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Review article
04 2022
:15;
103715
doi:
10.1016/j.arabjc.2022.103715

Enhanced oral bioavailability through nanotechnology in Saudi Arabia: A meta-analysis

 Faculty of Pharmacy, Middle East University, Amman, Jordan.
Received: , Accepted: ,
© The Author(s) 2022
Disclaimer:
This article was originally published by Elsevier and was migrated to Scientific Scholar after the change of Publisher.

Peer review under responsibility of King Saud University.

Abstract

Oral administration represents the most suitable mean among different means of administering drugs because it ensures high compliance by patients. Nevertheless, the lacking aqueoussolubility, as well as, inadequate metabolic/enzymatic stability of medicines are leading obstacles to successful drug administration by oral route. Among different systems, drug administration systems based on nanotechnology have the potential to surmount the problems associated with oral drug administration. Drug delivery systems based on nanotechnology offer an alternative to deliver antihypertensive agents with enhanced therapeutic effect and bioavailability. In this study, meta-analysis was utilized in combining data relating to oral bioavailability (area under plasma concentration time curve, AUC) enhancement through nanotechnology from multiple studies. Twenty-one studies of the total 37articles included in this study were from the kingdom of Saudi Arabia and were included in a specific meta-analysis. From the analysis conducted, the overall enhancement power of the nanotechnology based formulations on drug bioavailability was found to be 7.94% (95 %CI [5.809, 10.064]). Haven utilized comprehensive and recent data of the confirmed the enhancement of bioavailability using nanotechnology which for this study was grouped into five: solid lipid nanoparticles; polymer based nanoparticles; SNEEDS/Nanoemulsion; liposomes/proliposomes and; nanostructured lipid carriers. Furthermore, the meta-analysis, provided evidence of insignificant differences between APG Bio-SNEDDS and its free drug suspension (Apeginin, APG), though with relative bioavailabiilty of 1.91. Notwithstanding most of the treatment showed a substantial relative bioavailability.

Keywords

Nanoformulation
Nanoparticle
Nanotechnology
Oral bioavailability
Pharmacokinetic parameters
Saudi Arabia
1

1 Introduction

It is a common knowledge today that materials whose sizes are in the nanometer range have chemical, biological and physical properties from those which are not. This distinctive property of nanoparticlate materials has been studied widely for the possible use of nanotechnology in the field of media (Berardi and Bisharat, 2016). The utilization of nanotechnology for delivery of drugs is among the most promising as well as exciting application of this technology; nanotechnology mechanisms have the potentials to enhance the potency of drugs as well as efficiency of therapeutics given via various means of administration (Perrie, 2013). Nano technologies applied in delivery of drug consist of nano scale molecules or particles which are capable of improving the bioavailability of drugs. Molecular targeting is carried out through devices like nano-robots which are nano-engineered in order to maximize bioavailability both at definite areas in the body as well as over a period of time (Cavalcanti et al., 2008).

The most preferred and most frequently used route of administering drugs is the oral route: oral dosage types facilitate enhanced compliance of patients, are easy to receive and are less expensive than other dosage types. Over 70% of all drugs are given via oral route and they can either be in liquid forms (i.e. suspensions and solutions) or solid forms (i.e. capsules and tablets). It has been noted however, that “orally administered drugs, compared to those given via the parenteral route are not directly available in the systemic circulation to exert their therapeutic effect (McConnell and Basit, 2013; York, 2013). Instead, they must first transit through the gastro-intestinal (GI) tract and be absorbed before they reach the blood. Hence, the oral route for the delivery of drugs provides at best a delayed onset of action compared to the parenteral route or at worst it can be completely precluded for those drugs that cannot reach the blood”. The physical, biological and chemical relations of the medicine with the physiological parts of the GI tract determine whether or not as well as to what degree the drug can get to the blood circulation intact and carry out a complete effect.

According to Le, “orally administered drugs must pass through the intestinal wall and then the portal circulation to the liver; both are common sites of first-pass metabolism (metabolism that occurs before a drug reaches systemic circulation). Thus, many drugs may be metabolized before adequate plasma concentrations are reached. Low bioavailability is most common with oral dosage forms of poorly water-soluble, slowly absorbed drugs” (Le, 2020).

Low bioavailability generally results from inadequate time for absorption in the GI. Time may not be sufficient at the absorption site if the drug does not readily dissolve or is not able to do through the epithelial covering (if it is highly polar and ionized, for instance). Bioavailability may be low and highly variable in such instances.

Previous gastrointestinal surgery (like bariatric surgery), physical activities, age, genetic phenotype, sex, disorders (like mal-absorption syndromes and alchlorhydria) and stress can also affect bioavailability of drugs.

Bioavailability can also be reduced by chemical reactions that decrease absorption. Such reactions include hydrolysis by digestive enzymes or gastric acid (for example, penicillin and chloramphenicol palmitate hydrolysis), formation of a complex (for instance, polyvalent metal ions and tetracycline), other drugs absorption (example, cholestynamine and digoxin), metabolism by microflora in the lumen and conjugation in the wall of the intestine (example, sulfuconjugationof isoproterenol).

Oral administration represents the most suitable means among different means of administering drugs because it ensures high compliance by patients. Nevertheless, the lacking aqueous solubility as well as inadequate metabolic/enzymatic stability of medicines are leading obstacles to successful drug administration by oral route. There are many ways to improve hydrophobic drugs related problems (Bernkop-Schn¨urch, 2013; Zhang et al., 2013). Among different systems, drug administration systems based on nanotechnology have the potential to surmount the problems associated with oral drug administration (Sharma et al., 2016). Drug delivery systems based on nanotechnology offer an alternative to deliver antihypertensive agents with enhanced therapeutic effect and bioavailability (Prisant et al., 1992).

With the purpose of monitoring the presentprogress on the research on oral bioavailability and nanotechnology and finding out the application/capabilities of nano-technological approaches in enhancing the bioavailability of orally administered drugs, it is necessary to carry out a thorough investigation and analysis of related studies (compiled) on nanotechnology enhancement of oral bioavailability. In addition, the objective is to identify general patterns presented among results of related study, other relationships of interest, and possible sources of disagreement that may be revealed in course of multiple studies. Meta-analysis, a statistical technique which is suitable for this courseof “combining the findings from independent studies most often used to assess the clinical effectiveness of healthcare interventions” (Fong et al., 2016), was utilizedto analyze quantitatively, the related pharmacokinetic parameters compiled from multiple studies on enhanced oral bioavailability through nanotechnology and presented in this review.

Nanotechnologyhas been effectivelyutilized by previous studies in varying pharmaceutical formulations for oral bioavailability enhancement (Fong et al., 2016; Nasser et al., 2020; Fong et al., 2015; Jain, 2010; Singh and Lillard, 2009; Guan et al., 2011; Safari and Zarnegar, 2014; Khadka et al., 2014; Hetal et al., 2010; Berardi, 2016; Price and Patel, 2020; Anwar et al., 2011; Ma et al., 2015; Ipar et al., 2019; Suri et al., 2007; Agrawal et al., 2014; Moher et al., 2009). The aim of the current review was to provide quantitative answers to the questions on “how promising nanotechnologyis for bioavailability enhancement?”, “Whichtype of nanotechnology performs the best?” And “what are the most promising drug candidates from this review?” By performing a broad and systematic search of recent literature dating from the past 20 years (from 2000 to 2021) that reported nanotechnology for the enhancement of oral bioavailability of drugs and conducting a meta-analysis, the aforementioned questions have been dealt with and we foresee that the information in this study will be of importance to scientists who wish to implement nanotechnology in overcoming poor oral bioavailability.

2

2 Methods

2.1

2.1 Search strategy

This research followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analysis) guideline (Brakmane et al., 2012). Based on specified goals and eligibility criteria, we carried out a systematic literature search for all relevant studies up to July 2021 in Google Scholar (https://scholar.google.com), Pub Med (https://pubmed.ncbi.nlm.nih.gov), ResearchGate (https://www.researchgate.net) and Web of Science (http://www.webofknowledge.com) utililizing predefined keywords. Text words and phrase words were utilized. Also reference lists titles and full texts of studies on nanotechnology in oral bioavailability (Sharma et al., 2016; Nasser et al., 2020; Guan et al., 2011; Ma et al., 2015; Ipar et al., 2019; Suri et al., 2007; Agrawal et al., 2014; Moher et al., 2009; Xiaojun et al., 2007; Charoo et al., 2019; Arshad et al., 2021; Koo et al., 2005; Kumar, 2000; Higgins and Thompson, 2002; Yang et al., 2009; Gupta et al., 2020; Pandita et al., 2011; Li et al., 2012; Shah et al., 2006; Alsulays et al., 2019) in general and other related studies carried out in the kingdom of Saudi Arabia. Search terms used include: “biological availability”[MeSH Terms] OR bioavailability[Text Word]; “nanotechnology”[MeSH Terms] OR nanotechnology [Text Word], “enhance”, “nanoparticles”, “enhancement of oral bioavailability”, and ‘Enhanced Oral Bioavailability through Nanotechnology in Saudi Arabia’. The use of these terms ensured the inclusion of related studies pertaining to oral bioavailability and nanotechnology. To find out whether a study had fulfilled the eligibility requirements, one reviewer screen details and abstracts of all titles and manuscripts.

2.2

2.2 Inclusion and exclusion criteria

The title and abstracts of the various studies were screened so as to identify suitable studies on the association between oral bioavailability and nanotechnology. Preprints were excluded in the systematic review and meta-analysis, thus, only research articles published in peer-reviewed (refereed or scholarly) journals were searched.

Research papers considered eligible for assessment while screening, had to fulfill these criteria:

  1. Nanotechnology related formulation (nanoformulation).

  2. Nanotechnology was used as enhancement of oral bioavailability of drugs and/or solubility and permeability of drug.

  3. The intended route of delivery of the studied nanomedicine nanostructured polymer (such as nanoparticles, dendrimers, micelles and drug conjugates) was oral.

  4. Presence of pharmacokinetic (PK) parameters (relating to oral bioavailability) such as AUC, Cmax, Tmax or T1/2.

  5. PK parameters should be clearly stated either in table or text.

Duplicated studies and those not printed in the English or Arabic language were excluded. After studies that did notcontain original data (i.e research paper) nor provide information on nanotechnology, nano medicine, nano formulation, nano materials, oral bioavailability and enhancement of oral bioavailability, were further screened out.

2.3

2.3 Data extraction

Duplicated studies were sorted out with the aid of Zotero 5.0.96.2 ( http://www.zotero.org). The search results (literature) were screened and the eligible studies were selected after going through the titles, abstracts and full-texts.

2.4

2.4 Meta-analysis

Meta-analysis was carried out to reveal the overall enhancement of oralbioavailability of administered drugsthrough nanotechnology (experiment) as compared to actual drug suspension or solution (control). This is revealed by the pharmacokinetic parameters of the drugs, which are area under curve (AUC), maximum plasma concentration (Cmax), and time to reach maximum plasma concentration (Tmax). “Heterogeneity” was also measured as Meta-analysis brings togetherresult of different individual studies and presents a general conclusion (Yang et al., 2009). Hence, meta-analysis was carried out in this present study to assess the overall enhancement effect of oral bioavailability through nanotechnology across different publications.

The area under the curve (AUC) and the study sample size, mean and standard deviation (SD) were fed into an open source software funded by the Agency for Healthcare Research and Quality (AHRQ), OpenMetaAnalyst which is used for conducting meta-analysis and generate a forest plot. and to perform Meta analysis of the investigated studies and provide Forest plot.

A random effect model was utilized for this study as it takes into account the variability that exist between the studies. The “DerSimonian-Laird” was the random-effect method used. Also the heterogeneity was evaluated with the Q statistic, I2 and τ2 index. The Q statistic is the true statistical test for heterogeneity of the studies employed in this review and the degree of heterogeneity was indicated by I2 index. The study weights and forest plot (with mean ratio and confidence interval − 95 %CI estimates) wasconsideredin this study.

3

3 Result and discussion

3.1

3.1 Literature search

The search for relevant literatures pertaining to the context of this study gave 2,455 articles as seen in the identification phase of the PRISMA flow chart (Fig. 1). These were distributed across four database: PubMed (n = 539), Web of Science (n = 813) and ResearchGate (n = 611). Removing the duplicate documents (n = 108), those removed for other reasons such as not been relevant to the main subject and those not written in either English or Arabic (n = 72) left 2,275 items to be screened as seen in the screening phase in Fig. 1. Afterwards the selection was carried out by going through the titles and abstracts of this study to where irrelevant articles especially does not drug related, or other fields of studies were excluded (n = 1684). The full texts of reports sought for retrieval (n = 591) were further screenedbased on the exclusion criteria on full-text article excluded (n = 128) in the Fig. 1. The remaining reports assessed for eligibility were 463. Of these reports, a total of426 studies were excluded as they were not eligible to be used in the meta analysis. Thus, a total of 37 (21 fromSaudi Arabia and the remaining 16 from other places around the world) were included for this study. This is presented in the included phase of Fig. 1.

PRISMA 2020 flow chart diagram for this review which included the record indentified from database, screened, and those (full text) included in the meta-analysis. Exclusion criteria which comprised title and abstract excluded, full text article excluded and report (of result) excluded were all indicated.
Fig. 1
PRISMA 2020 flow chart diagram for this review which included the record indentified from database, screened, and those (full text) included in the meta-analysis. Exclusion criteria which comprised title and abstract excluded, full text article excluded and report (of result) excluded were all indicated.

3.2

3.2 Saudi Arabia

Twenty-one studies of the total 37articlesincluded in this study were from the kingdom of Saudi Arabia and were included in a specific meta-analysis, “Meta Analysis results summarizing the oral bioavailability indicated by the area under curve (AUC) of the investigated drugs from Saudi Arabia” as described in Table 1 below.

Table 1 Meta-Analysis results summarizing the bioavailability indicated by the area under curve (AUC) of the investigated drugs (Studies from Saudi Arabia, n = 21).
Group A: Treatment Group B: Control Type of nanotechnology Ref
PK: AUC (ng.h.mL−1) PK: AUC (ng.h.mL−1) Sub-Grp Type
Study No Mean SD No Mean SD SMD Lower Upper Ref
Penetratin (Alsulays et al., 2019) 5 20,760 4100 5 12,400 1800 2.383 0.762 4.004 1 (L-penetratin-INS-SLNs) 41
Alendronate sodium (Fosamax®) (Hosny, 2016) 6 2173 216.4 6 291.6 28.14 11.251 6.610 15.892 1 Optimized Eudragit coated ALS-SLN formula 42
Miconazole marketed capsules (MN) (Aljaeid and Hosny, 2016) 6 231 20 6 94 11 7.832 4.501 11.164 1 MN-SLNs 43
carvedilol (CVD) (El-Say and Hosny, 2018) 6 844.21 101.32 6 551.73 69.12 3.112 1.429 4.794 1 CVD-SLNs dispersion 44
Sildenafil citrate marketed tablet Hosny and Aljaeid, 2014) 6 1638 35 6 1032 22 19.129 11.393 26.866 1 Sildenafil citrate SLNs 45
Cyclosporine A (CyA) Binkhathlan et al., 2018 5 18,760 360 5 16,170 250 7.544 4.013 11.075 2 methoxypoly(ethyleneoxide)-block-poly(ε-caprolactone) (PEO-b-PCL) 46
Doxorubicin (DOX) (Ahmad et al., 2018) 6 20577.90 256.34 6 2130.75 49.56 92.202 55.297 129.107 2 Polymeric Nanoparticles (PEGylated-DOX-PLGA-NPs) 47
Thymoquinone (TQ) (Kalam et al., 2017) 6 1,657,700 7960 6 511.04 5.31 271.679 162.981 380.377 3 TQ-SNEDDS 48
Vinpocetine (VPN) (Ahmed et al., 2019) 6 2388.568 10.32 6 1498.34 9.12 84.351 50.585 118.117 2 VPN-loaded TPGS-micelles-ISG 49
Alendronate sodium (ALS) (Hosny et al., 2013) 6 4280 304.5 6 340.6 31.23 16.795 9.981 23.608 4 (EuC-ALS nanoliposomes) 50
Fenofibrate. (Moshin et al., 2016) 6 12414.46 86.28 6 7419.50 78.13 55.999 33.567 78.432 3 Fenofibrate-SNEDDS 51
ibrutinib (IBR) (Alshetaili et al., 2019) 3 2175.68 224.92 3 511.75 54.21 8.115 3.253 12.978 2 IBR PLGA Nanoparticles 52
Atazanavir (ATZ) (Khan et al., 2020) 3 705,670 64,180 3 468,300 52,930 3.926 2.702 5.150 5 ATZ-NLCs 53
Docosahexaenoic acid (DHA) (Alhakamy et al., 2020) 4 65,301 7504 4 19,609 583 7.457 3.549 11.365 3 DHA-SNEDDS 54
Domperidone (DOP) (Shazly et al., 2018) 6 205,430 30,610 6 78,400 70,190 2.165 0.740 3.590 1 DOP-SLNs 55
Atrovastin (At) (Shaker et al., 2021) 5 8759 0.407 5 2517 330 24.147 13.492 34.803 2 At-loaded ethylcellulose nanoparticle (At-NPs) 56
Apigenin (APG) (Kazi et al., 2020) 6 280.37 58.62 6 146.54 139.62 1.153 −0.069 2.375 3 APG Bio-SNEDDS 57
Delafloxacin(Anwer et al., 2020) 6 3717 1600 6 1618 301 1.682 0.366 2.999 4 Lipomer nanoparticle 58
Sertraline (SRT) (Rahman et al., 2019) 3 1125.67 38.34 3 181.19 32.68 21.155 9.079 33.230 1 SRT-SLNs 59
Furosemide microsuspension (Shariare et al., 2019) 5 4293.14 32.68 5 1610 27.13 80.646 45.280 116.012 3 Furosemide nanosuspension 60
Avanafil (AVA) (Fahmy et al., 2014) 6 7150.50 834.73 6 5130.24 717.42 2.395 0.912 3.878 3 AVA-SNEDDS 61

Group (A) is the treatment. It comprises nano-formulated drug conjugates as represented in the Subgroups (1–5) asrepresented in the Table 1: (1) Solid Lipid Nanoparticles (SLNs) (2) Polymer Based Nanoparticles (Polymer nanoparticles, polymeric micelles and or dendrimers) (3) SNEEDS/Nanoemulsion (4) Liposomes/proliposomes(5) Nanostructured Lipid Carriers (NLC), Group (B) is the control which is the actual/free drug suspension of any drug formulation (see Figs. 2–6).

General structure of solid lipid nanoparticle (SLN) loaded with drug (Mishra et al., 2018).
Fig. 2
General structure of solid lipid nanoparticle (SLN) loaded with drug (Mishra et al., 2018).
Structure of polymeric nanoparticle (Massadeh et al., 2016).
Fig. 3
Structure of polymeric nanoparticle (Massadeh et al., 2016).
Structure of SNEEDS/nanoemulsion loaded with drug. {A} O/W Nanoemulsion and {B} W/O Nanoemulsion (Halnor et al., 2018).
Fig. 4
Structure of SNEEDS/nanoemulsion loaded with drug. {A} O/W Nanoemulsion and {B} W/O Nanoemulsion (Halnor et al., 2018).
Mechanism of formation of Liposomes from Proliposome (Singh et al., 2019).
Fig. 5
Mechanism of formation of Liposomes from Proliposome (Singh et al., 2019).
A schematic illustration of nanostructured lipid carriers (NLC) and solid lipid nanoparticles (SLN) (Rahman et al., 2020).
Fig. 6
A schematic illustration of nanostructured lipid carriers (NLC) and solid lipid nanoparticles (SLN) (Rahman et al., 2020).

Given the presentation of the results in Table 1 above, all the studies except (Kazi et al., 2020) have established a significant increase in the AUC and accordingly the bioavailability of alldrugs investigated wasimproved as compared to their control (free drug suspensions) groups. This was confirmed as all the studies had positive confidence interval scoresexcept that carried out by Kazi et al and the conclusion drawn from a study by Mills et al. (Glasziou and Sanders, 2002).

On the whole, this study has proven to be extremely significant (P < 0.001) with a pooled estimate of 7.936 and positive confidence intervals of 5.809 and 10.064 for the lower and upper confidence intervals, respectively.

It is worthy of note that the degree of heterogeneity (I2) of the Meta Analysis study was 91 %.The cause of the heterogeneity could be as a result of several reasons ranging from chronological differences, differences intreatments (different subgroup of nanoparticles) investigated, differences in the method of preparation and experimental design used, or differences in the sample size (the number of animals used), variation in the types and/or species of animals used (Hathout, 2019; Pathak and Raghuvanshi, 2015). Some method of preparation utilized were – antisolvent participation method (Fahmy et al., 2014) utilized in Furosemide nanosuspension; double emulsification techniques employed (Hosny, 2016) in formulating insulin-loaded nanoparticles (INS-SLNs) used in preparing L-and D- penetratin; synthesizing PEO-b-PCL copolymers to form micelles encapsulating Cy A; development of different lipid-based nano carriers which is further differentiated for vesicle size, zeta potential, morphological characterization using transmission electron microscope and others.

These results confirm previous proposition regarding the effectiveness of nanotechnology in enhancing the bioavailability of orally administered drugs (Tatham et al., 2015) through different nanoformulations (Pathak and Raghuvanshi, 2015; Tatham et al., 2015; Sinha et al., 2010; Ekambaram et al., 2012; Elshafeey et al., 2009; Sanna et al., 2010). The result of this study is an affirmation of the enhancement of oral bioavailability through nanotechnology as this consistent with a variety of nanoformulation platforms that have established that “better oral bioavailability of a range of drugs for different indications” as reported in the study of Tatham, Rannard & Owen (Sinha et al., 2010).

SLN is not only the nanoformulation that performed best but also the most used nanosystem. Its pronounced usage is largely due to its several advantages such as excellent biocompatibility; ability to carry both lipophilic and hydrophilic drugs; target drug release; enhanced stability of drugs; and better drug content. Others include affordability; scalability; and easy validity for regulatory approval.

SLN was the best performing nanoformulation. An instance is seen form the SlN formulation of the Penetratin [L-Penetratin INS-SLN] with a relative bioavailability of over 1,800% (18.17-fold).

Two different studies utilizing different nano formulations on Alendronate sodium (ALS) were observed. The two studies utilized SLN [Eudragit coated ALS-SLN] and nano-liposome [Euc-ALS nanoliposome, EuC-NLS] nanoformulation respectively. Euc-NLS showed a higher relative bioavailability (12.57 folds) than ALS-SLN having a relative bioavailability of 7.47-fold.

Coating the ALS-NLS with Eudragit (EuC-NLS), increased the zeta potential to positive 4.92 mV (from negative −21.45 mV). The increase zeta potential also resulted in greater stability of ALS.

ALS-SLN showed higher encapsulation efficiency (74.3%) than EuC-NLS (41.92%). However, the two nanoformulations of ALS could eliminate eosophagal inflammation and/or bleeding among osteoporotic patients, which is a major drawback in conventionally used tablets.

Fig. 7 represents the Forest plot of the Meta Analysis study depicting the results of all thestudies where the red line indicates the estimated pooled mean and the squared dots representthe SMD of each study together with the confidences intervals on both sides.

The overall Forest plot of the published studies (n = 21) conducted in Saudi Arabia included in the Meta Analysis.
Fig. 7
The overall Forest plot of the published studies (n = 21) conducted in Saudi Arabia included in the Meta Analysis.

The weights of each study contributing in the overall pooled mean and the production of the Forest plot were also determined as shown in Table 4.

Going further, the investigated studies were sub-divided into five groups; solid lipid nanoparticles (1); polymer based nanoparticles (PbN) (2), SNEEDS/Nanoemulsion (3); liposomes/proliposomes (4) and; nanostructured lipid carriers (5).

All groups with the exception of group (5) were subject to meta-analysis as only studies within the ranges of two and above can be analysed using meta-analysis. The simple exclusion of group (5) was as a result of its sample size (n = 1) as only one study on nanostructured lipid carriers was included, thus disqualifies it from undergoing a meta-analysis as meta –analysis involves combination of several studies addressing the same outcome, and the result presented in the same measurement (Van Slooten et al., 2001).

These groups in Meta-Analysis revealed no significant differences between the two classes except that of group 4 (Liposome/proliposome), where the first (SLNs) scored an estimated mean of 6.748 associated with 3.880 and 9.616 as the lower and upper confidence intervals (CIs), respectively. The second (PbN) group had a mean estimate of 27.127 with 13.833 and 40.422 upper and lower CIs, respectively. The third group (SNEEDS/Nanoemulsion) had a mean estimate of 9.283with 3.376 and 15.190 upper and lower CIs, respectively. While the fourth group had an estimated mean of 8.854 with −5.937 and 23.644 as its lower and upper CIs. The overlapping confidence interval of the first three groups (group1, 2 and 3) points outa lack of significant differences between them. Thus, a fact that signifies similar bioavailability performance for the three (of the five) groups investigated (insignificant AUC values though profiles may differ). Meta-analysis on group 4 (Liposome/proliposome) shows no significant difference between the treatments and indicate a dissimilar bioavailability effectexistent between them. This is contrary to the study carried out by Nasser et al. (Nasser et al., 2020) who reported that “…the lipid vesicular drug carriers (Liposome) are sought; being superior to their non-vesicular counterparts due to their high compatibility with the cell membranes and further due to their sustained effects balanceyet, the high penetration abilities of the surfactants and co-surfactants components of the SMEDDS and the microemulsions together with their confirmed uptake through the lymphatic system led to the overall obtained balance” (Van Slooten et al., 2001; Daraee et al., 2016; Hathout et al., 2010; Wang et al., 2014; Ali et al., 2013; El-Shabouri, 2002). The reason for the non-significant performance of Liposome/Proliposome could be largely as a result of the extremely small sample size (n = 2), as each of these treatment in the Liposome/Proliposome subgroup independently enhanced bioavailability as seen in Table 1 above.

Most of the treatmentswere within the SLNs subgroup which are much economical as the lipids used for production are cheaper that those used in the productions of polymeric nanoparticles (Shah et al., 2013). Other benefits include increased drug stability (Porter et al., 2007) as well as decreased drug toxicity (Yeh et al., 2014); high drug payload (Porter et al., 2007).

Polymer based nanoparticles act as nanocarriers for drug solubilization and oral delivery; and thus enhance oral bioavailability of drugs. Binkhathlan et al. had reported that “PEO-b-PCL micelles can act as effective solubilizing agent and serve as good alternative to commercially available excipients used in oral formulation of a poorly soluble drug i.e. CyA” (Ahmad et al., 2018). Other advantages of polymer based nanoparticles include its good biocompatibility (Peer et al., 2007), reduced adverse reactions (Yan et al., 2015), effective administration due to its minute size (Zhen et al., 2020), and powerful targeting alongside an easy method of preparation (Dian et al., 2014).

The pros of SNEEDS such as increased rate of extent of absorption, increased drug dissolution rate and nano sized particles are features that make SNEEDS to better enhance oral exposure of poorly lipophilic drug (Yamasaki et al., 2019; Pandita et al., 2014). In bid to enhance bioavailability of drugs, SNEEDS not only improves the solubility of the drugs but also increases the membrane permeability of the GI tract (Pandita et al., 2014; Tian et al., 2018).

It is worthy of note that the Meta Analysis studies as a rule work with any number of sample size greater than one (n ≤ 2) taking into consideration the sample numbers in each study considered. However, the analysis is constantly limited with the number of related studies in the review.

3.3

3.3 Global studies including Saudi Arabia

A total of thirty-seven (37) studies were included in this study, and meta-analysis done on the data generated from them. The meta analysis result for the 37 studies which summarized the results on oral bioavailability indicated by the area under curve (AUC) of the investigated drugs were presented in Table 1 (APPENDIX III).

The result (presented Table 1 of the APPENDIX), revealed that all the studies except Dian et al (Yamasaki et al., 2019), Kazi et al. (Anwer et al., 2020), and El Shabouri (Pandita et al., 2014) established a significant increase in the AUC and accordingly the bioavailability of all drugs investigated was improved as compared to their control (free drug suspensions) groups. This was confirmed as all the studies had positive confidence interval scores except the aforementioned (Anwer et al., 2020; Yamasaki et al., 2019; Pandita et al., 2014).

Generally, the study (n = 37) has proven to be extremely significant (P < 0.001) having a pooled estimate of 6.715 and positive confidence intervals of 5.157 and 8.273 for the lower and upper confidence intervals, respectively (Table 2, APPENDIX III) (see Tables 3 and 4).

Table 2 Particle characterization of drug loaded with nano-particles.
Drug Particle Size (nm) Polydispersity index Zeta potential (mV) Encapsulation efficiency (%) Drug Content (μg/mg)
Penetratin (Alsulays et al., 2019) 618.5 ± 8.4 0.734 −17.0 ± 1.53 59.03 ± 4.21 1.64 ± 0.05
Alendronate sodium (Fosamax®) (Hosny, 2016) 100 – – 74.3 –
Miconazole marketed capsules (MN) (Aljaeid and Hosny, 2016) 23 – −16 90.2 –
carvedilol (CVD) (El-Say and Hosny, 2018) 31.3 0.3 25.2 ± 1.33 95 ± 4.12 –
Sildenafil citrate marketed tablet (Hosny and Aljaeid, 2014) 28.51 ± 3.43 – 14.34 ± 3.56 95.34 ± 3.22 –
Cyclosporine A (CyA) Binkhathlan et al., 2018 83.8 ± 1.6 0.17 ± 0.09 – 73.77 ± 1.18 –
Doxorubicin (DOX) (Ahmad et al., 2018) 183.10 ± 7.41 0.132 ± 0.010 −13.10 ± 1.04 76.86 ± 3.51 42.69 ± 1.97
Thymoquinone (TQ) (Kalam et al., 2017) 54.25 ± 3.54 0.125 −18.88 ± 1.12 – 100
Vinpocetine (VPN) (Ahmed et al., 2019) 13 ± 2 0.484 −2.79 ± 0.35 100 –
Alendronate sodium (ALS) (Hosny et al., 2013) 110 – 4.92 41.92 –
Fenofibrate. (Moshin et al., 2016) 219.91 ± 10.11 0.266 – – –
ibrutinib (IBR) (Alshetaili et al., 2019) – – – – –
Atazanavir (ATZ) (Khan et al., 2020) 227.6 ± 5.4 0.338 ± 0.021 −11.7 ± 0.47 71.09 ± 5.84 8.12 ± 2.7
Docosahexaenoic acid (DHA) (Alhakamy et al., 2020) 111.5 ± 4.2 0.269 ± 0.05 –23.53 ± 2.9 – –
Domperidone (DOP) (Shazly et al., 2018) 201.4 0.071 −6.2 66.3 –
Atrovastin (At) (Shaker et al., 2021) 319 ± 14.5 0.53 ± 0.12 −15.9 ± 1.7 73.8 ± 4.2 69.7 ± 2.1
Apigenin (APG) (Kazi et al., 2020) 57.12 ± 11.45 0.419 −14.21 ± 3.12 – 100
Delafloxacin(Anwer et al., 2020) 368 ± 5.2 0.215 ± 0.015 19.2 ± 1.4 80.4 ± 3.1 1.7 ± 0.1
Sertraline (SRT) (Rahman et al., 2019) 108.5 ± 2.77 0.183 ± 0.004 36.5 ± 0.43 73.22 ± 2.18 0.71 ± 0.03
Furosemide microsuspension (Shariare et al., 2019) 129.0 ± 3.0 0.09 ± 0.01 20 – –
Avanafil (AVA) (Fahmy et al., 2014) 95.0 12.22 – –
Table 3 Relative bioavailability of the study drugs.
Study names Sub-Group Nanosystem Relative bioavailability
Penetratin (Alsulays et al., 2019) 1 SLN 18.17-fold
Alendronate sodium (Hosny, 2016) 1 SLN 7.47-fold
Miconazole (Aljaeid and Hosny, 2016) 1 SLN 2.46-fold
Carvedilol (El-Say and Hosny, 2018) 1 SLN 1.53-fold
Sildenafil citrate (Hosny and Aljaeid, 2014) 1 SLN 1.59-fold
Cyclosporine A (Binkhathlan et al., 2018) 2 Polymeric Nanoparticles 1.16-fold
Doxorubicin (Ahmad et al., 2018) 2 Polymeric Nanoparticles 9.66-fold
Thymoquinone (Kalam et al., 2017) 3 SNEEDS/Nanoemulsion 3.24-fold
Vinpocetine(Ahmed et al., 2019) 2 Polymeric Nanoparticles 1.91-fold
Alendronate sodium(Hosny et al., 2013) 4 Liposomes/proliposomes 12.57-fold
Fenofibrate. (Moshin et al., 2016) 3 SNEEDS/Nanoemulsion 1.67-fold
Ibrutinib (Alshetaili et al., 2019) 2 Polymeric Nanoparticles 4.25-fold
Atazanavir (Khan et al., 2020) 5 NLC 2.36-fold
Docosahexaenoic acid (Alhakamy et al., 2020) 3 SNEEDS/Nanoemulsion 3.33-fold
Domperidone (Shazly et al., 2018) 1 SLN 2.62-fold
Atorvastatin (Shaker et al., 2021) 2 Polymeric Nanoparticles 3.48-fold
Apigenin (Kazi et al., 2020) 3 SNEEDS/Nanoemulsion 1.91-fold
Delafloxacin (Anwer et al., 2020) 4 Liposomes/proliposomes 2.30-fold
Sertraline (Rahman et al., 2019) 1 SLN 6.21-fold
Furosemide (Shariare et al., 2019) 3 SNEEDS/Nanoemulsion 2.67-fold
Avanafil (Fahmy et al., 2014) 3 SNEEDS/Nanoemulsion 1.39-fold
Table 4 The calculated weights of the studies included in the Meta Analysis (Studies from Saudi Arabi, n = 21).
Study names Weights
Penetratin (Alsulays et al., 2019) 7.637%
esodium (Hosny, 2016) 5.790%
Miconazole (Aljaeid and Hosny, 2016) 6.682%
Carvedilol (El-Say and Hosny, 2018) 7.611%
Sildenafil citrate (Hosny and Aljaeid, 2014) 3.885%
Cyclosporine A (Binkhathlan et al., 2018) 6.550%
Doxorubicin (Ahmad et al., 2018) 0.319%
Thymoquinone (Kalam et al., 2017) 0.038%
Vinpocetine (Ahmed et al., 2019) 0.378%
Alendronate sodium (Hosny et al., 2013) 4.392%
Fenofibrate. (Moshin et al., 2016) 0.808%
Ibrutinib (Alshetaili et al., 2019) 5.638%
Atazanavir (Khan et al., 2020) 7.786%
Docosahexaenoic acid (Alhakamy et al., 2020) 6.294%
Domperidone (Shazly et al., 2018) 7.715%
Atrovastin (Shaker et al., 2021) 2.660%
Apigenin (Kazi et al., 2020) 7.787%
Delafloxacin (Anwer et al., 2020) 7.754%
Sertraline (Rahman et al., 2019) 2.235%
Furosemide (Shariare et al., 2019) 0.346%
Avanafil (Fahmy et al., 2014) 7.693%

4

4 Conclusion

In the presentstudy, a total of 37obtainable ‘proof-of-concept’ studies were identified, included using certain eligibility criteria and analyzed for the oral bioavailability enhancement. 21 of the included studies where of vital importance as this study focused more on literatures and outcome from Saudi Arabia. In view of this the 21 studies obtained were analyzed oral bioavailability enhancement through nanotechnology in Saudi Arabia. Haven utilized comprehensive and recent data of the confirmed the enhancement of bioavailability using nanotechnology which for this study was grouped into five: solid lipid nanoparticles; polymer based nanoparticles; SNEEDS/Nanoemulsion; liposomes/proliposomes and; nanostructured lipid carriers. The result of this study can provide a better guide for drug formulators on enhancing the effectiveness of orally administered drugs especially the antineoplastic drugs. SLN was the best performing nanoformulation. An instance is seen form the SLN formulation of the Penetratin [L-Penetratin INS-SLN] with a relative bioavailability of over 1,800% (18.17-fold). Furthermore, the meta-analysis, provided evidence of insignificant differences between APG Bio-SNEDDS and its free drug suspension (Apeginin, APG), though with relative bioavailabiilty of 1.91. Notwithstanding most of the treatment showed a substantial relative bioavailability

Acknowledgment

The author is grateful to the Middle East University, Amman, Jordan for the financial support granted to cover the publication fee of this article.

Declaration of Competing Interest

The author declares that she have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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