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Ferulic acid (FA) has powerful antioxidant and antitumor activities, but it has low bioavailability owing to its poor water solubility. Our aim is to formulate polymeric mixed micelles loaded with FA to overcome its poor solubility and investigate its potential anticancer activity via miRNA-221/TP53INP1 axis-mediated autophagy in colon cancer. A D-optimal design with three factors was used for the optimization of polymeric mixed micelles by studying the effects of each of total Pluronics mixture (mg), Pluronic P123 percentage (%w/w), and drug amount (mg) on both entrapment efficiency (EE%) and particle size. The anticancer activity of FA and Tocopheryl polyethylene glycol 1000 succinate (TPGS) mixed micelles formula (O2) was assessed by MTT and flow cytometry. O2 showed an EE% of 99.89%, a particle size of 13.86 nm, and a zeta potential of − 6.02 mv. In-vitro drug release studies showed a notable increase in the release rate of FA from O2, as compared to the free FA. The (IC 50 ) values for FA from O2 and free FA were calculated against different cell lines showing a prominent IC 50 against Caco-2 (17.1 µg/ml, 191 µg/ml respectively). Flow cytometry showed that FA caused cell cycle arrest at the G2/M phase in Caco-2. RT-PCR showed that O2 significantly increased the mRNA expression level of Bax and CASP-3 (4.72 ± 0.17, 3.67 ± 0.14), respectively when compared to free FA (2.59 ± 0.13, 2.14 ± 0.15), while miRNA 221 levels were decreased by the treatment with O2 (0.58 ± 0.02) when compared to free FA treatment (0.79 ± 0.03). The gene expression of TP53INP1 was increased by the treatment with O2 compared to FA at P < 0.0001. FA-loaded TPGS mixed micelles showed promising results for enhancing the anticancer effect of FA against colorectal cancer, probably due to its enhanced solubility. Thus, FA-loaded TPGS mixed micelles could be a potential therapeutic agent for colorectal cancer by targeting miRNA-221/TP53INP1 axis-mediated autophagy.

The aim of the current study is to explore the potential of artificial intelligence (AI) when integrated with Quality by Design (QbD) approach in the formulation of a poorly water-soluble drug, for its potential use in carcinoma. Silymarin is used as a model drug for its potential effectiveness in liver cancer. A detailed QbD approach was applied. The effect of the critical process parameters was studied on each of the particle size, size distribution, and entrapment efficiency. Response surface designs were applied in the screening and optimization of lecithin/chitosan nanoparticles, to obtain an optimized formula. The release rate was tested, where artificial neural network models were used to predict the % release of the drug from the optimized formula at different time intervals. The optimized formula was tested for its cytotoxicity. A design space was established, with an optimized formula having a molar ratio of 18.33:1 lecithin:chitosan and 38.35 mg silymarin. This resulted in nanoparticles with a size of 161 nm, a polydispersity index of 0.2, and an entrapment efficiency of 97%. The optimized formula showed a zeta potential of +38 mV, with well-developed spherical particles. AI successfully showed high prediction ability of the drug’s release rate. The optimized formula showed an enhancement in the cytotoxic effect of silymarin with a decreased IC50 compared to standard silymarin. Lecithin/chitosan nanoparticles were successfully formulated, with deep process and product understanding. Several tools were used as AI which could shift pharmaceutical formulations from experience-dependent studies to data-driven methodologies in the future. Graphical abstract

Vanillic acid (VA) is a phenolic compound with potential antioxidant activity, which improves ischemia-induced myocardial degeneration, by reducing oxidative stress; however, it suffers poor bioavailability owing to its poor solubility. VA-loaded pharmacosomes were optimized using a central composite design, where the effect of phosphatidylcholine:VA molar ratio and the precursor concentration were studied. An optimized formulation (O 1 ) was prepared and tested for the release rate of VA, in vivo bioavailability, and cardioprotective potential on myocardial infarction-induced rats. The optimized formulation showed a particle size of 229.7 nm, polydispersity index of 0.29, and zeta potential of − 30 mV. O 1 showed a sustained drug release for 48 h. The HPLC–UV method was developed for the determination of VA in plasma samples using protein precipitation. The optimized formulation showed a great improvement in the bioavailability as compared to VA. The residence time of the optimized formula was 3 times longer than VA. The optimized formulation showed a more potent cardioprotective effect as compared to VA, via inhibition of the MAPK pathway with subsequent inhibition of PI3k/NF-κB signaling, in addition to its antioxidant effect. The optimized formulation showed normalization of many oxidative stress and inflammatory biomarkers. Thus, a VA-loaded pharmacosome formulation with promising bioavailability and cardioprotective activity potential was prepared. Graphical Abstract

The present study deals with the formulation of topical insulin for wound healing with extended stability and sustained release, by applying quality by design concepts. Insulin has been promoted as a promising therapeutic wound healing agent. Topical formulation of insulin faced major problems, as it cannot be delivered safely to the wound with a controlled rate. Formulation of insulin-loaded vesicles in optimized bio-adhesive hydrogels has been explored to ensure a safe delivery of insulin to wounds in a controlled manner. Quality by design (QbD) was applied to study the effect of several critical process parameters on the critical quality attributes. Ishikawa diagram was used to identify the highest risk factors, which were screened by a fractional factorial design and augmented by Box–Behnken design. The optimized formula was incorporated into a mucoadhesive gel, which was further subjected to stability and clinical studies. An optimized formula was obtained with a particle size of 257.751 nm, zeta potential − 20.548 mv, 87.379% entrapment efficiency, and a release rate of 91.521 μg/cm2/h. The results showed that liposomal insulin remained stable for 6 months in aqueous dispersion state at 4°C. Moreover, the release was sustained up to 24 h. The clinical study showed an improvement in the wound healing rate, 16 times, as the control group, with magnificent reduction in the erythema of the ulcer and no signs of hypoglycemia. Insulin-loaded liposomal chitosan gel showed a promising drug delivery system with high stability and sustained release.

Purpose Rosuvastatin calcium (RSC) is a statin which, in addition to its anti-hypercholesteremic effects, was found to have a potential anticancer activity. The target of the present study is to develop self nano-emulsifying drug delivery systems (SNEDDS) loaded with RSC to overcome its poor solubility, and augment its anticancer activity. Methods A combined mixture-process experimental design was chosen for the optimization of SNEDDS by changing its mixture and process components, where the mixture components were the percentage of Smixture (surfactant and co-surfactant) (X 1 ) and the percentage of oil (X 2 ). The process components were the ratio of surfactant to co-surfactant (X 3 ), and the type of surfactant (X 4 ). Twenty-four formulae were evaluated for % transmittance and saturated solubility. Results The optimized formula (O 1 ) was selected based on the highest % transmittance and highest drug solubility, where the % transmittance was 99.05 ± 0.09% and the saturated solubility was 80.52 ± 2.57 mg/ml. The optimized formula has a globule size of 17.53 ± 0.89 nm, a zeta potential of − 10.2 ± 0.21 mV, and a cloud point of 88.5 ± 0.54 °C. Transmission electron microscopy demonstrated spherical droplet morphology. In vitro drug release showed remarkable increase in the drug release from the optimized formula as compared to the corresponding standard RSC. The anticancer activity of O 1 was evaluated in HepG2 cell-line, where the IC 50 value was 16.2 ± 0.23 μg/ml. The optimized formula increased cell death by both apoptosis and necrosis. Conclusion Our results show that the optimized SNEDDS formula is promising for enhancing the anticancer effect of RSC.

Purpose Albumin nanoparticles are promising carriers for therapeutic agents, owing to their biocompatibility, safety, and versatility in fabrication. The formulation of albumin nanoparticles is highly affected by many product and process variables, resulting in a great variation in these nanoparticles. The aim of this work was to formulate and optimize albumin nanoparticles loaded with silymarin, as a model drug with low bioavailability, for the treatment of hepatocellular carcinoma, using quality by design (QbD) approach. Methods A thorough risk assessment for albumin nanoparticles formulation was developed and a complete quality product profile was defined using the QbD approach. A D-optimal design was used to optimize the amount of albumin and drug, which significantly affected the particle size (PS) and the entrapment efficiency (EE%), which was further tested on hepatocellular carcinoma. Results A design space was constructed, with an optimized formula showing a PS of 135 nm, a polydispersity index (PDI) of 0.09, an EE% of 88%, and a zeta potential of − 12.5 mV. The optimized formula (O 1 ) with spherical particles, showed an extended-release rate as compared to free silymarin. Moreover, a pronounced anti-proliferation activity of O 1 was observed on human hepatocellular carcinoma cell line HepG2 than the free drug. The flow cytometric analysis of the cell cycle showed a significant suppression of the S-phase after treating the HepG2 cell with O 1 , but not with free silymarin. Conclusion Thus, a detailed QbD study has been conducted, with deep product and process understanding, and resulted in a successful formulation of silymarin albumin nanoparticles for the suppression of hepatocellular carcinoma.

Background Androgenetic alopecia (AGA) is a common cause of hair loss in both genders that may be associated with disturbed systemic metabolism. Irisin is a hormone‐like myokine that greatly influences systemic metabolism and is linked to cardiovascular diseases. Aim To detect irisin role in AGA and its associated metabolic syndrome (MetS) and cardiovascular risk. Patients/Methods This case–control study included 44 AGA patients of both genders and 22 healthy individuals. Serum irisin level was measured using ELISA and scalp biopsy was taken to detect irisin immunohistochemically. Carotid Doppler ultrasonography was performed to measure carotid intima media thickness (CIMT). Results Higher serum irisin was significantly detected in AGA patients (p ˂ 0.001), and in males (p = 0.01) particularly severe cases (p ˂ 0.001). It was significantly higher in AGA patients presenting with MetS and those suffering from dyslipidemia (p ˂ 0.001 for both). Multivariate regression analysis proved BMI (p = 0.01) and serum irisin (p = 0.02) as independent predictors of CIMT abnormality among AGA patients. Regarding cutaneous irisin expression, the epidermal H‐score was significantly higher in AGA patients with MetS compared to those without (p = 0.04). Epidermal H‐score ˃100 was significantly associated with male gender (p = 0.05), severe AGA (p = 0.02), MetS (p = 0.03), dyslipidemia (p = 0.03), and abnormal CIMT (p = 0.03). Conclusion High serum irisin and upregulated epidermal irisin expression are associated with the incidence of MetS, dyslipidemia, and CIMT abnormality among AGA patients. This may indicate resistance to irisin, which hinders its favorable cardiometabolic actions. Further studies are warranted to investigate the concept of irisin resistance in AGA patients, which was uniquely discussed in the present study.

Objectives: The SF-6D is a preference-based measure of health developed to generate utility values from the SF-36. The aim of this pilot study was to examine the feasibility and acceptability of using the standard gamble (SG) technique to generate preference-based values for the Arabic version of SF-6D in a Lebanese population. Methods: The SF-6D was translated into Arabic using forward and backward translations. Forty-nine states defined by the SF-6D were selected using an orthogonal design and grouped into seven sets. A gender-occupation stratified sample of 126 Lebanese adults from the American University of Beirut were recruited to value seven states and the pits using SG. The sample size is appropriate for a pilot study, but smaller than the sample required for a full valuation study. Both interviewers and interviewees reported their understanding and effort levels in the SG tasks. Mean and individual level multivariate regression models were fitted to estimate preference weights for all SF-6D states. The models were compared with those estimated in the UK. Results: Interviewers reported few problems in completing SG tasks (0.8% with a lot of problems) and good respondent understanding (5.6% with little effort and concentration), and 25% of respondents reported the SG task was difficult. A total of 992 SG valuations were useable for econometric modeling. There was no significant change in the test–retest values from 21 subjects. The mean absolute errors in the mean and individual level models were 0.036 and 0.050, respectively, both of which were lower than the UK results. The random effects model adequately predicts the SG values, with the worst state having a value of 0.322 compared to 0.271 in the UK. Conclusion: This pilot confirmed that it was feasible and acceptable to generate preference values with the SG method for the Arabic SF-6D in a Lebanese population. However, further work is needed to extend this to a more representative population, and to explore why no utility values below zero were observed.