Table of Contents
Overview
Definition and Scope
Molecular pharmacology is defined as a subcategory of pharmacological research that focuses on understanding how drugs interact with cellular processes, structures, and macromolecules at a molecular level.[2.1] This branch of pharmacology is concerned with the study of pharmaceuticals and natural compounds used in the treatment of diseases, as well as the molecular basis of diseases themselves.[3.1] The primary aim of molecular pharmacologists is to develop pharmacologically active agents that can effectively target specific molecular pathways involved in disease processes.[3.1] Furthermore, molecular pharmacology has introduced a new dimension to the drug discovery paradigm by providing a molecular basis for tissue dysfunction.[4.1] The mapping of the human genome has enhanced this field, as it has led to the belief that defects in single genes can significantly impact drug interactions and therapeutic outcomes.[4.1] Overall, molecular pharmacology encompasses various aspects, including the basic concepts of pharmacology, routes of drug administration, pharmacokinetics, pharmacodynamics, and the molecular mechanisms of drug action, as well as the study of different types of receptors and receptor pharmacology.[1.1]Importance in Drug Development
Molecular pharmacology is pivotal in drug development, enhancing our understanding of drug interactions with biological systems at the molecular level. This knowledge is crucial for implementing pharmacogenomics, which customizes drug selection and dosing based on individual genetic profiles, thereby improving drug efficacy and safety. The clinical application of pharmacogenomics involves developing tools and infrastructures to support personalized medicine and researching new pharmacogenomic markers to enhance treatment outcomes in various clinical settings, such as chemotherapy for breast cancer and anticoagulant therapy for cardiovascular diseases.[5.1] The emergence of personalized medicine in the late 1990s underscored the importance of tailoring treatments to patients' unique genetic profiles. This approach has significantly influenced the development of targeted therapies, as demonstrated by the FDA approval of several cancer drugs with companion diagnostic assays, marking a shift from a "one size fits all" approach to a more individualized strategy in medical treatment.[7.1] Pharmacokinetics (PK) and pharmacodynamics (PD) are essential components of molecular pharmacology that inform drug development. PK examines how drugs are absorbed, distributed, metabolized, and excreted, while PD explores the relationship between drug concentration and its effects on physiological systems. The interplay between PK and PD is vital for optimizing drug dosing regimens, as variations in metabolism can significantly impact therapeutic outcomes. Understanding factors like the first-pass effect and organ function's impact on drug clearance helps clinicians determine appropriate dosing strategies for individual patients.[12.1] Furthermore, integrating artificial intelligence (AI) and machine learning into molecular pharmacology is transforming drug discovery and development. These technologies enhance the ability to predict drug interactions and optimize treatment plans based on genetic data, thereby improving the precision of pharmacotherapy. AI's role in reshaping pharmacogenomics allows for more effective treatment decisions, minimizing adverse reactions, and optimizing drug dosages, marking a significant advancement in personalized medicine.[14.1]In this section:
Molecular PharmacologyPharmacological ResearchPharmacologyMolecular BasisMolecular Pathways
History
Birth of Pharmacology
The origins of pharmacology can be traced back to ancient civilizations, where the use of herbs and plants for medicinal purposes was prevalent. Early healing practices laid the groundwork for pharmacological principles, with significant contributions from various cultures, including the Egyptians, Greeks, and Chinese. For instance, the Ebers Papyrus from ancient Egypt and Babylonian clay tablets from around 700 B.C. provide early documentation of medicinal substances and their applications, highlighting the systematic approach to healing that characterized these ancient practices.[48.1] The transition from traditional healing practices to more scientific methods of drug development began to take shape during the Renaissance, which saw the rediscovery and translation of ancient texts. This period fostered innovative research that propelled pharmacological progress, leading to the establishment of pharmacology as an independent discipline in the 19th century. Pivotal figures such as Oswald Schmiedeberg, often referred to as the "Father of Modern Pharmacology," played a crucial role in this transformation by advocating for experimental methods and the physiological basis of drug action.[50.1] In addition to the foundational contributions of ancient and Renaissance scholars, the evolution of pharmacology was significantly influenced by the advent of synthetic drugs in the 19th and 20th centuries. This era marked a shift towards more systematic and evidence-based approaches in drug development, as researchers began to understand disease processes and drug mechanisms more comprehensively. The integration of traditional medicinal knowledge, such as that found in Traditional Chinese Medicine (TCM), into modern drug discovery exemplifies the ongoing relevance of historical practices in contemporary pharmacology.[49.1] Furthermore, the mid-20th century brought about groundbreaking advancements in molecular biology, particularly with the discovery of DNA's structure and the development of recombinant DNA technology. These innovations laid the foundation for targeted therapies in molecular pharmacology, transforming treatment approaches and expanding the possibilities for drug development.[51.1] Thus, the birth of pharmacology is characterized by a rich tapestry of historical practices, scientific advancements, and the continuous interplay between traditional knowledge and modern methodologies.Key Figures and Milestones
Molecular pharmacology has evolved significantly over the years, marked by key figures and milestones that have shaped its development. The field began to take shape in the late 19th century, when pharmacology emerged as a distinct discipline, focusing on the physiological effects of drugs. However, it was not until the mid-20th century that molecular pharmacology began to flourish, driven by advancements in biochemistry and molecular biology. This period saw a pivotal shift from a purely physiological understanding of drug action to a more nuanced comprehension of molecular mechanisms, particularly with the discovery of receptors in the 1940s and 1950s, which laid the groundwork for future research and therapeutic applications.[42.1] One of the most influential figures in this transition was Oswald Schmiedeberg, often referred to as the "Father of Modern Pharmacology." His work helped establish pharmacology as a scientific discipline, emphasizing the importance of experimental methods in understanding drug action.[41.1] The emergence of organized pharmacology departments further facilitated the growth of the field, allowing for collaborative research and the establishment of formalized clinical trials, particularly during the early to mid-20th century.[41.1] The late 20th century marked another significant milestone with the advent of molecular targeted therapies, which have transformed cancer treatment. These therapies, which include small molecules, monoclonal antibodies, and immunotherapeutic agents, specifically target molecular pathways involved in cancer progression. For instance, the development of tyrosine kinase inhibitors (TKIs) and EGFR inhibitors exemplifies how molecular pharmacology has leveraged advancements in molecular biology to create effective treatments for oncogene-driven cancers.[54.1] This evolution reflects a broader trend towards personalized medicine, where treatments are tailored to the individual molecular profiles of patients, underscoring the importance of molecular pharmacology in contemporary healthcare.[41.1]In this section:
Mechanisms Of Action
Molecular Interactions
Molecular interactions are fundamental to understanding the mechanisms of action in molecular pharmacology. Target validation is a critical process that evaluates whether a molecular target plays a significant role in a disease process and whether pharmacological modulation of that target could be effective for a specific patient population.[86.1] This evaluation often involves a comprehensive analysis of the physicochemical properties of known drug-binding sites, which are hypothesized to contain advantageous characteristics for drug binding, referred to as "druggable microenvironments".[89.1] Advancements in genomics and proteomics have significantly enhanced our understanding of drug-ligand interactions. For instance, global proteomics can profile proteins that are differentially expressed between normal and disease states, providing candidates for drug development.[98.1] Additionally, activity-based protein profiling (ABPP) technologies have been employed to generate global maps of small molecule-protein interactions, thereby expanding the druggability of the human proteome.[99.1] These methodologies allow researchers to identify and validate potential drug targets more effectively. Moreover, high-throughput proteomics has become increasingly important in the drug development process, enabling the identification of numerous protein expression changes following drug treatment or disease perturbation.[102.1] This capability is crucial for target identification, as it allows for the development of efficacy and toxicity biomarkers that can inform the drug discovery process. Despite these advancements, challenges remain in elucidating the mechanisms of action for new compounds. The cell membrane acts as a natural barrier that can hinder therapeutic proteins, peptides, and oligonucleotides from reaching their sites of action.[112.1] To address this, researchers are exploring delivery-enhancing peptides that can facilitate the transport of these therapeutic agents across cellular barriers, thereby improving their pharmacological effects.Pharmacodynamics and Pharmacokinetics
Pharmacodynamics is a critical area of study in molecular pharmacology that focuses on the biochemical, cellular, and physiological actions of drugs, including the molecular mechanisms by which these actions are achieved. It encompasses the interactions between drugs and their biological targets, such as receptors and enzymes, which yield physiological responses.[78.1] The pharmacodynamic effects of drugs are influenced by their mechanisms of action, which include receptor interactions, enzyme inhibition, and modulation of ion channels.[82.1] Understanding these mechanisms is essential for guiding effective treatment strategies and improving patient outcomes. The pharmacodynamics of a drug is based on three main principles: the amount of drug that binds to receptors, the ability of the drug to influence these receptors, and the duration for which the drug remains present to exert its metabolic effects.[85.1] The time course of pharmacodynamic effects is dependent on the specific biochemical pathways of the target, which can lead to immediate or delayed effects following drug administration.[84.1] For instance, neuromuscular blocking agents like succinylcholine interact with nicotinic acetylcholine receptors, resulting in rapid muscle contraction followed by paralysis within a minute of administration.[84.1] Pharmacokinetics, on the other hand, deals with the absorption, distribution, metabolism, and excretion of drugs. Understanding excretion pathways is particularly important for optimizing drug therapy, especially in patients with impaired renal or hepatic function.[83.1] The pharmacokinetic properties of a drug can significantly influence its pharmacodynamic effects, as the concentration of the drug at the site of action is crucial for achieving the desired therapeutic outcome. The relationship between pharmacodynamics and pharmacokinetics is vital in drug development and patient care. For example, drugs that bind to receptors with high affinity often exhibit prolonged effects due to slow dissociation rates from the receptor.[90.1] This characteristic can be critical in designing drugs that require sustained action. Additionally, the structural characteristics of a drug, including its chemical composition and the specific amino acids at the binding site, play a significant role in determining its binding affinity to receptors or enzymes.[92.1] Understanding these interactions can lead to more effective drug design and improved therapeutic efficacy.Recent Advancements
Innovations in Drug Design
Recent advancements in molecular pharmacology have revolutionized drug design by integrating cutting-edge technologies and methodologies. A pivotal development is the use of multi-omics data, which includes genomics, transcriptomics, proteomics, and metabolomics. This comprehensive approach accelerates drug discovery by providing a deep understanding of the biological mechanisms underlying disease pathophysiology [137.1]. Artificial Intelligence (AI) is instrumental in processing this complex data, offering new insights that refine the drug design process. AI's role extends to enhancing cancer research by analyzing multi-omics data to identify novel anticancer targets and drugs. This is crucial given the high costs and lengthy timelines of traditional drug development, where only about 10% of candidates succeed in reaching the market due to efficacy and safety issues [138.1]. AI-driven techniques improve target identification and predict druggability, thus streamlining the drug discovery process [138.2]. An example of AI's impact is PaccMann, a framework that predicts cancer cell sensitivity to compounds by integrating molecular structures, gene expression profiles, and protein interaction data. This illustrates AI's potential to identify effective drug candidates efficiently [138.3]. Additionally, classifying diseases and stratifying patients based on molecular profiles enables personalized therapeutic approaches, optimizing treatment efficacy while reducing adverse effects [126.1]. Emerging trends in clinical pharmacology, such as the Model-Informed Drug Development (MIDD) pilot program, highlight the evolving landscape of drug design. This program leverages real-world data to inform drug development and evaluation processes [127.1]. Furthermore, the qualification of biomarkers, like KIM-1 for detecting acute drug-induced nephrotoxicity, underscores the importance of regulatory collaboration in advancing drug development methodologies [130.1].Targeted Therapies and Precision Medicine
Recent advancements in molecular pharmacology have significantly influenced the development of targeted therapies and precision medicine, particularly in the realm of cancer treatment. Personalized medicine, which tailors medical treatment to the individual characteristics of each patient, has emerged as a promising approach that leverages genetic information to optimize treatment strategies. This shift from a "one-size-fits-all" model to a more individualized understanding of health and disease is facilitated by advancements in genomics and biotechnology, enabling healthcare providers to predict disease risks and tailor treatments based on individual genetic profiles.[134.1] One of the key components of personalized medicine is pharmacogenomics, which examines how genetic variations affect individual responses to drugs. This field aims to enhance treatment efficacy and minimize adverse effects by considering patient-specific characteristics, including genetic makeup and biomarkers.[132.1] The integration of these factors allows for more precise treatment targeting and effective disease management, particularly in oncology.[133.1] In cancer therapy, the application of personalized medicine has led to the development of innovative treatment modalities, such as personalized cancer vaccines and immunotherapies. For instance, recent studies have demonstrated the efficacy of personalized cancer vaccines for renal cell carcinoma, achieving a remarkable 100% efficacy rate in clinical trials.[143.1] Additionally, immunotherapy has gained traction in treating non-small cell lung cancer (NSCLC), with ongoing research focusing on biomarkers to predict patient responses to therapies like checkpoint inhibitors.[144.1] Moreover, artificial intelligence (AI) is playing a transformative role in reshaping pharmacogenomics and drug therapy, enhancing the ability to guide treatment decisions and optimize drug dosages.[136.1] This synergy between AI and pharmacogenomics marks a significant advancement in the field of personalized medicine, offering a more effective and patient-centric approach to treatment. Despite the promising developments, challenges remain in the implementation of personalized medicine. The complexity of genetic data and the need for actionable clinical information can complicate the integration of these advancements into routine clinical practice.[142.1] Nonetheless, the potential benefits of personalized medicine, including improved treatment outcomes and the ability to tailor therapies to individual patient needs, underscore its importance in the future of healthcare.[141.1]In this section:
Research Methodologies
Experimental Techniques
Experimental techniques in molecular pharmacology encompass a variety of methodologies that are essential for understanding drug interactions and developing new therapeutic agents. These techniques include both traditional and innovative approaches that leverage advancements in genomics, proteomics, and analytical chemistry. One significant area of focus is the integration of genomics and proteomics, which enhances the understanding of drug interactions at the molecular level. Recent studies have demonstrated that combining these methodologies can lead to breakthroughs in drug discovery by identifying and validating drug targets, elucidating drug action mechanisms, and predicting drug resistance.[177.1] For instance, the analysis of human exomes has revealed the impact of rare protein-coding genetic variants on plasma proteins, providing insights into potential therapeutic targets.[176.1] In addition to genomic and proteomic approaches, molecular pharmacology relies heavily on various analytical techniques. High-performance liquid chromatography (HPLC), gas chromatography, and mass spectrometry are commonly employed to analyze drug interactions and pharmacokinetics.[187.1] These methods allow researchers to quantify drug concentrations and assess their effects in biological systems, thereby facilitating a deeper understanding of drug action and metabolism. Moreover, the field has seen the emergence of adaptive design methodologies in clinical trials, which promote flexibility in study designs based on real-time data. This approach allows for modifications in trial protocols to better address patient variability and optimize therapeutic outcomes.[181.1] Regulatory agencies, including the FDA and the European Medicines Agency, have recognized the importance of adaptive designs, which are increasingly being utilized to enhance the efficiency and effectiveness of drug development processes.[180.1]Computational Approaches
Recent advancements in computational approaches have significantly transformed the landscape of molecular pharmacology, particularly in drug discovery and development. The integration of various technologies, including virtual screening (VS), high-throughput screening (HTS), and computational modeling, has streamlined the identification and evaluation of lead compounds, enhancing the efficiency and success rates of drug discovery campaigns.[196.1] Virtual screening campaigns have become essential components of drug discovery, complementing traditional high-throughput screening methods. This integration allows for a more comprehensive assessment of potential drug candidates, as computational methods can rapidly analyze vast libraries of compounds, identifying those with the highest likelihood of therapeutic efficacy.[197.1] The advent of advanced computational techniques, such as molecular modeling, cheminformatics, and structure-based drug design (SBDD), has further revolutionized the process, enabling researchers to predict drug-ligand interactions and optimize lead compounds more effectively.[198.1] Moreover, the application of machine learning and artificial intelligence in drug discovery has facilitated the development of sophisticated models that can predict the pharmacological properties of compounds based on their molecular structures. For instance, the use of Graph Neural Networks (GNN) in conjunction with traditional cheminformatics has provided a robust framework for automating the drug discovery process, allowing for the prediction of drug potential and the refinement of protein structures.[198.1] This comprehensive approach not only accelerates the identification of promising candidates but also enhances the understanding of molecular interactions that underpin drug efficacy.[186.1]In this section:
Applications
Treatment of Diseases
Molecular pharmacology plays a pivotal role in the treatment of various diseases by enabling the development of personalized medicine approaches. One significant application is pharmacogenomics, which studies how genetic variations influence drug response, thereby facilitating the tailoring of drug therapies to individual patients. This approach has been instrumental in identifying genetic variants that affect the effectiveness of specific treatments, such as trastuzumab (Herceptin) for HER2-positive breast cancer. Pharmacogenomic testing allows healthcare providers to select medications that are more likely to be effective based on a patient’s genetic profile, ultimately leading to safer and more effective treatments.[224.1] Currently, pharmacogenomics is utilized for a limited number of health conditions and medications, including treatments for HIV, certain cancers, depression, and heart disease. By identifying genetic variations that influence drug metabolism, pharmacogenomics can guide the selection of drugs and dosages tailored to individual patients, thereby minimizing side effects and enhancing therapeutic outcomes.[225.1] Moreover, molecular pharmacology extends beyond pharmacogenomics to encompass a broader range of therapeutic strategies. It facilitates the classification of diseases and stratification of patients based on their molecular profiles, which maximizes treatment efficacy and minimizes adverse effects. This approach is particularly relevant in the development of molecular therapeutics, which utilize insights from genetics and biomarkers to create targeted treatments for various diseases, including autoimmune disorders and infectious diseases.[228.1] The integration of molecular pharmacology into clinical practice has shown promising results in improving patient outcomes. For instance, advancements in molecular medicine have led to the development of targeted therapies that provide more personalized and effective treatment options for cancer patients. Emerging technologies, such as gene editing and RNA therapies, are at the forefront of this revolution, holding immense potential for future therapeutic applications.[229.1]Development of New Therapeutics
Molecular pharmacology plays a pivotal role in the development of new therapeutics by focusing on the molecular mechanisms underlying drug action and disease processes. This branch of pharmacology not only investigates the molecular causes of diseases but also aims to discover pharmacologically active substances that can be utilized to treat various illnesses.[199.1] The integration of molecular biology techniques and computational approaches has significantly enhanced drug discovery processes, allowing researchers to predict drug targets and drug-ligand interactions more effectively.[200.1] Furthermore, molecular pharmacology contributes to the understanding of drug action at the cellular and molecular levels, which is essential for the development of new drug molecules.[200.1] The application of innovative structural biology, biochemistry, and molecular biology provides mechanistic insights that are crucial for addressing basic pharmacological problems.[201.1] These insights facilitate the identification of new therapeutic targets and the design of drugs that can interact more effectively with these targets. Advancements in medical imaging techniques and computational modeling have further enriched our understanding of drug-ligand interactions, which is vital for optimizing drug design.[203.1] For instance, accurate screening of candidate drug ligands against target proteins through computational methods allows for the prediction of binding affinities, thereby streamlining the drug development process.[204.1] Moreover, the emergence of personalized medicine, driven by pharmacogenomics, is transforming therapeutic development by tailoring treatments based on individual genetic profiles.[206.1] This approach not only enhances treatment efficacy but also minimizes adverse effects, thereby improving patient outcomes.[207.1] The integration of artificial intelligence in pharmacogenomics is also revolutionizing personalized medicine by optimizing drug dosages and guiding treatment decisions.[208.1] Finally, advancements in genomic technologies, such as next-generation sequencing (NGS), are opening new avenues in drug discovery and personalized medicine. NGS facilitates rapid identification of new drug targets and aids clinicians in selecting the most appropriate therapies for individual patients.[210.1] Overall, molecular pharmacology is at the forefront of developing innovative therapeutics that are increasingly personalized and effective.Challenges And Future Directions
Addressing Drug Resistance
Addressing drug resistance in molecular pharmacology is a critical area of focus, particularly in the context of cancer and cardiovascular diseases. One of the significant challenges is the development of precision medicine and genomics, which aims to tailor treatments to individual patients. This approach is essential for overcoming the limitations of traditional therapies that often fail due to the heterogeneity of diseases like cardiovascular diseases (CVDs) and cancer.[234.1] In cancer research, artificial intelligence (AI) plays a pivotal role in addressing drug resistance by analyzing multiomics data to identify novel anticancer targets and drugs. This integration of AI into drug discovery processes enhances the ability to develop effective therapies that can circumvent resistance mechanisms.[237.1] Furthermore, the optimization of drug bioavailability is crucial in this context. Researchers are exploring innovative strategies, such as probiotic formulations that can modulate the gut microbiome to improve drug absorption, thereby potentially reducing the incidence of drug resistance.[235.1] Another significant challenge in addressing drug resistance is the reliance on existing animal models, particularly in the study of Alzheimer's disease (AD). These models often fail to replicate the full spectrum of disease symptoms and may not accurately predict the efficacy of drugs in clinical settings. This discrepancy highlights the need for more representative models that can better inform drug development and resistance mechanisms.[236.1]Ethical Considerations in Research
Ethical considerations in molecular pharmacology research are increasingly significant, particularly as advanced technologies such as artificial intelligence (AI) and organ-on-a-chip systems are integrated into drug discovery and development processes. The use of AI in oncology, for instance, presents challenges related to data security, representation, and the explainability of AI-based predictions, especially in multidisciplinary decision-making contexts like cancer conferences. These challenges must be addressed to ensure that AI applications can effectively inform treatment decisions and improve patient outcomes while maintaining ethical standards in patient care and data handling.[239.1] Moreover, the integration of AI technologies into clinical practice is not without its hurdles. Promising studies indicate that AI can enhance imaging and other aspects of cancer care, yet substantial efforts are required to improve the quality and quantity of data available for research. This includes validating AI results across various institutions and translating findings into clinical settings, which raises ethical questions about the reliability and accountability of AI-driven decisions in patient treatment.[241.1] In addition, the pharmaceutical industry is exploring innovative methods for drug discovery, with organ-on-a-chip technology emerging as a potential game-changer. This technology mimics the physiological environment of human organs, allowing for more accurate disease modeling and drug testing. However, ethical considerations surrounding the use of such technologies must be carefully navigated, particularly regarding the implications for animal testing and the treatment of human subjects in research.[245.1] As molecular pharmacology continues to evolve, it is crucial to balance the benefits of these advanced technologies with the ethical responsibilities of researchers to ensure that patient welfare, data integrity, and the principles of informed consent are upheld throughout the research process.References
[1] Introduction to molecular pharmacology: basic concepts — This chapter discusses the basic concepts of pharmacology, different emerging branches of pharmacology, routes of drug administration, basics about the pharmacokinetics and pharmacodynamics of the drugs, molecular mechanisms of drug action, and different types of receptors and receptor pharmacology.
[2] Molecular Pharmacology - an overview | ScienceDirect Topics — Molecular pharmacology is defined as a subcategory of pharmacological research that focuses on understanding how drugs interact with cellular processes, structures, and macromolecules at a molecular level.
[3] What is Molecular Pharmacology? (with pictures) - AllTheScience — Molecular pharmacology is a branch of the field of pharmacology which is concerned with the study of pharmacology on a molecular basis. Molecular pharmacologists study the molecular study of pharmaceuticals and natural compounds used in the treatment of disease, and they also study disease on a molecular basis with the goal of developing pharmacologically active agents which could be used to
[4] Molecular Pharmacology - an overview | ScienceDirect Topics — Molecular pharmacology thus added a new dimension to the drug discovery paradigm with the provision of a molecular basis for tissue dysfunction (Enna, Fuerstein, Piette, & Williams, 2008). The mapping of the human genome provided an additional certainty to the molecular equation such that it was believed that defects in a single gene would be
[5] Pharmacogenomics and Personalized Medicine - PMC — These include clinical implementation of pharmacogenomics in clinical practice, development of tools or infrastractures to support this process, research of new pharmacogenomics markers to increase drug efficacy and safety, and the impact of rare genetic variants in pharmacogenomics. The study of genetics has been widely applied in precision medicine, and one of the emerging applications is pharmacogenomics-informed pharmacotherapy, tailoring drug selection and dosing to the patient’s genetic features. In conclusion, the studies collected in this volume underline the potential of innovative molecular approaches, including multilocus genotyping, sequencing of rare variants and epigenetic features, in identifying genetic determinants of interindividual variability in the effects of drugs in several important clinical settings, including chemotherapy of breast cancer and leukemia and anticoagulant therapy for cardiovascular diseases.
[7] Advancing Research in Personalized Medicine - U.S. Pharmacist — The National Institutes of Health’s National Human Genome Research Institute (NHGRI) indicates that the majority of medical treatments are designed for the general population with a “one size fits all” approach, and while many of these therapies are effective, not all patients may respond to them.1 According to the NHGRI, personalized medicine, also referred to as precision medicine, is a promising and evolving practice of medicine that employs an individual’s genetic profile, which can guide clinicians in ascertaining the best approaches to possibly prevent, diagnose, and treat and/or manage certain diseases and medical conditions.2 Additionally, using a patient’s genetic profile can be valuable in prescribing the best medication or therapy and dosage to suit the individual needs of the patient.1-3 The Personalized Medicine Coalition (PMC) indicates that personalized medicine has the potential to enhance treatment outcomes across a spectrum of diseases via targeted therapies, therefore adding to the effectiveness of medicine.
[12] Mechanisms of drug interactions: pharmacodynamics and pharmacokinetics ... — Pharmacodynamics describes the relationship between drug concentration and drug response. Pharmacokinetics describes the relationship between the rates of change of drug concentrations in the different parts of the body. Pharmacodynamic interactions occur between drugs with similar or opposite pharmacological effects.
[14] AI's role in revolutionizing personalized medicine by reshaping ... — AI's role in revolutionizing personalized medicine by reshaping pharmacogenomics and drug therapy - ScienceDirect Search ScienceDirect AI's role in revolutionizing personalized medicine by reshaping pharmacogenomics and drug therapy open access This paper examines the transformative impact of artificial intelligence (AI) on pharmacogenomics, signaling a paradigm shift in personalized medicine. The review emphasizes AI's role in guiding treatment decisions, minimizing adverse reactions, and optimizing drug dosages in clinical settings. This work underscores the synergy of AI and pharmacogenomics, offering a more effective and patient-centric approach to drug therapy, marking a significant advancement in the field of personalized medicine. Previous article in issue Next article in issue No articles found. For all open access content, the relevant licensing terms apply.
[41] History of Pharmacology — Ancient Beginnings: Pharmacological Knowledge in Earliest Civilizations Healing Traditions of PrehistoryPharmacology in Ancient MesopotamiaThe Ebers Papyrus and the Foundations of Egyptian MedicineGreek Contributions and the Notion of “Pharmakon”Development Through the Medieval and Islamic Golden Age Byzantine and Islamic ScholarsMonastic Medicine in EuropeParacelsus: “The Dose Makes the Poison”Renaissance to Early Modern Period: Laying Formal Foundations Herbalism and Expanding PharmacopeiasWilliam Withering and Clinical ObservationEmergence of Chemistry as a Scientific FieldThe 19th Century: Pharmacology Emerges as an Independent Discipline Shift Toward Physiological and Experimental ApproachesMagendie and Bernard: Foundational Experimental MethodsOswald Schmiedeberg: The “Father of Modern Pharmacology”Emergence of Organized Pharmacology DepartmentsThe Early to Mid-20th Century: Expansion and Institutionalization World Wars and Antibiotic RevolutionRise of Synthetic DrugsFormalized Clinical TrialsInstitutional Support and JournalsLate 20th Century: Molecular Pharmacology and Biotechnology Receptor Theory and Biochemical MechanismsPharmacokinetics and PharmacodynamicsBiotechnological Breakthroughs: Recombinant Proteins and Monoclonal AntibodiesGlobal Collaboration NetworksContemporary Pharmacology: Personalized Medicine and Beyond Genomics and Personalized MedicineHigh-Throughput Screening and Rational Drug DesignBiologics, Gene Therapy, and Novel ModalitiesEthical and Regulatory ChallengesKey Figures in Pharmacology: Brief Historical Portrait Gallery Teaching, Literature, and Ongoing Research Educational Pathways and TextbooksScientific Journals and Drug Information CentersOngoing and Future ResearchReflections on the Evolution of Pharmacology From Intuition to Experimental ScienceA Cornerstone of Modern HealthcareEthical Responsibilities and Global AccessConclusion
[42] Drug Development: Advances in Molecular Pharmacology - ScienceHolic — Molecular pharmacology emerged in the mid-20th century, driven by advancements in biochemistry and molecular biology. Before this period, pharmacology primarily focused on the physiological effects of drugs without a deep understanding of the underlying molecular mechanisms. A key milestone was the discovery of receptors in the 1940s and 1950s.
[48] The Evolution of Medicine | Pharmacology Mentor — The Evolution of Medicine | Pharmacology Mentor Reading: The Evolution of Medicine: From Ancient Remedies to Modern Therapeutics Pharmacology Mentor > Blog > Pharmacology > General > The Evolution of Medicine: From Ancient Remedies to Modern Therapeutics The Evolution of Medicine: From Ancient Remedies to Modern Therapeutics IntroductionAncient Therapeutic Writings: India and ChinaThe Vedas and AyurvedaChinese Materia MedicaWestern Medicine: Egypt, Assyria, and BabyloniaEgyptian PapyriBabylonian Clay TabletsHippocrates: The Father of Modern MedicineThe 19th Century: A Period of TransformationAllopathy and Heroic TreatmentThe Rise of HomeopathyConclusion A Babylonian clay tablet from around 700 B.C. lists approximately 300 drugs, providing another early glimpse into the world of medicine. TAGGED: medicine, Pharmacology Next Article Understanding Pharmacology: From Basic Principles to Nature of Drugs Pharmacology258 Pharmacology
[49] Historical Perspective of Traditional Indigenous Medical Practices: The ... — Our earlier endeavors, which focused on discussing the current research and development of Chinese herbal medicine (CHM), and the trend in drug discovery, as well as a variety of CAM, aimed to promote the utilization of natural and traditional resources for contemporary health care, including food/diet therapy [7, 21–24]. 2. Chinese Herbal Medicine (CHM) Chinese herbal medicine (CHM) in China. While therapeutic interventions using multiple drugs in modern medicine are based on an understanding of disease processes and drug mechanisms, the use of multicomponent herbal formulae (Fu-Fang in Chinese herbal medicine) is based on CM theory and practical experience.
[50] The Evolution of Pharmacology: From Ancient Herbs to Biopharma — The Evolution of Pharmacology: From Ancient Herbs to Biopharma - BiologyInsights Explore the journey of pharmacology's transformation from ancient herbal remedies to cutting-edge biopharmaceutical advancements. This article will explore pivotal moments that have shaped the field, beginning with ancient practices and moving through alchemical and renaissance contributions to modern advancements in synthetic drugs and biotechnology. The roots of pharmacology can be traced back to ancient civilizations, where the use of herbs and plants for medicinal purposes was common. The rediscovery and translation of ancient texts, coupled with innovative research, provided fertile ground for pharmacological progress. The 19th and 20th centuries heralded a new era in pharmacology with the advent of synthetic drugs, transforming the landscape of medicine.
[51] Future of Molecular Biotechnology: Advancements in Cancer Research — The foundations of molecular biotechnology were laid in the mid-20th century with the discovery of DNA's structure by James Watson and Francis Crick in 1953. The field gained momentum with the development of recombinant DNA technology in the 1970s, pioneered by Herbert Boyer and Stanley Cohen.
[54] PDF — Recent advancements in molecular biology and genomic sequencing have led to the development of therapies specifically designed to inhibit oncogene-driven cancers. Targeted therapies, such as tyrosine kinase inhibitors (TKIs), monoclonal antibodies, and small-molecule inhibitors, have shown promising results in treating cancers with oncogenic mutations. For example, EGFR inhibitors (e.g
[78] Pharmacodynamics: Molecular Mechanisms of Drug Action — Pharmacodynamics is the study of the biochemical, cellular, and physiological actions of drugs, including the molecular mechanisms by which these actions are achieved. Most drugs are small molecules that interact with macromolecular entities, or drug targets, intrinsic to the body or to pathogens.Drug targets include receptors for endocrine and paracrine factors, enzymes, voltage-gated ion
[82] Mechanisms of Drug Action to Know for Intro to Pharmacology - Fiveable — Understanding how drugs work is key in pharmacology. Mechanisms of drug action include receptor interactions, enzyme inhibition, and modulation of ion channels. These processes shape how drugs affect the body, guiding effective treatment strategies and improving patient outcomes. Receptor binding and activation
[83] Understanding Drug Actions: From Receptor Interactions to Development — Understanding excretion pathways is essential for optimizing drug therapy, particularly in patients with impaired renal or hepatic function. Pharmacodynamics. Pharmacodynamics explores the mechanisms by which drugs exert their effects on the body, focusing on the biochemical and physiological responses that follow drug administration.
[84] Pharmacodynamics - StatPearls - NCBI Bookshelf — Drugs produce their effects by interacting with biological targets, but the time course of the pharmacodynamic effect is dependent on the mechanism and biochemical pathway of the target. Neuromuscular blocking agents such as succinylcholine, which consists of 2 acetylcholine molecules linked end to end by their acetyl groups, interact with the nicotinic acetylcholine receptor on skeletal muscle cells and leave the channel in an open state, resulting in membrane depolarization and generation of an action potential, muscle contraction and then paralysis within 60 seconds after administration. Delayed effects can be secondary to direct drug effects. Pharmacodynamics emphasizes dose-receptor relationships, the interactions between the drug's concentration and its effect. For example, we can examine drug-receptor interactions according to the following formula:
[85] A Comprehensive Overview of Antibiotic Selection and the Factors ... — The pharmacodynamics of a drug is based on three main principles: (1) the amount of drug that binds to receptors, (2) the ability of the drug to influence receptors, and (3) the amount of time the drug is present so that it can exert its metabolic effect . While pharmacokinetic principles are absolutely necessary in the development of the drug
[86] Improving target assessment in biomedical research: the GOT-IT ... — Target validation can be understood in numerous ways depending on the context (Box 1), but usually describes the technical evaluation of whether a target has a key role in a disease process and whether pharmacological modulation of the target could be effective in a defined patient population 5. As projects on promising targets progress towards
[89] Identifying Druggable Targets by Protein Microenvironments Matching ... — We hypothesize that: (i) known drug-binding sites contain advantageous physicochemical properties for drug binding, or “druggable microenvironments” and (ii) given a target, the presence of multiple druggable microenvironments similar to those seen previously is associated with a high likelihood of druggability. DrugFEATURE compares a query site to a set of drug-binding sites and identifies similar druggable microenvironments (same colored spheres). Given a target protein, DrugFEATURE extracts druggable features or subsites by recognizing microenvironments that are similar to those in known drug-binding sites. We collected 10 druggable and 13 undruggable sites with ligand-binding information published by Hajduk et al.16 They provide experimental assessment of these targets by NMR-based screening against a drug-like fragment library (see Supplementary Table S1).
[90] Bonding, binding and isomerism - Anaesthesia & Intensive Care Medicine — Drugs that are bound to receptors and enzymes by covalent bonds (e.g. phenoxybenzamine) usually have a long duration of action. ... Thus if a drug has a high affinity for binding, it will have a slow rate of dissociation. ... these drugs may also alter the binding characteristics of other drugs that have affinity at the same site (such as the
[92] Drug-receptor interactions in anaesthesia - PMC - PubMed Central (PMC) — A drug's affinity (strength of binding) for a given receptor is the product of its association with receptor together with the rate of dissociation of drug-receptor complex. Affinity is described by K D, the equilibrium dissociation constant, which is the concentration of drug needed to occupy 50% of the available receptors. High affinity
[98] Proteomics and genomics: perspectives on drug and target discovery — Also discussed are methods for target identification, using global proteomics to profile proteins differentially expressed between normal versus disease states, which when validated serve as candidates for drug development. The integration of chemical biology and large-scale analyses by genomics and proteomics together with methods in computational biology and structural determination provide new perspectives for addressing problems in clinical medicine, and will continue to evolve rapidly to improve drug and target discovery. He uses structural proteomics to understand the functions of important bio-systems, for example, structural studies of enzyme targets for drug discovery and state-of-the art proteomic studies of post-translational protein modifications.
[99] Ligand discovery by activity-based protein profiling - Cell Press — In this review, Niphakis and Cravatt describe how activity-based protein profiling (ABPP) technologies generate global maps of small molecule-protein interactions in native systems, expanding the druggability of the human proteome. Highlighted are chemical tools discovered by ABPP, including those remodeling protein-protein interactions and acting through cryptic allosteric pockets.
[102] Application of proteomic technologies in the drug development process ... — Common applications of proteomics in the drug industry include target identification and validation, identification of efficacy and toxicity biomarkers from readily accessible biological fluids, and investigations into mechanisms of drug action or toxicity. As proteins are the principal targets of drug discovery, the evolution of proteomics techniques is of major importance to the drug development process. High-throughput proteomics, identifying potentially hundreds to thousands of protein expression changes in model systems following perturbation by drug treatment or disease, lends itself particularly well to target identification in drug discovery. In-house, drug companies have mainly focused on protein profiling for target identification, to develop efficacy and toxicity biomarkers, and to create valuable protein databases for access in future projects.
[112] The Peptide PROTAC Modality: A New Strategy for Drug Discovery — The cell membrane, as the boundary of cells, forms a natural barrier with its special structure and biological function, which hinders therapeutic proteins, peptides, and oligonucleotides from reaching the site of action and exerting their pharmacological effects. To overcome this obstacle, delivery‐enhancing peptides have emerged.
[126] Advances in Molecular Medicine: Unravelling Disease Complexity and ... — The ability to classify diseases and stratify patients precisely, based on their molecular profiles, facilitates the implementation of tailored therapeutic approaches, thereby maximising treatment efficacy and minimising adverse effects. Molecular therapeutics describes a wide range of therapeutic approaches that utilise our understanding of molecular pathways, genetics, and biomarkers to develop targeted treatments for various diseases, including personalised medicine and targeting some infectious diseases. Beyond cancer, molecular therapeutics holds potential for managing autoimmune disorders, rare genetic diseases, and infectious diseases, heralding a new era of precision medicine with tailored treatments for individual patients. More research is required to improve our understanding and develop targeted treatments for UFs. The following three reviews discuss how new therapeutic strategies for cancer treatment, particularly targeted therapies, have improved patient survival.
[127] Clinical Pharmacology Regulatory Sciences in Drug Development and ... — In addition, emerging trends in clinical pharmacology regulatory sciences were also discussed, including the Model-Informed Drug Development (MIDD) pilot program, the use of real-world data to generate real-world evidence, and leveraging advances in basic, biomedical, and clinical science into useful tools for drug development and evaluation. *The depicted common data networks include the FDA Sentinel Initiative, PCORnet (Patient-Centered Outcomes Research Network), i2b2/ACT (Informatics for Integrating Biology and the Bedside / Accrual to Clinical Trials), OMOP (Observational Medical Outcomes Partnership from Observational Health Data Sciences and Informatics), CDISC SDTM (Study Data Tabulation Model from Clinical Data Interchange Standards Consortium), USCDI HL7 FHIR R4 (The U.S. Core Data for Interoperability Health Level Seven Fast Healthcare Interoperability Resources Revision 4), and VA EHR-S (Veterans Affairs - Electronic Health Record System)
[130] Regulatory, Translational, and Operational Considerations for the ... — This article describes case studies of recent drug approvals that successfully leveraged validated and non-validated biomarkers (i.e., tofersen for the neurodegenerative disease amyotrophic lateral sclerosis (ALS) in adults; and osimertinib for treatment of patients with metastatic epidermal growth factor receptor (EGFR) T790M mutation-positive non-small cell lung cancer (NSCLC)). Available from: https://www.ema.europa.eu/en/documents/regulatory-procedural-guideline/final-conclusions-pilot-joint-european-medicines-agency-food-and-drug-administration-vxds-experience-qualification-nephrotoxicity-biomarkers_en.pdf. Available from: https://www.ema.europa.eu/en/documents/regulatory-procedural-guideline/qualification-novel-methodologies-drug-development-guidance-applicants_en.pdf. Available from: https://www.fda.gov/drugs/biomarker-qualification-program/status-biomarker-qualification-submissions. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Available from: https://www.ema.europa.eu/en/documents/regulatory-procedural-guideline/final-conclusions-pilot-joint-european-medicines-agency-food-and-drug-administration-vxds-experience-qualification-nephrotoxicity-biomarkers_en.pdf. Available from: https://www.ema.europa.eu/en/documents/regulatory-procedural-guideline/qualification-novel-methodologies-drug-development-guidance-applicants_en.pdf. Available from: https://www.fda.gov/drugs/biomarker-qualification-program/status-biomarker-qualification-submissions.
[132] Personalized Medicine and Advancements in Pharmacology: Shaping the ... — One of the key areas in personalized medicine is genomics, which focuses on analyzing an individual’s genetic information to predict disease susceptibility, determine optimal treatment strategies, and identify potential adverse reactions.1 Pharmacogenomics, a subset of genomics, explores the relationship between an individual’s genetic variations and their response to drugs. By considering individual patient characteristics, including genetic variations, biomarkers, and clinical data, personalized medicine aims to optimize treatment efficacy, minimize adverse effects, and improve patient outcomes across diverse medical fields. Personalized medicine enables tailored treatment approaches based on individual patient characteristics, such as genetic makeup, biomarkers, and clinical data.
[133] Revolutionizing Personalized Medicine: Synergy with Multi-Omics Data ... — The history of personalized medicine is punctuated by significant milestones in genetics, technology, and clinical applications, shifting healthcare from a one-size-fits-all approach to a more individualized understanding of the molecular basis of health and disease and effective treatment strategies . Advances in genomics and biotechnology in the 21st century are enabling more personalized approaches to medicine, predicting disease risks, and tailoring treatments to individual genetic profiles. Personalized medicine leverages these images in conjunction with genetic data to gain deeper insights into disease mechanisms in individual patients, enhancing precision in diagnosis and treatment strategies . Through the integration of genetic, molecular, and clinical data, personalized medicine enables more accurate diagnosis, precise treatment targeting, and effective disease management.
[134] Advancing Research in Personalized Medicine - U.S. Pharmacist — The National Institutes of Health’s National Human Genome Research Institute (NHGRI) indicates that the majority of medical treatments are designed for the general population with a “one size fits all” approach, and while many of these therapies are effective, not all patients may respond to them.1 According to the NHGRI, personalized medicine, also referred to as precision medicine, is a promising and evolving practice of medicine that employs an individual’s genetic profile, which can guide clinicians in ascertaining the best approaches to possibly prevent, diagnose, and treat and/or manage certain diseases and medical conditions.2 Additionally, using a patient’s genetic profile can be valuable in prescribing the best medication or therapy and dosage to suit the individual needs of the patient.1-3 The Personalized Medicine Coalition (PMC) indicates that personalized medicine has the potential to enhance treatment outcomes across a spectrum of diseases via targeted therapies, therefore adding to the effectiveness of medicine.
[136] AI's role in revolutionizing personalized medicine by reshaping ... — AI's role in revolutionizing personalized medicine by reshaping pharmacogenomics and drug therapy - ScienceDirect Search ScienceDirect AI's role in revolutionizing personalized medicine by reshaping pharmacogenomics and drug therapy open access This paper examines the transformative impact of artificial intelligence (AI) on pharmacogenomics, signaling a paradigm shift in personalized medicine. The review emphasizes AI's role in guiding treatment decisions, minimizing adverse reactions, and optimizing drug dosages in clinical settings. This work underscores the synergy of AI and pharmacogenomics, offering a more effective and patient-centric approach to drug therapy, marking a significant advancement in the field of personalized medicine. Previous article in issue Next article in issue No articles found. For all open access content, the relevant licensing terms apply.
[137] AI-Driven Multi-Omics Integration for Enhanced Drug Discovery Pipelines ... — Integration of multi-omics data-genomics, transcriptomics, proteomics, and metabolomics-has become a crucial approach in the recent era for accelerating drug discovery. Artificial Intelligence synthesizes this multifarious data to provide novel insights into complex biological mechanisms underlying disease pathophysiology. In this study, AI-driven machine learning algorithms were utilized to
[138] Integrating artificial intelligence in drug discovery and early drug ... — There are several limitations, specific to drug discovery and development in cancer, that can be summarized in the following concepts: (1) High Costs and Long Timelines: 10–15 years for a drug candidate to receive regulatory approval ; (2) Low Success Rates: approximately 90% of candidates that enter early clinical trials do not reach the market ; and (3) Complex Disease Biology: cancer involves complex, interconnected biological pathways that are difficult to target effectively with classical methods. As the main reasons for failures in drug development are insufficient efficacy and safety levels, methods based on AI could help mitigate challenges in the analysis of multiomics data by improving target identification and predicting druggability, which enhances the overall drug discovery process. An example of the integration of biological data for drug identification is PaccMann, an AI-driven framework designed to predict cancer cell sensitivity to compounds by integrating molecular structures, gene expression profiles, and protein interaction data.
[141] Personalized Medicine: Recent Progress in Cancer Therapy — Personalized Medicine: Recent Progress in Cancer Therapy - PubMed Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation Search in PubMed doi: 10.3390/cancers12041009. Personalized Medicine: Recent Progress in Cancer Therapy DOI: 10.3390/cancers12041009 Personalized Medicine: Recent Progress in Cancer Therapy Search in PubMed doi: 10.3390/cancers12041009. DOI: 10.3390/cancers12041009 The change from an organ-centric concept guiding treatment choice towards deep molecular analysis, driving a personalized approach, is one of the most important advances of modern oncology. How to personalize cancer treatment from the… doi: 10.3390/cancers16162862. Berger M.F., Mardis E.R. The emerging clinical relevance of genomics in cancer medicine. - DOI - PMC - PubMed - DOI - PMC - PubMed - DOI - PubMed - DOI - PMC - PubMed - DOI - PMC - PubMed Search in PubMed
[142] Expanding the Reach of Personalized Medicine in Cancer Care: Current ... — Tumor genomics and biomarkers are increasingly becoming critical parts of routine clinical care for patients with many cancer types. With these advances also comes a unique challenge to distill these complex and wide-ranging data points into actionable clinical information, so as to expand the reach and benefits of precision medicine to a diverse patient population.
[143] Adjuvant personalized cancer vaccine: is this the end of ... - Nature — The first study of personalized cancer vaccines for renal cell carcinoma with breakthrough results in the adjuvant setting has been published, showing a 100% efficacy rate and negligible toxic
[144] Cancer biomarkers: Emerging trends and clinical implications for ... — Immunotherapy has gained prominence in the treatment of non-small cell lung cancer (NSCLC), encompassing early-stage, locally advanced, and metastatic cases.30 Despite the progression free and overall survival benefits derived from the use of checkpoint inhibition, the number of patients benefiting from durable disease control is limited.30,31 Therefore, stratification using Final efficacy results from B-F1RST, a prospective phase II trial evaluating blood-based tumour mutational burden (bTMB) as a predictive biomarker for atezolizumab (atezo) in 1L non-small cell lung cancer (NSCLC) Cemiplimab monotherapy for first-line treatment of advanced non-small-cell lung cancer with PD-L1 of at least 50%: a multicentre, open-label, global, phase 3, randomised, controlled trial
[176] Links between genetics and biology to advance drug discovery - AstraZeneca — Delving deeper: Combining genomics with proteomics to advance drug discovery In a breakthrough study conducted by our Centre for Genomic Research (CGR) research team, we analysed over 50,000 human exomes in the UK Biobank dataset to uncover the contribution of rare protein-coding genetic variants on nearly 3,000 plasma proteins. 1 Plasma
[177] Genomics and Proteomics in Drug Design and Discovery — Genomics and Proteomics in Drug Design and Discovery - ScienceDirect Chapter 20 - Genomics and Proteomics in Drug Design and Discovery This chapter presents an overview of recent progresses in genomic and proteomic research strategies that have an impact on drug discovery and their applications in identification and validation of drug targets, illustrating drug action mechanisms, prediction of drug resistance, and biomarkers discovery for determining clinical effects. Chemical proteomics makes use of synthetic organic chemistry, cell biology, biochemistry, and mass spectrometry (MS) to design specific protein-modifying reagents that can be used for functional studies of distinct proteins within a certain proteome. Computational Biology and Chemistry, Volume 78, 2019, pp. Characterization and Biology of Nanomaterials for Drug Delivery, 2019, pp.
[180] Adaptive design clinical trials: Methodology, challenges and prospect — One of the innovations strongly recommended by the FDA is the use of adaptive design methods in clinical trials and the potential use of the Bayesian approach in clinical research and development. The European Medicines Agency (EMEA) has also issued a draft paper in 2006 concerning flexible or adaptive design clinical trials in new drug development. The purpose of adaptation in clinical trials is to give the investigator the flexibility for identifying the optimal clinical benefit of the test treatment under study without undermining the validity and integrity of the intended study. Although the concept of adaptive design clinical trials is still in its infancy but, with growing knowledge, positive signals have emerged from regulatory agencies and from industry alike.
[181] Latest Developments in "Adaptive Enrichment" Clinical Trial Designs in ... — As cancer has become better understood on the molecular level with the evolution of gene sequencing techniques, considerations for individualized therapy using predictive biomarkers (those associated with a treatment's effect) have shifted to a new level. In the last decade or so, randomized "adaptive enrichment" clinical trials have become increasingly utilized to strike a balance
[186] 3D molecular generative framework for interaction-guided drug design — 3D molecular generative framework for interaction-guided drug design | Nature Communications Here, we propose an interaction-aware 3D molecular generative framework that leverages the universal nature of protein–ligand interactions to guide structure-based drug design. While a target pocket can form different combinations of protein–ligand interaction types depending on the binding ligand and its binding pose, we aim to inversely design a ligand that fulfills a specific combination of interactions using a 3D conditional generative model, named DeepICL, which can be applied to any kind of protein. & Kim, W.Y. 3D molecular generative framework for interaction-guided drug design.
[187] Editorial: Drug-drug interactions in pharmacology - PMC — Analytical methods represent an important aspect of drug-drug interaction pharmacokinetic studies. To this concern, Tang et al. developed and validated a UHPLC-MS/MS method to quantify almonertinib in rat plasma. The method was successfully applied to study the pharmacokinetic interaction between paxlovid and almonertinib in an in vivo rat model.
[196] Integration of virtual and high-throughput screening - Nature — High-throughput and virtual screening are important components of modern drug discovery research. Typically, these screening technologies are considered distinct approaches, as one is experimental
[197] Computational approaches streamlining drug discovery - Nature — Advertisement View all journals Search Log in Explore content About the journal Publish with us Subscribe Sign up for alerts RSS feed nature review articles article Review Published: 26 April 2023 Computational approaches streamlining drug discovery Anastasiia V. Sadybekov ORCID: orcid.org/0000-0003-3925-983X1,2 & Vsevolod Katritch ORCID: orcid.org/0000-0003-3883-45051,2,3 Nature volume 616, pages 673–685 (2023)Cite this article 106k Accesses 387 Citations 530 Altmetric Metrics details Subjects Cheminformatics Virtual screening Abstract Computer-aided drug discovery has been around for decades, although the past few years have seen a tectonic shift towards embracing computational technologies in both academia and pharma. This shift is largely defined by the flood of data on ligand properties and binding to therapeutic targets and their 3D structures, abundant computing capacities and the advent of on-demand virtual libraries of drug-like small molecules in their billions. Taking full advantage of these resources requires fast computational methods for effective ligand screening. Here we review recent advances in ligand discovery technologies, their potential for reshaping the whole process of drug discovery and development, as well as the challenges they encounter.
[198] Deep learning pipeline for accelerating virtual screening in drug discovery — By integrating molecular graph construction, Graph Neural Network (GNN) modeling, virtual screening, and compound clustering, VirtuDockDL provides a comprehensive framework to automate the drug discovery process. At its foundation, the GNN model, featuring multiple custom layers, employs molecular structure (descriptors and fingerprints) data to predict the drug potential of compounds. This integrative approach of combining graph-based learning with traditional cheminformatics features, is summarized as, \(Features=Graphs\left(G\right)+Descriptors\left(D\right)+Fingerprints \left(F\right)\), empowers our GNN model to achieve a comprehensive understanding of molecular structures and their properties. The application also provides functionality for protein structure refinement and ligand docking, critical steps in molecular modeling and drug discovery workflows.
[199] Applications of molecular pharmacology in drug discovery — The branch of pharmacology that focuses on the study of pharmacology at the molecular level is called "molecular pharmacology." In addition to studying the molecular causes of diseases, molecular pharmacologists also investigate the molecular causes of diseases in an effort to discover pharmacologically active substances that may be utilized to cure illnesses .
[200] Molecular Pharmacology - an overview | ScienceDirect Topics — Today’s consequents in the advancement of drug discovery molecular pharmacology play a crucial role via the prediction of drug target, drug–ligand interaction, involvement of genomics and proteomics, and the study of drug action at the cellular and molecular level and their application methods, which provides a great platform in the process of drug development and discovery of new drug molecules. Utilizing the molecular biology technique and computational approach in a combined form exposes the researchers to the introduction of systemic pharmacology, which mainly34 describes a field of research that provides us with a comprehensive view of drug action rooted in molecular interactions between drugs and their targets in a human cellular context.
[201] Home Page: Molecular Pharmacology — Molecular Pharmacology publishes findings derived from the application of innovative structural biology, biochemistry, biophysics, physiology, genetics, and molecular biology to basic pharmacological problems that provide mechanistic insights that are broadly important for the fields of pharmacology and toxicology. Relevant topics include:
[203] Advances in Biomedical Imaging Techniques: A Comprehensive Review ... — Advances in Biomedical Imaging Techniques: A Comprehensive Reviews. Mubashar Ilyas 1,2, Saniyah Amin 2,3, ... These methods give important insights into disease processes, tumor imaging and molecular interactions and have uses in both preclinical research and clinical settings. There is a lot of promise for additional development in the field
[204] Improved Prediction of Ligand-Protein Binding Affinities by Meta-modeling — The accurate screening of candidate drug ligands against target proteins through computational approaches is of prime interest to drug development efforts. Such virtual screening depends in part on methods to predict the binding affinity between ligands and proteins. Many computational models for binding affinity prediction have been developed, but with varying results across targets. Given
[206] Personalized Medicine and Advancements in Pharmacology: Shaping the ... — One of the key areas in personalized medicine is genomics, which focuses on analyzing an individual’s genetic information to predict disease susceptibility, determine optimal treatment strategies, and identify potential adverse reactions.1 Pharmacogenomics, a subset of genomics, explores the relationship between an individual’s genetic variations and their response to drugs. By considering individual patient characteristics, including genetic variations, biomarkers, and clinical data, personalized medicine aims to optimize treatment efficacy, minimize adverse effects, and improve patient outcomes across diverse medical fields. Personalized medicine enables tailored treatment approaches based on individual patient characteristics, such as genetic makeup, biomarkers, and clinical data.
[207] Personalized Medicine - Future Impact, Pharma Industry Perspective — Personalized Medicine – Future Impact, Pharma Industry Perspective - PMC A .gov website belongs to an official government organization in the United States. Search Search Search in PMC Add to search Find articles by A Ayers Despite the challenges, personalized medicine is widely believed to offer the best prospect of effective treatment and cure for patients with serious diseases. The relevant stakeholders – Pharma and biotech, diagnostic companies, regulatory agencies, payers and policy makers, must be committed to working together to provide incentives and remove obstacles so that this goal can become a reality. Articles from Journal of Biomolecular Techniques : JBT are provided here courtesy of The Association of Biomolecular Resource Facilities Collections Cited by other articles Add to Collections Name your collection * NLM
[208] AI's role in revolutionizing personalized medicine by reshaping ... — AI's role in revolutionizing personalized medicine by reshaping pharmacogenomics and drug therapy - ScienceDirect Search ScienceDirect AI's role in revolutionizing personalized medicine by reshaping pharmacogenomics and drug therapy open access This paper examines the transformative impact of artificial intelligence (AI) on pharmacogenomics, signaling a paradigm shift in personalized medicine. The review emphasizes AI's role in guiding treatment decisions, minimizing adverse reactions, and optimizing drug dosages in clinical settings. This work underscores the synergy of AI and pharmacogenomics, offering a more effective and patient-centric approach to drug therapy, marking a significant advancement in the field of personalized medicine. Previous article in issue Next article in issue No articles found. For all open access content, the relevant licensing terms apply.
[210] Next-Generation Sequencing (NGS) in Drug Discovery & Development and ... — Recent advancements in NGS have opened up many possibilities in drug discovery and personalized medicine. The roles of these new technologies in drug discovery and medicine span from speeding up the identification of new drug targets to potentially helping clinicians choose the best drug for an individual patient. Next-Generation Sequencing in
[224] Understanding the Role of Pharmacogenomics in Personalized Medicine — Early examples of pharmacogenomic applications included the identification of genetic variants that influenced the effectiveness of certain cancer treatments, such as the drug trastuzumab (Herceptin), used in HER2-positive breast cancer. Pharmacogenomic testing can help identify which medications are more likely to be effective based on a patient’s genetic profile. Pharmacogenomic testing can help identify genetic variations that affect drug metabolism, guiding the selection of drugs and dosages that are safer and more effective for each patient. By identifying genetic variations that influence how patients metabolize and respond to medications, pharmacogenomics offers the potential for more tailored, effective, and safer treatments. By using pharmacogenomic data, drug developers can design medications that are tailored to specific genetic profiles, increasing the likelihood that a drug will be effective across a broader range of patients.
[225] What Is Pharmacogenomics (Pharmacogenetics)? - Cleveland Clinic — Pharmacogenomics can help your healthcare provider prescribe a medication that leads to fewer side effects or that may work better for you. Currently, providers only use pharmacogenomics for a limited number of health conditions and medications. Examples include some medications for HIV, certain cancers, depression and heart disease.
[228] Advances in Molecular Medicine: Unravelling Disease Complexity and ... — The ability to classify diseases and stratify patients precisely, based on their molecular profiles, facilitates the implementation of tailored therapeutic approaches, thereby maximising treatment efficacy and minimising adverse effects. Molecular therapeutics describes a wide range of therapeutic approaches that utilise our understanding of molecular pathways, genetics, and biomarkers to develop targeted treatments for various diseases, including personalised medicine and targeting some infectious diseases. Beyond cancer, molecular therapeutics holds potential for managing autoimmune disorders, rare genetic diseases, and infectious diseases, heralding a new era of precision medicine with tailored treatments for individual patients. More research is required to improve our understanding and develop targeted treatments for UFs. The following three reviews discuss how new therapeutic strategies for cancer treatment, particularly targeted therapies, have improved patient survival.
[229] Molecules in Medicine: Personalised Therapies | Open Medscience — Molecules in Medicine: Personalised Therapies | Open Medscience The article concludes by reflecting on the future directions of molecular medicine, focusing on personalised medicine, advances in drug delivery, and the ethical challenges in this evolving field. The molecular approach to medicine encompasses understanding the molecular mechanisms of diseases, developing targeted therapies, and creating diagnostics that can detect disease at an early stage. Gene therapies and nucleic acid-based drugs target the genetic level of diseases. Cancer treatment has greatly benefited from molecular medicine, with targeted therapies providing more personalised and effective treatment options. Small molecules, peptides, proteins, and nucleic acids are at the forefront of this revolution, and emerging technologies like nanomedicine, gene editing, and RNA therapies hold immense potential.
[234] Progress in Pharmaceutical Sciences and Future Challenges — From a prospective point of view, key challenges in pharmacological sciences for the treatment of cardiovascular diseases, cancer, and central nervous system (CNS) disorders would be the following: (i) Cardiovascular diseases (CVDs) Challenges: (a) Precision Medicine and Genomics: The future of cardiovascular treatment lies in personalized
[235] Overcoming Challenges in Small-Molecule Drug Bioavailability: A ... - MDPI — By providing rapid estimates of intestinal permeability, these models enable researchers to optimize molecular structures for enhanced oral bioavailability early in the drug design process. This growing understanding is leading to novel approaches for enhancing bioavailability, such as the development of probiotic formulations that can modulate the gut microbiome to favor drug absorption or the design of drugs that leverage microbial metabolism for activation or enhanced solubility. For pharmaceutical scientists and drug developers, this review emphasizes the importance of the early consideration of bioavailability optimization through integrated approaches combining computational prediction, advanced formulation, and biological understanding. "Overcoming Challenges in Small-Molecule Drug Bioavailability: A Review of Key Factors and Approaches" International Journal of Molecular Sciences 25, no.
[236] 2 Drug Development Challenges - National Center for Biotechnology ... — Lawrence Goldstein, director of the UCSD Stem Cell Program and distinguished professor in the department of neurosciences at the UCSD School of Medicine, highlighted several challenges related to existing animal models of AD, including the inability to develop all the symptoms of AD; overexpression of proteins linked to disease (e.g., APP) at levels high enough to produce abnormal phenotypes; transgenic mouse models that fail to fully recapitulate AD pathology (Duff and Suleman, 2004); lack of sporadic AD models, which account for 95 percent of cases (Young and Goldstein, 2012); and inability of drugs found efficacious in animal models to translate to clinical trials.
[237] Advances in cancer therapy: unveil the immunomodulatory protein ... — AI further enhances cancer research by analyzing multiomics data, aiding in the identification of novel anticancer targets and drugs. https://doi.org/10.3390/cancers12020437 You Y, Lai X, Pan Y, Zheng H, Vera J, Liu S, Deng S, Zhang L (2022) Artificial intelligence in cancer target identification and drug discovery. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. https://doi.org/10.3390/cancers12020437 You Y, Lai X, Pan Y, Zheng H, Vera J, Liu S, Deng S, Zhang L (2022) Artificial intelligence in cancer target identification and drug discovery.
[239] Challenges and perspectives in use of artificial intelligence to ... — Major challenges in the use of AI in oncology and decision‐making tools are data security, data representation, and explainability of AI‐based outcome predictions, in particular for decision‐making processes in multidisciplinary cancer conferences. Major challenges in the use of AI in clinical oncology and decision‐making tools are data security, data representation, and explainability of AI‐based outcome predictions, in particular for decision‐making processes in multidisciplinary cancer conferences. Moreover, AI applications can be used to predict the survival of cancer patients, representing key information for any treatment decisions in oncology in order to adapt the treatment regime to achieve the highest possible survival outcome as well as quality of life.
[241] Challenges and opportunities for artificial intelligence in oncological ... — Promising studies suggest that AI technology in imaging may lead to significant advances in cancer care; however, significant work is required to increase the quantity and quality of data available for research, validating promising results across institutions and in real clinical settings, and translating the work into clinical practice.
[245] Organ-on-a-Chip: A New Paradigm for Drug Development — The pharmaceutical industry has been desperately searching for efficient drug discovery methods. Organ-on-a-Chip, a cutting-edge technology that can emulate the physiological environment and functionality of human organs on a chip for disease modeling and drug testing, shows great potential for revolutionizing the drug development pipeline.