Implementation of green-assessed nanotechnology and quality by design approach for development of optical sensor for determination of tobramycin in ophthalmic formulations and spiked human plasma.

A fast eco-friendly colorimetric method was developed for the determination of Tobramycin in drug substance, ophthalmic formulations, and spiked human plasma using silver nanoparticles optical sensor. Even though tobramycin is non-UV-visible absorbing, the developed method is based on measuring the absorbance quenching of silver nanoparticles resulting from the interaction with tobramycin. Different factors affecting the absorbance intensity were studied as; silver nanoparticle concentration, pH, buffer type, and reaction time using quality by design approach. Validation of the proposed method was performed according to ICH guidelines and was found to be accurate, precise, and sensitive. The linearity range of tobramycin was 0.35-4.0 µg/mL. The optical sensor was successfully applied for the determination of Tobramycin in ophthalmic formulations and spiked human plasma without pre-treatment. Additionally, the binding between Tobramycin and PVP- capped silver nanoparticles was studied using molecular docking software. The method was assessed and compared to colorimetric reported methods for the green character using Green Analytical Procedure Index (GAPI) and Analytical GREEnness calculator (AGREE) tools and found to be greener.

Enhancing Effector Jurkat Cell Activity and Increasing Cytotoxicity against A549 Cells Using Nivolumab as an Anti-PD-1 Agent Loaded on Gelatin Nanoparticles.

The current research investigated the use of gelatin nanoparticles (GNPs) for enhancing the cytotoxic effects of nivolumab, an immune checkpoint inhibitor. The unique feature of GNPs is their biocompatibility and functionalization potential, improving the delivery and the efficacy of immunotherapeutic drugs with fewer side effects compared to traditional treatments. This exploration of GNPs represents an innovative direction in the advancement of nanomedicine in oncology. Nivolumab-loaded GNPs were prepared and characterized. The optimum formulation had a particle size of 191.9 ± 0.67 nm, a polydispersity index of 0.027 ± 0.02, and drug entrapment of 54.67 ± 3.51%. A co-culture experiment involving A549 target cells and effector Jurkat cells treated with free nivolumab solution, and nivolumab-loaded GNPs, demonstrated that the latter had significant improvements in inhibition rate by scoring 87.88 ± 2.47% for drug-loaded GNPs against 60.53 ± 3.96% for the free nivolumab solution. The nivolumab-loaded GNPs had a lower IC50 value, of 0.41 ± 0.01 µM, compared to free nivolumab solution (1.22 ± 0.37 µM) at 72 h. The results indicate that administering nivolumab-loaded GNPs augmented the cytotoxicity against A549 cells by enhancing effector Jurkat cell activity compared to nivolumab solution treatment.

Nanofiberous facemasks as protectives against pandemic respiratory viruses.

INTRODUCTION: Wearing protective face masks and respirators has been a necessity to reduce the transmission rate of respiratory viruses since the outbreak of the coronavirus (COVID-19) disease. Nevertheless, the outbreak has revealed the need to develop efficient air filter materials and innovative anti-microbial protectives. Nanofibrous facemasks, either loaded with antiviral nanoparticles or not, are very promising personal protective equipment (PPE) against pandemic respiratory viruses. AREAS COVERED: In this review, multiple types of face masks and respirators are discussed as well as filtration mechanisms of particulates. In this regard, the limitations of traditional face masks were summarized and the advancement of nanotechnology in developing nanofibrous masks and air filters was discussed. Different methods of preparing nanofibers were explained. The various approaches used for enhancing nanofibrous face masks were covered. EXPERT OPINION: Although wearing conventional face masks can limit viral infection spread to some extent, the world is in great need for more protective face masks. Nanofibers can block viral particles efficiently and can be incorporated into face masks in order to enhance their filtration efficiency. Also, we believe that other modifications such as addition of antiviral nanoparticles can significantly increase the protection power of facemasks.

Simplex Lattice Design and Machine Learning Methods for the Optimization of Novel Microemulsion Systems to Enhance p-Coumaric Acid Oral Bioavailability: In Vitro and In Vivo Studies.

Novel p-coumaric acid microemulsion systems were developed to circumvent its absorption and bioavailability challenges. Simplex-lattice mixture design and machine learning methods were employed for optimization. Two optimized formulations were characterized using in vitro re-dispersibility and cytotoxicity on various tumor cell lines (MCF-7, CaCO2, and HepG2). The in vivo bioavailability profiles of the drug loaded in the two microemulsion systems and in the suspension form were compared. The optimized microemulsions composed of Labrafil M1944 CS (5.67%)/Tween 80 (38.71%)/Labrasol (38.71%)/water (16.92%) and Capryol 90 (0.50%)/Transcutol P (26.67%)/Tween 80 (26.67%)/Labrasol (26.67%)/water (19.50%), respectively. They revealed uniform and stable p-coumaric acid-loaded microemulsion systems with a droplet size diameter of about 10 nm. The loaded microemulsion formulations enhanced the drug re-dispersibility in contrast to the drug suspension which exhibited 5 min lag time. The loaded formulae were significantly more cytotoxic on all cell lines by 11.98-16.56 folds on MCF-7 and CaCo2 cells and 47.82-98.79 folds on HepG2 cells higher than the pure drug. The optimized microemulsions were 1.5-1.8 times more bioavailable than the drug suspension. The developed p-coumaric acid microemulsion systems could be considered a successful remedy for diverse types of cancer.

Do the chitosan nanoparticles really augment the drugs' transdermal fluxes: ending the debate using meta-analysis.

INTRODUCTION: Transdermal delivery has been extensively investigated as a successful alternative to the oral and parenteral routes of administration. The use of polymeric nanoparticles as drug delivery systems through this route has always been controversial. The use of meta-analyses is a useful quantitative means to decide upon the efficiency of this type of vehicles transporting drugs through the skin. AREAS COVERED: In this meta-analysis study, polymeric nanoparticles were quantitatively compared to conventional formulations in order to investigate the feasibility of using these particles in transdermal delivery. Natural versus synthetic polymeric sub-groups were also contrasted to determine the most efficient class for transdermal drug enhancement. EXPERT OPINION: Meta-analyses are gaining ground in the drug delivery field as they can exploit the mines of the literature and pick up by statistical evidence the superior formulations administered through several routes of administration. This is the first study that utilized the transdermal fluxes as the meta-analysis study effect and could prove the superiority of natural polymeric nanoparticles in transdermal delivery. In our opinion, there is paucity in research work regarding this type of nanocarriers, specifically on chitosan nanoparticles. More studies are warranted for full exploitation of its benefits.

Nose-to-brain delivery of 18ß-Glycyrrhetinic acid using optimized lipid nanocapsules: A novel alternative treatment for Alzheimer's disease.

Alzheimer's disease (AD) is a neurodegenerative disorder and the most relevant form of dementia affecting people worldwide. AD was reported to be associated with increased oxidative stress ending up with neuronal damage. 18ß-Glycyrrhetinic acid (GA), triterpenoid aglycone of glycyrrhizin, was reported for its powerful antioxidant activities. However, its high molecular weight and lipophilicity are two major obstacles that limit its use and cause very low brain bioavailability. The aim of the present study was to formulate the GA in lipid nanocapsules (LNCs) for enhanced nose-to-brain delivery, as well as to elucidate its potential neuroprotective effect in AD. The optimized GA-loaded LNCs exhibited nanometric size range, good stability over 6 months, sustained drug release over 24 h and high steady state flux and permeability coefficient across nasal mucosa over 8 h. In-vivo studies were conducted on five groups; control, scopolamine (SCOP)-treated, SCOP + GA-LNCs, SCOP + oral GA suspension, and SCOP + intranasal GA suspension groups. Intranasal administration of GA-LNCs, at a reduced dose of 1 mg/kg, improved scopolamine-induced memory impairment in rats evidenced by behavioral testing, histological examination, and oxidative stress markers; catalase and superoxide dismutase. Collectively, GA-loaded LNCs (with 50 times lower dose) may provide a promising remedy for AD patients worldwide.

Nanocarriers significantly augment the absorption of ocular-delivered drugs: A comparative meta-analysis study.

This study presents a meta-analysis that compiles information collected from several studies aiming to prove, by evidence, that nanocarriers out-perform conventional formulations in augmenting the bioavailability of ocular topically administered drugs. Data was further categorized into two subgroups; polymeric-based nanocarriers versus their lipid-based counterparts, as well as, naturally-driven carriers versus synthetically-fabricated ones. After normalization, the pharmacokinetic factor, area under the curve (AUC), was denoted as the "effect" in the conducted study, and the corresponding Forest plots were obtained. Our meta-analysis study confirmed the absorption enhancement effect of loading drugs into nanocarriers as compared to conventional topical ocular dosage forms. Interestingly, no significant differences were recorded between the polymeric and lipidic nanocarriers included in the study, while naturally-driven nanoplatforms were proven superior to the synthetic alternatives.

Cerium Oxide Nanoparticles/Polyacrylonitrile Nanofibers as Impervious Barrier against Viral Infections.

BACKGROUND: Using face masks is one of the protective measures to reduce the transmission rate of coronavirus. Its massive spread necessitates developing safe and effective antiviral masks (filters) applying nanotechnology. METHODS: Novel electrospun composites were fabricated by incorporating cerium oxide nanoparticles (CeO2 NPs) into polyacrylonitrile (PAN) electrospun nanofibers that can be used in the future in face masks. The effects of the polymer concentration, applied voltage, and feeding rate during the electrospinning were studied. The electrospun nanofibers were characterized using SEM, XRD, FTIR, and tensile strength testing. The cytotoxic effect of the nanofibers was evaluated in the Vero cell line using the MTT colorimetric assay, and the antiviral activity of the proposed nanofibers was evaluated against the human adenovirus type 5 (ADV-5) respiratory virus. RESULTS: The optimum formulation was fabricated with a PAN concentration of 8%, w/v loaded with 0.25%, w/v CeO2 NPs with a feeding rate of 26 KV and an applied voltage of 0.5 mL/h. They showed a particle size of 15.8 ± 1.91 nm and a zeta potential of -14 ± 0.141 mV. SEM imaging demonstrated the nanoscale features of the nanofibers even after incorporating CeO2 NPs. The cellular viability study showed the safety of the PAN nanofibers. Incorporating CeO2 NPs into these fibers further increased their cellular viability. Moreover, the assembled filter could prevent viral entry into the host cells as well as prevent their replication inside the cells via adsorption and virucidal antiviral mechanisms. CONCLUSIONS: The developed cerium oxide nanoparticles/polyacrylonitrile nanofibers can be considered a promising antiviral filter that can be used to halt virus spread.

Meta-Analysis: A Convenient Tool for the Choice of Nose-to-Brain Nanocarriers.

OBJECTIVES: The intranasal route represents a high promising route of administration aiming for brain delivery. Yet, it represents one of the most difficult and complicated routes. Accordingly, scientists are in a continuous search for novel drug delivery vehicles such as the lipid and polymeric nanoparticles that are apt to enhance the bioavailability of the administered drugs to reach the brain. In this study, a certain number of publications were selected from different databases and literature. Meta-analysis studies using two different algorithms (DerSimonian-Laird and inverse variance) followed aiming to explore the published studies and confirm by evidence the superiority of nanocarriers in enhancing the brain bioavailability of various drugs. Furthermore, the quantitative comparison of lipid versus polymeric nanosystems was performed. METHODS: The area under the curve (AUC) as an important pharmacokinetic parameter extracted from in vivo animal studies was designated as the "effect" in the performed meta-analysis after normalization. Forest plots were generated. KEY FINDINGS AND CONCLUSIONS: The meta-analysis confirmed the augmentation of the AUC after the comparison with traditional preparations such as solutions and suspensions. Most importantly, lipid nanoparticles were proven to be significantly superior to the polymeric counterparts.

The skin delivery of tofacitinib citrate using transethosomes and hybridized ethosomes/nanostructured lipid carriers for vitiligo therapy: Dermatopharmacokinetics and in vivo assays.

Vitiligo is an autoimmune disease where its current treatment strategies are lengthy in course and do not guarantee complete cure. Tofacitinib citrate (JAK inhibitor) is a potential cure of vitiligo through halting JAK-STAT pathway preventing the destruction of melanocytes. The dermato-pharmacokinetics of the prepared transethosomes (Et) and the hybridized ethosomes/nanostructured lipid carriers (Eth/NLC), namely formulations; M.E-Cr and M.E-S.M, were evaluated. In addition, in vivo studies on C57/BL6 vitiligo mouse model were conducted to confirm effectiveness of Tofacitinib citrate delivery. The results unveiled that the transethosomes (359.46 ± 11.82 nm) were suitable for dermal delivery while M.E-Cr (179.64 ± 11.16 nm), a hybrid Eth/NLC formulation, was mostly suitable for transdermal delivery. Nevertheless, another hybrid formulation, M.E-S.M (253.60 ± 14.64 nm), was apt for both dermal and transdermal delivery. The histopathology confirmed re-pigmentation of mice skin where formulations Et and M.E-S.M showed severe pigmentation compared to the control healthy and induced mice. On the other hand, M.E-Cr showed mild pigmentation. Immunohistochemical assay was performed to evaluate infiltration of CD 8+T-lymphocytes where mild infiltration was observed. However, the systemic IFN-γ was significantly reduced in case of M.E-Cr and M.E-S.M. The present work proposed potential effective formulations to improve the treatment of vitiligo with potential reduction in the total therapeutic dose, drug's side effects, and treatment costs.

Structural Optimization of Platinum Drugs to Improve the Drug-Loading and Antitumor Efficacy of PLGA Nanoparticles.

Currently, molecular dynamics simulation is being widely applied to predict drug-polymer interaction, and to optimize drug delivery systems. Our study describes a combination of in silico and in vitro approaches aimed at improvement in polymer-based nanoparticle design for cancer treatment. We applied the PASS service to predict the biological activity of novel carboplatin derivatives. Subsequent molecular dynamics simulations revealed the dependence between the drug-polymer binding energy along with encapsulation efficacy, drug release profile, and the derivatives' chemical structure. We applied ICP-MS analysis, the MTT test, and hemolytic activity assay to evaluate drug loading, antitumor activity, and hemocompatibility of the formulated nanoparticles. The drug encapsulation efficacy varied from 0.2% to 1% and correlated with in silico modelling results. The PLGA nanoparticles revealed higher antitumor activity against A549 human non-small-cell lung carcinoma cells compared to non-encapsulated carboplatin derivatives with IC50 values of 1.40-23.20 µM and 7.32-79.30 µM, respectively; the similar cytotoxicity profiles were observed against H69 and MCF-7 cells. The nanoparticles efficiently induced apoptosis in A549 cells. Thus, nanoparticles loaded with novel carboplatin derivatives demonstrated high application potential for anticancer therapy due to their efficacy and high hemocompatibility. Our results demonstrated the combination of in silico and in vitro methods applicability for the optimization of encapsulation and antitumor efficacy in novel drug delivery systems design.

Green synthesis of gold nanoparticles using plant products and plants extracts aiming for cancer therapy: helping the beauty to beat 'cure' the beast.

Since there is a noticed paucity in manuscripts exploiting the green synthesis methods in the preparation of gold nanoparticles, hence this editorial is introduced in order to encourage the researchers to more focussing on this topic. Brief demonstration of the different conducted green methods, examples of used plants and plants extracts and novel advanced methods such as the one-step synthesis of gold-coated polypyrrole photothermal nanoparticles and their use in cancer therapy are introduced.

Augmented in vitro and in vivo Profiles of Brimonidine Tartrate Using Gelatinized-Core Liposomes.

Background: The low entrapment efficiency of the hydrophilic drugs such as brimonidine tartrate (BRT) in liposomes represents a challenge that requires interventions. Gelatinized core liposomes (GCLs) were fabricated to increase the drug entrapment, corneal penetration, and physical stability of the investigated molecule. Research Design and Methods: GCLs encapsulating BRT were prepared and optimized utilizing D-optimal design (DOD). The effect of plasticizer incorporation on the physicochemical characteristics and on the in vivo performance was studied. The optimized formulations were investigated for pH, rheological properties, morphological characteristics, in vitro release profiles, biological performance, safety profile. The effects of storage and gamma sterilization were also investigated. Results: The results revealed the great success of the prepared formulations to achieve high entrapment efficiency reaching 98% after a maturation period of 10 days. The addition of glycerol as plasticizer significantly minimized the particle size and shortened the maturation period to 7 days. The selected formulations were stable for 3 months after gamma sterilization. The formulations showed significant lowering of intra-ocular pressure (IOP) in glaucomatous rabbits with sustainment of the pharmacological effect for 24 hours compared to drug solution. Conclusions: Enhanced in vitro and in vivo profiles of brimonidine tartrate loaded gelatinized-core-liposomes were obtained.

Sesamol Loaded Albumin Nanoparticles: A Boosted Protective Property in Animal Models of Oxidative Stress.

The current study evaluated the ability of sesamol-loaded albumin nanoparticles to impart protection against oxidative stress induced by anthracyclines in comparison to the free drug. Albumin nanoparticles were prepared via the desolvation technique and then freeze-dried with the cryoprotectant, trehalose. Albumin concentration, pH, and type of desolvating agent were assessed as determining factors for successful albumin nanoparticle fabrication. The optimal nanoparticles were spherical in shape, and they had an average particle diameter of 127.24 ± 2.12 nm with a sesamol payload of 96.89 ± 2.4 µg/mg. The drug cellular protection was tested on rat hepatocytes pretreated with 1 µM doxorubicin, which showed a 1.2-fold higher protective activity than the free sesamol. In a pharmacokinetic study, the loading of a drug onto nanoparticles resulted in a longer half-life and mean residence time, as compared to the free drug. Furthermore, in vivo efficacy and biochemical assessment of lipid peroxidation, cardiac biomarkers, and liver enzymes were significantly ameliorated after administration of the sesamol-loaded albumin nanoparticles. The biochemical assessments were also corroborated with the histopathological examination data. Sesamol-loaded albumin nanoparticles, prepared under controlled conditions, may provide an enhanced protective effect against off-target doxorubicin toxicity.

Do Polymeric Nanoparticles Really Enhance the Bioavailability of Oral Drugs? A Quantitative Answer Using Meta-Analysis.

The oral route remains one of the most popular and important routes of administration for drugs-one that warrants the development of advanced drug delivery systems, such as polymeric nanoparticles capable of enhancing the absorption and bioavailability of the used drugs. In this work, a systematic review of published works on several databases, followed by a meta-analysis, were utilized in order to navigate the published studies and access literature-based evidence about the capability of polymeric nanoparticulate systems to augment the absorption and bioavailability of orally administered drugs. The pharmacokinetic parameter of the area under the curve (AUC) was utilized as the "effect" of this meta-analytical study. The meta-analysis demonstrated a significant increase in AUC compared to conventional formulations. Furthermore, comparing the synthetic polymeric nanoparticles, versus their naturally-based administered counterparts, as subgroups of the meta-analysis, revealed no significant differences.

Breaking the challenge of polyherbal quality control using UV and HPLC fingerprints combined with multivariate analysis.

INTRODUCTION: Traditional herbal medicines are mostly composed of more than one herb which act synergistically; hence, there is high demand for proper quality control methods to ensure the consistent quality of polyherbal formulations. AIMS: Proposing a simple, reliable, and efficient method for the qualitative and quantitative analysis of a polyherbal product using multivariate analysis of ultraviolet-visible (UV-Vis) spectroscopy or HPLC-PDA data. METHODOLOGY: An antiobesity formula consisting of equal proportions of Trachyspermum ammi, Cuminum cyminum, and Origanum majorana was prepared as well as spiked with one of each herb simultaneously, representing accepted and unaccepted samples. Full factorial design (2k ) was applied to study the effect of temperature, sonication, and stirring time for extraction optimisation. The HPLC and UV spectral fingerprints were separately subjected to multivariate analysis. The soft independent modelling of class analogy (SIMCA) and partial least squares (PLS) models were developed to segregate the accepted from the unaccepted samples and to predict the herbal composition in addition to the thymol content in each sample. RESULTS: The SIMCAuv and SIMCAhplc models showed correct discrimination between the accepted and unaccepted samples with excellent selectivity and sensitivity. The PLSuv , PLShplc , and PLSthym models showed excellent linearity and accuracy with R2  > 0.98, slope close to 1, intercept close to 0, low root mean square error of calibration (RMSEC), and root mean square error of prediction (RMSEP) (close to 0). On validation, the PLS models correctly predicted the quantity of the three herbs and thymol content with ±5% accuracy. CONCLUSION: This study demonstrates the reliability and efficiency of HPLC and UV spectroscopy coupled with multivariate statistical analysis (MVA) for ensuring the consistency of polyherbal preparations.

In silico prediction of siRNA ionizable-lipid nanoparticles In vivo efficacy: Machine learning modeling based on formulation and molecular descriptors.

In silico prediction of the in vivo efficacy of siRNA ionizable-lipid nanoparticles is desirable as it can save time and resources dedicated to wet-lab experimentation. This study aims to computationally predict siRNA nanoparticles in vivo efficacy. A data set containing 120 entries was prepared by combining molecular descriptors of the ionizable lipids together with two nanoparticles formulation characteristics. Input descriptor combinations were selected by an evolutionary algorithm. Artificial neural networks, support vector machines and partial least squares regression were used for QSAR modeling. Depending on how the data set is split, two training sets and two external validation sets were prepared. Training and validation sets contained 90 and 30 entries respectively. The results showed the successful predictions of validation set log (siRNA dose) with Rval 2= 0.86-0.89 and 0.75-80 for validation sets one and two, respectively. Artificial neural networks resulted in the best Rval 2 for both validation sets. For predictions that have high bias, improvement of Rval 2 from 0.47 to 0.96 was achieved by selecting the training set lipids lying within the applicability domain. In conclusion, in vivo performance of siRNA nanoparticles was successfully predicted by combining cheminformatics with machine learning techniques.

Elaborated survey in the scope of nanocarriers engineering for boosting chemotherapy cytotoxicity: A meta-analysis study.

Cancer is the prime cause of mortality throughout the world. Although the conventional chemotherapeutic agents damage the cancerous cells, they exert prominent injury to the normal cells owing to their lack of specificity. With advances in science, many research studies have been established to boost the cytotoxic effect of the chemotherapeutic agents via innovating novel nano-formulations having different variables. In the current meta-analysis study, combined data from different research articles were gathered for the evidence-based proof of the superiority of drug loaded nanocarriers over their corresponding conventional solutions in boosting the cytotoxic effect of chemotherapy in terms of IC50 values. The meta-analysis was subdivided into three subgroups; nanoparticles versus nanofibers, surface functionalized nanocarriers versus naked ones, and protein versus non-protein-based platforms. The different subgroups interestingly showed distinct scoring outcome data paving the road for cytotoxicity enhancement of the anti-cancer drugs in an evidence-based manner.

Synchronizing In Silico, In Vitro, and In Vivo Studies for the Successful Nose to Brain Delivery of an Anticancer Molecule.

Sesamol is a sesame seed constituent with reported activity against many types of cancer. In this work, two types of nanocarriers, solid lipid nanoparticles (SLNs) and polymeric nanoparticles (PNs), were exploited to improve sesamol efficiency against the glioma cancer cell line. The ability of the proposed systems for efficient brain targeting intranasally was also inspected. By the aid of two docking programs, the virtual loading pattern inside these nanocarriers was matched to the real experimental results. Interactions involved in sesamol-carrier binding were also assessed, followed by a discussion of how different scoring functions account for these interactions. The study is an extension of the computer-assisted drug formulation design series, which represents a promising initiative for an upcoming industrial innovation. The results proved the power of combined in silico tools in predicting members with the highest sesamol payload suitable for delivering a sufficient dose to the brain. Among nine carriers, glyceryl monostearate (GMS) and polycaprolactone (PCL) scored the highest sesamol payload practically and computationally. The EE % was 66.09 ± 0.92 and 61.73 ± 0.47 corresponding to a ΔG (binding energy) of -8.85 ± 0.16 and -5.04 ± 0.11, respectively. Dynamic light scattering evidenced the formation of 215.1 ± 7.2 nm and 414.25 ± 1.6 nm nanoparticles, respectively. Both formulations demonstrated an efficient cytotoxic effect and brain-targeting ability compared to the sesamol solution. This was evidenced by low IC50 (38.50 ± 10.37 µM and 27.81 ± 2.76 µM) and high drug targeting efficiency (7.64 ± 1.89-fold and 13.72 ± 4.1-fold) and direct transport percentages (86.12 ± 3.89 and 92.198 ± 2.09) for GMS-SLNs and PCL-PNs, respectively. The results also showed how different formulations, having different compositions and characteristics, could affect the cytotoxic and targeting ability.

Evolution of the Computational Pharmaceutics Approaches in the Modeling and Prediction of Drug Payload in Lipid and Polymeric Nanocarriers.

This review describes different trials to model and predict drug payload in lipid and polymeric nanocarriers. It traces the evolution of the field from the earliest attempts when numerous solubility and Flory-Huggins models were applied, to the emergence of molecular dynamic simulations and docking studies, until the exciting practically successful era of artificial intelligence and machine learning. Going through matching and poorly matching studies with the wet lab-dry lab results, many key aspects were reviewed and addressed in the form of sequential examples that highlighted both cases.