Enhanced dissolution of amphotericin B through development of amorphous solid dispersions containing polymer and surfactants.

Amphotericin B (AmB) is the gold standard for antifungal therapy; however, its poor solubility limits its administration via intravenous infusion. A promising formulation strategy to achieve an oral formulation is the development of amorphous solid dispersions (ASDs) via spray-drying. Inclusion of surfactants into ASDs is a newer concept, yet it offers increased dissolution opportunities when combined with a polymer (HPMCAS 912). We developed both binary ASDs (AmB:HPMCAS 912 or AmB:surfactant) and ternary ASDs (AmB:HPMCAS 912:surfactant) using a variety of surfactants to determine the optimal surfactant carbon chain length and functional group for achieving maximal AmB concentration during in vitro dissolution. The ternary ASDs containing surfactants with a carbon chain length of 14 ± 2 carbons and a sulfate functional group increased the dissolution of AmB by 90-fold compared to crystalline AmB. These same surfactants, when added to a binary ASD, however, were only able to achieve up to a 40-fold increase, alluding to a potential interaction occurring between excipients or excipient and drug. This potential interaction was supported by dynamic light scattering data, in which the ternary formulation produced a single peak at 895.2 d.nm. The absence of more than one peak insinuates that all three components are interacting in some way to form a single structure, which may be preventing AmB self-aggregation, thus improving the dissolution concentration of AmB.

Development of a drying method for proteins based on protein-hyaluronic acid precipitation.

This study aims to develop a new method to dry proteins based on protein-hyaluronic acid (HA) precipitation and apply the precipitation-redissolution technique to develop highly concentrated protein formulations. Lysozyme was used as a model protein and HA with various molecular weights (MW) were investigated. Under low ionic strength, low-MW HA (e.g., MW: around 5 K) did not induce lysozyme precipitation. Conversely, high-MW HA (e.g., MW: approximately from 40 K to 1.5 M) precipitated more than 90 % of lysozyme. The dried lysozyme-HA precipitates had moisture levels between 4 % and 5 %. The lysozyme-HA precipitates could be redissolved using PBS (pH 7.4, ionic strength: ∼ 163 mM). The viscosity of the reconstituted solution was dependent on HA MW, e.g., 4 cP for HA40K, and 155 cP for HA1.5 M, suggesting low-MW HA might be a proper excipient for highly concentrated solution formulations for subcutaneous/intraocular injection and high-MW HA may fit for other applications. The tertiary structure of lysozyme after the precipitation-redissolution steps had no significant difference from that of the original lysozyme as confirmed by fluorescence spectroscopy. The denaturation temperature of lysozyme after the precipitation-redissolution steps and that of the original lysozyme were close, indicating they possessed similar thermal stability. The accelerated stability study revealed that lysozyme stored in the dry precipitates was more physically stable than that in the buffer solution. Overall, this new drying technique is suitable for drying proteins and exhibits several benefits such as minimum energy consumption, cost effectiveness, high production yield, and mild processing conditions. In addition, the precipitation-redissolution technique proposed in this study can potentially be used to develop highly concentrated formulations, especially for proteins experiencing poor stability in the liquid state.

Molecular Dynamics Simulation of an Iron(III) Binding Site on the Fc Domain of IgG1 Relevant for Visible Light-Induced Protein Fragmentation.

Molecular dynamics simulations were employed to investigate the interaction between Fe(III) and an iron-binding site composed of THR259, ASP252, and GLU261 on the Fc domain of an IgG1. The goal was to provide microscopic mechanistic information for the photochemical, iron-dependent site-specific oxidative fragmentation of IgG1 at THR259 reported in our previous paper. The distance between Fe(III) and residues of interest as well as the binding pocket size was examined for both protonated and deprotonated THR259. The Fe(III) binding free energy (ΔG) was estimated by using an umbrella sampling approach. The pKa shift of the THR259 hydroxyl group caused by the presence of nearby Fe(III) was estimated based on a thermodynamic cycle. The simulation results show that Fe(III) resides inside the proposed binding pocket and profoundly changes the pocket configuration. The ΔG values indicate that the pocket possesses a strong binding affinity for Fe(III). Furthermore, Fe(III) profoundly lowers the pKa value of the THR259 hydroxyl group by 5.4 pKa units.

Tuning sterol extraction kinetics yields a renal-sparing polyene antifungal.

Decades of previous efforts to develop renal-sparing polyene antifungals were misguided by the classic membrane permeabilization model1. Recently, the clinically vital but also highly renal-toxic small-molecule natural product amphotericin B was instead found to kill fungi primarily by forming extramembraneous sponge-like aggregates that extract ergosterol from lipid bilayers2-6. Here we show that rapid and selective extraction of fungal ergosterol can yield potent and renal-sparing polyene antifungals. Cholesterol extraction was found to drive the toxicity of amphotericin B to human renal cells. Our examination of high-resolution structures of amphotericin B sponges in sterol-free and sterol-bound states guided us to a promising structural derivative that does not bind cholesterol and is thus renal sparing. This derivative was also less potent because it extracts ergosterol more slowly. Selective acceleration of ergosterol extraction with a second structural modification yielded a new polyene, AM-2-19, that is renal sparing in mice and primary human renal cells, potent against hundreds of pathogenic fungal strains, resistance evasive following serial passage in vitro and highly efficacious in animal models of invasive fungal infections. Thus, rational tuning of the dynamics of interactions between small molecules may lead to better treatments for fungal infections that still kill millions of people annually7,8 and potentially other resistance-evasive antimicrobials, including those that have recently been shown to operate through supramolecular structures that target specific lipids9.

Development of Drug Release Model for Suspensions in ESCAR (Emulator of SubCutaneous Absorption and Release).

We recently developed an in vitro testing system, namely, ESCAR (Emulator of SubCutaneous Absorption and Release). The objective of this work was to investigate drug release behaviors of unmilled and milled suspensions in ESCAR. A mass transport-based model was developed to describe the multi-step drug release process, including drug dissolution, particle settling, drug distribution/partition, and drug permeation through the membrane(s). To address the particle settling effect, a correction factor was included in the model and its value was obtained by data fitting. It was found that, for both suspensions, (i) the experimental data of various dose/formulation combinations could be fit by the developed model; (ii) the dose effect on drug release was offset by the particle settling effect. This model may help to reduce experimental efforts and facilitate subcutaneous suspension formulation development using ESCAR.

Biorelevant Dissolution Method Considerations for the Appropriate Evaluation of Amorphous Solid Dispersions: are Two Stages Necessary?

Biorelevant dissolution testing has been widely used to better understand a drug or formulation's behavior in the human gastrointestinal (GI) tract. The successful evaluation of biorelevant dissolution behavior requires recognizing the importance of utilizing suitable biorelevant media in conjunction with an appropriate dissolution method, especially for supersaturating drug delivery systems, such as amorphous solid dispersions (ASDs). However, most conventional biorelevant dissolution testing methods are not able to accurately reflect the dissolution, supersaturation, and precipitation tendencies of a drug or formulation, which could misinform ASD formulation screening and optimization. In this study, we developed a single compartment 2-stage pH-shift dissolution testing method to simulate the changes in pH, media composition, and transit time in the GI tract, and results were compared against the conventional single compartment 1-stage dissolution method. Nine model drugs were selected based on their ionization properties (i.e. acid, base or neutral) and precipitation tendency (i.e. moderate or slow crystallizer). The dissolution results confirmed that 2-stage pH-shift dissolution is the preferred biorelevant dissolution method to assess non-ionized weak base (nifedipine) and neutral (griseofulvin) compounds exhibiting a moderate precipitation rate from solution when formulated as ASDs. Finally, we designed a flowchart guidance for the appropriate biorelevant dissolution performance characterization of different categories of ASD formulations.

Development of an In Vitro System To Emulate an In Vivo Subcutaneous Environment: Small Molecule Drug Assessment.

A reliable in vitro system can support and guide the development of subcutaneous (SC) drug products. Although several in vitro systems have been developed, they have some limitations, which may hinder them from getting more engaged in SC drug product development. This study sought to develop a novel in vitro system, namely, Emulator of SubCutaneous Absorption and Release (ESCAR), to better emulate the in vivo SC environment and predict the fate of drugs in SC delivery. ESCAR was designed using computer-aided design (CAD) software and fabricated using the three-dimensional (3D) printing technique. ESCAR has a design of two acceptor chambers representing the blood uptake pathway and the lymphatic uptake pathway, respectively, although only the blood uptake pathway was investigated for small molecules in this study. Via conducting a DoE factor screening study using acetaminophen solution, the relationship of the output (drug release from the "SC" chamber to the "blood circulation" chamber) and the input parameters could be modeled using a variety of methods, including polynomial equations, machine learning methods, and Monte Carlo simulation-based methods. The results suggested that the hyaluronic acid (HA) concentration was a critical parameter, whereas the influence of the injection volume and injection position was not substantial. An in vitro-in vivo correlation (IVIVC) study was developed using griseofulvin suspension to explore the feasibility of applying ESCAR in formulation development and bioequivalence studies. The developed LEVEL A IVIVC model demonstrated that the in vivo PK profile could be correlated with the in vitro release profile. Therefore, using this model, for new formulations, only in vitro studies need to be conducted in ESCAR, and in vivo studies might be waived. In conclusion, ESCAR had important implications for research and development and quality control of SC drug products. Future work would be focused on further optimizing ESCAR and expanding its applications via assessing more types of molecules and formulations.

Advanced Formulations/Drug Delivery Systems for Subcutaneous Delivery of Protein-Based Biotherapeutics.

Multiple advanced formulations and drug delivery systems (DDSs) have been developed to deliver protein-based biotherapeutics via the subcutaneous (SC) route. These formulations/DDSs include high-concentration solution, co-formulation of two or more proteins, large volume injection, protein cluster/complex, suspension, nanoparticle, microparticle, and hydrogel. These advanced systems provide clinical benefits related to efficacy and safety, but meanwhile, have more complicated formulations and manufacturing processes compared to conventional solution formulations. To develop a fit-for-purpose formulation/DDS for SC delivery, scientists need to consider multiple factors, such as the primary indication, targeted site, immunogenicity, compatibility, biopharmaceutics, patient compliance, etc. Next, they need to develop appropriate formulation (s) and manufacturing processes using the QbD principle and have a control strategy. This paper aims to provide a comprehensive review of advanced formulations/DDSs recently developed for SC delivery of proteins, as well as some knowledge gaps and potential strategies to narrow them through future research.

Investigating protein diffusivities in diluted hyaluronic acid solutions using dynamic light scattering.

This study aimed to investigate the diffusivities of lysozyme (LYS), ovalbumin (OVA), and hyaluronic acid (HA) in buffered solvents using dynamic light scattering (DLS). For protein/solvent and HA/solvent binary systems, the diffusion coefficients of protein or HA were obtained from autocorrelation function (ACF) curve fitting. Whereas, for protein/HA/solvent ternary systems, the two eigenvalues of the mutual diffusion coefficient matrix were obtained from ACF curve fitting. The results of binary systems showed that at low ionic strength, the diffusion coefficients of protein and HA increased linearly with concentration; at high ionic strength, the diffusion coefficients of OVA and LYS were independent on protein concentration; for HA, the positive linear relationship between diffusion coefficient and concentration existed at high and low ionic strengths, but the slope at high ionic strength was smaller compared to that at low ionic strength. For OVA/HA/solvent ternary systems, the sum of two eigenvalues (D1DLS + D2DLS) was slightly smaller compared to (DOVA + DHA), where DOVA and DHA were the diffusion coefficients in their binary systems. On the contrary, for LYS/HA/solvent ternary systems, (D1DLS + D2DLS) were significantly smaller than (DLYS + DHA) and the diffusion coefficients in binary and ternary systems exhibited an opposite trend with respect to ionic strength change. The DLS and MD simulation results indicated strong attractive intermolecular interaction existed between LYS and HA molecules, especially at low ionic strength. By using DLS, it was possible to characterize the diffusion coefficients of diluted protein/HA binary and ternary systems.

Do Macrocyclic Peptide Drugs Interact with Bile Salts under Simulated Gastrointestinal Conditions?

Peptide drugs face several barriers to oral delivery, including enzymatic degradation in the gastrointestinal tract and low membrane permeability. Importantly, the direct interaction between various biorelevant colloids (i.e., bile salt micelles and bile salt-phospholipid mixed micelles) present in the aqueous gastrointestinal environment and peptide drug molecules has not been studied. In this work, we systematically characterized interactions between a water-soluble model peptide drug, octreotide, and a range of physiologically relevant bile salts in solution. Octreotide membrane flux in pure bile salt solutions and commercially available biorelevant media, i.e., fasted state simulated intestinal fluid (FaSSIF) and fed state simulated intestinal fluid (FeSSIF), was evaluated using a side-by-side diffusion cell equipped with a cellulose dialysis membrane. All seven micellar bile salt solutions as well as FaSSIF and FeSSIF decreased octreotide membrane flux, and dihydroxy bile salts were found to have a much larger effect than trihydroxy bile salts. An inverse relationship between octreotide membrane flux and pancreatic enzymatic stability was also observed; bile salt micelles and bile salt-phospholipid mixed micelles provided a protective effect toward enzymatic degradation and prolonged octreotide half-life in vitro. Diffusion ordered nuclear magnetic resonance (DOSY NMR) spectroscopy and dynamic light scattering (DLS) were used as complementary experimental techniques to confirm peptide-micelle interactions in solution. Experiments were also performed using desmopressin as a second model peptide drug; desmopressin interacted with bile salts in solution, albeit to a lower extent relative to octreotide. The findings described herein demonstrate that amphiphilic, water-soluble peptide drugs do interact with bile salts and phospholipids in solution, with an effect on peptide membrane flux and enzymatic stability. Correspondingly, oral peptide drug absorption and bioavailability may be impacted.

Particle Size Limits to Pass the Acceptance Value (AV)-Based USP Content Uniformity Test for Tablets.

The papers published by Yalkowsky et al. and Rohrs et al. offer a method to correlate the probability of passing USP content uniformity (CU) test with maximum allowed particle size and distribution. Their work also provides a guidance for setting the particle size specification especially for a low dose drug. However, their methods are developed based on the previous USP CU test and the up-to-date version of USP/NF (e.g., USP42/NF37) has adopted a new Acceptance Value (AV)-based CU criterion. In this study, using the same assumptions and conditions that are utilized in their papers, we develop a new method to calculate the upper limit of particle size that ensures the pass of the AV-based CU test at a given probability (e.g., 0.99). It turns out that, compared to the previous CU test (e.g., the CU test in USP28/NF23), to pass the AV-based CU test, similar but slightly smaller particle size is needed.

Simulating particle movement inside subcutaneous injection site simulator (SCISSOR) using Monte-Carlo method.

This study used Monte Carlo method to simulate particle movement inside a commercialized instrument called Subcutaneous Injection Site Simulator (SCISSOR). A series of parameters related to instrument, injection device, operation, formulation, as well as medium were thoroughly investigated. Also, several events that particles may occur in the subcutaneous (SC) space, including diffusion, binding, and aggregation, were implemented in our Monte Carlo based algorithms. The simulation result revealed that membrane area and position, diffusivity in the simulated SC medium, as well as injection position significantly affected release profile. Diffusivity in the injection volume could only influence release profile when this diffusivity was extremely low. Other factors, including initial injection shape, injection volume, and formulation concentration, had only minor impact on release profile. In addition, binding slowed down release, whereas aggregation reduced both total percentage of release and release rate. This study presented Monte Carlo method would potentially become a powerful tool to support multiple development activities related to experimental design, parameter sensitivity analysis, and control strategy development.

Applications of Machine Learning in Solid Oral Dosage Form Development.

This review comprehensively summarizes the application of machine learning in solid oral dosage form development over the past three decades. In both academia and industry, machine learning is increasingly applied for multiple preformulation/formulation and process development studies. Further, this review provides the authors' perspectives on how pharmaceutical scientists can use machine learning for right projects and in right ways; some key ingredients include (1) the determination of inputs, outputs, and objectives; (2) the generation of a database containing high-quality data; (3) the development of machine learning models based on dataset training and model optimization; (4) the application of trained models in making predictions for new samples. It is expected by the authors and others that machine learning will promisingly play a more important role in tomorrow's projects for solid oral dosage form development.

Investigating the Influence of Tablet Location Inside Dissolution Test Apparatus on Polymer Erosion and Drug Release of a Surface-Erodible Sustained-Release Tablet Using Computational Simulation Methods.

The objective of this work was to investigate the influence of tablet location along the bottom of a USP apparatus II vessel on polymer erosion and drug release of surface-erodible sustained-release tablets using computational simulation methods. Computational fluid dynamics (CFD) methods were performed to simulate the velocity distribution. A mathematical model was developed to describe polymer erosion and tablet deformation according to the mass transfer coefficient. Numerical analysis was used to simulate drug release controlled by drug diffusion and polymer erosion. The results indicated that tablets located at the off-center position deformed faster than the tablets located at the center position. However, tablet location had no profound impact on drug release rate since all drug release profiles were "similar" according to the f2 similarity values which were above 50. Hence, our simulation supported that the USP apparatus II was a reliable and robust device for the dissolution testing of surface-erodible sustained-release tablets.

Machine Learning Attempts for Predicting Human Subcutaneous Bioavailability of Monoclonal Antibodies.

PURPOSE: One knowledge gap related to subcutaneous (SC) delivery is unpredictable and variable bioavailability. This study was aimed to develop machine learning methods to predict whether mAb's bioavailability was ≥70% or below, without completely knowing the mechanism and causality between inputs and outputs. METHODS: A database of mAb SC products was built. The model training and validation were accomplished based on this database and a set of the inputs (product properties) were mapped to the output (bioavailability) using different machine learning algorithms. Dimensionality reduction was undertaken using principal component analysis (PCA). RESULTS: The bioavailability of the mAb products being investigated varied from 35% to 90%. The tree-based methods, including random forest (RF), Adaptive Boost (AdaBoost), and decision tree (DT) presented the best predictability and generalization power on bioavailability classification. The models based on Multi-layer perceptron (MLP), Gaussian Naïve Bayes (GaussianNB), and k nearest neighbor (kNN) algorithms also provided acceptable prediction accuracy. CONCLUSION: Machine learning could be a potential tool to predict mAb's bioavailability. Since all input features were acquired using theoretical calculations and predictions rather than experiments, the models may be particularly applicable to some early-stage research activities such as mAb molecule triage, design/optimization, mutant screening, molecule selection, and formulation design.

Enhancing Intestinal Absorption of a Model Macromolecule via the Paracellular Pathway using E-Cadherin Peptides.

Membrane permeation enhancers have received significant attention in recent years for enabling the oral absorption of poorly permeable drug molecules. In this study, we investigated the ability of His-Ala-Val (HAV) and Ala-Asp-Thr (ADT) peptides derived from the extracellular-1 (EC1) domain of E-cadherin proteins to increase the paracellular permeation and intestinal bioavailability of the poorly permeable model macromolecule, fluorescein-isothiocyanate dextran with average molecular weight 4000 (FD4). The in vitro enzymatic stability of linear and cyclic E-cadherin peptides was characterized under simulated gastric and intestinal conditions, and the cyclic E-cadherin peptides, HAVN1 and ADTC5, which demonstrated excellent stability in vitro, were advanced to in vivo intestinal instillation studies and compared against the established surfactant membrane permeation enhancer, sodium caprate (C10). Cyclic HAVN1 and ADTC5 peptides increased FD4 bioavailability by 7.2- and 4.4-fold compared to control, respectively (not statistically significant). In contrast, C10 provided a statistically significant 10.7-fold relative bioavailability enhancement for FD4. Importantly, this study represents the first report of cyclic E-cadherin peptides as intestinal membrane permeation enhancers. The findings described herein demonstrate the potential of enzymatically stabilized cyclic E-cadherin peptides for increasing poorly permeable drug absorption via the oral route.

The application of machine learning algorithms in understanding the effect of core/shell technique on improving powder compactability.

This study systemically investigated the application of core/shell technique to improve powder compactability. A 28-run Design-of-Experiment (DoE) was conducted to evaluate the effects of the type of core and shell materials and their concentrations on tensile strength and brittleness index. Six machine learning algorithms were used to model the relationships of product profile outputs and raw material attribute inputs: response surface methodology (RSM), Support Vector Machine (SVM), and four different types of artificial neural networks (ANN), namely, Backpropagation Neural Network (BPNN), Genetic Algorithm Based BPNN (GA-BPNN), Mind Evolutionary Algorithm Based BPNN (MEA-BPNN), and Extreme Learning Machine (ELM). Their predictive and generalization performance were compared with the training dataset as well as an external dataset. The results indicated that the core/shell technique significantly improved powder compactability over the physical mixture. All machine learning algorithms being evaluated provided acceptable predictability and capability of generalization; furthermore, the ANN algorithms were shown to be more capable of handling convoluted and non-linear patterns of dataset (i.e. the DoE dataset in this study). Using these models, the relationship of product profile outputs and raw material attribute inputs were disclosed and visualized.

Preparation of lapatinib ditosylate solid dispersions using solvent rotary evaporation and hot melt extrusion for solubility and dissolution enhancement.

The objective of this study was to enhance solubility and dissolution of lapatinib (LB) ditosylate (DT) using solid dispersions (SD) prepared by solvent rotary evaporation (SRE) and hot melt extrusion (HME). A series of models based on solubility parameter, the solid-liquid equilibrium equation, and the Flory-Huggins equation were employed to provide insight to data and evaluate drug/polymer interactions. Experimentally, nine SD formulas were prepared and characterized by various analytical techniques including differential scanning calorimetry (DSC), powder X-ray diffraction (PXRD), scanning electron microscope (SEM), solubility, and dissolution. It was found that both material attributes (e.g., drug loading and solid state) and process parameters (e.g., extrusion temperature) significantly affected manufacturability and solubility/dissolution behaviors. Among the formulas investigated, Formula #9 containing LB-DT, Soluplus®, and poloxamer 188 at a weight ratio of 1:3:1 was screened as the first ranked one. While comparing production routes, the SDs prepared by SRE showed more amorphicity as well as higher solubility/dissolution. This study provided the insight of introducing theoretical models to guide SD formulation/process development and illustrating the potential of bioavailability enhancement for LB-DT.

The expanding role of prodrugs in contemporary drug design and development.

Prodrugs are molecules with little or no pharmacological activity that are converted to the active parent drug in vivo by enzymatic or chemical reactions or by a combination of the two. Prodrugs have evolved from being serendipitously discovered or used as a salvage effort to being intentionally designed. Such efforts can avoid drug development challenges that limit formulation options or result in unacceptable biopharmaceutical or pharmacokinetic performance, or poor targeting. In the past 10 years, the US Food and Drug Administration has approved at least 30 prodrugs, which accounts for more than 12% of all approved small-molecule new chemical entities. In this Review, we highlight prodrug design strategies for improved formulation and pharmacokinetic and targeting properties, with a focus on the most recently marketed prodrugs. We also discuss preclinical and clinical challenges and considerations in prodrug design and development.

Oral Delivery of Highly Lipophilic, Poorly Water-Soluble Drugs: Self-Emulsifying Drug Delivery Systems to Improve Oral Absorption and Enable High-Dose Toxicology Studies of a Cholesteryl Ester Transfer Protein Inhibitor in Preclinical Species.

BMS-A is an inhibitor of cholesteryl ester transfer protein and is a highly lipophilic compound (clogP 10.5) with poor aqueous solubility (<0.0001 mg/mL at pH 6.5). The compound exhibits low oral exposure when dosed as cosolvent solution formulations. The purpose of this study was to evaluate lipid-based formulations for enabling high-dose toxicology studies and enhancing toxicology margins of BMS-A in preclinical studies in nonrodent species. The solubility of BMS-A was screened in lipid and cosolvent/surfactant excipients, and prototype formulations were developed. In vitro tests showed that fine/microemulsions were formed after aqueous dilution of lipid formulations, and BMS-A was transferred from oil phase to aqueous phase with enhanced solubility following lipid digestion. When dosed in dogs at 200 mg/kg, a Gelucire-based formulation exhibited more than 10-fold higher exposure compared to the solution formulation and was thus selected for toxicology studies in dogs. For monkeys, an olive oil formulation was developed, and the exposure was about 7-fold higher than that from the solution. In summary, lipid-based drug delivery could be applied in early stages of drug discovery to enhance oral exposure and enable preclinical toxicology studies of highly lipophilic compounds, while facilitating the candidate selection of a molecule which is more specifically designed for bioperformance in a lipid-based drug delivery strategy.