Pharmaceutical Research最新文献

Background: Mitochondria besides being the powerhouse of the cell are also involved in performing a multitude of critical cellular functions. Any failure in maintenance of these organelles is implicated in multiple human pathologies, including neurodegenerative disorders. Over the past two decades, significant efforts have been made to investigate the pharmacodynamic propensity of various potential compounds, which could be engaged as efficient therapeutic approach in modulating mitochondrial dynamics during neuronal dysfunctions.

Method: This review comprehensively overviews the contribution of potential compounds that could be employed as mitochondrial medicine in reversing neurological pathologies, with special focus on their significant roles as: metabolic antioxidants, conjugated molecules for mitochondrial function modulation, mitochondrial targeted peptides, optogenetic based induction of the mitochondria, potential mitochondrial biomarkers and other advanced transportation systems for mitochondrial delivery to brain.

Results and discussion: The manuscript discusses the mechanism of action of potential compounds (natural and pharmacologically synthesized), and other advance approaches that could efficiently modulate mitochondrial machinery in terms of regulating mitochondrial biogenesis, mitophagy, bioenergetics pathways, oxidative stress, calcium homeostasis and mitochondrial DNA stability.

Conclusion: The optimal maintenance of mitochondrial dynamics offered by variety of mitochondria targeting compounds highlights their prospective value for considering them as futuristic neurotherapeutic agents, which could be considered in managing neurodegenerative conditions.

Background: The beginning of precision medicine has come to rise in a new era of targeted therapies. Among these innovations, light-activatable antibody photo drug conjugates/photoimmunoconjugates termed as "PhotoBodies" have emerged as next-generation theranostic agents. By remaining inert until irradiated with a specific wavelength, PhotoBodies offer controlled diagnosis or treatment of diseased cells, tissues, or organs.

Objective: This review aims to summarize the evolution of new generation of photosensitizers, linkers, and antibody formats employed in PhotoBodies, to assess current preclinical and clinical developments, to identify unaddressed challenges, and propose a roadmap for future PhotoBodies.

Methods: We conducted a comprehensive literature survey focusing on studies reporting the designing and theranostic applications of PhotoBodies in both preclinical models and clinical trials.

Results: More than 15 PhotoBodies are currently in clinical trials for targeted diagnosis and two for therapeutic application in cancers. PhotoBodies have also demonstrated their flexibility to combat the silent pandemic of the world i.e., non-oncological. Advances in photosensitizer chemistry have improved photostability, singlet-oxygen quantum yield, and tissue penetration. From conventional antibodies (full length antibodies/mAb) to non-conventional antibodies (antibody fragments including Fab, F(ab')₂, scFv, diabodies, minibodies, and single-domain antibodies), all the formats have been explored to balance the pharmacokinetics of PhotoBodies with tissue accessibility. PolyBodies^® based antibody partners in PhotoBodies have begun to enhance the clinical utility of PhotoBodies by improving their targeting efficacy. However, promising future includes key hurdles such as optimizing light delivery in deep tissues, managing immunogenicity, standardizing conjugation protocols, and navigating regulatory pathways.

Conclusion: PhotoBodies represent a promising frontier in precision theranostics by combining the specificity of antibody targeting with the controllability of photochemistry. Continued refinement of photosensitizer, linkers and antibody engineering will accelerate the clinical translation of PhotoBodies and realize their full potential in next-generation precision medicine. PolyBodies (containing polyvalent and polyspecific) based antibody carriers possess an upper hand in changing the current landscape of PhotoBodies and redefine their future.

Purpose: Amorphous active pharmaceutical ingredients (APIs) are generally considered to have significantly higher bioavailability, compared to their crystalline counterpart, due to the enhanced solubility of the disordered phase. However, an akin functionality can be also adopted by the particle size of the powdered API. In this case study, a detailed investigation of the particle-size-influenced properties of amorphous griseofulvin powders will be introduced.

Methods: The crystallization of amorphous griseofulvin powders in the range 20 - 1000 μm (+ 2 - 10 μm only for crystalline form) was studied calorimetrically, spectroscopically, and microscopically. Dissolution profiles of pharmaceutical tablets with incorporated either amorphous or crystalline griseofulvin were obtained under conditions simulating the path through the gastrointestinal tract.

Results: Standard crystal growth regime was accompanied by the rapid diffusionless growth mode, which was detected at low heating rates for the finest griseofulvin powders. The dissolution profiles of the pharmaceutical tablets with incorporated individual griseofulvin powder fractions were described in terms of the Korsmeyer-Peppas model (indicating the release by super case II transport).

Conclusion: Particle size was found to play dominant role in the dissolution kinetics, whereas the difference in the dissolution rates of the crystalline and amorphous particles was rather negligible. This is a beneficial finding, considering the very low stability of finely powdered amorphous griseofulvin, but at the same time, it negates the primary purpose of amorphization. Main benefit is thus that of the coarse amorphous griseofulvin powder, which can be utilized to fine-tune the dissolution profile due to its delayed dissolution.

Objective: Pharmaceutical products are under constant development and improvements are continuously made. Implementing a change can have impact on the stability of the product. Comparing stability slopes of post-change batches monitored over short duration with those of pre-change batches monitored during long-term studies is not entirely straightforward as the longer the time frame the lower the uncertainty on the estimated slope, and therefore the pre-change and post-change slopes cannot be compared directly. The purpose is to develop a procedure making maximal use of all the information in the pre-change batches.

Methods: The knowledge in the complete pre-change data set in terms of slopes and variability is captured in a posterior distribution using a Bayesian analysis. Using this pre-change knowledge together with the time points used for a post-change batch, it is then studied if the observed slope of the post-change batch is in line with the predictive distribution for the post-change slope as based on the pre-change data.

Results: The proposed methodology is presented and applied to real data obtained in a stability comparability study at Merck & Co., Inc., Rahway, NJ, USA.

Conclusion: The method is suitable for assessing comparability of stability slopes.

Background: Thrombotic diseases remain a major global health burden. Current anticoagulants are often limited by bleeding risks and narrow therapeutic windows, largely due to their single-target mechanisms. In contrast, medicinal leeches secrete diverse peptides that naturally and synergistically modulate multiple steps of the hemostatic system.

Methods: This paper systematically reviews published biochemical, structural, functional, and omics studies on leech-derived anticoagulant peptides, classifying them according to their molecular targets and antithrombotic mechanisms.

Results: Leech-derived peptides act synergistically at multiple key points of the coagulation cascade: (1) they inhibit platelet adhesion and aggregation by blocking the vWF-collagen interaction or suppressing GPIIb/IIIa; (2) they directly inhibit core coagulation proteases, such as thrombin and factor Xa; and (3) they interfere with fibrin stabilization and promote its dissolution by inhibiting factor XIIIa or modulating the fibrinolytic and intrinsic protease systems. From a molecular perspective, multispecies omics analyses have revealed a significant expansion of antithrombotic gene families and identified numerous novel peptide candidate genes.

Conclusions: Leech-derived peptides provide a unique natural platform for multi-target anticoagulation and represent promising leads for next-generation antithrombotic agents. Combining traditional purification with genomics-guided discovery will accelerate mechanism elucidation, structural optimization, and translational development.

Purpose: This study investigated the phenomenon of polymorphism in the pharmaceutical salt riluzole salicylate with the aim to modify the aqueous solubility and dissolution rate of riluzole.

Methods: Preparation routes and transformation pathways were investigated using mechanoactivation, sonication, sublimation and melt crystallization. The thermal-induced phase transformations were interpreted by thermal microscopy and ex situ PXRD analysis. The crystal structure of Form 3 was solved from powder diffraction data. The differences in non-covalent interactions in crystals of Form 1 and Form 3 and their role in structure stabilization were studied by QTAIMC analysis, fingerprint plots, energy frameworks and lattice energy calculations. Cocrystallization thermodynamic functions and relationships between three polymorphs were established based on DSC, solubility and lattice energy data.

Results: Two novel polymorphs of riluzole salicylate with higher melting points were discovered and characterized in addition to reported Form 1. The stable Form 3 can be obtained easily by milling or from the slurry, while the metastable Form 2 forms only by melt crystallization or resublimation. Form 3 has stronger hydrogen bonding and more balanced non-covalent interactions than Form 1, making it thermodynamically favored at room temperature, while Form 1 is more stable near absolute zero.

Conclusion: Polymorphism significantly affects the pharmaceutical properties of riluzole salicylate. Selective preparation of polymorphs enables tuning of solubility and dissolution, linking crystal structure and thermodynamics to drug delivery optimization. Slower release kinetics of Form 1 compared to Form 3 and parent RLZ indicates its potential use as a prolonged form.

Objective: Lung cancer chemoprevention modalities are gaining wide attention as it is the second most diagnosed cancer type and the leading cause of cancer-related deaths. Our previous studies reported unique lung cancer chemoprevention capability with a repurposed drug combination of sulfasalazine (SAS) and disulfiram (DSF). However, their efficacy is limited by poor bioavailability. To overcome this challenge, we developed bioenhanced oil-in-water (o/w) nano self-emulsifying drug delivery system (Nano-SEDDS) formulations of SAS and DSF.

Methods: Unique isotropic Nano-SEDDS of SAS and DSF were developed and optimized using a single-step mix method followed by in vitro physicochemical characterization and stability studies. An in vivo pharmacokinetic and tissue-biodistribution study was undertaken to test the proposed hypothesis of bioavailability enhancement with Nano-SEDDS of SAS and DSF.

Results: The optimal Nano-SEDDS formulation exhibited low nanodroplet sizes (< 200 nm), high drug content, and 4.5-fold (p < 0.01) and 3.75-fold (p < 0.01) enhancement in in vitro dissolution of SAS and DSF compared to the respective free drugs. The Nano-SEDDS formulations were also confirmed to be stable at room temperature in compliance with ICH guidelines. Further, SAS Nano-SEDDS showed a dose-dependent increment in oral bioavailability as shown by a significant 7.9-fold (p < 0.0001) enhancement in dose-normalized AUC at a dose of 10 mg/kg compared to free drug treatment at a control dose of 250 mg/kg.

Conclusion: Overall, the studies corroborated the successful formulation of bioavailability-enhanced SAS and DSF Nano-SEDDS with future co-delivery applications for lung cancer prevention.

Nanoparticles (NPs), due to their small size and large surface area, have advanced their use as drug carriers for delivering various therapeutic molecules. When entering biological environments, nanoparticles typically adsorb proteins, forming a surface layer known as a protein corona that significantly affects the biological and therapeutic functions of a delivery system. Understanding and predicting protein adsorption is essential for optimizing nanoparticle design in drug delivery, diagnostics, and therapy. Machine learning and deep learning (ML/DL) offer promising methods for designing nanoparticles with specific properties, particularly given recent advancements in computation and nanoparticle analysis. This review explores ML/DL studies of nanoparticle-protein interactions and emphasizes the popularity of Random Forest (RF) and Deep Learning (DL) models in predicting protein corona compositions. RF models are highly valued for managing high-dimensional data and offering interpretability, which helps identify key NP features influencing protein adsorption. Conversely, DL excels at modeling non-linear relationships and detecting subtle interaction patterns. While most current research focuses on protein coronas, future models may also include other biocorona components. This is particularly relevant for soft materials, such as lipid nanoparticles (LNPs), which are now approved for delivering mRNA and peptide-based vaccines. Our findings underscore the need for advanced modeling techniques and high-quality, diverse experimental data to drive innovations in nanomedicine. Combining RF and DL approaches leverages their complementary strengths to overcome the challenge of limited experimental data and further improve NP designs for biomedical use.

Background: Therapeutic proteins are playing an increasingly important role in marketed drugs and clinical candidates. However, their development still faces major challenges, particularly aggregation.

Objectives: This review explores the recent advancements, current limitations, and future directions of new research methods for therapeutic proteins.

Results: Characterization techniques identify aggregation tendencies and elucidate underlying mechanisms, while computational chemistry provides microscopic insights into the aggregation process. Theoretical modeling and machine learning offer tools for predicting protein stability, enabling high-throughput screening in early formulation development.

Conclusion: Fostering interdisciplinary collaboration will be essential. The integration of diverse approaches offers a more comprehensive understanding of protein aggregation and unlocks new opportunities for innovation in protein formulation development.