Hasil untuk "Therapeutics. Pharmacology"

Sina Elahimanesh, Mohammadali Mohammadkhani, Sara Zahedi Movahed et al.

While large language models (LLMs) excel at open-ended dialogue, effective psychotherapy requires structured progression and adherence to clinical protocols, making the design of psychotherapist chatbots challenging. We investigate how different LLM-based designs shape perceived therapeutic dialogue in a chatbot grounded in the Self-Attachment Technique (SAT), a novel self-administered psychotherapy rooted in attachment theory. We compare three architectural variants: (1) a multi-agent system utilizing finite state machine aligned with therapeutic stages and a shared long-term memory, (2) a single-agent using identical knowledge-base and the same prompts, and (3) an unguided LLM. In an eight-day randomized controlled trial (RCT) with N=66 Farsi-speaking participants, balanced across the three chatbots, the multi-agent system is perceived as significantly more natural and human-like than the other variants and achieves higher ratings across most other metrics. These findings demonstrate that for therapeutic AI, architectural orchestration is as critical as prompt engineering in fostering natural, engaging dialogue.

Nguyen Manh Son, Pham Huu Vang, Nguyen Thi Dung et al.

Cancer is recognized as a complex group of diseases, contributing to the highest global mortality rates, with increasing prevalence and a trend toward affecting younger populations. It is characterized by uncontrolled proliferation of abnormal cells, invasion of adjacent tissues, and metastasis to distant organs. Garcinia cowa, a traditional medicinal plant widely used in Southeast Asia, including Vietnam, is employed to treat fever, cough, indigestion, as a laxative, and for parasitic diseases. Numerous xanthone compounds isolated from this species exhibit a broad spectrum of biological activities, with some showing promise as anti cancer and antimalarial agents. Network pharmacology analysis successfully identified key bioactive compounds Rubraxanthone, Garcinone D, Norcowanin, Cowanol, and Cowaxanthone alongside their primary protein targets (TNF, CTNNB1, SRC, NFKB1, and MTOR), providing critical insights into the molecular mechanisms underlying their anti-cancer effects. The Graph Attention Network algorithm demonstrated superior predictive performance, achieving an R2 of 0.98 and an RMSE of 0.02 after data augmentation, highlighting its accuracy in predicting pIC50 values for xanthone based compounds. Additionally, molecular docking revealed MTOR as a potential target for inducing cytotoxicity in HeLa cancer cells from Garcinia cowa.

Santiago Berrezueta-Guzman, WenChun Chen, Stefan Wagner

Virtual Reality (VR) offers promising avenues for innovative therapeutic interventions in populations with intellectual disabilities (ID). This paper presents the design, development, and evaluation of Space Exodus, a novel VR-based role-playing game specifically tailored for children with ID. By integrating immersive gameplay with therapeutic task design, Space Exodus aims to enhance concentration, cognitive processing, and fine motor skills through structured hand-eye coordination exercises. A six-week pre-test/post-test study was conducted with 16 children in Ecuador, using standardized assessments, the Toulouse-Pieron Cancellation Test, and the Moss Attention Rating Scale complemented by detailed observational metrics. Quantitative results indicate statistically significant improvements in concentration scores, with test scores increasing from 65.2 to 80.3 and 55.4 to 68.7, respectively (p < 0.01). Qualitative observations revealed reduced task attempts, enhanced user confidence, and increased active participation. The inclusion of a VR assistant provided consistent guidance that further boosted engagement. These findings demonstrate the potential of immersive, game-based learning environments as practical therapeutic tools, laying a robust foundation for developing inclusive and adaptive rehabilitation strategies for children with ID.

Chen Xu, Zhenyu Lv, Tian Lan et al.

Although large language models (LLMs) hold significant promise in psychotherapy, their direct application in patient-facing scenarios raises ethical and safety concerns. Therefore, this work shifts towards developing an LLM as a supervisor to train real therapists. In addition to the privacy of clinical therapist training data, a fundamental contradiction complicates the training of therapeutic behaviors: clear feedback standards are necessary to ensure a controlled training system, yet there is no absolute "gold standard" for appropriate therapeutic behaviors in practice. In contrast, many common therapeutic mistakes are universal and identifiable, making them effective triggers for targeted feedback that can serve as clearer evidence. Motivated by this, we create a novel therapist-training paradigm: (1) guidelines for mistaken behaviors and targeted correction strategies are first established as standards; (2) a human-in-the-loop dialogue-feedback dataset is then constructed, where a mistake-prone agent intentionally makes standard mistakes during interviews naturally, and a supervisor agent locates and identifies mistakes and provides targeted feedback; (3) after fine-tuning on this dataset, the final supervisor model is provided for real therapist training. The detailed experimental results of automated, human and downstream assessments demonstrate that models fine-tuned on our dataset MATE, can provide high-quality feedback according to the clinical guideline, showing significant potential for the therapist training scenario.

Haydn Thomas Jones, Natalie Maus, Josh Magnus Ludan et al.

AI-driven discovery can greatly reduce design time and enhance new therapeutics' effectiveness. Models using simulators explore broad design spaces but risk violating implicit constraints due to a lack of experimental priors. For example, in a new analysis we performed on a diverse set of models on the GuacaMol benchmark using supervised classifiers, over 60\% of molecules proposed had high probability of being mutagenic. In this work, we introduce Medex, a dataset of priors for design problems extracted from literature describing compounds used in lab settings. It is constructed with LLM pipelines for discovering therapeutic entities in relevant paragraphs and summarizing information in concise fair-use facts. Medex consists of 32.3 million pairs of natural language facts, and appropriate entity representations (i.e. SMILES or refseq IDs). To demonstrate the potential of the data, we train LLM, CLIP, and LLava architectures to reason jointly about text and design targets and evaluate on tasks from the Therapeutic Data Commons (TDC). Medex is highly effective for creating models with strong priors: in supervised prediction problems that use our data as pretraining, our best models with 15M learnable parameters outperform larger 2B TxGemma on both regression and classification TDC tasks, and perform comparably to 9B models on average. Models built with Medex can be used as constraints while optimizing for novel molecules in GuacaMol, resulting in proposals that are safer and nearly as effective. We release our dataset at https://huggingface.co/datasets/medexanon/Medex, and will provide expanded versions as available literature grows.

Niels Bassler, Giuseppe Schettino, Hugo Palmans et al.

Spatially Fractionated Radiation Therapy (SFRT) produces highly heterogeneous dose distributions, for which conventional metrics such as peak, valley, or average dose can yield ambiguous or inconsistent estimates of therapeutic window changes. These dose descriptors are not uniquely linked to biological outcome, complicating comparisons between modalities. We introduce the Biologically Effective Particle Number Ratio (BPNR), a model-independent and outcome-based framework that quantifies therapeutic window changes using directly measurable delivery quantities rather than spatial dose metrics. BPNR is defined as the ratio of total particle numbers (proportional to monitor units, MU) required to reach specified levels of tumor control probability (TCP) and normal tissue complication probability (NTCP). The relative BPNR (RBPNR) compares therapeutic windows across modalities and avoids ambiguities of spatial dose averaging by relying solely on biological endpoints. As an illustration, we apply the framework to preclinical proton minibeam radiotherapy (pMBRT) versus conventional proton therapy. The absence of normal tissue complications at the highest tested MU in the pMBRT arm yields an RBPNR > 1.4, indicating a widened therapeutic window. The BPNR/RBPNR methodology provides a concise, experimentally grounded, and modality-agnostic way to quantify therapeutic window changes, with potential applications across SFRT, FLASH, high-LET radiation, and combination therapies.

E. J. Kuijer, L. H. Marinelli, S. J. Bailey et al.

ABSTRACT Nalfurafine is the only clinically approved kappa opioid receptor (KOPr) agonist that can cross the blood–brain barrier and exert CNS effects. Because its clinical use is not associated with dysphoria, it is widely believed to have an atypical pharmacological profile. Nalfurafine's atypical properties are proposed to result from its G‐protein‐biased KOPr agonist property, leading to the widespread use of nalfurafine as a nonaversive KOPr agonist in preclinical research. The validity of nonaversive claims for nalfurafine was investigated in mice by comparing its antinociceptive and aversive effects with those of the typical, nonbiased KOPr agonist U50,488 in tail withdrawal and conditioned place aversion (CPA) tests. Dose responses for tail withdrawal with nalfurafine and U50,488 were determined in warm (52°C) water in adult male and female C57BL/6J mice. Doses of U50,488 produced antinociception from 5 mg/kg, and doses of nalfurafine from 0.06 mg/kg. Four‐fold lower doses of either KOPr agonist (U50,488: 1.25 mg/kg; nalfurafine: 0.015 mg/kg) were subthreshold for antinociception. No sex differences were seen. Antinociceptive effects were fully blocked by the KOPr antagonist norBNI (10 mg/kg). Antinociceptive doses of nalfurafine (0.06 mg/kg) and U50,488 (5.0 mg/kg) both induced CPA. Subantinociceptive doses of nalfurafine (0.015 mg/kg) and U50,488 (1.25 mg/kg) were nonaversive in CPA. Thus, in mice, at doses that are antinociceptive, CPA was evident for both KOPr agonists. Neither nalfurafine nor U50,488 showed a separation between their antinociceptive and aversive effects, contradicting the hypothesis that nalfurafine is a nonaversive analgesic in mice. The findings caution against assuming nalfurafine is a nonaversive KOPr agonist for use in preclinical research.

Weimin Gao, Zhigang Xia, Tingfeng Zhou et al.

BackgroundHead and neck squamous cell carcinoma (HNSCC) remains a significant global health concern, with treatment outcomes for advanced or metastatic stages being suboptimal despite the availability of various targeted therapies and immunotherapies. This study evaluates five FDA-approved anti-HNSCC drugs—cetuximab, pembrolizumab, nivolumab, atezolizumab, and durvalumab—focusing on the adverse drug reactions (ADRs) associated with their use as reported in the WHO VigiAccess database.MethodsA retrospective analysis was conducted on ADR reports from the WHO-VigiAccess database, focusing on demographic information (age, gender, and geographical distribution) and ADR classification. The disproportionality analysis was used to identify ADRs through Reporting Odds Ratios (ROR) and Proportional Reporting Ratios (PRR). ADRs were categorized into 27 system organ classes (SOCs) for comparison across the five drugs.ResultsA total of 145,678 ADR reports were analyzed. Cetuximab exhibited the highest incidence of skin and subcutaneous tissue disorders (20.88%), while durvalumab showed elevated respiratory system disorders (18.53%). Pembrolizumab and nivolumab had notable immune-related adverse events, with malignant neoplasm progression reported at 5.56% and 4.23%, respectively. Atezolizumab was primarily associated with blood and lymphatic system disorders (5.51%). Disproportionality analysis revealed significant safety concerns for each drug, such as skin toxicity for cetuximab, respiratory complications for durvalumab, and reproductive system risks for nivolumab.ConclusionThis comparative pharmacovigilance study highlights the diverse safety profiles of the five anti-HNSCC drugs. Clinicians should consider these ADRs when treating patients, especially elderly individuals or those with comorbidities. Personalized monitoring strategies should be developed to minimize risks and optimize therapeutic outcomes for HNSCC patients.

Anqi Li, Yu Lu, Nirui Song et al.

Robust therapeutic relationships between counselors and clients are fundamental to counseling effectiveness. The assessment of therapeutic alliance is well-established in traditional face-to-face therapy but may not directly translate to text-based settings. With millions of individuals seeking support through online text-based counseling, understanding the relationship in such contexts is crucial. In this paper, we present an automatic approach using large language models (LLMs) to understand the development of therapeutic alliance in text-based counseling. We adapt a theoretically grounded framework specifically to the context of online text-based counseling and develop comprehensive guidelines for characterizing the alliance. We collect a comprehensive counseling dataset and conduct multiple expert evaluations on a subset based on this framework. Our LLM-based approach, combined with guidelines and simultaneous extraction of supportive evidence underlying its predictions, demonstrates effectiveness in identifying the therapeutic alliance. Through further LLM-based evaluations on additional conversations, our findings underscore the challenges counselors face in cultivating strong online relationships with clients. Furthermore, we demonstrate the potential of LLM-based feedback mechanisms to enhance counselors' ability to build relationships, supported by a small-scale proof-of-concept.

Pavan K. Inguva, Saikat Mukherjee, Pierre J. Walker et al.

Nucleic acids such as mRNA have emerged as a promising therapeutic modality with the capability of addressing a wide range of diseases. Lipid nanoparticles (LNPs) as a delivery platform for nucleic acids were used in the COVID-19 vaccines and have received much attention. While modern manufacturing processes which involve rapidly mixing an organic stream containing the lipids with an aqueous stream containing the nucleic acids are conceptually straightforward, detailed understanding of LNP formation and structure is still limited and scale-up can be challenging. Mathematical and computational methods are a promising avenue for deepening scientific understanding of the LNP formation process and facilitating improved process development and control. This article describes strategies for the mechanistic modeling of LNP formation, starting with strategies to estimate and predict important physicochemical properties of the various species such as diffusivities and solubilities. Subsequently, a framework is outlined for constructing mechanistic models of reactor- and particle-scale processes. Insights gained from the various models are mapped back to product quality attributes and process insights. Lastly, the use of the models to guide development of advanced process control and optimization strategies is discussed.

Zahra Masoumpour, Aliyeh daryabor, Abbas Rahimi et al.

Background: This study aimed to investigate kinematic parameters of lower limb joints during gait on inclined surfaces compared to level ground. Methods: In this cross-sectional study, 15 healthy individuals walked at their self-selected speed on level ground with a zero slope and on two inclined surfaces. These surfaces were constructed to mimic real environments with slopes of +8 (uphill) and -8 (downhill) along an eight-meter distance. The measured variables included the angles of the ankle, knee, and hip joints sagittal plane during different phases of gait, captured through a three-dimensional motion capture system. Results: Significant differences were observed in uphill walking compared to level-ground walking, including an increase in ankle, hip, and knee angles at initial contact, maximum ankle dorsiflexion and plantarflexion, maximum knee flexion in the stance phase, and maximum knee extension in the swing phase. There was also a reduction in the maximum extension of the hip joint (P<0.05). In downhill walking compared to level ground, significant differences were observed in the increase of ankle and knee angles at initial contact, maximum ankle dorsiflexion, maximum knee flexion in both stance and swing phases, and a decrease in the maximum angle of hip extension. However, no significant difference was observed in the hip joint angle at initial contact maximum ankle plantarflexion, maximum knee extension in swing phase between level and downhill surfaces and at maximum knee flexion in swing phase between uphill and level surfaces (P>0.05). Conclusion: Walking on inclined surfaces influences the flexion and extension angles of lower limb joints during different phases of gait, necessitating increased joint movement. These alterations are more pronounced during uphill walking than downhill, especially at the initial contact point.

Xinyi Wei, Yanding Su, Qian Cheng et al.

Objective: A remarkably sensitive, accurate, and efficient ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) approach was developed as a facile and expeditious method for measuring cilofexor concentration in beagle dogs, the herb-drug interactions between silybinin and cilofexor was explored based on pharmacokinetics.Methods: The plasma sample protein of the beagles were rapidly sedimented with acetonitrile, and cilofexor and tropifexor (internal standard, ISTD) were separated by gradient elution using a 0.1% formic acid aqueous solution and acetonitrile as the mobile phase. The concentrations were detected using positive ion multiple reaction monitoring (MRM) mode. Mass transfer pairs were m/z 587.91→267.91 for cilofexor and m/z 604.08→228.03 for ISTD, respectively. A two-period self-controlled experimental design was adopted for the HDIs experiment. In the first period (Group A), six beagle dogs were orally administered cilofexor at a dose of 1 mg/kg. In the second period (Group B), silybinin (3 mg/kg) was orally administered to the six beagle dogs twice a day for seven consecutive days, after which cilofexor was orally administered. The cilofexor concentration in beagle dogs was determined, and HDIs were evaluated based on their pharmacokinetics.Results: The accuracy and precision of cilofexor were both less than 15%, and the recoveries, matrix effects, and stability met the relevant requirements. The Cmax of cilofexor in group B was 49.62% higher than that in group A, whereas the AUC(0-t) and AUC(0−∞) of cilofexor in group B were 47.85% and 48.52% higher, respectively, than those in group A. Meanwhile, the t1/2 extended from 7.84 h to 9.45 h, CL and Vz decreased in Group B.Conclusion: A novel UPLC-MS/MS approach was successfully applied for the measurement of cilofexor in beagle dog plasma. Silybinin can alter the pharmacokinetics of cilofexor in beagle dogs, thereby increasing plasma exposure to cilofexor.

Sheng Mai

Mild cognitive impairment (MCI) leading to dementia results in a constellation of psychiatric disorders including depression, mood disorders, schizophrenia and others. With increasing age, mild cognitive impairment leads to increased disability-adjusted life-years and healthcare burden. A huge number of drug trials for the treatment of MCI associated with Alzheimer's disease have undergone failure leading to the development of drugs that could avert the progression of the disease. However, some novel non-drug-based therapies like ultrasound ablation of amyloid plaques have influenced researchers to explore the non-pharmacological modalities for the treatment of mild cognitive impairment. To compensate for neurodegenerative loss resulting in coexisting psychiatric disorders, neurofeedback therapy has also been proven to improve behavioural outcomes by inducing neuroplasticity. The aim of the current review is to highlight the pathophysiological aspects of mild cognitive impairment leading to dementia that could be addressed with no pharmacological interventions and to understand the mechanisms behind the effects of these interventions.

Simone Varandas, Conceição Fernandes, Edna Cabecinha et al.

Freshwater bivalves are widely used as accumulation indicators and monitoring tools for assessing contaminant effects on different levels of biological integration. This pilot study aimed to explore the phylogenetic diversity of <i>Escherichia coli</i> isolated from freshwater mussels (<i>Margaritifera margaritifera</i> and <i>Potomida littoralis</i>) and characterize their phenotypes and antibiotic resistance profiles. Samples were collected in the Rabaçal and Tua Rivers, in the Douro basin, Portugal—two sites representing different levels of anthropogenic contamination. Antimicrobial susceptibility testing was performed via the disk diffusion method with 21 antibiotics. Results showed that 31% of isolates were multidrug-resistant (MDR). Thus, freshwater mussels provide an effective and time-integrated approach for identifying/quantifying fecal indicators, including MDR bacteria. PCR-based assays were designed for assessing phylogenetic <i>E. coli</i> groups. Among the <i>E. coli</i> isolates, the highest prevalence (44%) was observed in group D or E, followed by group E or Clade I (25%), group A (19%), and group B1 (13%). <i>E. coli</i> isolated from <i>M. margaritifera</i> predominantly exhibited a higher prevalence of phylogroups D or E, whereas <i>E. coli</i> from <i>P. littoralis</i> showed associations with phylogroups E or clade I, B1, A, and D or E. Our results provide new insights into the phylogenetic diversity of <i>E. coli</i> in freshwater bivalves. Additionally, the findings highlight the possible linkage of phylogroups with the host species, the geographical location in the water stream, and human activity. Using <i>E. coli</i> as a bioindicator isolated from freshwater mussels helps us grasp how human activities affect the environment. This study has important implications for those interested in safeguarding water resources, especially in tackling antibiotic resistance in aquatic ecosystems.

Li Gu, Xin Jin, Huaiyuan Liang et al.

Oral multitarget tyrosine kinase inhibitors (TKIs), such as sorafenib, which suppress tumor cell proliferation and tumor angiogenesis, have been approved to treat patients with hepatocellular carcinoma (HCC). Of note, only approximately 30% of patients can benefit from TKIs, and this population usually acquires drug resistance within 6 months. In this study, we intended to explore the mechanism associated with regulating the sensitivity of HCC to TKIs. We revealed that integrin subunit β 5 (ITGB5) is abnormally expressed in HCC and contributes to decreased the sensitivity of HCC to sorafenib. Mechanistically, unbiased mass spectrometry analysis using ITGB5 antibodies revealed that ITGB5 interacts with EPS15 to prevent the degradation of EGFR in HCC cells, which activates AKT-mTOR signaling and the MAPK pathway to reduce the sensitivity of HCC cells to sorafenib. In addition, mass spectrometry analysis showed that CSNK1A1 binds to ITGB5 in HCC cells. Further study indicated that ITGB5 increased the protein level of CSNK1A1 through the EGFR-AKT-mTOR pathway in HCC. Upregulated CSNK1A1 phosphorylates ITGB5 to enhance the interaction between ITGB5 and EPS15 and activate EGFR in HCC cells. Thus, we identified a positive feedback loop between ITGB5-EPS15-EGFR-CSNK1A1 in HCC cells. This finding provides a theoretical basis for the future development of therapeutic strategies to improve the anti-HCC efficacy of sorafenib.

Lan Tang, Kaijuan Huang, Wenhui Jiang et al.

AbstractD-alpha-tocopheryl polyethylene glycol 1000 succinate (TPGS) is a commonly used nonionic surfactant used as a pharmaceutical carrier in different drug delivery systems. TPGS can reverse P-glycoprotein (P-gp)-mediated multidrug resistance (MDR) and also has anticancer activities. It suggests that when designing antitumor drug preparation, it’s necessary to take into account the antitumor activity of TPGS. Our in vivo studies showed that TPGS exerted the strongest cytotoxicity in MCF-7-ADR cells when compared with seven other tumor cell lines. The further study revealed TPGS caused apoptosis and blocked MCF-7 cell growth in G2/M phase. Mechanistic insights suggested that TPGS increased intracellular calcium ion concentrations, leading to apoptosis via the mitochondrial pathway. Furthermore, two in vivo experiments were performed. One was TPGS, and DOX solution was administered by tail vein injection on MCF-7-ADR tumor bearing nude mice. The other was temperature sensitive TPGS gel (TPGS-TG) was administered by intratumoral injection on MCF-7-ADR tumor bearing nude mice combined with paclitaxel albumin nanoparticles (Abraxane®) administered by tail vein injection. The findings confirmed that TPGS could play its role in anti-tumor to reduce the toxicity of chemotherapeutic drugs and improve the efficiency of drug-resistant tumors, thereby enhancing the development of safe oncology therapeutics.

Baihan Lin, Guillermo Cecchi, Djallel Bouneffouf

The therapeutic working alliance is an important predictor of the outcome of the psychotherapy treatment. In practice, the working alliance is estimated from a set of scoring questionnaires in an inventory that both the patient and the therapists fill out. In this work, we propose an analytical framework of directly inferring the therapeutic working alliance from the natural language within the psychotherapy sessions in a turn-level resolution with deep embeddings such as the Doc2Vec and SentenceBERT models. The transcript of each psychotherapy session can be transcribed and generated in real-time from the session speech recordings, and these embedded dialogues are compared with the distributed representations of the statements in the working alliance inventory. We demonstrate, in a real-world dataset with over 950 sessions of psychotherapy treatments in anxiety, depression, schizophrenia and suicidal patients, the effectiveness of this method in mapping out trajectories of patient-therapist alignment and the interpretability that can offer insights in clinical psychiatry. We believe such a framework can be provide timely feedback to the therapist regarding the quality of the conversation in interview sessions.

Luis Fernando Valladales-Restrepo, Jaime Andrés Giraldo-Correa, Brayan Stiven Aristizábal-Carmona et al.

The impact of COVID-19 prompted a race to find a treatment that would reduce its mortality. Most studies have not shown favorable results for many of these drugs, but they are still used. The aim as to determine the differences and similarities in the hospital pharmacological management of patients with COVID-19 according to sex, age group, and geographical region of Colombia, 2020–2021. Descriptive cross-sectional study was conducted on the prescription patterns of the medications given to patients diagnosed with COVID-19 treated in eight clinics in Colombia between 6 March 2020 and 31 May 2021. We performed a descriptive analysis of the sociodemographic, clinical, and pharmacological variables of the patients. A total of 8596 patients from 170 cities were identified, with a median age of 53.0 years and 53.3% of them men. A total of 24.3% required care in the intensive care unit, and 18.7% required invasive mechanical ventilation. The most commonly used drugs for the treatment of COVID-19 were systemic corticosteroids (63.6%), followed by colchicine (12.8%), azithromycin (8.9%), and ivermectin (6.4%). Corticosteroids, anticoagulants, colchicine, azithromycin, ivermectin, and hydroxychloroquine were prescribed more frequently in men, and their overall use increased with age. There were differences in prescriptions between geographic regions. The majority of patients were managed with medications included in the management guidelines. There were differences between sexes, age groups, and geographical regions.

Mahboob Alam, Farogh Ahsan, Tarique Mahmood et al.

Objective: Medicinal plants having antioxidant potential possess numerous constituents which are responsible for different beneficial effects and are used as an alternative resource of medicine to lessen diseases linked with oxidative stress. Flavonoids are identified in the plants since ages and display wide spectrum of biological actions that might be able to stimulate the steps which are disturbed in different diseases. Flavonoids are significant natural compounds with various biologic properties, among which the most common is the anti-oxidant potential.Citrus flavonoids establish an important stream of flavonoids. Naringin, very common flavonoids present in the diet, belongs to the family of flavanone. It is the principal constituent of citrus family that contains flavonoids for example tomatoes, grapefruits and oranges.Materials and Methods: In this article, we reviewed naringin with respect to sources, chemical property, pharmacokinetics, pharmacological activity, and novel formulations. The literature survey has been done by searching different databases such as Psyc INFO, Science Direct, PubMed, EMBASE, Google, Google Scholar, Medline.Results: Naringin is known to behave as an antioxidant and possess anti-inflammatory, anti-apoptotic, anti-atherosclerotic, neuroprotective, anti-psychotic, anti-asthmatic, anti-diabetic, hepatoprotective, anti-tussive, cardioprotective, and anti-obesity activity. Further clinical studies using large sample sizes remain essential to obtain the appropriate dose and form of naringin for averting diseases. Furthermore, the therapeutic approach of these bioflavonoids is significantly inappropriate due to the lack of clinical evidence. Different plants must be explored further to find these bioflavonoids in them.Conclusion: The results of this exploration provides biological actions of bioflavonoid (naringin), predominantly on pharmacological and novel dosage forms of naringin.