Indian Journal of Pharmaceutical Chemistry and Analytical Techniques
The Indian Journal of Pharmaceutical Chemistry and Analytical Techniques (IJPCAT)is an international peer-reviewed devoted to pharmaceutical, organic, inorganic, physical, analytical, and Biochemistry. IJPCAT aims to increase the impact of pharmaceutical research in academia and industry, with a strong emphasis on quality and originality. IJPCAT publishes original research articles, short communications, and review articles on all pharmaceutical chemistry, organic chemistry, inorganic chemistry, physical chemistry, analytical chemistry, biochemistry, materials science, environmental chemistry, and nanotechnology.
Structure-Based Molecular Docking Study of Curcuma longa Phytoconstituents in Rheumatoid Arthritis Therapy
Rheumatoid arthritis (RA) is a chronic, systemic autoimmune disease that manifests as synovial inflammation and subsequent erosive joint destruction coupled with extra-articular manifestations, which lead to considerable disability and decreased quality of life. Established disease-modifying antirheumatic drugs (DMARDs) and biological agents that target either cytokines or intracellular kinases have revolutionized the management of RA, but they are not without their drawbacks, including high costs, incomplete response in a subset of patients, and safety concerns such as increased risk for infection or malignancy. As a result, there is an ongoing quest to discover new, less toxic anti-inflammatory and immunomodulatory drugs, including those from medicinal plants. Curcuma longa L. (turmeric) has been used for centuries in traditional medicine to treat inflammatory and musculoskeletal disorders. Its main polyphenolic component, curcumin, along with closely related curcuminoids and other phytoconstituents, has shown powerful anti-inflammatory, antioxidant, and immunomodulatory actions that are important in RA pathogenesis. Utilizing molecular docking, which is commonly combined with molecular dynamics (MD), pharmacophore modeling, and ADMET prediction approaches, enables a systematic evaluation of C. longa phytochemicals across various stages and numerous RA-related molecular targets, including cytokines, enzymes, kinases, and transcription factors. This review compiles existing data on structure-based docking studies of C. longa phytoconstituents for RA treatment. It begins by summarizing RA pathophysiology and the pharmacology of C. longa and its major constituents. It then describes docking studies for curcumin and analogues with key targets in RA such as tumor necrosis factor-α (TNF‑α) converting enzyme (TACE), interleukin‑1β converting enzyme (ICE/caspase‑1), cyclooxygenase-2 (COX-2), p38 MAP kinase, and arachidonate 5-lipoxygenase (ALOX5) along the pharmacology network derived target. The report focuses on the consistency of docking predictions with in vitro/in vivo anti-RA data, scrutinizes ADMET and drug-likeness profiles, and covers the limitations of current iterative in silico work. Overall, the aforementioned existing docking and computational studies lay a foundation for concluding that curcumin and other structurally similar C. longa phytochemicals can bind with suitable affinities to several proteins relevant to RA pertaining to their known therapeutic effects on cytokines processing, eicosanoid synthesis, NF‑κB and MAPK signaling pathways, as well as leukotriene biosynthesis of which reaffirms its structure-function relationship with regard to its established multiphasic anti-inflammatory and disease-modifying capacities. Translation of these findings to benefit patients presents integrated challenges of standardized phytochemistry, rigorous docking and MD protocols, experimental validation of target engagement, delivery systems and carefully designed clinical trials.
Curcuma longa; Rheumatoid arthritis; Molecular docking; Curcumin; Anti-inflammatory activity
Copyright (c) 2025 This is an Open Access article distributed under the terms of the Creative Commons Attribution (CC BY NC), which permits unrestricted use, distribution, and reproduction in any medium, as long as the original authors and source are cited. No permission is required from the authors or the publishers. (https://creativecommons.org/licenses/by-nc/4.0/) https://creativecommons.org/licenses/by/4.0
Recent Advances in Anticancer Drug Development: A Medicinal Chemistry Perspective
The development of anticancer drugs over the past few years has been heavily influenced by developments in the field of medicinal chemistry, especially due to the convergence of rational drug design, Structure-Activity Relationship (SAR) studies and novel drug delivery systems. The current review highlights animal-based preclinical trials that show the efficacy of a variety of therapeutic strategies such as targeted small molecules, natural product-derived molecules, prodrug delivery, nanomedicine, and combination therapies. Murine tumor models have shown evidence of significant improvement in the therapeutic outcomes, including reduction in tumor mass, apoptosis induced through mitochondrial and caspase pathways, angiogenesis inhibition, and pharmacokinetic and bioavailability. The use of the sophisticated animal models, which include xenograft, syngeneic, orthotopic and the genetically engineered mouse models, have offered in-depth information about tumor biology, drug mechanism and response to therapy under controlled conditions. Also, there is a promising prospect of nanotechnology-based delivery systems and prodrug strategies to enhance tumor-specific targeting and reduce systemic toxicity. Although these results are promising, a number of issues remain, such as translational differences between the animal model and clinical response, heterogeneity in the tumor, and the safety of highly potent compounds. In sum, this review in conjunction shows the central role of medicinal chemistry in the development of next-generation anticancer therapies and the significance of balancing the application of chemical innovation with biological validation to realize more effective and safer cancer therapies.
Anticancer drug development, Medicinal chemistry, Animal models, Structure–Activity Relationship (SAR), Targeted therapy, Nanomedicine, Prodrugs, Combination therapy.
Copyright (c) 2026 This is an Open Access article distributed under the terms of the Creative Commons Attribution (CC BY NC), which permits unrestricted use, distribution, and reproduction in any medium, as long as the original authors and source are cited. No permission is required from the authors or the publishers. (https://creativecommons.org/licenses/by-nc/4.0/) https://creativecommons.org/licenses/by/4.0
Network Pharmacology and Molecular Docking-Based Evaluation of Bacopa monnieri for Neuroprotection in Alzheimer’s Disease
Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that leads to memory loss, cognitive decline, and eventually functional impairment; neuropathological features include extracellular amyloid-β (Aβ) plaque deposition and intracellular neurofibrillary tangles of hyperphosphorylated tau in addition to synaptic dysfunction and significant neuronal cell death. Currently approved therapies include acetylcholinesterase inhibitors and the NMDA receptor antagonist memantine, which offer only modest symptomatic benefits and limited effects on pathophysiological mechanisms within AD, indicating an urgent need for multi-target disease-modifying approaches. Bacopa monnieri (L.) Wettst. (Brahmi), An ancient Ayurvedic nootropic, it emerged as a potent neuroprotective agent due to its broad-based profile of phytoconstituents, such as triterpenoid saponins (bacosides) and flavonoids, with antioxidant, anti-inflammatory, anti-amyloidogenic, and neurogenic activity. Biotechnological approaches such as network pharmacology and molecular docking are increasingly significant for exploring the multi-component, multi-target nature of herbal medicines like B. monnieri in complex disease systems like AD. This review provides a comprehensive overview on the possible neuroprotective role of B. monnieri in AD using network pharmacological and molecular docking-based approaches to further evaluate potential therapeutic targets. We overview AD pathophysiology and the ethnomedicinal and pharmacological background of B. monnieri, summarize its phytochemistry and pharmacokinetics, and critically appraise in vitro, in vivo and clinical evidence for cognitive- and neuroprotection effects. We then outline the principles and workflows of network pharmacology and docking as they apply to B. monnieri, review key studies that dock bacosides and related compounds against BACE1, cholinesterases, tau kinases, inflammatory mediators, and neurotransmitter receptors with experimental data when available. Combined analysis suggests that the constituents of B. monnieri can modulate multiple pathways associated with AD, such as PI3K/Akt, MAPK, and NF-κB signaling and neurotrophin signaling pathways, along with cholinergic synapse function and Aβ production through inhibition of BACE1 activity, while providing antioxidant effects, regulating inflammation, and supporting synaptic plasticity. Yet considerable gaps still exist, notably between brain bioavailability of active metabolites, quantitative target engagement in vivo and strong clinical evidence in AD populations. Such postulates, in conjunction with rigorous multi-omics-driven network pharmacology, better in vitro and in vivo models, rational formulation strategy, and biomarker-rich clinical trials, will be necessary for translating the traditional usage and pre-clinical therapeutic potential of B. monnieri into an evidence-based neuroprotective therapy against AD.
Bacopa monnieri; Alzheimer’s disease; Network pharmacology; Molecular docking; Neuroprotection
Role of Analytical Chemistry in Drug Metabolism and Pharmacokinetics Studies
The preclinical drug development is based on drug metabolism and pharmacokinetics (DMPK), which defines the efficacy, safety, and dosage profile of therapeutic agents. Analytical chemistry has been crucial in the understanding of absorption, distribution, metabolism, and excretion (ADME) in animal model studies and therefore offers a useful way of understanding pharmacokinetic pathways and metabolic mechanisms. This review examines the influential works of analytical chemistry in the field of DMPK research with focus on chromatographic and spectroscopic methods, bioanalytical methods, and more advanced metabolite profiling using the advanced mass spectrometry. It also considers the weaknesses of current methods of analysis, issues in animal model research, and how current methods can be improved to achieve more accurate, sensitive, and translational quality of analytical analysis in preclinical drug metabolism and pharmacokinetics.
Analytical chemistry, Drug metabolism, Pharmacokinetics, ADME, Chromatography, Mass spectrometry, Bioanalytical techniques
Molecular Docking and Simulation Studies in Drug Discovery: Principles, Applications, and Current Limitations
Molecular docking and molecular dynamics (MD) simulations have become indispensable tools in modern drug discovery, enabling researchers to accelerate the identification and optimisation of therapeutic compounds. This comprehensive review examines the fundamental principles underlying these computational approaches, their diverse applications in pharmaceutical development, and the significant limitations that currently constrain their predictive accuracy and applicability. We discuss structure-based drug design methodologies, scoring functions, binding-affinity prediction, conformational sampling strategies, and the integration of artificial intelligence into computational drug discovery. Furthermore, we address critical challenges, including protein flexibility representation, ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) prediction accuracy, and the persistent discrepancy between in silico predictions and experimental validation. Recent advances in hardware acceleration, force-field development, and machine learning are reshaping the landscape of computational drug discovery. This review synthesises current knowledge and highlights future opportunities for enhancing the reliability and efficiency of molecular docking and simulation studies in pharmaceutical research.
Molecular Docking, Molecular Dynamics Simulations, Structure-Based Drug Design, Scoring Functions, Binding Affinity, ADMET Prediction, Computer-Aided Drug Design, Drug Discovery
Click Chemistry in Peptide-Based Drug Discovery: Recent Advances, Emerging Applications, and Future Perspectives in Medicinal Chemistry
Click chemistry has fundamentally transformed modern medicinal chemistry by providing a versatile, high-yielding, and chemoselective strategy for assembling complex molecular architectures under mild reaction conditions. Since its introduction, this synthetic approach has become an indispensable tool for the rapid construction of biologically active molecules, particularly in peptide-based drug discovery, where structural precision, metabolic stability, and synthetic efficiency are critical determinants of therapeutic success. Among the various click reactions, copper (I)-catalyzed azide-alkyne cycloaddition (CuAAC) has gained widespread recognition because of its exceptional regioselectivity, functional-group tolerance, and ability to generate stable 1,2,3-triazole linkages that effectively mimic peptide and amide bonds. These attributes have significantly expanded opportunities for developing peptide therapeutics with improved pharmacological performance and enhanced resistance to enzymatic degradation. This review critically examines the scientific evolution of click chemistry and its expanding role in peptide engineering, drug design, and pharmaceutical innovation. Particular emphasis is placed on the mechanistic basis of major click reactions, triazole-mediated peptide modification, peptide cyclization, stapling strategies, and the development of therapeutics for cancer, infectious diseases, inflammatory disorders, and other clinically significant conditions. Recent advances in bio-orthogonal chemistry, targeted drug delivery, molecular imaging, Nano medicine, and bio molecular conjugation are also discussed to illustrate the broad translational impact of click chemistry across contemporary biomedical research. In addition, the review highlights the emerging convergence of click chemistry with artificial intelligence, machine learning, and computational drug discovery, emphasizing how predictive molecular design, reaction optimization, and virtual screening are reshaping medicinal chemistry workflows. Current limitations, including catalyst-associated toxicity, scalability, manufacturing challenges, and regulatory considerations, are critically evaluated alongside promising solutions that support sustainable and clinically translatable pharmaceutical development. By integrating foundational concepts with recent scientific advances, this review provides a comprehensive perspective on the present status of click chemistry and outlines future directions for its application in peptide therapeutics, precision medicine, and next-generation drug discovery.
Click chemistry; Peptide therapeutics; Triazole chemistry; Medicinal chemistry; Drug discovery
A Review on Structure-Based Drug Design and Its Role in Modern Medicinal Chemistry
The Structure-Based Drug Design (SBDD) has become one of the most sophisticated and rational methods of modern medicinal chemistry, profoundly changing the conventional process of drug discovery by applying the detailed 3D structural knowledge of biological targets, enzymes, receptors and ion channels. This review gives an in-depth review of the principles, methodologies and preclinical applications of SBDD with special interest in animals. It also emphasizes the combination of major computational methodologies, such as molecular docking, virtual screening, and molecular dynamics simulations, and experimental methods, such as X-ray crystallography and cryo-electron microscopy that, together, provide efficient prediction and analysis of drug-target interactions on a molecular scale. The animal models are considered vital in verifying the pharmacokinetics, pharmacodynamics, efficacy, and safety of SBDD-derived compounds, thus sealing the gap between the theoretical design and biological systems. Moreover, the review covers key drug development milestones, such as target identification, lead compound discovery, and optimization, and successful uses of SBDD in disease models, such as cancer, neurological disorders, infectious diseases, and inflammatory diseases. Although its benefits are significant (greater drug specificity, decreased development time, and higher success rates), SBDD has several issues connected with relying on high-resolution structural data, high implementation costs, and difficulties in the translation of computational predictions into in vivo results.
Structure-Based Drug Design (SBDD), Molecular Docking, Preclinical Studies, Animal Models, Drug Discovery, Lead Optimization, Computational Biology, Medicinal Chemistry
Applications of Spectroscopic Methods in Chemical and Pharmaceutical Analysis: A Review
Spectroscopic techniques are some of the most vital analytical techniques in chemical and pharmaceutical sciences. The methods rest on the interaction of electromagnetic radiation with matter and are commonly used to qualitatively identify and quantitatively estimate, characterize the structure of a structure, identify impurities, and control quality. This has made them very important as they are analytical in a quick, precise, sensitive and in most cases not destructive way compared to the traditional wet chemical method. This review discusses the use of some of the common spectroscopic methods, including UV-Visible Spectroscopy, Infrared Spectroscopy, Nuclear Magnetic Resonance, Mass Spectrometry, Raman spectroscopy, fluorescence spectroscopy and atomic spectroscopy in chemical as well as pharmaceutical analysis. The review encompasses the theoretical principles, instrumentation, methodologies, applications, key findings, strengths, limitations, and future perspectives. The most important results are that spectroscopic techniques improve the accuracy of analysis, minimize time of processing, increase compliance with regulations, and aid in real-time quality control. Portable instruments, automation, chemometrics, and artificial intelligence are expected to further develop in the future.
Microwave-Assisted Organic Synthesis (MAOS); Microwave Irradiation; Green Chemistry; Reaction Kinetics; Solvent-Free Synthesis
Microwave-Assisted Organic Synthesis: A Review of Techniques and Applications
Microwave-assisted organic synthesis (MAOS) has proven to be a rapid and eco-friendly technique for organic chemical synthesis. This review examines the underlying principles, methods and uses of microwave-assisted synthesis. This review spans the principles of heating, equipment, reaction techniques, and a wide range of applications in pharmaceuticals, material science and agrochemicals. Literature review shows that the use of MAOS leads to faster reactions, higher yield and selectivity, and lower energy and environmental costs. The review also highlights key challenges, such as scale-up issues, initial investment in equipment, and safety hazards associated with high-pressure reactions. In conclusion, MAOS is a disruptive technology that meets contemporary green chemistry goals and has great potential for future research and industrial applications.
Microwave-Assisted Organic Synthesis (MAOS); Microwave Irradiation; Green Chemistry; Reaction Kinetics; Solvent-Free Synthesis.
Digital Interventions for Zoophilia (Paraphilic, Bestiality) Disorders: Evaluating the Efficacy of AI-Driven Cognitive Behavioral Therapy in Mitigating Zoophilic Chemical Impulses (Zoophilic Desires)
Paraphilic disorders encompass persistent abnormal sexual interests accompanied by psychological distress, compulsive actions, emotional dysregulation, and dysfunction. Of all the paraphilias, zoophilic disorder is among the least studied areas in psychiatry and forensic psychology both scientifically and socially. This paper will investigate the possibilities of using AI-powered cognitive-behavioral therapy and digital mental health care solutions to treat maladaptive zoophilic cognition, compulsive sexual urges, and related psychological problems in human beings. The paper will analyze neurocognitive and psychological processes underlying sexual compulsivity, such as cognitive distortions, behavioral conditioning, trauma triggers, and impulse regulation difficulties. The article will further explore the development of AI-enabled psychotherapy software, conversational therapy chatbots, emotional surveillance devices, telepsychiatry apps, and relapse prevention platforms that offer discreet, convenient, and customized psychological services. It is expected that AI-powered CBT can facilitate increased treatment availability, enhanced emotional insight, better behavioral accountability, and timely counseling services for individuals hesitant to access traditional psychiatric interventions due to stigma and social prejudice.
Artificial Intelligence, Cognitive Behavioral Therapy, Zoophilic Disorder, Paraphilic Disorders, Digital Mental Health, Compulsive Sexual Behavior, Emotional Regulation, Telepsychiatry
Recent Developments in Catalytic Organic Reactions for Industrial Applications
Catalytic organic reactions are essential in current industrial chemistry due to their ability to make processes more efficient, selective, sustainable, and economically feasible. Modern advances in the science of catalysis have produced highly efficient catalytic technologies, such as transition-metal catalysts, heterogeneous catalytic materials, photocatalysts, biocatalysts, and green catalytic media for environmentally benign industrial synthesis. These technologies have helped produce pharmaceuticals, petrochemicals, polymers, agrochemicals, and fine chemicals efficiently without wasting energy or producing toxic waste products. This review highlights current advances in catalytic organic reactions focusing on their applications in industry. It covers topics including transition-metal catalysis, heterogeneous catalysis based on materials like metal–organic frameworks (MOFs) and covalent organic frameworks (COFs), green catalysis, photocatalysis, biocatalysis, and continuous-flow catalysis. Additionally, the industrial significance of each approach is assessed together with its strengths, weaknesses, and sustainability aspects. Current results suggest that catalytic approaches make significant contributions to industrial productivity and green chemistry efforts. Nevertheless, issues associated with catalyst durability, scalability, and high costs are still important challenges in need of additional investigation.
Catalytic Organic Reactions; Transition-Metal Catalysis; Heterogeneous Catalysis; Green Chemistry; Metal–Organic Frameworks (MOFs); Covalent Organic Frameworks (COFs); Photocatalysis; Biocatalysis; Continuous-Flow Catalysis; Industrial Organic Synthesis
Recent Trends in Chromatographic Techniques for Pharmaceutical Analysis: A Review
Chromatography is a critical instrument in pharmaceutical analysis, as it allows the successful separation, identification, and determination of complex drug formulations and biological matrices. Over recent years, large improvements in chromatographic technology, such as High-Performance Liquid Chromatography (HPLC), UPLC, Gas Chromatography (GC), Supercritical Fluid Chromatography (SFC) and other hyphenated techniques, have made major improvements in the sensitivity and speed of analysis and accuracy. This review makes a concise review of the recent trends in chromatographic techniques, alongside a special focus on their use in animal studies pertaining to pharmacokinetics, toxicology and drug metabolism. The literature has been systematically evaluated to assess the methodological developments, technological innovations, and performance of analysis. The results emphasize that high-throughput, high-sensitivity, and environmentally friendly chromatographic methods have become more and more important in contemporary pharmaceutical research.
Chromatography; Pharmaceutical Analysis; HPLC; UPLC; Animal-Based Studies; Pharmacokinetics; Drug Metabolism; Toxicology
Natural Products as Lead Compounds in Medicinal Chemistry: Opportunities and Challenges
Natural products have attracted significant attention as the important sources of lead compounds in medicinal chemistry by virtue of their extraordinary structural diversity, biological specificity, and capacity to react with a variety of molecular targets. The review focuses on evidence obtained solely based on animal-based preclinical studies to evaluate the therapeutic potential, mechanisms of action, pharmacokinetic behavior and safety profiles of natural compounds. Results in the animal models indicate that natural products have great pharmacological activities, such as anticancer effects via the induction of apoptosis and angiogenesis inhibition, anti-inflammatory effects via suppressing pro-inflammatory cytokines and oxidative stress, antimicrobial effects against resistant pathogens, and neuroprotective effects via the regulation of neuronal signaling and inhibition of toxic Although these are encouraging results, there are various limitations that are encountered, including low bioavailability, low solubility, rapid metabolism and variability in natural sources, which collectively limit their clinical uses. Moreover, physiological differences between animal models and humans also create translational challenges to predictability of preclinical findings. To overcome such limitations, new developments in drug delivery systems, such as nanoparticle-based drug delivery systems, liposomes, and polymeric formulations, as well as structural changes, such as prodrug development, have demonstrated the possibility of improving stability and therapeutic effectiveness. In general, although natural products still have enormous potential as lead compounds, pharmacokinetic and translational challenges are critical to their effective transition into clinically useful drugs.
Natural Products, Medicinal Chemistry, Lead Compounds, Pharmacokinetics, Drug Discovery, Bioavailability, Toxicity Evaluation
Role of Heterocyclic Compounds in Drug Discovery: A Comprehensive Review
The heterocyclic compounds are a foundation of contemporary drug discovery due to their outstanding structural diversity, chemical versatility, and capacity to engage selectively with diverse biological targets. This is a comprehensive survey of the importance of heterocyclic scaffolds in pharmaceutical development with special emphasis on animal-based preclinical trials which offer important insights into the effectiveness of drugs, safety and drug mechanisms of action. It emphasizes their wide-ranging therapeutic possibilities in important fields like anticancer, antimicrobial, anti-inflammatory and central nervous system diseases. The review also discusses the key experimental methods, such as acute and chronic toxicity experiments, pharmacokinetic and pharmacodynamic tests, and disease specific animal models, which combine together to validate the preclinical development of these compounds. Further, it explains the importance of structural design, positive pharmacokinetic profiles, and multi-target mechanisms to improve drug functionality and therapeutic effects. New innovations (including nanotechnology-aided delivery of drugs, green synthesis, and the design of multi-functional heterocyclic agents) are also examined in a critical fashion. Although these developments have been made, several issues such as variability of species, ethical issues, scarcity of long-term toxicity data, and absence of standardized protocols continue to pose major obstacles to clinical translation. Thus, the review underscores how better experimental models, combination of computational and in vitro methods, and further innovation in the field of heterocyclic chemistry can be used to enable the production of safer, more effective and specific therapeutic agents in future.
Heterocyclic Compounds; Drug Discovery; Animal-Based Studies; Pharmacokinetics; Mechanism of Action; Nanotechnology; Green Synthesis; Preclinical Evaluation
Green Chemistry Approaches in Organic Synthesis: A Review of Sustainable Methods
Green chemistry has become a revolutionary and sustainable practice in organic synthesis with the goal of minimizing environmental impact and maximizing the safety, efficiency and the overall quality of chemical reactions. This review thoroughly reviews different green synthetic techniques that include use of eco-friendly solvents, biocatalysis, microwave- and ultrasound-assisted techniques, green catalysts, and specifically how they have been validated using animal-based studies. Preclinical evidence with mice, rats, and zebrafish show that compounds produced via green methodologies have much lower acute and chronic toxicity, increased biocompatibility, and better pharmacological profiles than those generated via conventional methodologies. Aspiratory in vivo examination methods including toxicity, pharmacokinetic profiling, histopathology, biochemical and behavioural analysis give a comprehensive insight into the biological interactions and safety profiles of these compounds. Moreover, the application of green chemistry principles such as atom economy, minimization of waste, and energy efficiency helps to decrease the harmful by-products and help to create safer chemical entities. Although these benefits exist, issues like the fact that the protocol is not yet standardized to synthesize these materials, differences in results of the experimental results and scanty long-term toxicity evidence especially in nano-catalysts and other emerging green materials are also of concern. In general, this review highlights the great importance of green chemistry in achieving balance between environmental sustainability and innovation in biomedical fields as a promising avenue of creating effective, environmentally friendly and biologically safe organic compounds.
Green Chemistry, Organic Synthesis, Sustainable Methods, Animal Studies, Biocompatibility, Green Solvents, Biocatalysis, Toxicity Evaluation
Advancements in Electrochemical Sensors for Environmental and Biomedical Analysis
The capability to change chemical information into measurable electrical signals with high sensitivity, quick response, and low cost has made electrochemical sensors a highly efficient and versatile analysis tool in environmental and biomedical analysis. In this review, the recent developments in the field of electrochemical sensors are assessed in detail, paying special attention to validation and use in animal research. Amperometric, conductometric and potentiometric sensors are discussed and important advancements made by incorporation of nanomaterials like graphene, carbon nanotubes and metal nanoparticles which are discussed in relation to enhanced electron transfer, selectivity and limits of detection. The review demonstrates the applicability of these sensors in the monitoring of a broad spectrum of analytes, such as heavy metals, glucose, neurotransmitters and pesticides, in dynamic in vivo and ex vivo conditions in animal models. In addition, the incorporation of biosensing components, wearable and implantable devices, microfluidic technologies, and artificial intelligence has increased their potential in terms of real-time, continuous, and multi-analyte detection. The review highlights the importance of designing new materials, enhancing biocompatibility, standardizing the methods, and developing state-of-the-art data analytics to improve the reliability, scalability, and practical use of electrochemical sensors. Taken collectively, these technologies have significant potential in further developing the fields of environmental monitoring, enhancing preclinical diagnostic capabilities, and even future translation of biomedical research.
Electrochemical Sensors, Nanomaterials, Biosensors, Animal-Based Studies, Environmental Monitoring, Biomedical Analysis, Real-Time Detection, Wearable Sensors
Quantum Dots in Materia Medica: Emerging Tools for Bioimaging and Targeted Drug Delivery
Quantum dots (QDs) have revolutionized biomedical sciences by offering exceptional optical, electronic, and chemical versatility for simultaneous imaging, diagnostics, and targeted drug delivery. These semiconductor nanocrystals (2–10 nm), with their size-dependent fluorescence, high quantum yield, and superior photostability compared to conventional organic dyes, enable multiplexed bioimaging, real-time drug tracking, and precisely controlled theranostic applications. The tunable surface chemistry of QDs allows functional modification with targeting ligands, therapeutic agents, and biocompatible coatings, facilitating receptor-mediated targeting and stimuli-responsive drug release across diverse disease contexts. Advanced synthesis strategies—including colloidal, hydrothermal, and green (biogenic) methods—have enabled the production of eco-friendly alternatives to heavy-metal-based QDs, such as carbon quantum dots, graphene QDs, and silicon-based systems, which maintain superior optical performance while minimizing cytotoxicity concerns. Functionally, QDs act as multifunctional nanocarriers via mechanisms including fluorescence resonance energy transfer (FRET), pH-responsive release, enzyme-triggered activation, and light-mediated delivery. Pharmacokinetically, QD biodistribution is governed by size, surface charge, and coating, with optimal formulations achieving prolonged circulation and tissue-specific accumulation. Clinical successes in tumor imaging, gene delivery tracking, and theranostic platforms underscore their translational potential. However, challenges including long-term toxicity from heavy metals, physicochemical stability in biological fluids, batch-to-batch reproducibility, and regulatory standardization remain critical barriers. The integration of artificial intelligence for imaging interpretation and predictive pharmacokinetic modeling, alongside advances in biodegradable and personalized QD engineering, represents the next frontier. Collectively, quantum dots epitomize the convergence of materials science, molecular pharmacology, and digital health—transforming precision diagnostics and therapy into seamlessly integrated, patient-centric nanomedicines.
Quantum Dots, Nanomedicine, Targeted Drug Delivery, Bioimaging, Theranostics, Fluorescence, Nanocarriers, Photodynamic Therapy, Carbon Quantum Dots, Biodistribution, Pharmacokinetics, Precision Medicine, Stimuli-Responsive Delivery, Metal-Free Nanoparticles
Pharmacological Evaluation of Metal–Organic Frameworks (MOFs): Emerging Nanocarriers in Modern Pharmaceutics
Metal–organic frameworks (MOFs) have emerged as powerful next-generation nanocarriers in modern pharmaceutics, offering unique advantages over conventional delivery systems through their exceptional porosity, tunability, and modular architecture. This review provides a comprehensive evaluation of MOF-based drug delivery platforms, emphasizing their structural fundamentals, synthesis strategies, drug-loading mechanisms, pharmacokinetics, and therapeutic potential. Pharmaceutical-grade MOFs are now engineered through advanced solvothermal, microwave-assisted, mechanochemical, and microfluidic methods, supported by green chemistry innovations and precise post-synthetic modifications. Their versatile loading mechanisms accommodate small-molecule drugs, biomacromolecules, and nucleic acids, while physicochemical attributes—such as pore size, surface chemistry, and degradability—dictate in vivo biodistribution and release kinetics. MOFs demonstrated significant pharmacological applications in cancer therapy, antimicrobial and antiviral treatment, gene delivery, gas storage, and enzyme-based therapeutics. However, concerns regarding cytotoxicity, degradation products, immunogenicity, and long-term accumulation highlight the importance of rigorous toxicological evaluation and biosafety-focused design. Emerging trends—including biomimetic coatings, MOF–polymer hybrids, stimuli-responsive systems, AI-guided design, and theranostic platforms—are rapidly advancing their clinical relevance. Despite ongoing challenges related to scalability, reproducibility, and regulatory approval, MOF nanocarriers hold strong potential to revolutionize personalized and precision medicine through smart, adaptable, and multifunctional therapeutic delivery systems
Metal–Organic Frameworks (Mofs); Nanocarriers; Drug Delivery; Pharmacokinetics; Biodistribution; Nucleic Acid Delivery; Anticancer Therapy; Biomimetic Coatings; Stimuli-Responsive Systems; Theranostics; Pharmaceutical Nanotechnology
Synthesis and Characterization of Novel Organometallic Complexes for Catalytic Applications
The discovery of effective organometallic catalysts is instrumental in driving catalytic processes in numerous industrial processes. The present research examines the synthesis, characterization, and catalytic activity of new organometallic complexes, including palladium (II) acetate (Pd(OAc)₂), platinum (II) chloride (PtCl₂), and rhodium (III) chloride (RhCl₃), and their ligand-based analogues. The complexes were prepared and characterized through NMR, IR, and XRD spectroscopy to establish their purity and structure. Catalytic experiments for hydrogenation and cross-coupling reactions were carried out, and the data indicated that Pd(OAc)₂ (ligand present) showed the highest catalytic activity, with 95% conversion and 93% yield for hydrogenation and 88% conversion and 85% yield for cross-coupling. Statistical evaluation by ANOVA supported the importance of differences in catalytic performance, where the Pd(OAc)₂ complexes were better than the rest of the tested catalysts. This research reveals the improved catalytic activity of Pd(OAc)₂ (with ligand), giving important insights into future industrial catalysis applications. The results imply that optimization and further investigation into ligand changes could result in more efficient and selective catalysts for a vast array of reactions
Organometallic complexes, Palladium acetate (Pd(OAc)₂), Platinum chloride (PtCl₂), Rhodium chloride (RhCl₃), Catalytic efficiency, Hydrogenation reaction, Cross coupling reaction
Analytical Method Validation in Pharmaceutical Quality Control: Current Guidelines and Challenges
Analytical method validation (AMV) in the veterinary field forms an important aspect of quality control in pharmaceutical companies in which drugs are used to treat various species of animals to guarantees safety, efficacy and regulatory actions are adhered to. This review points to the significance of the species-based approaches in pharmacokinetics of drug absorption, distribution, metabolism, and residue detection with a focus on the issues of physiological diversity, complex biological samples and ethical requirement. Modern methods such as HPLC, UPLC, GC, LC-MS/MS, UV-Vis, and FTIR are characterized by sensitivity, specificity, and reproducibility and newer techniques such as capillary electrophoresis and microfluidic-based technology, high-resolution mass spectrometry and bioinformatics-directed validation incorporates enhanced sensitivity, specificity, reproducibility, reduced sample volumes, and increased throughput. Future methodological advances in multi-dimensional platforms, green analytical chemistry, chemometrics, and machine learning offer new ways of addressing matrix effects and resource limitations and regulatory limitations. Taken together, these strategies can contribute to effective veterinary drug monitoring, food safety, and sustainable and species-specific AMV practices and direct future research at achieving harmonized and technologically more advanced validation processes.
Veterinary Pharmaceuticals, Analytical Method Validation, Species-Specific Validation, LC-MS/MS, Microfluidics, Chemometrics, Residue Monitoring, Green Analytical Chemistry
Artificial Intelligence (AI): Drug Design and Formulation
The way pharmaceutical companies find, develop, and evaluate new treatments is changing as a result of the combination of AI and machine learning. This method is more accurate and efficient, which not only expedites drug discovery but also raises the likelihood of successful drug approvals. AI-driven formulation design has emerged as a potential technique in recent years to enhance the body's absorption and distribution of medications. AI also has the ability to improve drug distribution, which is essential to guaranteeing that medications go to their targeted locations.One significant benefit of AI-assisted formulation design is the potential to increase drug bioavailability. Many medications have limited distribution choices due to issues like low solubility or stability; however, AI interventions can improve formulations and bring novel delivery techniques like tailored drug administration. By lowering the number of tests required to find the best preparation, collaborating with AI in formulation design speeds up the entire formulation development process and aids in the rapid creation of novel drugs.
Artificial intelligence, Machine learning, Drug Design, Pharmaceutical Industry.
Green Pharmaceutical Manufacturing: A Focus on Sustainable Approaches to Drug Formulation Development, Production & Case Studies
Pharmaceutical manufacturing is a cornerstone of modern medicine but it’s also one of the most resource-intensive and environmentally burdensome industrial sectors. Traditional synthesis and formulation processes consume massive amounts of energy, water, and toxic solvents, generating significant waste and greenhouse emissions. The concept of green pharmaceutical manufacturing has emerged as a transformative framework that integrates sustainability principles into every stage of the drug lifecycle as from raw material sourcing and process development to formulation and packaging. This review discusses the major sustainable approaches in pharmaceutical production, including green chemistry, solvent substitution, biocatalysis, continuous manufacturing, renewable feedstocks and eco-friendly formulation technologies. It also explores Life Cycle Assessment (LCA), regulatory initiatives and industrial case studies which demonstrates shift toward cleaner, safer and more efficient drug production systems.
Green Chemistry, Sustainable Manufacturing, Pharmaceutical Formulation, Eco-Design, Biocatalysis, Solvent-Free Synthesis, Continuous Processing, Life Cycle Assessment
Copyright (c) 2025 Indian Journal of Pharmaceutical Chemistry and Analytical Techniques
Quantitative Analysis of Nanoparticles in Complex Biological Matrices: Insights from Preclinical Studies
Nanoparticles (NPs) have emerged as crucial agents in biomedical applications, including drug delivery, imaging, and diagnostics. Accurate quantification of nanoparticles in complex biological matrices, such as blood, tissue, and organs, is essential for understanding their biodistribution, pharmacokinetics, and toxicological profiles. This review comprehensively examines analytical methodologies employed in preclinical animal studies for nanoparticle quantification, highlighting their advantages, limitations, and suitability for different nanoparticle types. Key findings indicate that while techniques like inductively coupled plasma mass spectrometry (ICP-MS), atomic absorption spectroscopy (AAS), and fluorescence-based imaging provide sensitive and reliable results, challenges persist in matrix interferences, sample preparation, and detection limits. The review emphasizes the importance of methodological standardization and proposes future directions to enhance quantitative accuracy, reproducibility, and translational relevance.
Nanoparticles, Quantification, Biological Matrices, ICP-MS, AAS, Fluorescence Imaging, Preclinical Studies, Biodistribution, Pharmacokinetics, Toxicology
Development of Green Analytical Methods for Trace Heavy Metal Detection in Water Samples
The development of sensitive, precise, and environmentally acceptable analytical techniques for the identification of heavy metals in water has become necessary due to the growing concern over environmental pollution by these metals, including lead (Pb), cadmium (Cd), mercury (Hg), and arsenic (As). Conventional analytical methods frequently use energy-intensive processes, hazardous chemicals, and large solvent usage, all of which run counter to the ideas of green chemistry. The development and validation of green analytical techniques for the detection of trace heavy metals in water samples using plant-based extractants, biodegradable solvents, and energy-efficient technologies such portable electrochemical sensors and green spectrophotometry are the main goals of this project. After analyzing a number of water samples gathered from various sources, the developed techniques were assessed for sensitivity, selectivity, reproducibility, and eco-sustainability. The findings showed that while having less of an adverse effect on the environment, green approaches were just as sensitive as traditional methods. This study offers a viable framework for upcoming analytical procedures and demonstrates the viability of incorporating green chemistry concepts into environmental monitoring.
Green analytical chemistry, heavy metals, water quality, eco-friendly detection, trace analysis
Artificial Intelligence-Assisted Analytical Method Development
The research examines how Artificial Intelligence (AI) can be applied to revolutionize the development of analytical methods by leveraging the weaknesses of the traditional trial-and-error method. Based on the descriptive and exploratory research design, the study is a synthesis of secondary sources in 50 peer-reviewed articles, industry reports, and case-based studies that were published between 2015 and 2025. The results indicate that AI-supported approaches are far much better than traditional ones in a variety of aspects. The optimization cycles were cut by 58 percent, parameter accuracy also improved by 19 percent, and the general efficiency of the process was enhanced by a cut in the development time of 45 percent, a reduction in cost of 38 percent and reduction in human error by 52 percent. Pharmaceutical analysis, environmental chemistry, and food quality testing case studies further attested that the reproducibility always increased above 89 percent in contrast with a common of 73 percent through the conventional techniques. In spite of these developments, problems like the scarcity of data, interpretation problems, and regulatory acceptability were discovered. Nevertheless, potential adoption in the future is high where it is estimated that the integration level is more than 77 percent in all of the categories evaluated. The paper highlights the role of AI in improving efficiency, accuracy and reproducibility and minimizing dependency on resources hence presenting substantial advantages to the laboratories, industries and regulatory authorities. On the whole, AI can be discussed as one of the defining tools that can make an analytical procedure redefined, innovative, and become more reliable in terms of scientific practices.
Artificial Intelligence, Analytical Method Development, Optimization, Reproducibility, Efficiency, Pharmaceutical Sciences, Data-Driven Analysis.
Recent Advances in Benzoxazole Synthesis: A Therapeutic Perspective on Antidepressant and Anxiolytic Activity
Benzoxazole derivatives have garnered significant attention in medicinal chemistry due to their diverse pharmacological activities, including antimicrobial, anticancer, and notably, central nervous system (CNS) effects such as antidepressant and anxiolytic properties. Recent advancements in the synthesis of benzoxazole compounds have led to the development of novel derivatives with enhanced therapeutic potential. Studies have demonstrated that structural modifications of the benzoxazole nucleus can yield compounds exhibiting significant antidepressant-like effects in animal models. For instance, certain benzoxazole derivatives have shown high affinities for serotonin receptors, which are implicated in mood regulation, thereby producing marked antidepressant-like effects in behavioral tests such as the forced swimming test (FST) and the tail suspension test (TST). Furthermore, the incorporation of specific functional groups, such as triazole moieties, into the benzoxazole scaffold has resulted in compounds with dose-dependent antidepressant-like activity, highlighting the importance of molecular hybridization strategies in drug design. Additionally, benzoxazole derivatives have been explored for their anxiolytic potential, with certain compounds exhibiting promising activity in preclinical studies. These findings underscore the therapeutic relevance of benzoxazole-based compounds and provide a foundation for the development of new antidepressant and anxiolytic agents.​
Benzoxazole Derivatives, Antidepressant Activity, Anxiolytic Potential, Synthetic Advances, CNS Drug Development
Synthesis of Different Benzoxazole Derivatives for The Evaluation of Anti-Anxiety/Anti-Depressants
Anxiety and depression are among the most prevalent mental health disorders, often co-occurring and presenting significant challenges to current pharmacological and psychotherapeutic interventions. Existing treatments such as SSRIs and cognitive behavioral therapy are limited by delayed therapeutic effects, variable patient responses, and undesirable side effects, highlighting the urgent need for novel therapeutic agents. Benzoxazole derivatives, due to their heterocyclic structure and ability to interact with biomolecules, offer promising potential as psychoactive compounds. This research focused on the synthesis, characterization, and evaluation of novel benzoxazole derivatives using various synthetic methods, including formylation, cyclization, Suzuki coupling, and nucleophilic substitution reactions. The compounds were characterized through TLC, NMR, IR, and GC-MS analyses to confirm structural integrity and purity. Preclinical studies were conducted using Wistar albino rats, where antidepressant activity was assessed through forced swim and tail suspension tests. Results demonstrated that all synthesized derivatives exhibited significant antidepressant activity, with high-dose derivatives, particularly D2, showing superior efficacy compared to the standard drug, imipramine hydrochloride. These findings suggest that benzoxazole derivatives may represent an effective class of compounds for the treatment of depressive disorders. The study supports further investigation into their mechanism of action and potential clinical application in mental health therapeutics
Antidepressant activity, Synthetic methods, Behavioral pharmacology, Mental health therapeutics.
Hybrid Molecules for Dual Enzyme Inhibition in Alzheimer’s Disease
Alzheimer disease (AD) is a multi-factorial neurodegenerative disorder that appears in cognitive decline with a progressive memory loss which is mostly influenced by the pathological benchmarks which include amyloid-beta plaques and cholinergic deficiencies. The given paper describes the logic-based design, synthesis, and biological testing of new hybrid molecules directed against two enzymes that play a role in AD: acetylcholinesterase (AChE) and beta-secretase (BACE-1). Twelve hybrid molecules were designed by structure-based drug design (SBDD) and investigated through in silico docking, ADMET profiling and in vitro enzyme inhibition analyses. Among these, HM-07 was found to be the strongest dual inhibitor under the study, with the docking scores of -8.9 kcal/mol (AChE) and -8.4 kcal/mol (BACE-1) and IC 50 of 0.41 um and 0.56 um respectively. ADMET analysis showed that it has a great drug-likeness and blood-brain barrier (BBB) permeability along with oral bioavailability. Computational modeling displayed high predictivity with respect to biological activity, showing strong inverse correlation (r = =0.86) between docking affinity and biological activity. The results imply that HM-07 is a good lead drug development that can be used in developing multitarget therapeutics in the treatment of Alzheimer disease.
Alzheimer’s Disease, Hybrid Molecules, Dual Enzyme Inhibition, Acetylcholinesterase, Beta-Secretase, Molecular Docking
Structure-Based Drug Design of Kinase Inhibitors for Targeted Cancer Therapy
The recent increased focus on high precision of cancer treatment has fueled the advancement of molecularly targeted inhibitors especially the kinase inhibitors, which interfere with the signaling pathway involved in oncogenesis in a highly specific manner. This paper uses a structure-based drug design (SBDD) to determine and develop novel kinase inhibitors based on the in silico approach used comprehensively. All 100 kinase-ligand complexes were docked, profiled, and screened on binding interactions and pharmacokinetics. Besides, two structure-based designed lead compounds revealed high binding affinities to several relevant cancer-related targets like BCR-ABL, EGFR, and VEGFR, and scored low with an energy value as low as -10.2 Kcal/mol compared to current inhibitors. Interaction-related studies revealed the possibilities of stable ligand binding through hydrogen bridges and hydrophobic contacts, whereas screening with ADMET properties revealed good drug-like properties and oral absorption. The Lead Compound 1 turned out to be the most encouraging one, being highly specific, significantly non-toxic, and excellently pharmacokinetically. The results support the usefulness of SBDD to discover effective and selective kinase-targeting anticancer drugs as a basis of continuing the preclinical verification and development of the project.
Structure-Based Drug Design, Kinase Inhibitors, Molecular Docking, ADMET Prediction, Targeted Cancer Therapy
Green Chemistry Approaches in The Synthesis of Anti-Inflammatory Drug
The overall work on the development of anti-inflammatory drug candidates has taken a new twist as green chemistry has been introduced in the aim of keeping the environment unharmed or impacted, even though the effectiveness of the drugs and dosage support the mention of efficacy and safety. This review article examines the recent developments on sustainable and environmentally friendly green processes in the synthesis of anti-inflammatory compounds both in relation to the animal trials and not the human ones. It includes review of topic of green solvents, biocatalysis, microwave-assisted synthesis, ionic liquids and other environmentally compatible strategies used during the preparation of pharmaceually active compounds. The focus is usually laid on minimization of hazardous reagents, energy efficiency and renewable feedstock utilization. It provides a critical review of major routes that include their results alongside comparative advantages over the traditional chemical routes and the existing shortcomings and likely trends in this area of study.
Green Chemistry, Anti-inflammatory Drugs, Biocatalysis, Microwave-assisted Synthesis, Sustainable Synthesis, Animal-based Studies