Constructing an In Silico Three-Class Predictor of Human Intestinal Absorption With Caco-2 Permeability and Dried-DMSO Solubility

Absorption of drugs is the first step after dosing, and it largely affects drug bioavailability. Hence, estimating the fraction of absorption (Fa) in humans is important in the early stages of drug discovery. To achieve correct exclusion of low Fa compounds and retention of potential compounds, we developed a freely available model to classify compounds into 3 levels of Fa capacity using only the chemical structure. To improve Fa prediction, we added predicted binary classification results of membrane permeability measured using Caco-2 cell line (Papp) and dried–dimethyl sulfoxide solubility (accuracy, 0.836; kappa, 0.560). The constructed models can be accessed via a web application.     

Molecular Dynamics Simulation to Uncover the Mechanisms of Protein Instability During Freezing

Freezing is a common process applied in the pharmaceutical industry to store and transport biotherapeutics. Herewith, multi-scale molecular dynamics simulations of Lactate dehydrogenase (LDH) protein in phosphate buffer with/without ice formation performed to uncover the still poorly understood mechanisms and molecular details of protein destabilization upon freezing. Both fast and slow ice growing conditions were simulated at 243 K from one or two-side of the simulation box, respectively. The rate of ice formation at all-atom simulations was crucial to LDH stability, as faster freezing rates resulted in enhanced structural stability maintained by a higher number of intramolecular hydrogen bonds, less flexible protein's residues, lower solvent accessibility and greater structural compactness. Further, protein aggregation investigated by coarse-grained simulations was verified to be initiated by extended protein structures and retained by electrostatic interactions of the salt bridges between charged residues and hydrogen bonds between polar residues of the protein. Lastly, the study of free energy of dissociation through steered molecular dynamics simulation revealed LDH was destabilized by the solvation of the hydrophobic core and the loss of hydrophobic interactions. For the first time, experimentally validated molecular simulations revealed the detailed mechanisms of LDH destabilization upon ice formation and cryoconcentration of solutes.     

Bile acid coordinates microbiota homeostasis and systemic immunometabolism in cardiometabolic diseases

Cardiometabolic disease (CMD), characterized with metabolic disorder triggered cardiovascular events, is a leading cause of death and disability. Metabolic disorders trigger chronic low-grade inflammation, and actually, a new concept of metaflammation has been proposed to define the state of metabolism connected with immunological adaptations. Amongst the continuously increased list of systemic metabolites in regulation of immune system, bile acids (BAs) represent a distinct class of metabolites implicated in the whole process of CMD development because of its multifaceted roles in shaping systemic immunometabolism. BAs can directly modulate the immune system by either boosting or inhibiting inflammatory responses via diverse mechanisms. Moreover, BAs are key determinants in maintaining the dynamic communication between the host and microbiota. Importantly, BAs via targeting Farnesoid X receptor (FXR) and diverse other nuclear receptors play key roles in regulating metabolic homeostasis of lipids, glucose, and amino acids. Moreover, BAs axis per se is susceptible to inflammatory and metabolic intervention, and thereby BAs axis may constitute a reciprocal regulatory loop in metaflammation. We thus propose that BAs axis represents a core coordinator in integrating systemic immunometabolism implicated in the process of CMD. We provide an updated summary and an intensive discussion about how BAs shape both the innate and adaptive immune system, and how BAs axis function as a core coordinator in integrating metabolic disorder to chronic inflammation in conditions of CMD.     

Prediction Accuracy of Mechanism-Based Oral Absorption Model for Dogs

The purpose of the present study was to evaluate the prediction accuracy of a mechanism-based oral absorption model for the fraction of a dose absorbed (Fa) in dogs, focusing on poorly soluble drugs. As an open mechanism-based model, the gastrointestinal unified theoretical framework was used in this study. The prediction accuracy of the gastrointestinal unified theoretical framework was evaluated using Fa data in dogs (63 data sets for marketed drugs and proprietary compounds). For neutral compounds, Fa was accurately predicted, suggesting that the physiological parameters of dogs were appropriate except for gastrointestinal pH. An extensive literature survey on the small intestinal pH of dogs was then conducted. The result suggested that the pH value ranged between 6.5 and 7.5, with the midst value of 7.0, but there was a great variation among the literature. To confirm the appropriateness of this pH value, the Fa of free acid compounds was predicted by setting the small intestinal pH to 6.5, 7.0, and 7.5. The proportions of compounds with <2-fold error were 57%, 90%, and 76%, respectively. The results of the present study would enable an appropriate use of a mechanism-based model for drug discovery and development.     

Application of a High Throughput and Automated Workflow to Therapeutic Protein Formulation Development

Rapid and efficient formulation development is critical to successfully bringing therapeutic protein drug products into a competitive market under increasingly aggressive timelines. Conventional application of high throughput techniques for formulation development have been limited to lower protein concentrations, which are not applicable to late stage development of high concentration therapeutics. In this work, we present a high throughput (HT) formulation workflow that enables screening at representative concentrations via integration of a micro-buffer exchange system with automated analytical instruments. The operational recommendations associated with the use of such HT systems as well as the efficiencies gained (reduction in hands-on time and run time by over 70% and 30%, respectively), which enable practical characterization of an expanded formulation design space, are discussed. To demonstrate that the workflow is fit for purpose, the formulation properties and stability profiles (SEC and CEX) from samples generated by the HT workflow were compared to those processed by ultrafiltration/diafiltration, and the results were shown to be in good agreement. This approach was further applied to two case studies, one focused on a formulation screen that studied the effects of pH and excipient on viscosity and stability, and the other focused on selection of an appropriate viscosity mimic solution for a protein product.     

Applying Two Orthogonal Methods to Assess Accuracy of Plasma Protein Binding Measurements for Highly Bound Compounds

Significant advances have been made over the years to accurately measure plasma protein binding (PPB) of highly bound compounds. However, because of perceived uncertainty based on historical suboptimal methods and limitation of radiochemical purity of radiolabeled materials, current regulatory guidelines recommend using an arbitrary cutoff fraction unbound (f_u) of 0.01 as the lower limit for drug-drug interaction (DDI) prediction. This can result in significant overprediction of DDI for highly bound compounds, unnecessary DDI clinical trials and more restrictive drug product labels. To build confidence in the accuracy of PPB measurement for highly bound compounds, 2 orthogonal methods, equilibrium dialysis and ultracentrifugation, are assessed in this study to measure PPB of 10 highly bound drugs (f_u < 0.01). The results show that the 2 very different methods yield comparable f_u values, generally within 2-fold of each other. The data suggest that PPB of highly bound compounds can be measured accurately using current state-of-art methods, and the experimental f_u should be used for DDI prediction to provide a more realistic evaluation of DDI risk in the clinic.     

Predicting the Molecular Mechanism of EGFR Domain II Dimer Binding Interface by Machine Learning to Identify Potent Small Molecule Inhibitor for Treatment of Cancer

Epidermal growth factor receptor (EGFR) is a transmembrane druggable target controlling cellular differentiation, proliferation, migration, survival and invasion. EGFR activation mainly occurs by its homo/hetro dimerization molecular phenomenon leading to tumor development and invasion. Several tyrosine kinase based inhibitors were discovered as potent anti-cancer drugs. However, mutations in its kinase domain confer resistance to most of these drugs. To overcome this drug resistance, development of small molecule inhibitors disrupting the EGFR Domain II dimer binding by machine learning methods are promising. Based on this insight, a structure-based drug repurposing strategy was adopted to repurpose the existing FDA approved drugs in blocking the EGFR Domain II mediated dimerization. We identified five best repurposed drug molecules showing good binding affinity at its key arm-cavity dimer interface residues by different machine learning methods. The molecular mechanisms of action of these repurposed drugs were computationally validated by molecular electrostatics potential mapping, point mutations at the dimer arm-cavity binding interface, molecular docking and receptor interaction studies. The present machine learning strategy thus forms the basis of identifying potent and putative small molecule drugs for the treatment of different types of cancer.     

A Novel Fluorescence-Based Method to Evaluate Ileal Apical Sodium-Dependent Bile Acid Transporter ASBT

This study aimed to demonstrate usefulness of the fluorophore-labeled bile acid derivative, N-(24-[7-(4-N,N-dimethylaminosulfonyl-2,1,3-benzoxadiazole)]amino-3α,7α,12α-trihydroxy-27-nor-5β-cholestan-26-oyl)-2′-aminoethane sulfonate (tauro-nor-THCA-24-DBD) as a substrate of apical sodium-dependent bile acid transporter (ASBT, SLC10A2), which is expressed at distal ileum for reabsorption of bile acids and to find a novel fluorescence-based method to evaluate ASBT activity. In HPLC analysis, chromatogram of tauro-nor-THCA-24-DBD showed double peaks: R- and S-isomers of the compound. When ASBT was expressed in Xenopus laevis oocytes, their uptakes were higher than those by control oocytes, demonstrating both are transported by ASBT. Therefore, results were analyzed separately as peak 1, peak 2 and sum of them. Concentration dependent uptake of tauro-nor-THCA-24-DBD in ASBT-expressing oocytes was saturable with Km 122 μM and Vmax 1.49 pmol/oocyte/30 min for peak 1, 30.7 μM and 1.34 pmol/oocyte/30 min for peak 2, and 40.6 μM and 2.36 pmol/oocyte/30 min for sum, respectively. These uptakes were decreased in the presence of taurocholic acid and in the Na⁺ free condition. Furthermore, in Caco-2 cells, tauro-nor-THCA-24-DBD uptake was also Na⁺-dependent and saturable. Additionally, these uptakes were decreased by elobixibat, a selective ASBT inhibitor. Accordingly, it was concluded that tauro-nor-THCA-24-DBD is a substrate of ASBT and useful to evaluate the intestinal ASBT transport activity.     

Design of a Novel Nucleus-Targeted NLS-KALA-SA Nanocarrier to Delivery Poorly Water-Soluble Anti-Tumor Drug for Lung Cancer Treatment

In this study, we designed a novel nucleus-targeted nanocarrier (NLS-KALA-SA, NKSN) consisting of Kala peptide (KALA), nuclear localization signal (NLS) and stearic acid (SA) using Fmoc solid phase synthesis method. We chose Curcumin (CUR), Paclitaxel (PTX), Ginsenoside compound K(CK) as models of poorly water-soluble antitumor drugs, The drugs loaded NLS-KALA-SA nanoparticles (CUR/NKSN, PTX/NKSN, CK/NKSN) were obained by the dialysis method, their physicochemical properties were determined and antitumor activity were evaluated. The NLS-KALA-SA nanoparticles were spherical shaped with an average size of 76.4 ± 7.6 mm and a zeta potential of 43.7 ± 5.8 mV. The drug-loaded NLS-KALA-SA nanoparticles were above 86.1% and 17.1% in entrapment efficiency and drug loading capacity, and had sustained drug release behavior. Biodistribution and cellular uptake study exhibited that PTX/NKSN mainly distributed in tumor site of A549-bearing mice, and coumarin-6(C6) loaded NLS-KALA-SA nanoparticle (C6/NKSN) was predominantly accumulated in the nucleus of A549 cells. Western blot analysis indicated that PTX/NKSN could more remarkably inhibit Bcl-2 expression and enhance the expression of Bax and Caspase-3 as compared to the controls in A549 cells. Cell apoptosis and antitumor activity study showed that PXT/NKSN could more obviously induce apoptosis of A549 cells compared with free PXT, the PTX/NKSN administration was more effective than free PTX for lung cancer treatment and displayed mild toxicity in A549-bearing mice. The results demonstrates that the NLS-KALA-SA nanoparticles system could enhance the antitumor effects of the encapsulated drug and reduce tissue toxicity due to its long circulating properties and tumor targeting, which might provide a promising strategy for lung cancer treatment.     

Extended Characterization and Impact of Visible Fatty Acid Particles - A Case Study With a mAb Product

In recent years, there has been increased scrutiny on the presence and formation of product-related particles in biopharmaceutical formulations. These types of particles, originating from the degradation of the active pharmaceutical ingredient or the excipients, can be challenging to identify and characterize due to their fragility. Additionally, the mechanisms of their formation as well as the impact of their presence on drug product safety can be complicated to elucidate. In this work, a case study is presented in which multiple batches of one formulated monoclonal antibody (mAb-A) were analyzed at different batch ages to better understand the formation of visible particles resulting from degradation of the surfactant polysorbate 20. The particle identity was determined by Raman spectroscopy as free fatty acid (FFA) and the particle composition over time was monitored by mass spectrometry. Further experimental work includes the counts and morphologies of subvisible particles by flow imaging microscopy. Finally, we evaluated the consequences of saline and human plasma exposure to the visible particles to better understand their fate upon dilution and/or administration which is routinely performed in the clinical setting. The experiments performed in this work can be used to support risk assessments of visible product-related particles.     

Development of Pyro-Drive Jet Injector With Controllable Jet Pressure

Various jet injectors have been developed and used for the effective and efficient administration of drugs. Jet injections overcome the limitations of other drug delivery methods, such as ablation, iontophoresis, electroporation, sonophoresis, and microneedles, because jet injection is not limited by the diffusion rates of different drugs. However, controlling the jet pressure during drug delivery is difficult with most conventional jet injectors. Efficacy evaluation of such devices on laboratory animals is strongly required before initiating human clinical trials, but minimal research has been performed for the device developments. Therefore, we developed jet injector devices based on pyrotechnics using 2 types of explosives with different burning rates; we call these pyro-drive jet injectors. The liquid jet pressure profile suggests that the penetration depth and injection volume for soft materials and skin tissue are controllable. Here, we propose the pyro-drive jet injectors as another candidate well-controlled jet injector for laboratory animals in drug discovery testing as well as human clinical use.     

Interaction of Differently Coated Silver Nanoparticles With Skin and Oral Mucosal Cells

Silver nanoparticles (AgNP) can be found in different consumer products and various medical devices due to their excellent biocidal properties. Despite extensive scientific literature reporting biological effects of AgNP, there is still a lack of scientific evidence on how different surface functionalization affects AgNP interaction with the human skin and the oral epithelium.This study aimed to investigate biological consequences following the treatment of HaCaT and TR146 cells with AgNP stabilized with negatively charged sodium bis(2-ethylhexyl)-sulfosuccinate (AOT), neutral polyvinylpyrrolidone (PVP), and positively charged poly-l-lysine (PLL). All AgNP were characterized by means of size, shape and surface charge. Interactions with biological barriers were investigated in vitro by determining cell viability, particle uptake, oxidative stress response and DNA damages following AgNP treatment. Results showed a significant difference in cytotoxicity depending on the surface coating used for AgNP stabilization. All three types of AgNP induced apoptosis, oxidative stress response and DNA damages in cells, but AOT- and PVP-coated AgNP exhibited lower toxicity than positively charged PLL-AgNP.Considering the number of data gaps related to the safe use of nanomaterials in biomedicine, this study highlights the importance of particle surface functionalization that should be considered during design and development of future AgNP-based medical products.     

Evaluation of a 3D Human Artificial Lymph Node as Test Model for the Assessment of Immunogenicity of Protein Aggregates

The immunogenicity of protein aggregates has been investigated in numerous studies. Nevertheless, it is still unknown which kind of protein aggregates enhance immunogenicity the most. The ability of the currently used in vitro and in vivo systems regarding their predictability of immunogenicity in humans is often questionable, and results are partially contradictive. In this study, we used a 2D in vitro assay and a complex 3D human artificial lymph node model to predict the immunogenicity of protein aggregates of bevacizumab and adalimumab. The monoclonal antibodies were exposed to different stress conditions such as light, heat, and mechanical stress to trigger the formation of protein aggregates and particles, and samples were analyzed thoroughly. Cells and culture supernatants were harvested and analyzed for dendritic cell marker and cytokines. Our study in the artificial lymph node model revealed that bevacizumab after exposure to heat triggered a TH1- and proinflammatory immune response, whereas no trend of immune responses was seen for adalimumab after exposure to different stress conditions. The human artificial lymph node model represents a new test model for testing the immunogenicity of protein aggregates combining the relevance of a 3D human system with the rather easy handling of an in vitro setup.     

Simultaneous Analysis of Dissolution and Permeation Profiles of Nanosized and Microsized Formulations of Indomethacin Using the In Vitro Dissolution Absorption System 2

The in vitro dissolution absorption system 2 (IDAS2), a recent invention comprised a conventional dissolution vessel containing 2 permeation chambers with Caco-2 cell monolayers mounted with their apical side facing the dissolution media, permits simultaneous measurement of dissolution and permeation of drugs from intact clinical dosage forms. The objectives of this study were (1) to assess the utility of IDAS2 in the determination of the effect of particle size on in vitro performance of indomethacin and (2) to find out whether the behavior in IDAS2 of 2 indomethacin products differing in particle size is correlated with their in vivo behavior. Indomethacin dissolution and permeation across Caco-2 cell monolayers were simultaneously measured in IDAS2; the dissolution and permeation profiles were simultaneously modeled using a simple two-compartment model. Compared to microsized indomethacin, the nanosized formulation increased the dissolution rate constant by fivefold, whereas moderately increasing the permeation rate constant and the kinetic solubility. As a result, the drug amount permeated across the Caco-2 cell monolayers doubled in the nanosized versus microsized formulation. The in vitro results showed a good correlation with in vivo human oral pharmacokinetic parameters, thus emphasizing the physiological relevance of IDAS2 data in predicting in vivo absorption.     

Investigating a Modified Apparatus to Discriminate the Dissolution Capacity In Vitro and Establish an IVIVC of Mycophenolate Mofetil Tablets in the Fed State

In this study, a modified dissolution apparatus was developed by equipping a USP apparatus Ⅰ with an open-loop system to discriminate the dissolution capacity in vitro and establish an in vitro and in vivo correlation (IVIVC) for mycophenolate mofetil (MMF) tablets. MMF had strong pH-dependent solubility that could influence the dissolution rate in vivo after the meal. Dissolution tests involving reference (Cellcept®) and test formulations (F1 and F2) were conducted using pH 4.5 acetate buffer to simulate gastric fluids in the fed state. The dissolution profiles of the reference and test formulations were distinguished by using the modified dissolution apparatus and compared with those determined using the USP apparatuses Ⅱ and Ⅳ, and the dissolution capacities of the formulations were discriminated at different sampling time-points. The results of human bioequivalence (BE) studies in the fed state were consistent with in vitro evaluations that the maximum concentrations (C_{max, in vivo}) of both F1 and F2 fell below the acceptable range (80.00%). A level A IVIVC between the absorption fraction in vivo and dissolution in vitro, and a level C correlation between C_{max, in vivo} and C_{max, in vitro}, were established to guide the optimization of the tablet formulation containing MMF.     

Applying Pattern Recognition as a Robust Approach for Silicone Oil Droplet Identification in Flow-Microscopy Images of Protein Formulations

Discrimination between potentially immunogenic protein aggregates and harmless pharmaceutical components, like silicone oil, is critical for drug development. Flow imaging techniques allow to measure and, in principle, classify subvisible particles in protein therapeutics. However, automated approaches for silicone oil discrimination are still lacking robustness in terms of accuracy and transferability. In this work, we present an image-based filter that can reliably identify silicone oil particles in protein therapeutics across a wide range of parenteral products. A two-step classification approach is designed for automated silicone oil droplet discrimination, based on particle images generated with a flow imaging instrument. Distinct from previously published methods, our novel image-based filter is trained using silicone oil droplet images only and is, thus, independent of the type of protein samples imaged. Benchmarked against alternative approaches, the proposed filter showed best overall performance in categorizing silicone oil and non-oil particles taken from a variety of protein solutions. Excellent accuracy was observed particularly for higher resolution images. The image-based filter can successfully distinguish silicone oil particles with high accuracy in protein solutions not used for creating the filter, showcasing its high transferability and potential for wide applicability in biopharmaceutical studies.     

A practical strategy to develop isoform-selective near-infrared fluorescent probes for human cytochrome P450 enzymes

Currently, the development of selective fluorescent probes toward targeted enzymes is still a great challenge, due to the existence of numerous isoenzymes that share similar catalytic capacity. Herein, a double-filtering strategy was established to effectively develop isoenzyme-specific fluorescent probe(s) for cytochrome P450 (CYP) which are key enzymes involving in metabolism of endogenous substances and drugs. In the first-stage of our filtering approach, near-infrared (NIR) fluorophores with alkoxyl group were prepared for the screening of CYP-activated fluorescent substrates using a CYPs-dependent incubation system. In the second stage of our filtering approach, these candidates were further screened using reverse protein-ligand docking to effectively determine CYP isoenzyme-specific probe(s). Using our double-filtering approach, probes S9 and S10 were successfully developed for the real-time and selective detection of CYP2C9 and CYP2J2, respectively, to facilitate high-throughput screening and assessment of CYP2C9-mediated clinical drug interaction risks and CYP2J2-associated disease diagnosis. These observations suggest that our strategy could be used to develop the isoform-specific probes for CYPs.