect, stability, and safety [13, 59]. Statistical experimental designs play a vital role in this optimization process, allowing researchers to systematically study the effects of multiple factors and their interactions on the formulation’s performance [59]. A short description of various statistical experimental designs commonly used in drug formulation development along with the advantages of employing statistical models is as follows [18, 60]:

• Factorial Design:

  Factorial designs are used to evaluate the effects of two or more factors simultaneously. This design allows for the investigation of the individual effects of each factor and their interactions on the outcome, such as particle size, encapsulation efficiency, or drug release rate.

• Response Surface Methodology (RSM)

  RSM is a collection of statistical techniques used for modelling and analysing problems in which a response of interest is influenced by several variables. It’s particularly useful for optimizing the formulation process by identifying the optimal levels of factors for the desired response.

• Box-Behnken Design (BBD)

  BBD is a type of response surface methodology that requires fewer experimental runs than full factorial designs. It’s used for exploring quadratic response surfaces and constructing second-order polynomial models without involving full factorial combinations.

• Central Composite Design (CCD)

CCD is another approach within RSM, commonly used for fitting a quadratic surface. It helps in understanding the relationship between the process variables and the responses for optimization.

Based on the above description some advantages of using statistical models in liposome formulation studies are as follows [18, 60]:

Efficiency

Statistical models enable researchers to conduct fewer experiments by efficiently exploring the effects of multiple variables and their interactions.

Predictive power

They provide predictive insights into how changes in formulation parameters can affect performance outcomes, allowing for targeted improvements.

Optimization

Facilitate the identification of optimal formulation conditions for achieving the best performance characteristics of the liposome formulation.

Risk reduction

By understanding the formulation space better, statistical models help in minimizing the risk of failure in later stages of development.

In conclusion, the use of statistical experimental designs in the optimization of drug-loaded liposome formulations enhances the efficiency and effectiveness of the development process, leading to better-designed drug delivery systems with optimal performance characteristics [18, 60].

Challenges observed in optimization of liposomes for drug delivery

During the optimization of liposomes for drug delivery, researchers encounter several challenges that can impact the efficacy and translational potential of these formulations. These challenges include:

Biological stability

Liposomes may undergo destabilization upon interaction with biological fluids, leading to premature drug release or aggregation. Strategies to enhance biological stability involve surface modification or incorporation of stabilizing agents to mitigate these effects [61].

Controlled drug release

Achieving controlled and sustained drug release from liposomes poses a significant challenge. Factors such as lipid composition, size, and surface properties influence drug release kinetics. Optimization strategies focus on tailoring these parameters to achieve the desired release profile [62].

Scale-up and manufacturing challenges

Translating liposome formulations from laboratory-scale to industrial production presents challenges related to reproducibility, scalability, and cost-effectiveness. Development of scalable manufacturing processes and optimization of formulation parameters are essential for successful scale-up [62].

Targeting and specificity

While liposomes offer the potential for targeted drug delivery, achieving selective accumulation at the desired site remains challenging. Strategies such as surface modification with targeting ligands or stimuli-responsive formulations aim to improve targeting efficacy [63, 64, 65].

Biocompatibility and immunogenicity

Liposomal formulations must demonstrate biocompatibility and minimal immunogenicity to ensure safety and tolerability. Lipid composition, surface charge, and size can influence interactions with the immune system. Optimization efforts focus on minimizing adverse immune responses while maintaining therapeutic efficacy [61, 66, 67].

Addressing these challenges requires a multidisciplinary approach integrating expertise in chemistry, materials science, pharmacology, and engineering to design liposomal formulations with optimal drug delivery properties.

Summary on factors for consideration in optimization of liposomes

In optimizing liposomal drug loading and release, several key factors play pivotal roles. Among these factors, the phospholipid to cholesterol ratio, drug to lipid ratio, type of lipid utilized in liposome formulation, and the volume of the aqueous phase during the hydration of the lipid film stand out as particularly influential [61, 62]. The phospholipid to cholesterol ratio is crucial as it directly impacts the structural integrity and fluidity of the liposomal membrane, affecting drug encapsulation efficiency and release kinetics [62, 63]. Likewise, the drug to lipid ratio significantly influences drug loading capacity within the liposomes, with higher ratios correlating with increased drug encapsulation. The choice of lipid type dictates the physicochemical properties of the liposomes, thereby influencing drug loading, release profile, and stability. Additionally, the volume of the aqueous phase during lipid film hydration affects the size, homogeneity, and encapsulation efficiency of the resultant liposomes. While each of these factors contributes uniquely to liposomal drug delivery optimization, their collective interplay underscores the complexity involved in achieving desired drug loading and release characteristics influential [61–63].

Recent advancements in the development of optimized liposomes

There have been significant advancements in developing optimized drug-loaded liposomes for clinical applications. A crucial study describing the liposome delivery of CRISPR/cas9 was able to inhibit HPV (Human Papillomavirus) inducing autophagy and cell death related immune activation in treatment of HPV infection-associated cervical cancer [68]. The study explained how the combination of HPV-targeting guide RNA–liposomes with immune inhibitors and death-1 antibodies produced highly effective antitumor effects especially in treatment of cervical cancer. The development of Nucleic acid drug delivery through liposomes is expanding exponentially as there are many potential targets and therapies designed for application in preclinical and clinical stages [69]. The FDA approved drug ONPATTRO^® is used clinically for the treatment of hereditary transthyretin-mediated amyloidosis (hATTR amyloidosis) thereby proving the effectiveness of RNA-based therapeutics [69]. A summary of the current state of nucleic acid based liposomal drugs can be seen in Table 1 [69].

Table 1. Studies involving nucleic acids-loaded liposomes in various clinical stages.

Study No.	Status	Study title	Target Condition	Phase	Study reference
1	Recruiting	A Study of RNA-lipid Particle (RNA-LP) Vaccines	Adult Glioblastoma	Phase I	NCT04573140
2	Recruiting	mRNA liposomal Vaccine in Combination with (Neo-)Adjuvant Chemotherapy (OLIVIA)	Ovarian Cancer	Phase I	NCT04163094
3	Active	EphA2 siRNA in Treating Advanced or Recurrent Solid tumours	Advanced Malignant Solid Neoplasm	Phase I	NCT01591356
4	Completed	Study to determine maximum tolerated dose of LErafAON Linked with Radiotherapy	Neoplasms	Phase I	NCT00024648
5	Completed	Study with Atu027 in Patients with Advanced Solid Cancer	Advanced Solid Tumours	Phase I	NCT00938574
6	Completed	Study of Gene Therapy for Cystic Fibrosis	Cystic Fibrosis	Phase I	NCT00004471
7	Completed	Interleukin Gene or Methotrexate in Treating Patients with Recurrent or Refractory Stage III and IV Head and Neck Cancer	Head and Neck Cancer	Phase II	NCT00006033
8	Completed	Phase I Study of IV DOTAP: CHOL-Fus1 in NSCLC	Lung Cancer	Phase I	NCT00059605
9	Recruiting	BP1001 in Pattern with Venetoclax Plus Decitabine in AML	Acute Myeloid Leukaemia (AML)	Phase II	NCT02781883
10	Completed	BP1001 (L-Grb-2 Antisense Oligonucleotide) in CML, AML, ALL & MDS	CML, AML, ALL & MDS	Phase I	NCT01159028
11	Active	Cancer Vaccine to treat Advanced Melanoma (Lipo-MERIT)	Melanoma	Phase I	NCT02410733
12	Recruiting	Autogene Cevumeran (RO7198457) as a Single Agent and in Sequence with Atezolizumab in Participants with Locally Advanced or Metastatic Tumours	Solid Cancers	Phase I	NCT03289962
15	Completed	Gene Therapy in CF Patients	Cystic Fibrosis	Phase II	NCT016211867

Conclusion

Liposomes have shown potential as drug carriers for the treatment of various complex diseases. These nanocarriers are biocompatible and can help mitigate the side effects of conventional therapies. Its ability to encapsulate multiple drugs and diagnostic agents has been demonstrated in various clinically approved formulations. The studies discussed in this review clearly demonstrated the advantages of optimizing drug-loaded liposomes. The goal of this review is to highlight the significance of selecting every individual factor for optimization, which will help researchers design the statistical experimental sections of their respective projects. The importance of selecting each factor and its influence on the outcome variable should be studied in detail to represent a validated approach for conducting optimization studies.

Author contributions

Dr. Shantanu Pande is the sole author of this review. This section certifies that Dr. Shantanu Pande (Sole Author) was responsible for the conception and design of this study. Similarly, the drafting, revision, and final approval of this article were performed by Dr. Shantanu Pande.

Acknowledgements

This paper is based on the thesis of Pande Shantanu. It has been published on the institutional website: https://www.proquest.com/docview/2586987897?parentSessionId=iEboRmyca4cqVFpW0HbvWiEDHKuqEvZrI1TQnGMOPJw%3D.

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Data availability statement

There is no new data related to this submission.

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.