Pharmaceutical Research最新文献

Angelica gigas Nakai (AGN) root is a medicinal herbal widely used in traditional medicine in Korea. AGN root ethanolic extracts have been marketed as dietary supplements in the United States for memory health and pain management. We have recently reviewed the pharmacokinetics (PK) and first-pass hepatic metabolism of ingested AGN supplements in humans for the signature pyranocoumarins decursin (D, C_max 1x), decursinol angelate (DA, C_max ~ 10x) and their common botanical precursor and hepatic metabolite decursinol (DOH, C_max ~ 1000x). Here we update in vivo medicinal activities of AGN and/or its pyranocoumarins and furanocoumarin nodakenin in cancer, pain, memory loss, cerebral ischemia reperfusion stroke, metabolic syndrome and vascular endothelial dysfunctions, anxiety, sleep disorder, epilepsy, inflammatory bowel disease, osteoporosis and osteoarthritis. Given their polypharmacology nature, the pertinent mechanisms of action are likely misrepresented by many cell culture studies that did not consider the drug metabolism knowledge. We report here Rho-associated protein kinases (ROCK1/2) as novel targets for DA and DOH. Combining with published inhibitory activity of DOH on acetylcholinesterase, agonist activity of DOH and antagonist/degrader activity of DA/D on androgen and estrogen receptors, D/DA promoting activity for glutamic acid decarboxylase (GAD)- gamma-aminobutyric acid (GABA) inhibitory axis and inhibition of glutamate dehydrogenase (GDH), monoamine oxidase-A (MAO-A) and transient receptor potential vanilloid 1 (TRPV1), we postulate their contributions to neuro-cognitive, metabolic, oncologic, vascular and other beneficial bioactivities of AGN extracts. A clinical trial is being planned for an AGN extract to manage side effects of androgen deprivation therapy in prostate cancer patients.

Purpose: Drug-induced liver injury, or DILI, affects numerous patients and also presents significant challenges in drug development. It has been attempted to predict DILI of a chemical by in silico approaches, including data-driven machine learning models. Herein, we report a recent DILI deep-learning effort that utilized our molecular representation concept by manifold embedding electronic attributes on a molecular surface.

Methods: Local electronic attributes on a molecular surface were mapped to a lower-dimensional embedding of the surface manifold. Such an embedding was featurized in a matrix form and used in a deep-learning model as molecular input. The model was trained by a well-curated dataset and tested through cross-validations.

Results: Our DILI prediction yielded superior results to the literature-reported efforts, suggesting that manifold embedding of electronic quantities on a molecular surface enables machine learning of molecular properties, including DILI.

Conclusions: The concept encodes the quantum information of a molecule that governs intermolecular interactions, potentially facilitating the deep-learning model development and training.

Background: High concentration protein formulation (HCPF) development needs to balance protein stability attributes such as conformational/colloidal stability, chemical stability, and solution properties such as viscosity and osmolality.

Methodology: A three-phase design is established in this work. In Phase 1, conformational and colloidal stability are measured by 384-well-based high-throughput (HT) biophysical screening while viscosity reduction screening is performed with HT viscosity screening. Collectively, the biophysical and viscosity screening data are leveraged to design the phase 2 of short-term stability study, executed using 96-well plates under thermal and freeze/thaw stresses. In phase 2, samples are analyzed by stability-indicating assays and processed with pair-wise Student's t-test analyses to choose the final formulations. In phase 3, the final formulations are then confirmed through a one-month accelerated stability in glass vials.

Results: Using a model antibody A (mAb-A), the initial HT screening successfully established the 384-well based platform. A lead formulation was chosen from the second round based on statistical analyses and subsequently tested against the commercial formulation of mAb-A as a control. Compared to the control, the lead formulation reduced the viscosity of mAb-A by 30% and decreased subvisible particles after thermal stress by 80%.

Conclusions: HT biophysical screening in 384-well plates was demonstrated to effectively guide the rational design of a high-throughput stability screening study using 96-well plates. This platform enables the identification of a high concentration formulation within seven weeks within the first two phases of study that strategically balance stability with solution properties, thus achieving a rapid development of HCPF.

Objective: Ulcerative colitis (UC) treatment currently faces multiple challenges including adverse effects, prolonged therapy durations, and high costs. Baicalin (BA) has demonstrated anti-inflammatory benefits for inflammatory bowel disease, and the objective of this scholarly work is to address the challenges associated with the poor aqueous solubility and diminished oral bioavailability of the compound in question, thereby offering an innovative therapeutic approach for the management of ulcerative colitis.

Methods: We developed a baicalin-arginine complex (BA-Arg) by screening for suitable basic compounds and utilizing a freeze-drying method, resulting in an amorphous solid dispersion of BA.

Results: Our findings revealed that BA·Arg significantly enhances the intestinal absorption and transmembrane transport of BA without inducing toxicity in Caco-2 cells. Pharmacokinetic studies in healthy Wistar rats demonstrated significantly higher plasma concentrations of BA compared to free BA. In a mouse model induced by 3.5% dextran sodium sulfate, BA·Arg treatment markedly alleviated colitis symptoms as evidenced by reduced inflammatory cell infiltration, decreased lymphocyte aggregation in the colon, and better preservation of intestinal mucosa. This improved the overall anti-colitis efficacy of BA.

Conclusions: Overall, our study presents a simple, eco-friendly formulation process that enhances BA solubility without the need for organic solvents, offering a practical and sustainable solution for developing BA-based therapies for UC.

Objective: Microfluidics has emerged as a promising technique to prepare nanoparticles. However, the current microfluidic devices are mainly chip-based and are often integrated into expensive systems that lack on-the-spot versatility. The aim of this study was to set up a modular microfluidic system based on low-cost capillaries and reusable, easy-to-clean building blocks that can prepare poly(D,L-lactic-co-glycolic acid) (PLGA) nanoparticles with and without incorporated water-soluble biomacromolecules.

Methods: A two-syringe system variant of the microfluidic system was set up to prepare PLGA particles and to investigate how the flow rates, solvents, and PLGA concentrations impacted the PLGA nanoparticle formation. A three-syringe system was designed to examine the incorporation of proteins into the PLGA particles.

Results: The formation of the nanoparticles was affected by the PLGA concentration in the organic solvent, where an increasing concentration led to larger particle diameters (33-180 nm), and by the total flow rate, where an increase in the total flow rate led to smaller nanoparticles (197-77 nm). Using ultrapure water as the aqueous solvent resulted in precipitation at the outlet at higher PLGA concentrations. Aqueous poly(vinyl alcohol) created neutral particles in contrast to the negatively charged particles obtained with ultrapure water or an ethanol-water mixture. Incorporation of the proteins ovalbumin or lysozyme with a three-syringe system resulted in encapsulation efficiencies above 40%.

Conclusion: A cheap and easily adjustable modular microfluidic system was developed to prepare PLGA nanoparticles with highly reproducible particle diameters that can effectively be loaded with proteins for drug and vaccine delivery.

The unique potential of nanomedicine to address challenging health issues is rapidly advancing the field, leading to the generation of more effective products. However, these complex systems often pose several challenges with respect to their design for specific functionality, scalable manufacturing, characterization, quality control, and clinical translation. In this regard, the application of artificial intelligence (AI) and machine learning (ML) approaches can enable faster and more accurate data assessment, identifying trends and predicting outcomes, leading to efficient nanomedicine product development. This perspective paper discusses the potential of AI and ML in nanomedicine product development with a focus on their applications in discovery, assessment, manufacturing, and clinical trials. The potential limitations of AI and ML approaches in nanomedicine product development are also covered.

Objective: Malignant pleural mesothelioma (MPM) is the most prevalent subtype of malignant mesothelioma that affects the pleural lining of the lungs. Conventionally, chemotherapy via systemic injections has shown limited efficacy due to off-target effects, and inefficacious deposition at the disease site. In our previous study, we reported the development and optimization of UV-initiated methacrylate gelatin (GelMa)-acrylamide based hydrogel formulation for local intracavitary administration of therapies. The current study utilizes a pre-established GelMa formulation for delivering a small molecule chemotherapeutic agent, Doxorubicin (Dox), against in-vitro MPM models.

Methods: Dox-loaded hydrogel (DLH) precursor solution was prepared by dissolving Dox in the precursor solution. The gels were characterized for physical properties such as gelling time, swelling index, bio adhesion, and injectability and were compared to blank hydrogels. Dox-loaded hydrogels were also tested for therapeutic efficacy in MPM cells in various 2D and 3D cell culture models.

Results: It was revealed that Dox-loaded hydrogels retained similar physical properties, including gelling time (< 25 s), swelling index (~ 1,200%), bio-adhesion (> 20 g detachment force), and injectability (< 2N force for injecting precursor), compared to blank hydrogels. Moreover, the gel formulation effectively sustained the release of hydrophilic Dox HCl over a period of 12 days by increasing the degree of crosslinking between GelMa and its crosslinkers. Further, the therapeutic efficacy of Dox was retained even after loading into hydrogels, indicating that no chemical interactions took place between gel excipients and the drug. Studies in MPM cell-based models revealed that DLH showed excellent potential in inhibiting 2D and 3D cell growth, with DLH being more effective than plain Dox in suppressing tumor growth in 3D spheroid models.

Conclusions: Overall, the results of the present study suggest that Dox-loaded hydrogels (DLH) may be a good candidate for efficacy study in preclinical mesothelioma models, with strong potential for clinical translation.

Purposes: Antibody-drug conjugate (ADC) size variants are frequently assessed by size exclusion chromatography (SEC). However, poor chromatography performance is often observed during SEC analysis. Existing studies have primarily focused on qualitatively describing non-specific interactions between ADCs and the column matrix. The purposes of the current study are to introduce an underlying cause from a novel perspective on the protein-protein interaction (PPI) mechanism, characterized by quantifying diffusion interaction parameter (k_D) values, and to provide several strategies to reduce PPI and improve column performance during SEC analysis.

Methods: Two kinds of ADCs with varying hydrophobicity properties and their corresponding monoclonal antibodies are used as models. The hydrophobicity of these products was verified using the relative calculated logarithm of the partition coefficient of a substance in n-octanol (oil) and water (rCLogP) and reversed-phase high performance liquid chromatography (RP-HPLC), and the size variants were analyzed using SEC. Finally, the PPI was characterized by k_D values of these four products.

Results: The results of rCLogP and RP-HPLC indicated that ADC-1 is relatively hydrophobic, whereas ADC-2 is relatively hydrophilic. In the SEC analysis of the ADC-1, substituting sodium chloride with L-arginine hydrochloride or adding a specific concentration of acetonitrile as an organic solvent to the mobile phase resulted in reduced PPI and enhanced column performance. Conversely, the impact on ADC-2 was negligible.

Conclusions: This study provides insights into improving the performance of SEC analysis for ADCs through strategies involving alterations in mobile phase composition. The changes in column performance can be quantitatively explained by the PPI mechanism.

Purpose: Typical clinical "in use" conditions for topical semisolids involve their application as a thin film, often with rubbing that can induce metamorphic stress. Yet, product quality and performance tests often characterize the manufactured product, and may not consider product metamorphosis (e.g., shear history) during dispensing and administration. This work sought to elucidate how such metamorphosis might alter product quality and performance.

Methods: We evaluated the effect of "in use" stresses on drug crystal metamorphosis in acyclovir creams by optical microscopy. The amount of dissolved acyclovir was determined by separation of the cream base by ultra-centrifugation and quantification by HPLC. IVPT was undertaken on Zovirax^® US and Aciclostad^® comparing static and "in use" application of a finite dose. A mechanistic IVPT study was also conducted to understand the influence of acyclovir particle size reduction by "in use" rubbing on skin permeation.

Results: Reduction in acyclovir particle size was seen after "in use" rubbing with increases in the amount of dissolved acyclovir after rubbing (30 and 60 s) compared to static for both products. "In use" application resulted in significantly higher acyclovir permeation from both products. The mechanistic IVPT study proved the role of product metamorphosis.

Conclusion: These results highlight the role of metamorphosis of product microstructure and its influence on performance.