Adv. Pharmacol. [JOURNAL]
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200 papers
Risk of senescence, polypharmacy, and their outcomes in elderly cardiovascular disease patients.
Cebe T, Kızılyel F
Adv Pharmacol · 2025 · PMID 40716935 · Publisher ↗
Cardiovascular diseases (CVDs) are closely associated with a chronic inflammatory condition known as senescence and present a considerable challenge when managed alongside age-associated comorbidities. Due to the coexist...
Cardiovascular diseases (CVDs) are closely associated with a chronic inflammatory condition known as senescence and present a considerable challenge when managed alongside age-associated comorbidities. Due to the coexistence of three main predisposing factors (advanced age, multiple morbidity, and polypharmacotherapy), elderly patients with CVDs are prone to the occurrence of drug interactions and adverse effects of incorrect drug combinations. Polypharmacy, routine cardiovascular medications, and age-related pharmacokinetic alterations are the major challenges in cardiovascular practice. Polypharmacy might impair the post-surgical recovery process due to ADRs and side effects. Ironically, patients with CVDs may also require conventional senotherapeutic drugs such as cardiac glycosides, statins, aspirin, ACE inhibitors, and angiotensin receptor blockers for their daily routine. Considering medical necessities, polypharmacy, and drug safety of the elderly population, the management of elderly cases presents a serious challenge. We aim to present the cardiometabolic impacts of polypharmacy management in elderly patients and to design optimal senotherapeutic strategies and drug management strategies in cardiac surgical practice.
Cellular senescence and senotherapeutics in cardiovascular diseases.
Pal A
Adv Pharmacol · 2025 · PMID 40716934 · Publisher ↗
Cellular senescence (CS) is characterized by stable cell cycle arrest and is resistant to growth-promoting stimuli allied with aging. Cardiac senescent cells (SCs) are highly heterogeneous cells that can regulate the pat...
Cellular senescence (CS) is characterized by stable cell cycle arrest and is resistant to growth-promoting stimuli allied with aging. Cardiac senescent cells (SCs) are highly heterogeneous cells that can regulate the pathophysiology of cardiovascular diseases (CVDs). SCs accumulate in the cardiovascular system, leading to typical age-related cardiovascular conditions. Such conditions advance in cardiovascular pathologies, including heart failure, coronary artery disease, cardiac fibrosis, etc., by evocating the production of proinflammatory mediators and profibrotic senescence-associated secretory phenotype (SASP). SCs release different factors depending on the cell type that became senescent. Many factors are responsible for CS with the aging process. The primary senescence causes are oxidative stress, metabolic dysfunction, telomere shortening, and epigenetic deregulation. However, it isn't easy to understand the molecular mechanisms that lead to CS and the consequences of CS in developing new strategies and therapeutic approaches to treat CVDs. Among all, senotherapies are an emerging approach for intervening against CS mechanisms in CVDs to potentially prevent and treat CVDS. Senotherapies allow targeting the underlying causes of aging rather than treating disorders and could reduce polypharmacy. Essentially, senotherapeutics represent an emerging anti-SC treatment and comprise three therapeutic approaches such as molecules to selectively kill SCs that are defined senolytics, compounds able to reduce evocated SC SASP, acting hence as SASP suppressors, called senomorphics, and inhibition of increase of the number of SCs in the cardiovascular tissues. Senotherapies might delay or prevent the CVDs in the elderly. Therefore, senotherapeutics represent the potential clinical application in CVDs, stressing benefits and signifying potential solutions for applying them as soon as effective anti-CVD treatments.
Mitochondria-associated membranes (MAMs) in age-related heart diseases, role of endoplasmic reticulum stress.
Silva-Palacios A, Ceja-Galicia ZA, Zúñiga-Muñoz AM … +1 more , Zazueta C
Adv Pharmacol · 2025 · PMID 40716933 · Publisher ↗
The study of interoganellar contactology represents a substantial advance in conceiving cells and their organelles. This presents a great challenge in terms of understanding their function and response to aging and in th...
The study of interoganellar contactology represents a substantial advance in conceiving cells and their organelles. This presents a great challenge in terms of understanding their function and response to aging and in the development of different pathologies. This chapter will address changes in mitochondria-associated membranes (MAMs) in aging-related heart diseases, such as acute myocardial infarction and heart failure, emphasizing the role of endoplasmic reticulum stress (ERS). We also discuss the role of MAMs as possible markers of cardiovascular disease progression in geriatrician clinics, with a view to personalized therapy. Finally, we will contemplate the use of naturally occurring drugs that have been used in the experimental setting for the regulation of mitochondrial-ER communication. (119 words).
Molecular imaging for senescent cells-targeted therapeutics in aging and age-related diseases.
Cen P
Adv Pharmacol · 2025 · PMID 40716932 · Publisher ↗
Senescent cells are attributed to aging and age-related diseases. Clearance of senescent cells can delay the aging process and treat age-related diseases. Senescent cells have typical phenotypes including permanent cell...
Senescent cells are attributed to aging and age-related diseases. Clearance of senescent cells can delay the aging process and treat age-related diseases. Senescent cells have typical phenotypes including permanent cell cycle arrest, metabolic changes, senescence-associated secretory phenotype, and other structural and functional changes. Senescent cells-targeted therapeutics containing senolytics and senomorphics have been widely investigated but still insufficient, and the internal processes are still unclear, leaving a large gap between preclinical and clinical usage for aging and age-related disease management. Thus, it is urgently demanded to discover many more drugs or new targets with in vivo pharmacodynamics and pharmacokinetics evaluation and monitoring, promoting clinical translation. As a revolutionizing approach, molecular imaging exhibited great potential in exploring the in vivo pathophysiological mechanisms and further promoting the diagnosis and therapies of diseases. It can realize the visualization of complex biochemical processes from living cells, tissues, and organs, to subjects. Benefiting from the numerous imaging probes designed and synthesized with specificity and sensitivity, molecular imaging can vigorously facilitate exploring underlying in vivo mechanisms of senescent cells and senotherapeutics for aging and age-related diseases. Moreover, conjugating the senolytics and senomorphics with imaging probes can realize in vivo image-guided therapy for senescent cells, reversing the dysfunction of aging and treating age-related diseases. Molecular imaging exhibits great potential in visualizing and monitoring senescent cells-targeted therapeutics for aging and age-related diseases, and can forcefully contribute to the clinical translation of gerophamocology.
Cellular parabioisis as a senotherapeutic approach.
Sencan S, Onaran I
Adv Pharmacol · 2025 · PMID 40716931 · Publisher ↗
Beyond cell death and differentiation, cell senescence is profoundly influenced by the social nature of cells, which is intricately linked to cell communication as a fundamental aspect of biological systems shaping both...
Beyond cell death and differentiation, cell senescence is profoundly influenced by the social nature of cells, which is intricately linked to cell communication as a fundamental aspect of biological systems shaping both individual and collective cellular behaviors. As demonstrated by cellular parabiosis, sophisticated communication plays a critical role in maintaining tissue health and delaying age-related diseases. It is now widely accepted that signaling crosstalk, through both direct cell-to-cell interactions and indirect mechanisms, drives cell heterogeneity and cell state transitions, and that increasing cell heterogeneity with age significantly contributes to the development of age-related diseases. Aging is also associated with increased stem cell heterogeneity, leading to functional decline and decreased regenerative capacity. Heterochronic parabiosis and stem cell transplantation studies have indicated that impaired regeneration observed in aging organisms can be reversed by a youthful systemic environment that restores balanced signaling and rejuvenates aged cells. Multiple reports on autologous and allogeneic transplantation have confirmed the rejuvenative potential of hematopoietic stem cell and various tissue-derived mesenchymal stem cell transplants, providing insights into the potential of integrating cellular parabiosis-like approaches into regenerative medicine to combat aging and its associated pathologies. Scientific advances in these areas are now progressing to clinical trials. In this chapter, we first summarize the current knowledge of cellular parabiosis as a complex physiological process and emphasize heterogeneity in senescent cells. Subsequently, it reviews therapeutic approaches for treating aging-induced stem cell dysfunction as innovative solutions for addressing this issue. Finally, the chapter discusses future directions and challenges for senotherapeutic applications, highlighting their potential to advance the field of regenerative medicine.
Isothiocyanates from cruciferous plants as geroprotectors.
Dmytriv TR, Lushchak VI
Adv Pharmacol · 2025 · PMID 40716930 · Publisher ↗
Isothiocyanates (ITCs) are plant secondary metabolites predominantly found in the Brassicaceae family, responsible for their characteristic pungent taste and noted for their bioactive properties. The pungency of these pl...
Isothiocyanates (ITCs) are plant secondary metabolites predominantly found in the Brassicaceae family, responsible for their characteristic pungent taste and noted for their bioactive properties. The pungency of these plants arises from mustard oils, which are generated from glucosinolates when the plant material is chewed, cut, or otherwise damaged. This chapter delves into the potential of ITCs as promising geroprotectors - agents capable of delaying aging and mitigating age-related diseases. Compounds such as sulforaphane, a well-studied ITC, exhibit remarkable antioxidant and anti-inflammatory properties, which modulate key cellular signaling pathways involved in aging. Additionally, ITCs have been shown to induce autophagy, a critical cellular process that reduces the accumulation of damaged proteins and age-related aggregates, thereby supporting cellular health. The chapter reviews the biosynthesis and bioavailability of ITCs, their role in promoting longevity, and the molecular mechanisms underlying their protective effects. It also addresses potential adverse effects and challenges associated with their application. The evidence presented underscores the potential of ITCs to contribute to healthy aging and the prevention of age-associated conditions, highlighting the need for further exploration in geriatric medicine and therapeutic development.
Pharmacological potential of calorie restriction mimetics in mitigating brain aging.
Pai V, Singh I, Singh AK
Adv Pharmacol · 2025 · PMID 40716929 · Publisher ↗
Quality of life is strongly influenced by brain aging, which is closely associated with neurodegeneration. With brain aging, various changes occur at the cellular, tissue, and organ levels, such as loss of proteostasis;...
Quality of life is strongly influenced by brain aging, which is closely associated with neurodegeneration. With brain aging, various changes occur at the cellular, tissue, and organ levels, such as loss of proteostasis; dysregulation of nutrient sensing; abnormalities in the functions of mitochondria; and changes in neurophysiology. These changes also affect cognitive capabilities and result in mild to severe cognitive impairment. The three main mechanisms of brain aging, namely, senescence, inflammation, and oxidative stress, are being investigated in experimental models. Interventions such as caloric restriction, ketone diets, and intermittent fasting have shown the potential for slowing brain aging by modulating nutrition-sensing pathways, which improve metabolic health, decrease oxidative stress, and reduce inflammatory responses. However, noncompliance with these traditional interventions makes them inefficient. To overcome this drawback, caloric restriction mimetics (CRMs), which tend to produce greater effects than traditional methods without affecting dietary intake, are better therapeutic options. This chapter focuses on the transition of CRMs from preclinical to clinical trials in humans.
Pharmacological frontiers in senescence: Transforming senescence with drug repurposing.
Shahzadi A, Ozyazgan S, Çakatay U
Adv Pharmacol · 2025 · PMID 40716928 · Publisher ↗
Repurposing conventional drugs as senotherapeutics offers a pragmatic and efficient approach to targeting cellular senescence, a key driver of aging-related diseases. Instead of relying solely on novel drug development,...
Repurposing conventional drugs as senotherapeutics offers a pragmatic and efficient approach to targeting cellular senescence, a key driver of aging-related diseases. Instead of relying solely on novel drug development, repurposing allows for the use of existing drugs with well-characterized pharmacokinetics, safety profiles, and clinical data, thereby accelerating their translation into senescence-targeted interventions. This chapter provides a comprehensive classification of senotherapeutics into senolytics, senomorphics, senoblockers, and senoreversers, detailing their mechanisms of action, molecular targets, and therapeutic applications. By categorizing these conventional agents based on their functional roles, this chapter presents a structured framework for understanding the pharmacological landscape of senotherapeutics. Additionally, this chapter discusses tissue-specific targeting, optimizing the dosing strategy to enhance the precision and safety of repurposed senotherapeutics. This chapter offers a systematic evaluation of drug repurposing, bridges the gap between preclinical and clinical applications, addressing both opportunities and challenges in repurposing the drugs. Eventually, this approach holds the potential to extend healthspan, mitigate age-related dysfunction, and provide more accessible and effective therapeutic options for disorders associated with cellular senescence.
Senotherapeutics: Milestones, innovations, and future prospects.
Atasever E, Atayik MC, Çakatay U
Adv Pharmacol · 2025 · PMID 40716927 · Publisher ↗
Gerontological practice has evolved over the decades in response to various diseases, comorbidities, and demographic factors. The many subfields that have emerged from our advancement include the study of biomedical gero...
Gerontological practice has evolved over the decades in response to various diseases, comorbidities, and demographic factors. The many subfields that have emerged from our advancement include the study of biomedical gerontology. Geropharmacology, which began to be recognized as a distinct subfield in the latter part of the 20th century, is the study of how the elderly population responds to pharmaceutical interventions, considering the effects, interactions, and side effects, along with appropriate dosages and routes. In the past, aging has generally received negative coverage. "Everyone wants to live longer, but no one wants to grow old." It is feared that old age will be rustier than gold. In recent decades, the importance of geropharmacology has increased due to the challenges we face in managing the elderly groups, alongside the growing elderly population, since these groups have altered pharmacokinetics and a higher number of comorbidities. Gerotherapeutics are pharmacological agents that can impede or decrease the rate of aging-related degenerative processes and extend lifespans by repairing damage or modulating stress resistance. Current research in the field of geropharmacology not only investigates the effects of existing conventional pharmacologic agents such as quercetin, rapamycin, aspirin, cardiac glycosides, metformin, and JAK inhibitors on the elderly population but also includes the development of new promising gerotherapeutics. AI-assisted senotherapeutic drug discovery is a continuing task in geropharmacology. No candidate drug with senescent cell targeting has yet been widely clinically tested since the senotherapeutic approach has many limitations in geriatric practice. Senescence, also, is a physiological process that continues throughout the lifespan and should not be viewed as only an effect of aging. Senescent cells found in different organs show heterogeneous phenotypes. Induction of senescence is initially a protective response that prevents older, damaged, or cancerous cells from replicating and causing further harm to the tissues. When discussing senotherapeutic medicines and their potential application in clinical practice, it is important to consider their nonspecific action on senescent cells, which may potentially aid in cancer prevention and stimulate processes related to wound healing.
Essential database resources for modern drug discovery.
Yadav S, Koka SS, Jain P … +2 more , Darwhekar GN, Vinchurkar K
Adv Pharmacol · 2025 · PMID 40175056 · Publisher ↗
In the fast-expanding field of drug discovery, researchers and pharmaceutical professionals require immediate access to critical database resources. This book chapter explains essential databases used in various stages o...
In the fast-expanding field of drug discovery, researchers and pharmaceutical professionals require immediate access to critical database resources. This book chapter explains essential databases used in various stages of drug development, such as target selection, chemical screening, and clinical trial management. Databases including PubChem, ChEMBL, and Drug Bank, highlight their contributions to providing detailed chemical knowledge, biological activity data, and drug interaction profiles. Using powerful computer programs like AI and machine learning to combine data from these sources improves decision-making, speeds up time-to-market, and raises the chances of finding effective medicines. This book chapter signifies the importance of key databases, their uses, and how they integrate into the current drug discovery process.
ADMET tools in the digital era: Applications and limitations.
Shinde SS, Giram PS, Wakte PS … +1 more , Bhusari SS
Adv Pharmacol · 2025 · PMID 40175055 · Publisher ↗
The high rate of medication failures poses a significant challenge for the pharmaceutical sector. Selecting appropriate data from experiments for ADMET (absorption, distribution, metabolism, excretion, and toxicity) pred...
The high rate of medication failures poses a significant challenge for the pharmaceutical sector. Selecting appropriate data from experiments for ADMET (absorption, distribution, metabolism, excretion, and toxicity) prediction and applying it effectively in the context of physiological characteristics is difficult. Currently, ADMET prediction is conducted early in the drug design process to filter out molecules with weak pharmacokinetic properties. Numerous ADMET models for prediction have been designed using computational methods. Verified ADMET datasets have been determined through experiments, utilizing key classifying factors and descriptors to develop in silico approaches. This chapter discusses the relevance of ADMET evaluation in drug design, methodologies for model creation, available ADMET predictive tools, and the limitations of these predicted models.
Predictive cavity and binding site identification: Techniques and applications.
Chandel S, Parashar B, Ali SA … +1 more , Sharma S
Adv Pharmacol · 2025 · PMID 40175054 · Publisher ↗
Strategies for recognizing predictive cavities and binding site identification are decisive for drug discovery, molecular docking, and tracing protein-ligand interactions. The two major approaches experimental and comput...
Strategies for recognizing predictive cavities and binding site identification are decisive for drug discovery, molecular docking, and tracing protein-ligand interactions. The two major approaches experimental and computational strive for prognosticating and distinguishing protein's binding sites. Profuse diminutive molecules are associated with the binding sites and influence normal biological functioning. The various structure-based strategies such as molecular dynamics, docking simulations, algorithms for pocket identification, and homology modeling are covered under computational techniques, where they propound the exhaustive comprehension of possible binding pockets hinge on the structure of protein and its physiochemical properties. The various sequence-based approaches rely on the homogeneousness of the sequence and machine learning replicas edified on already known protein and ligand composites to anticipate the interactive sites of novel proteins. The high-resolution structural identification and foot printing of protein to map the confirmational changes attributable to ligand and binding sites can be identified through diverse experimental methods such as NMR spectroscopy, mass spectrometry, and x-ray crystallography. These techniques are pivotal for drug discovery and designing, as the efficiency and specificity of ligands can be amplified through virtual screening and structural-based drug designing. Moreover, the ongoing developments in this domain promise to drive the revolution and efficiency in drug discovery and research in molecular biology.
Future prospective of AI in drug discovery.
Bhowmick M, Goswami S, Bhowmick P … +3 more , Hait S, Rath D, Yasmin S
Adv Pharmacol · 2025 · PMID 40175053 · Publisher ↗
Drug discovery and development is very expensive and long with an inferior success rate. It is quite inefficient and costly due to huge R&D costs and lower productivity in pharmaceutical industries, to discover effective...
Drug discovery and development is very expensive and long with an inferior success rate. It is quite inefficient and costly due to huge R&D costs and lower productivity in pharmaceutical industries, to discover effective drugs and their development. AI can revolutionize the history of drug discovery and development because it will solve all these problems. AI can identify some promising drug candidates, reduce costs, and increase precision. AI algorithms analyze large datasets, predict molecular interactions, and help optimize the design of clinical trials, making the process of drug discovery and biomedical research much more efficient. By combining cutting-edge computation with more conventional pharmaceutical strategy, AI aids in expediting the process of therapeutics development. This chapter is an investigation of the core reasons behind lower approval rates of new drugs, the potential scope of AI to improve the drug discovery and development scenario, and the practical applications in the field. This article will further explore future opportunities, key methodologies, and challenges in the implementation of AI in pharmaceutical research.
Challenges and limitations of computer-aided drug design.
Sur S, Nimesh H
Adv Pharmacol · 2025 · PMID 40175052 · Publisher ↗
Molecular Modelling in Drug Designing or Computer Aided Drug Designing (CADD) plays a significant role in new drug identification in the current world. However, it has sensitivity challenges and limitation because theore...
Molecular Modelling in Drug Designing or Computer Aided Drug Designing (CADD) plays a significant role in new drug identification in the current world. However, it has sensitivity challenges and limitation because theoretical models involve assumption and approximations Computational models are not very accurate, some of the major challenges that face these models include the following. These include, for instance, molecular-docking or molecular-dynamics-simulation models which may not represent an accurate biological system and thus the predictions will be wrong. CADD depends on the availability of accurate, high-quality structural information for target proteins and ligand. Unfortunately, there are instances when experimental structures are not available, and homology models are employed, which can be imprecise. The computational cost is another drawback; only high accuracy simulations call for huge amounts of computational power and time well-suited for screening a multitude of agents. Moreover, they have weaknesses in determining pharmacokinetic and toxicity patterns of compounds that influence drug performance and effectiveness. In other words, even though CADD greatly helps drug discovery, it is still constrained by experimental validation to solve its drawbacks and optimize its foretelling.
Real-world application of molecular docking in drug discovery.
Dutta S, Biswas I, Goswami S … +1 more , Verma A
Adv Pharmacol · 2025 · PMID 40175051 · Publisher ↗
Computational drug designing comprising mainly Molecular Docking has surged in popularity due to its efficiency and precision in identifying potential therapeutic candidates, often collectively referred to as virtual scr...
Computational drug designing comprising mainly Molecular Docking has surged in popularity due to its efficiency and precision in identifying potential therapeutic candidates, often collectively referred to as virtual screening. This method enables researchers to screen large compound libraries virtually, significantly speeding up the initial stages of drug development. The significance of molecular docking is particularly evident in the fight against rapidly evolving pathogens like SARS-CoV-2. Lately, the emergence of new COVID-19 variants, such as the highly transmissible XBB.1.5, is incessantly posing challenges. Conventional drug development approaches aimed on a single strain, outgazing the importance of virus' evolution which is well-facilitated by molecular docking that provides better assessment of therapeutic efficacy against multiple variants of this virus. In the present study, molecular docking was executed to screen potential phytochemicals against the spike protein XBB.1.5 variant, known for its critical mutations that enhance infectivity. As part of the entire screening protocol, other tools like Schrödinger's suite, SwissADME, and ProTox-II were utilized to identify the top leads. These computational facilitators assisted in estimation of binding affinity, pharmacokinetics and toxicity profiles. Estimation of these factors led to identification of promising lead compounds that depicted strong binding interactions against the mutated spike protein, suggesting their potential as broad-spectrum antiviral agents. The present study emphasizes the importance of computational tools and techniques like molecular docking in addressing the variants generated against continuous evolution of SARS-COV2. The methodologies adapted can be deployed against other disease towards development of targeted therapeutics, ensuring a proactive approach to global health threats.
Innovations in vaccine design: Computational tools and techniques.
Nag R, Srivastava S, Rizvi S … +2 more , Ahmed S, Raza ST
Adv Pharmacol · 2025 · PMID 40175050 · Publisher ↗
The advancements in computational tools have revolutionized vaccine development by organizing and analyzing large-scale immunological data through immuno-informatics. This field combines computational and mathematical ap...
The advancements in computational tools have revolutionized vaccine development by organizing and analyzing large-scale immunological data through immuno-informatics. This field combines computational and mathematical approaches to model molecular interactions during antigen presentation and processing. These tools have significantly accelerated vaccine development, making it more efficient and cost-effective. Applications such as SCWRL and SCAP help in side chain and backbone modeling to improve antibodies and forecast secondary structures. Multi-graft and multivalent scaffolds present antigens to elicit strong immune responses; antibodyomics studies the sequences of antibodies to find antibodies that can neutralize. It is another traditional way of doing vaccines where the pathogen's genome is scanned by diacide such as Vaxign to identify the likely vaccine agents. Codon optimization, as implemented with the aid of COOL and OPTIMIZER tools, enhances the output of proteins among which vaccines are needed. These tools also allow for predicting epitope structures the more accurately, or so. Prediction tools that include immunogenicity screening tests that map B-cell epitope and T-cell epitope such as ElliPro and DiscoTope aid in drug design, while the application of Fusion technologies facilitates vaccine development and kit diagnostics. The percentage of time trying to identify possible vaccine candidates is reduced alongside the costs with the application of these tools allowing the improvement in the prediction of vaccine candidates. The purpose of this chapter is to emphasize the invention of computational tools and methods that together are revolutionizing vaccine design and development and to underline the importance of tissue engineering and immunology advances.
Integrative computational approaches in pharmaceuticals: Driving innovation in discovery and delivery.
Bhojwani HR, Rajnani NP, Hare A … +1 more , Kurup NS
Adv Pharmacol · 2025 · PMID 40175049 · Publisher ↗
In recent years, the pharmaceutical industry has increasingly emphasized the role of lead compound identification in developing new therapeutic agents. Lead compounds show promising pharmacological activity against speci...
In recent years, the pharmaceutical industry has increasingly emphasized the role of lead compound identification in developing new therapeutic agents. Lead compounds show promising pharmacological activity against specific targets and are critical in drug development. Integrative computational approaches streamline this process by efficiently screening chemical libraries and designing potential drug candidates. This chapter highlights various computational techniques for lead compound discovery, including molecular modeling, cheminformatics, ligand- and structure-based drug design, molecular dynamics simulations, ADMET prediction, drug-target interaction analysis, and high-throughput screening. These methods improve drug discovery's efficiency, cost-effectiveness, and target-specific focus. Computational pharmaceutics has gained popularity due to the longer formulation development time which in turn increases the cost as well as decrease in the drug discovery production. Conventionally, formulation development relied on costly and unpredictable trial-and-error methods. However, analyzing the big data, artificial intelligence, and multi-scale modeling in computational pharmaceutics is transforming drug delivery. This chapter provides valuable insights throughout pre-formulation, formulation screening, in vivo predictions, and personalized medicine applications. Multiscale computational modeling is advancing drug delivery systems, enabling targeted treatments with multifunctional nanoparticles. Although in its early stages, this approach helps understand complex interactions between drugs, delivery systems, and patients.
Emerging horizons of AI in pharmaceutical research.
Bachhar S, Kumar S, Dutta B … +1 more , Das S
Adv Pharmacol · 2025 · PMID 40175048 · Publisher ↗
Artificial Intelligence (AI) has revolutionized drug discovery by enhancing data collection, integration, and predictive modeling across various critical stages. It aggregates vast biological and chemical data, including...
Artificial Intelligence (AI) has revolutionized drug discovery by enhancing data collection, integration, and predictive modeling across various critical stages. It aggregates vast biological and chemical data, including genomic information, protein structures, and chemical interactions with biological targets. Machine learning techniques and QSAR models are applied by AI to predict compound behaviors and predict potential drug candidates. Docking simulations predict drug-protein interactions, while virtual screening eliminates large chemical databases through efficient sifting. Similarly, AI supports de novo drug design by generating novel molecules, optimized against a particular biological target, using generative models such as generative adversarial network (GAN), always finding lead compounds with the most desirable pharmacological properties. AI used in clinical trials improves efficiency by pinpointing responsive patient cohorts leveraging genetic profiles and biomarkers and maintaining propriety such as dataset diversity and compliance with regulations. This chapter aimed to summarize and analyze the mechanism of AI to accelerate drug discovery by streamlining different processes that enable informed decisions and bring potential life-saving therapies to market faster, amounting to a breakthrough in pharmaceutical research and development.
Pharmacophore modeling in drug design.
Momin Y, Beloshe V
Adv Pharmacol · 2025 · PMID 40175047 · Publisher ↗
A successful and expanded area of computational drug design is pharmacophore modeling. A pharmacophore is a description of the structural features of a compound that are essential to its biological activity. The rational...
A successful and expanded area of computational drug design is pharmacophore modeling. A pharmacophore is a description of the structural features of a compound that are essential to its biological activity. The rational design of new drugs has made extensive use of the pharmacophore concept. By schematically illustrating the essential components of molecular recognition, Pharmacophores can be used to represent and identify molecules in two or three dimensions. Besides target identification, the pharmacophore concept is also helpful for side effects, off-target, and absorption, distribution, and toxicity modeling. Moreover, to enhance virtual screening, pharmacophores, and molecular docking simulations are frequently coupled. A completely new area of drug design has been made possible by the development of machine learning techniques and pharmacophore mapping algorithms, wherein an ineffective molecule with the right modifications may have the potential to function as an inhibitor. This approach has been stimulated by its predictive abilities to assess the possibility that a set of compounds will be active against protein targets of interest. With alignment to the standard pharmacophore model, active compounds of the protein target can be developed. The pharmacophore modeling/screening technique is used to identify possible proteins of interest and seek out/suggest novel therapeutic uses for the drug.
The translational impact of bioinformatics on traditional wet lab techniques.
Suveena S, Rekha AA, Rani JR … +2 more , V Oommen O, Ramakrishnan R
Adv Pharmacol · 2025 · PMID 40175046 · Publisher ↗
Bioinformatics has taken a pivotal place in the life sciences field. Not only does it improve, but it also fine-tunes and complements the wet lab experiments. It has been a driving force in the so-called biological scien...
Bioinformatics has taken a pivotal place in the life sciences field. Not only does it improve, but it also fine-tunes and complements the wet lab experiments. It has been a driving force in the so-called biological sciences, converting them into hypothesis and data-driven fields. This study highlights the translational impact of bioinformatics on experimental biology and discusses its evolution and the advantages it has brought to advancing biological research. Computational analyses make labor-intensive wet lab work cost-effective by reducing the use of expensive reagents. Genome/proteome-wide studies have become feasible due to the efficiency and speed of bioinformatics tools, which can hardly be compared with wet lab experiments. Computational methods provide the scalability essential for manipulating large and complex data of biological origin. AI-integrated bioinformatics studies can unveil important biological patterns that traditional approaches may otherwise overlook. Bioinformatics contributes to hypothesis formation and experiment design, which is pivotal for modern-day multi-omics and systems biology studies. Integrating bioinformatics in the experimental procedures increases reproducibility and helps reduce human errors. Although today's AI-integrated bioinformatics predictions have significantly improved in accuracy over the years, wet lab validation is still unavoidable for confirming these predictions. Challenges persist in multi-omics data integration and analysis, AI model interpretability, and multiscale modeling. Addressing these shortcomings through the latest developments is essential for advancing our knowledge of disease mechanisms, therapeutic strategies, and precision medicine.
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