Biological Drug Development Research Articles

Synthetic Biology‐Based Engineering Cells for Drug Delivery

ABSTRACTAlthough drug delivery technology has promoted the clinical translation of small molecule drugs, there is an urgent need for advanced delivery systems to overcome complex physiological barriers and the increasing development of biological drugs. This review overviews the emerging applications of synthetic biology‐based engineered cells for drug delivery. We first introduce synthetic biology strategies to engineer cells for biological drug delivery and discuss the benefits in terms of specificity, intelligence, and controllability. Furthermore, we highlight the cutting‐edge advancements at the convergence of synthetic biology and nanotechnology in drug delivery. Nanotechnology expands the engineering design and construction concepts of synthetic biology, and synthetic biology drives the development for biotechnology‐driven nanomaterial synthesis. In the future, synthetic biology‐based engineered cells may be developed to be more modular, standardized, and intelligent, leading to significant breakthroughs in the construction of advanced drug delivery systems.

Target protein identification in live cells and organisms with a non-diffusive proximity tagging system.

Identifying target proteins for bioactive molecules is essential for understanding their mechanisms, developing improved derivatives, and minimizing off-target effects. Despite advances in target identification (target-ID) technologies, significant challenges remain, impeding drug development. Most target-ID methods use cell lysates, but maintaining an intact cellular context is vital for capturing specific drug-protein interactions, such as those with transient protein complexes and membrane-associated proteins. To address these limitations, we developed POST-IT (Pup-On-target for Small molecule Target Identification Technology), a non-diffusive proximity tagging system for live cells, orthogonal to the eukaryotic system. POST-IT utilizes an engineered fusion of proteasomal accessory factor A and HaloTag to transfer Pup to proximal proteins upon directly binding to the small molecule. After significant optimization to eliminate self-pupylation and polypupylation, minimize depupylation, and optimize chemical linkers, POST-IT successfully identified known targets and discovered a new binder, SEPHS2, for dasatinib, and VPS37C as a new target for hydroxychloroquine, enhancing our understanding these drugs' mechanisms of action. Furthermore, we demonstrated the application of POST-IT in live zebrafish embryos, highlighting its potential for broad biological research and drug development.

Disulfide-Directed Multicyclic Peptides with N-Terminally Extendable α-Helices for Recognition and Activation of G Protein-Coupled Receptors.

Many peptide hormones adopt long α-helical structures upon interacting with their cognate receptors but often exhibit flexible conformations when unbound. Strategies that can stabilize long α-helices without disrupting their binding to receptors are still lacking, which hinders progress in their biological applications and drug development. Here, we present an approach that combines rational design with library screening to create and identify a unique disulfide-directed multicyclic peptide (DDMP) scaffold, which could effectively stabilize N-terminally extendable α-helices while displaying exceptional efficiency in disulfide pairing and oxidative folding. This DDMP scaffold was then utilized for stabilizing the α-helical structure of glucagon-like peptide-1 (GLP-1), resulting in a potent GLP-1 receptor (GLP-1R) agonist with a significantly improved α-helicity and proteolytic stability. By incorporating external α-helices into the DDMP scaffold, we can effectively preserve the native N-terminal α-helical structures while allowing for extensive evolution of the C-terminal disulfide-rich domain for enhancing target binding, as demonstrated by the generation of the DDMP-stabilized GLP-1 (g1:Ox). The cryo-electron microscopy structure of the g1:Ox-GLP-1R in complex with heterotrimeric Gs reveals the molecular basis for the potent binding between g1:Ox and GLP-1R. Specifically, the DDMP moiety establishes additional interactions with the extracellular domain of GLP-1R, which are absent in the case of GLP-1. Thus, this work offers a novel and effective approach for engineering therapeutic peptides and other peptide α-helices, ensuring that both the N- and C-terminal regions remain essential for target recognition and activation.

PreMLS: The undersampling technique based on ClusterCentroids to predict multiple lysine sites.

The translated protein undergoes a specific modification process, which involves the formation of covalent bonds on lysine residues and the attachment of small chemical moieties. The protein's fundamental physicochemical properties undergo a significant alteration. The change significantly alters the proteins' 3D structure and activity, enabling them to modulate key physiological processes. The modulation encompasses inhibiting cancer cell growth, delaying ovarian aging, regulating metabolic diseases, and ameliorating depression. Consequently, the identification and comprehension of post-translational lysine modifications hold substantial value in the realms of biological research and drug development. Post-translational modifications (PTMs) at lysine (K) sites are among the most common protein modifications. However, research on K-PTMs has been largely centered on identifying individual modification types, with a relative scarcity of balanced data analysis techniques. In this study, a classification system is developed for the prediction of concurrent multiple modifications at a single lysine residue. Initially, a well-established multi-label position-specific triad amino acid propensity algorithm is utilized for feature encoding. Subsequently, PreMLS: a novel ClusterCentroids undersampling algorithm based on MiniBatchKmeans was introduced to eliminate redundant or similar major class samples, thereby mitigating the issue of class imbalance. A convolutional neural network architecture was specifically constructed for the analysis of biological sequences to predict multiple lysine modification sites. The model, evaluated through five-fold cross-validation and independent testing, was found to significantly outperform existing models such as iMul-kSite and predML-Site. The results presented here aid in prioritizing potential lysine modification sites, facilitating subsequent biological assays and advancing pharmaceutical research. To enhance accessibility, an open-access predictive script has been crafted for the multi-label predictive model developed in this study.

Structure‐based design of antibodies targeting the EBNA1 DNA‐binding domain to block Epstein–Barr virus latent infection and tumor growth

AbstractThe Epstein–Barr virus (EBV) nuclear antigen 1 (EBNA1) is critically involved in maintaining episomes during latent infection and promoting tumorigenesis. The development of an epitope‐specific monoclonal antibody (mAb) for EBNA1 holds great promise due to its high affinity and specificity, offering a new and innovative approach for the treatment of EBV‐related diseases. In this proof‐of‐concept study, we employed a structure‐based design strategy to create three unique immunogens specifically targeting the DNA binding state of the EBNA1 DBD. By immunizing mice, we successfully generated a mAb, named 5E2‐12, which selectively targets the DNA binding interface of EBNA1. The 5E2‐12 mAb effectively disrupts the interaction between EBNA1 and DNA binding, resulting in reduced proliferation of EBV‐positive cells and inhibition of xenograft tumor growth in both cellular assays and mouse tumor models. These findings open up new avenues for the development of innovative biological macromolecular drugs that specifically target EBNA1 and provide potential for clinical therapy options for early‐stage EBV‐positive tumors. The epitope‐specific mAb approach demonstrates novelty and innovation in tackling EBV‐related diseases and may have broad implications for precision medicine strategies in the field of viral‐associated cancers.

Gene expression prediction from histology images via hypergraph neural networks.

Spatial transcriptomics reveals the spatial distribution of genes in complex tissues, providing crucial insights into biological processes, disease mechanisms, and drug development. The prediction of gene expression based on cost-effective histology images is a promising yet challenging field of research. Existing methods for gene prediction from histology images exhibit two major limitations. First, they ignore the intricate relationship between cell morphological information and gene expression. Second, these methods do not fully utilize the different latent stages of features extracted from the images. To address these limitations, we propose a novel hypergraph neural network model, HGGEP, to predict gene expressions from histology images. HGGEP includes a gradient enhancement module to enhance the model's perception of cell morphological information. A lightweight backbone network extracts multiple latent stage features from the image, followed by attention mechanisms to refine the representation of features at each latent stage and capture their relations with nearby features. To explore higher-order associations among multiple latent stage features, we stack them and feed into the hypergraph to establish associations among features at different scales. Experimental results on multiple datasets from disease samples including cancers and tumor disease, demonstrate the superior performance of our HGGEP model than existing methods.

Benefits of a Juvenile Arthritis Support Program (JASP-1) for children recently diagnosed with Juvenile Idiopathic Arthritis and their parents

BackgroundMedical treatment for children with Juvenile Idiopathic Arthritis (JIA) has improved radically since the development of biological disease-modifying antirheumatic drugs. However, children suffer from pain and anxiety, and parents often experience loneliness and lack of support. Some parents reported that information provided at the time their child was diagnosed could be difficult to assimilate. Therefore, the aim of this study was to develop a Juvenile Arthritis Support Program (JASP-1) for children recently diagnosed with JIA and their parents. Moreover, the aim was to explore patients´ and parents´ experiences with JASP-1 and its potential impact on patients´ physical health.MethodsJASP-1 included seven patient- and family-centered clinical visit from time of diagnose and one year ahead. Data were collected from a study-specific questionnaire answered by children and their parents after participation in JASP-1 and from the pediatric rheumatology register. The study-specific questionnaire explored participants´ experience with the care they received during their first year with JIA. Registry and questionnaire data from the intervention (JASP-1) group was compared to a control group.ResultsThe analysis revealed that children and parents who completed JASP-1 were more satisfied with the care they had received during their first year with JIA than the control group. The results also showed that children who completed JASP-1 were assessed as having better overall health after 12 months, than children in the control group (JASP-1 = mean 4.33, 95% Confidence Interval (CI) 4.17 − 4.46), (Control = mean 3.68, 95% CI 3.29 − 4.06), (p = 0.002). Moreover, children in the JASP-1 group had less disease impact on daily life (JASP-1 = mean 0.15, 95% CI 0.07 − 0.24) (Control = mean 0.40, 95% CI 0.13 − 0.67), (p = 0.017) and less active joints than the control group (JASP-1 = mean 0.62, 95% CI 0.35 − 1.58), (Control = mean 0.87, 95% CI 0.18 − 1.56), (p = 0.054).ConclusionA support program like JASP-1 could be an effective way of not only supporting children newly diagnosed with JIA and their parents psychologically but may also increase children’s overall physical health and improve quality of care within pediatric rheumatology.Trial registrationRetrospectively registered in ClinicalTrials.gov, the 13th of February with ID NCT06284616.

Mimicking chirality floralform heterostructure: A multivariate metal-based nanoparticles with highly charge transformation interface and multivariate recognition

Enantioselective identification of chiral molecules holds immense significance in the fields of biological processes, chemical reactions, and drug development due to the optical rotation properties of enantiomers. Moreover, the chiral nanocomposite plays an important role in capable of selectively interacting with specific chiral molecules. By utilizing the chiral surfaces of metal polyphenol framework, an enantioselective identification chiral nanocomposite is fabricated on polyphenol colloidal spheres (PCS). The multivariate metal-based nanocomposite use L-tartaric acid (TA) and copper as a chiral recognition selector and signal corrector, aminothiophenol (PATP) anchoring Ag NPs as artificial traction skeleton. Applying L-/ D-cysteine as patterns enantiomers, the chiral recognition selector Cu- L-TA framework perform stereoselective recognition of target molecules through strong affinity and hydrogen interaction. The discriminative SERS signal and CT-related totally symmetric (a1) value of Cu- PCS@Ag NPs and PATP molecules is regarded as discriminating part and internal standard to correct the signal drifting. The put forward method has a good linearity in the concentration range of 1 nM ∼ 10 mM and detection limits as low as 0.37 pM and 0.30 pM for L/D-Cys. This work provides specific method for the chiral molecule recognition and determination in complex matrix sample.

Comprehensive Review on Bimolecular Fluorescence Complementation and Its Application in Deciphering Protein-Protein Interactions in Cell Signaling Pathways.

Signaling pathways are responsible for transmitting information between cells and regulating cell growth, differentiation, and death. Proteins in cells form complexes by interacting with each other through specific structural domains, playing a crucial role in various biological functions and cell signaling pathways. Protein-protein interactions (PPIs) within cell signaling pathways are essential for signal transmission and regulation. The spatiotemporal features of PPIs in signaling pathways are crucial for comprehending the regulatory mechanisms of signal transduction. Bimolecular fluorescence complementation (BiFC) is one kind of imaging tool for the direct visualization of PPIs in living cells and has been widely utilized to uncover novel PPIs in various organisms. BiFC demonstrates significant potential for application in various areas of biological research, drug development, disease diagnosis and treatment, and other related fields. This review systematically summarizes and analyzes the technical advancement of BiFC and its utilization in elucidating PPIs within established cell signaling pathways, including TOR, PI3K/Akt, Wnt/β-catenin, NF-κB, and MAPK. Additionally, it explores the application of this technology in revealing PPIs within the plant hormone signaling pathways of ethylene, auxin, Gibberellin, and abscisic acid. Using BiFC in conjunction with CRISPR-Cas9, live-cell imaging, and ultra-high-resolution microscopy will enhance our comprehension of PPIs in cell signaling pathways.

Establishment of an Embryo Implantation Model In Vitro.

Embryo implantation is the first step in the establishment of a successful pregnancy. An in vitro model for embryo implantation is critical for basic biological research, drug development, and screening. This paper presents a simple, rapid, and highly efficient in vitro model for embryo implantation. In this protocol, we first introduce mouse blastocyst acquisition and human endometrial adenocarcinoma cells (Ishikawa)preparation for implantation, followed by the co-culture method for mouse embryos and Ishikawa cells. Finally, we conducted a study to assess the impact of varying concentrations of 17-β-estradiol (E2) and progesterone (P4) on embryo adhesion rates based on this model. Our findings revealed that high concentrations of E2 significantly reduced embryo adhesion, whereas the addition of progesterone could restore the adhesion rate. This model offers a simple and fast platform for evaluating and screening molecules involved in the adhesion process, such as cytokines, drugs, and transcription factors controlling implantation and endometrial receptivity.

Group sparse-based Taylor expansion method for liver pharmacokinetic parameters imaging of dynamic fluorescence molecular tomography

Objective. Pharmacokinetic parametric images obtained through dynamic fluorescence molecular tomography (DFMT) has ability of capturing dynamic changes in fluorescence concentration, thereby providing three-dimensional metabolic information for applications in biological research and drug development. However, data processing of DFMT is time-consuming, involves a vast amount of data, and the problem itself is ill-posed, which significantly limits the application of pharmacokinetic parametric images reconstruction. In this study, group sparse-based Taylor expansion method is proposed to address these problems. Approach. Firstly, Taylor expansion framework is introduced to reduce time and computational cost. Secondly, group sparsity based on structural prior is introduced to improve reconstruction accuracy. Thirdly, alternating iterative solution based on accelerated gradient descent algorithm is introduced to solve the problem. Main results. Numerical simulation and in vivo experimental results demonstrate that, in comparison to existing methods, the proposed approach significantly enhances reconstruction speed without a degradation of quality, particularly when confronted with background fluorescence interference from other organs. Significance. Our research greatly reduces time and computational cost, providing strong support for real-time monitoring of liver metabolism.

Dehydroxylative radical N-glycosylation of heterocycles with 1-hydroxycarbohydrates enabled by copper metallaphotoredox catalysis

N-Glycosylated heterocycles play important roles in biological systems and drug development. The synthesis of these compounds heavily relies on ionic N-glycosylation, which is usually constrained by factors such as labile glycosyl donors, precious metal catalysts, and stringent conditions. Herein, we report a dehydroxylative radical method for synthesizing N-glycosides by leveraging copper metallaphotoredox catalysis, in which stable and readily available 1-hydroxy carbohydrates are activated for direct N-glycosylation. Our method employs inexpensive photo- and copper- catalysts and can tolerate some extent of water. The reaction exhibits a broad substrate scope, encompassing 76 examples, and demonstrates high stereoselectivity, favoring 1,2-trans selectivity for furanoses and α-selectivity for pyranoses. It also exhibits high site-selectivity for substrates containing multiple N-atoms. The synthetic utility is showcased through the late-stage functionalization of bioactive compounds and pharmaceuticals like Olaparib, Axitinib, and Metaxalone. Mechanistic studies prove the presence of glycosyl radicals and the importance of copper metallaphotoredox catalysis.

The Role of Interleukin 23/17 Axis in Psoriasis Management: A Comprehensive Review of Clinical Trials.

Psoriasis pathogenesis is influenced by genetic factors and characterized by a complex interplay between genetic predisposition and various environmental triggers. These triggers set off metabolic processes involving inflammation, cell signaling, immune response dysregulation, and antigen presentation. Several types of innate and adaptive immune cells are involved in psoriasis. Among the cytokine cascade which leads to psoriasis development, the interleukin (IL)-23/Th17 axis, especially IL-17 production, emerges as crucial. Recognizing the pivotal role of this axis has facilitated the development of selective and effective biological drugs, such as anti-IL17 and anti-IL23 monoclonal antibodies. These drugs aim to achieve the complete or near-complete disappearance of psoriatic lesions, as indicated by PASI100 and PASI90 responses, respectively. In this context, the aim of our review was to delve into the functioning of the IL-23/Th17 axis, its dysregulation in psoriasis pathogenesis, and the therapeutic potential of its inhibition. Currently, 4 anti-IL17 (secukinumab, ixekizumab, bimekizumab and brodalumab) and 3 anti-IL23 (guselkumab, risankizumab and tildrakizumab) have been approved. All these drugs showed high levels of effectiveness in both clinical trials and real-life experiences, with an excellent profile in terms of safety. Certainly, furthers studies will allow for better characterization of biologics' profile, in order to administer the right drug for the right patients at the right moment.

Precision medicine to personalize medicine in allergic airway disease.

The purpose of this study is to understand the approach to precision medicine and personalized medicine in the management of allergic airway disease. Identification of biomarkers as key tools used in precision medicine has led to the development of multiple biologic drugs being used as new treatments for allergic airway disease. In addition to these advances, there is still much needed effort to improve the feasibility and utility of integrating biologic omics data of precision medicine with physicochemical, behavioral, psychological, and social data to deliver optimized treatments that is personalized for each individual.

A triggered DNA nanomachine with enzyme-free for the rapid detection of telomerase activity in a one-step method

BackgroundTelomerase is considered a biomarker for the early diagnosis and clinical treatment of cancer. The rapid and sensitive detection of telomerase activity is crucial to biological research, clinical diagnosis, and drug development. However, the main obstacles facing the current telomerase activity assay are the cumbersome and time-consuming procedure, the easy degradation of the telomerase RNA template and the need for additional proteases. Therefore, it is necessary to construct a new method for the detection of telomerase activity with easy steps, efficient reaction and strong anti-interference ability. ResultsHerein, an efficient, enzyme-free, economical, sensitive, fluorometric detection method for telomerase activity in one-step, named triggered-DNA (T-DNA) nanomachine, was created based on target-triggered DNAzyme-cleavage activity and catalytic molecular beacon (CMB). Telomerase served as a switch and extended few numbers of (TTAGGG)n repeat sequences to initiate the signal amplification in the T-DNA nanomachine, resulting in a strong fluorescent signal. The reaction was a one-step method with a shortened time of 1 h and a constant temperature of 37 °C, without the addition of any protease. It also sensitively distinguished telomerase activity in various cell lines. The T-DNA nanomachine offered a detection limit of 12 HeLa cells μL−1, 9 SK-Hep-1 cells μL−1 and 3 HuH-7 cells μL−1 with a linear correlation detection range of 0.39 × 102–6.25 × 102 HeLa cells μL−1 for telomerase activity. SignificanceIn conclusion, our study demonstrated that the triggered-DNA nanomachine fulfills the requirements for rapid detection of telomerase activity in one-step under isothermal and enzyme-free conditions with excellent specificity, and its simple and stable structure makes it ideal for complex systems. These findings indicated the application prospect of DNA nanomachines in clinical diagnostics and provided new insights into the field of DNA nanomachine-based bioanalysis.

Cyclodepsipeptides: Isolation, Bioactivities, Biosynthesis and Total Synthesis

Abstract: Cyclodepsipeptides, mainly derived from marine organisms and soil microorganisms, are amphiphilic molecules consisting of short oligopeptides with fatty acid tails attached to form a macrocyclic structure. Studies on the activity of cyclodepsipeptides have shown that they have cytotoxicity, antibacterial and anthelmintic effects, and are widely used in biological control, drug development, environmental remediation and disease treatment. Cyclodepsipeptides play a prominent role in the development of new drugs and drug lead compounds, especially as antibiotics with great medicinal potentiall, and are slowly seeping into the public consciousness. The biosynthesis of cyclodepsipeptides is mainly based on the synthesis of non-ribosomal peptide synthases, and selection of key regulatory enzymes for homologue regulation and biosynthetic strategies using genetic engineering and metabolic engineering approaches. The biosynthesis method is miniaturised, recyclable, and safer. The total synthesis methods of cyclodepsipeptides are mainly combined solid-liquid phase methods, which synthesise cyclodepsipeptides faster and are easy to purify. This paper reviews the biological activities of cyclodepsipeptides, their biosynthesis, and total synthesis.

Methodological and regulatory aspects of pharmaceutical development of biological products

The aim of the work was to conduct an analysis of the current state and current trends in the approval of drugs, as well as some aspects of the methodology for their development based on biological molecules and registration.Materials and methods. The material for the analysis was taken from the abstract databases of PubMed, Google Scholar and e-library.ru. The search was carried out using publications for the period from 2008 to 2023, the keywords were as follows: “biologicals”, “new drug approval”, “drug authorization”, “drug development”, “biosimilar”, taking into account various spellings.Results. Over the past 15 years, scientists have been observing revolutionary trends and processes in the field of the drug development, especially biopharmaceuticals. Significant advances have been made in gene, immune and cell therapies, resulting in the approval of such drugs more than doubling over the past ten years. The development of biological drugs includes the identification and testing of molecular targets and requires a deep understanding of the structure and functioning of the polypeptides involved in the development of the effect. The features of these active pharmaceutical substances are a high molecular weight, a complex three-dimensional structure and a high immunogenic potential. Preclinical and clinical studies of biologics have unique challenges. Selecting appropriate animal species, understanding the immunogenicity, and assessing pharmacodynamics and toxicological properties require a multilevel, detailed approach. The article discusses the regulatory framework under which these drugs are registered, summarizing the guidelines provided by international organizations such as the International Council for Harmonization and various national agencies.Conclusion. The analysis highlights the current advances and prospects in the development of biologics, highlighting their key role in future transformations in the treatment of rare diseases and oncology, approaching the era of personalized medicine. Monitoring the development directions and technological approaches, as well as the commitment to global methodological and regulatory aspects can become a catalyst in the development of the Russian pharmacology.

Characterizing the D-Amino Acid Position in Peptide Epimers by Using Higher-Energy Collisional Dissociation Tandem Mass Spectrometry: A Case Study of Liraglutide.

D-amino acid-containing peptides (DAACPs) occur in biological and artificial environments. Since the importance of DAACPs has been recognized, various mass spectrometry-based analytical approaches have been developed. However, the capability of higher-energy collisional dissociation (HCD) fragmentation to characterize DAACP sites has not been evaluated. In this study, we compared the normalized spectra intensity under different conditions of HCD and used liraglutide along with its DAACPs as examples. Our results indicated that the difference in the intensity of y ions between DAACPs and all-L liraglutide could not only distinguish them but also localize the sites of D-amino acids in the DAACPs. Our data demonstrate the potential of using HCD for the site characterization of DAACPs, which may have great impact in biological studies and peptide drug development.

Decaging-to-labeling: Development and investigation of quinone methide warhead for protein labeling

Biomolecule labeling in living systems is crucial for understanding biological processes and discovering therapeutic targets. A variety of labeling warheads have been developed for multiple biological applications, including proteomics, bioimaging, sequencing, and drug development. Quinone methides (QMs), a class of highly reactive Michael receptors, have recently emerged as prominent warheads for on-demand biomolecule labeling. Their highly flexible functionality and tunability allow for diverse biological applications, but remain poorly explored at present. In this regard, we designed, synthesized, and evaluated a series of new QM probes with a trifluoromethyl group at the benzyl position and substituents on the aromatic ring to manipulate their chemical properties for biomolecule labeling. The engineered QM warhead efficiently labeled proteins both in vitro and under living cell conditions, with significantly enhanced activity compared to previous QM warheads. We further analyzed the labeling efficacy with the assistance of density functional theory (DFT) calculations, which revealed that the QM generation process, rather than the reactivity of QM, contributes more predominantly to the labeling efficacy. Noteworthy, twelve nucleophilic residues on the BSA were labeled by the probe, including Cys, Asp, Glu, His, Lys, Asn, Gln, Arg, Ser, Thr, Trp and Tyr. Given their high efficiency and tunability, these new QM warheads may hold great promise for a broad range of applications, especially spatiotemporal proteomic profiling for in-depth biological studies.

CELL MEMBRANE COATED POLYMERIC NANOCARRIERS: A NOVEL DRUG DELIVERY APPROACH FOR THE TARGETED THERAPY OF RHEUMATOID ARTHRITIS

Rheumatoid arthritis is a chronic inflammatory disorder that affects the joints and can lead to significant disability. RA may affect other parts of the body, leading to various issues including damage to the joints, deformity, disability, and reduced mobility. The pathogenesis of RA involves a complex interplay between genetic, environmental and immunological factors. The treatment of rheumatoid arthritis typically reduces inflammation, manages pain, stiffness and prevents joint damage. However, these medications have several side effects no single therapeutic remedy directly targets the disease. Researchers in the field are focused on developing new treatments that are more effective and have fewer side effects as well as understanding the underlying mechanisms of the disease. Some areas of current research include the use of nanotechnology such as cell membrane-coated nanoparticles for the treatment of RA as well as the development of new biologic drugs that target specific molecules involved in inflammation. The use of cell membrane-coated nanoparticles for the treatment of rheumatoid arthritis has several potential benefits including targeted drug delivery, reduced inflammation, improved safety and biocompatibility, and reduced frequency of administration. However, more research is needed to fully understand the potential benefits and limitations of this approach to develop effective cell membrane coated nanoparticle-based therapies for RA. In this review cell membrane-coated nanoparticles may become valuable for numerous biomedical problems.