Welcome to the 2026 issue of Journal of Pharmaceutical Research and Integrated Medical Sciences. This issue showcases the remarkable breadth and depth of contemporary research across multiple disciplines. From cutting-edge applications of machine learning in climate science to the revolutionary potential of quantum computing in drug discovery, our featured articles demonstrate the power of interdisciplinary collaboration in addressing global challenges.
We are particularly excited to present research that bridges traditional academic boundaries, reflecting our journal's commitment to fostering innovation through cross-disciplinary dialogue. The integration of artificial intelligence with environmental science, the application of blockchain technology to supply chain management, and the convergence of urban planning with smart city technologies exemplify the transformative potential of collaborative research.
As we continue to navigate an era of rapid technological advancement and global challenges, the research presented in this issue offers both insights and solutions that will shape our future. We thank our authors, reviewers, and editorial board members for their continued dedication to advancing knowledge and promoting scientific excellence.
Dr. Arpan Kumar Tripathi Editor-in-Chief Journal of Pharmaceutical Research and Integrated Medical Sciences
The oral bioavailability of many medications, especially BCS Class II and Class IV substances, is significantly limited by poor water solubility. Three main options for improving bioavailability are examined in this review: solid dispersions, lipid-based drug delivery systems, and nanotechnology-based methods. Lipid-based systems like SEDDS, SMEDDS, and SNEDDS promote solubilisation and absorption, whereas solid dispersions improve drug dissolution by amorphization and improved wettability. By increasing surface area and improving permeability, nanotechnology-based carriers—such as nanoparticles, nanosuspensions, and nanoemulsions—further boost drug delivery. These technologies considerably increase oral bioavailability, solubility, and dissolution rate, according to the reviewed research. Stability, scalability, production, and regulatory approval are still issues, though. Promising prospects for future developments in oral medication delivery are provided by cutting-edge techniques, including hybrid delivery systems and formulation design aided by artificial intelligence.
Oral bioavailabilitypoorly water-soluble drugsSolid dispersionsLipid-based drug delivery systemsSEDDS.
Lassa fever and septic fever are important infectious diseases which cause high morbidity, mortality and healthcare burden, especially in resource-limited areas. The clinical features of both diseases are so similar, and include fever, hypotension, respiratory failure, and multi-organ failure, that early diagnosis and treatment are challenging. The clinical features, epidemiological features, risk factors, early clinical predictors and biomarkers of disease severity and mortality are analyzed. Prognosis assessment and therapeutic monitoring is an important role of a number of biomarkers, such as lactate, procalcitonin, cystatin-C, and inflammatory cytokines. The review also notes that artificial intelligence, machine learning, 3D imaging technologies and epidemiological surveillance systems are increasingly playing a key role in the prediction, monitoring and clinical decision-making of diseases. The combination of biomarker-based diagnostics, AI-driven predictive modelling, and digital healthcare technologies could greatly enhance the management of infectious diseases and the preparedness of healthcare systems. The multidisciplinary research and international co-operation continue to be critical to decrease the global burden of severe infectious diseases.
Lassa feverSeptic feverSepsisBiomarkersMortality predictorsArtificial intelligence+4 more
Jampala Raghu Ram, Obaid Alhilali, Mohammed Ashfaq Hussain, Mohammed Abdul Farhan
Nonalcoholic fatty liver disease (NAFLD) has become the most prevalent chronic liver disorder globally, affecting over 30% of adults. It is increasingly recognized as a multisystem disease with significant cardiometabolic and oncologic consequences. Recent advances between 2021 and 2025 have substantially transformed its conceptual understanding, diagnosis, and clinical management. Objective: This review aims to critically evaluate global progress in NAFLD research and management from 2021 to 2025, with emphasis on epidemiology, pathophysiology, diagnostic innovations, therapeutic developments, and the emergence of precision hepatology, while addressing the transition toward metabolic dysfunction-associated fatty liver disease (MAFLD). Methods: A comprehensive literature search was conducted across PubMed, Scopus, and Web of Science databases, covering studies published between June 2021 and December 2025. Relevant clinical trials, guidelines, and high-impact research articles were systematically analyzed across key domains including epidemiology, molecular mechanisms, diagnostics, therapeutics, and public health strategies. Results: The global prevalence of NAFLD has increased across diverse populations, including pediatric, elderly, lean, and socioeconomically disadvantaged groups. The MAFLD terminology has gained traction for better reflecting metabolic dysfunction, although debates persist. Mechanistic insights highlight the roles of insulin resistance, lipotoxicity, mitochondrial dysfunction, impaired autophagy, and gut microbiota dysbiosis. Advances in genomics and epigenetics have identified key variants such as PNPLA3 and TM6SF2, along with circulating biomarkers including miR-122 and Pro-C3. Non-invasive diagnostic tools, particularly imaging modalities and artificial intelligence-based systems, are increasingly replacing liver biopsy. Although no pharmacological therapy has yet received full regulatory approval, several agents, including obeticholic acid, resmetirom, lanifibranor, and semaglutide, are in advanced stages of clinical development. Lifestyle modification remains the cornerstone of management. NAFLD is strongly associated with increased risk of cardiovascular disease, type 2 diabetes, chronic kidney disease, and malignancies. Emerging precision hepatology approaches integrating multi-omics, artificial intelligence, and digital health technologies are enabling personalized disease management. Conclusion: NAFLD is evolving from a liver-specific disorder into a global multisystem health challenge. Despite significant advances, key challenges remain in standardizing diagnostic criteria, ensuring equitable access to therapies, and addressing global health disparities. The integration of precision medicine, digital technologies, and public health strategies holds promise for reducing the burden of NAFLD in the coming decade.
NAFLDMAFLDNASHfibrosismetabolic syndromegut–liver axis+6 more
Poor aqueous solubility is a major limitation in pharmaceutical development, affecting nearly 40% of approved drugs and up to 90% of drug candidates in the discovery pipeline. Low solubility directly compromises oral bioavailability, therapeutic effectiveness, dose proportionality, and clinical reproducibility, particularly for drugs classified under Biopharmaceutical Classification System (BCS) Classes II and IV. To address these challenges, formulation science has advanced significantly over the past two decades. This review critically evaluates recent progress from 2022 to 2025 in three major technological approaches: solid dispersions, lipid-based formulations, and nanotechnology-enabled drug delivery systems. Emphasis is placed on mechanistic principles governing solubility enhancement, formulation design strategies, in vivo performance outcomes, and translational considerations. Emerging hybrid platforms that integrate polymers, lipids, and nanocarriers are also discussed, as they demonstrate synergistic improvements in dissolution rate, permeability, and systemic exposure, often achieving 3–7 fold enhancement in oral bioavailability. In addition, the evolving regulatory landscape for complex and nanotechnology-based formulations is examined, highlighting current expectations for characterization, stability, and safety evaluation. Overall, this review provides an updated and integrated perspective on formulation strategies for poorly soluble drugs, offering practical insights for both academic research and industrial development.
Poor aqueous solubilityOral bioavailabilitySolid dispersionsLipid-based drug deliveryNanotechnologyBCS Class II and IV drugs+2 more
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline, synaptic dysfunction, amyloid-β deposition, tau hyper phosphorylation, oxidative stress, neuroinflammation, and mitochondrial dysfunction. Conventional drug discovery has largely relied on the "one drug-one target" paradigm, which has demonstrated limited success in managing this multifactorial disease. Recent advances in artificial intelligence (AI), chemical language models (CLMs), and systems pharmacology have created new opportunities for designing multi-target-directed ligands capable of simultaneously modulating interconnected pathological pathways.Objective: This study proposes an integrated AI-driven computational framework for discovering novel multi-target drug candidates against Alzheimer's disease by combining transformer-based chemical language models, network pharmacology, de novo molecular generation, molecular docking, molecular dynamics simulation, MM/PBSA free-energy calculations, and in-silico ADMET prediction. Disease-associated targets were prioritized using network pharmacology and literature mining. Transformer-based CLMs generated structurally diverse molecules optimized through reinforcement learning and multi-objective scoring. Drug-likeness filtering, molecular docking, molecular dynamics simulations, MM/PBSA binding energy calculations, pharmacophore analysis, and comprehensive ADMET evaluation were performed to identify promising therapeutic candidates. The proposed workflow successfully identified several chemically diverse lead molecules demonstrating favourable binding affinities toward multiple Alzheimer's disease targets, including acetylcholinesterase, glycogen synthase kinase-3β, β-secretase (BACE1), monoamine oxidase-B, and tau-associated kinases. Molecular dynamics simulations confirmed structural stability of protein-ligand complexes, while ADMET analyses predicted acceptable pharmacokinetic properties and blood-brain barrier permeability. Multi-objective optimization significantly improved molecular diversity, predicted efficacy, and safety compared with conventional virtual screening approaches.AI-assisted multi-target drug discovery represents a transformative paradigm capable of overcoming the limitations of single-target therapeutics for complex neurological disorders. The proposed framework provides a scalable strategy for accelerating rational drug discovery while improving therapeutic efficacy, reducing resistance mechanisms, and minimizing adverse effects.
Alzheimer's diseaseMulti-target drug designChemical language modelsMolecular dockingArtificial intelligence
VEXAS syndrome (Vacuoles, E1 enzyme, X-linked, Autoinflammatory, Somatic syndrome) is a more recently described, acquired somatic mutation in the UBA1 gene, and is an autoinflammatory disorder of adults. Its clinical features include systemic inflammation, clonal hematopoiesis, abnormalities of the bone marrow and various hematological, rheumatological and dermatologic changes. This review discusses the molecular pathogenesis of VEXAS syndrome with emphasis on the UBA1 mutations, immune dysfunction and disease pathogenesis. In addition, it emphasizes the importance of artificial intelligence, next generation sequencing (NGS), integration of multi-omics and three-dimensional (3D) genomic fingerprinting in the improvement of diagnosis and molecular characterization. The current therapeutic options such as the use of corticosteroids, JAK inhibitors, azacitidine and biologic agents, as well as novel stem cell-based therapies are reviewed. Special focus is on the most promising potentially curative therapy, namely, allogeneic hematopoietic stem cell transplantation (HSCT). Although genomic medicine and precision diagnostics has come a long way, there are still issues to be addressed, particularly with respect to diagnosis at an early stage and longer-term management. The synergy of genomics, artificial intelligence (AI), and regenerative medicine could have a profound impact on the care of VEXAS syndrome patients in the future.
VEXAS SyndromeUBA1 MutationClonal HematopoiesisArtificial IntelligenceGenomic Medicine3D Genomic Fingerprinting+4 more
