ABSTRACT
Boron neutron capture therapy (BNCT) is expected to be a promising next-generation cancer treatment. In 2020, Japan, which has led the research on this treatment modality, was the first country in the world to approve BNCT. The boron agents that have been clinically applied in BNCT include a caged boron compound (mercaptoundecahydrododecaborate: BSH) and a boron-containing amino acid (p-boronophenylalanine: BPA). In particular, the BPA preparation Steboronine® is the only approved drug for BNCT. However, the problem with BPA is that it is poorly retained in the tumor and has very low solubility in water. This cannot be overlooked for BNCT, which requires large amounts of boron in the tumor. The high dosage volume, together with low tumor retention, leads to reduced therapeutic efficacy and increased physical burden on the patient. In the case of BSH, its insufficient penetration into the tumor is problematic. Based on drug delivery system (DDS) technology, we have developed a next-generation boron pharmaceutical superior to Steboronine®. Our approach involves the redevelopment of BPA using innovative ionic liquid formulation technology. Here, we describe previous boron agents and introduce our recent efforts in the development of boron compounds.
Subject(s)
Borohydrides , Boron Compounds , Boron Neutron Capture Therapy , Drug Delivery Systems , Neoplasms , Phenylalanine , Boron Neutron Capture Therapy/methods , Humans , Neoplasms/radiotherapy , Neoplasms/therapy , Neoplasms/drug therapy , Boron Compounds/administration & dosage , Phenylalanine/analogs & derivatives , Sulfhydryl Compounds , Drug DevelopmentABSTRACT
The endocannabinoid system (ECS) is a critical regulatory network composed of endogenous cannabinoids (eCBs), their synthesizing and degrading enzymes, and associated receptors. It is integral to maintaining homeostasis and orchestrating key functions within the central nervous and immune systems. Given its therapeutic significance, we have launched a series of drug discovery endeavors aimed at ECS targets, including peroxisome proliferator-activated receptors (PPARs), cannabinoid receptors types 1 (CB1R) and 2 (CB2R), and monoacylglycerol lipase (MAGL), addressing a wide array of medical needs. The pursuit of new therapeutic agents has been enhanced by the creation of specialized labeled chemical probes, which aid in target localization, mechanistic studies, assay development, and the establishment of biomarkers for target engagement. By fusing medicinal chemistry with chemical biology in a comprehensive, translational end-to-end drug discovery strategy, we have expedited the development of novel therapeutics. Additionally, this strategy promises to foster highly productive partnerships between industry and academia, as will be illustrated through various examples.
Subject(s)
Chemistry, Pharmaceutical , Drug Discovery , Endocannabinoids , Endocannabinoids/metabolism , Endocannabinoids/chemistry , Humans , Drug Industry , Monoacylglycerol Lipases/metabolism , Monoacylglycerol Lipases/antagonists & inhibitors , Drug Development , AcademiaABSTRACT
With the COVID-19 pandemic, the importance of vaccines has been widely recognized and has led to increased research and development efforts. Vaccines also play a crucial role in cancer treatment by activating the immune system to target and destroy cancer cells. However, enhancing the efficacy of cancer vaccines remains a challenge. Adjuvants, which enhance the immune response to antigens and improve vaccine effectiveness, have faced limitations in recent years, resulting in few novel adjuvants being identified. The advancement of artificial intelligence (AI) technology in drug development has provided a foundation for adjuvant screening and application, leading to a diversification of adjuvants. This article reviews the significant role of tumor vaccines in basic research and clinical treatment and explores the use of AI technology to screen novel adjuvants from databases. The findings of this review offer valuable insights for the development of new adjuvants for next-generation vaccines.
Subject(s)
Adjuvants, Immunologic , Artificial Intelligence , COVID-19 , Cancer Vaccines , Neoplasms , Humans , Cancer Vaccines/immunology , Cancer Vaccines/therapeutic use , Neoplasms/immunology , Neoplasms/therapy , COVID-19/prevention & control , COVID-19/immunology , SARS-CoV-2/immunology , Animals , Vaccine Development , Drug DevelopmentABSTRACT
Natural products (NPs) have long been used as a rich source of bioactive compounds for drug development. Recent technological advancements have revitalised natural products research as evidenced by increased publications in this field. In this editorial review, we highlight key points from the 2020 British Journal of Pharmacology (BJP) practical guide, which outlines standards for natural products research reports, and provide papers published in BJP between years 2020 to 2023 that demonstrate adherence to these guidelines. Looking ahead, we discuss the potential of chemical proteomics approaches to elucidate natural products mechanisms of action and identify therapeutic targets for future research. By fostering innovation, we aim to advance natural products research and contribute to the development of novel therapeutics that will have a significant impact on healthcare.
Subject(s)
Biological Products , Biological Products/pharmacology , Biological Products/chemistry , Humans , Animals , Periodicals as Topic , Pharmacology , Proteomics , Drug DevelopmentABSTRACT
Androgen receptor (AR) and its ligand androgens are important for development and physiology of various tissues. AR and its ligands also play critical role in the development of various diseases, making it a valuable therapeutic target. AR ligands, both agonists and antagonists, are being widely used to treat pathological conditions, including prostate cancer and hypogonadism. Despite AR being studied widely over the last five decades, the last decade has seen striking advances in the knowledge on AR and discoveries that have the potential to translate to the clinic. This review provides an overview of the advances in AR biology, AR molecular mechanisms of action, and next generation molecules that are currently in development. Several of the areas described in the review are just unraveling and the next decade will bring more clarity on these developments that will put AR at the forefront of both basic biology and drug development.
Subject(s)
Receptors, Androgen , Humans , Receptors, Androgen/metabolism , Receptors, Androgen/chemistry , Animals , Androgen Receptor Antagonists/chemistry , Androgen Receptor Antagonists/pharmacology , Androgen Receptor Antagonists/therapeutic use , Ligands , Drug DevelopmentABSTRACT
Neglected tropical diseases (NTDs) pose a major threat in tropical zones for impoverished populations. Difficulty of access, adverse effects or low efficacy limit the use of current therapeutic options. Therefore, development of new drugs against NTDs is a necessity. Compounds containing an aminopyridine (AP) moiety are of great interest for the design of new anti-NTD drugs due to their intrinsic properties compared with their closest chemical structures. Currently, over 40 compounds with an AP moiety are on the market, but none is used against NTDs despite active research on APs. The aim of this review is to present the medicinal chemistry work carried out with these scaffolds, against protozoan NTDs: Trypanosoma cruzi, Trypanosoma brucei or Leishmania spp.
[Box: see text].
Subject(s)
Aminopyridines , Antiprotozoal Agents , Neglected Diseases , Trypanosoma brucei brucei , Trypanosoma cruzi , Neglected Diseases/drug therapy , Humans , Antiprotozoal Agents/pharmacology , Antiprotozoal Agents/chemistry , Antiprotozoal Agents/chemical synthesis , Trypanosoma cruzi/drug effects , Aminopyridines/chemistry , Aminopyridines/pharmacology , Trypanosoma brucei brucei/drug effects , Leishmania/drug effects , Drug Development , Parasitic Sensitivity Tests , AnimalsABSTRACT
Antibody-drug conjugates (ADCs) are fusions of therapeutic drugs and antibodies conjugated by a linker, designed to deliver a therapeutic payload to cells expressing the target antigen. By delivering the highly cytotoxic agent directly to cancer cells, ADCs are designed to enhance safety and broaden the therapeutic window. Recently, ADCs have demonstrated promising efficacy in various solid tumors and are rapidly expanding their indications. The prognosis of patients with advanced head and neck squamous cell carcinoma (HNSCC) remains poor, with no new therapeutics since the advent of anti-PD-1 antibodies in 2016, highlighting a critical need for innovative therapies. Recent preliminary results suggest that ADCs could be promising treatment options for HNSCC as they explore a variety of target antigens, payloads, and linkers. However, for successful adaptation of ADCs in the treatment of HNSCC, addressing key challenges such as payload toxicities, antigen heterogeneity, and adaptive resistance will be essential. Current research focused on new ADC structures, including multispecific antibodies and noncytotoxic payloads, and diverse combination approaches, show promise for future advancements.
Subject(s)
Head and Neck Neoplasms , Immunoconjugates , Humans , Immunoconjugates/therapeutic use , Head and Neck Neoplasms/drug therapy , Head and Neck Neoplasms/immunology , Squamous Cell Carcinoma of Head and Neck/drug therapy , Squamous Cell Carcinoma of Head and Neck/immunology , Drug DevelopmentABSTRACT
Developing new therapeutic strategies to target specific molecular pathways has become a primary focus in modern drug discovery science. Fibroblast growth factor receptor 2 (FGFR2) is a critical signaling protein involved in various cellular processes and implicated in numerous diseases, including cancer. Existing FGFR2 inhibitors face limitations like drug resistance and specificity issues. In this study, we present an integrated structure-based bioinformatics analysis to explore the potential of FGFR2 inhibitors-like compounds from the PubChem database with the Tanimoto threshold of 80%. We conducted a structure-based virtual screening approach on a dataset comprising 2336 compounds sourced from the PubChem database. Primarily, the selection of promising compounds was based on several criteria, such as drug-likeness, binding affinities, docking scores, and selectivity. Further, we conducted all-atom molecular dynamics (MD) simulations for 200 ns, followed by an essential dynamics analysis. Finally, a promising FGFR2 inhibitor with PubChem CID:507883 (1-[7-(1H-benzimidazol-2-yl)-4-fluoro-1H-indol-3-yl]-2-(4-benzoylpiperazin-1-yl)ethane-1,2-dione) was screened out from the study. This compound indicates a higher potential for inhibiting FGFR2 than the control inhibitor, Zoligratinib. The identified compound, CID:507883 shows >80% structural similarity with Zoligratinib. ADMET analysis showed promising pharmacokinetic potential of the screened compound. Overall, the findings indicate that the compound CID:507883 may have promising potential to serve as a lead candidate against FGFR2 and could be further exploited in therapeutic development.
Subject(s)
Molecular Docking Simulation , Molecular Dynamics Simulation , Receptor, Fibroblast Growth Factor, Type 2 , Receptor, Fibroblast Growth Factor, Type 2/antagonists & inhibitors , Receptor, Fibroblast Growth Factor, Type 2/chemistry , Receptor, Fibroblast Growth Factor, Type 2/metabolism , Humans , Protein Kinase Inhibitors/chemistry , Protein Kinase Inhibitors/pharmacology , Protein Binding , Drug Development , Structure-Activity RelationshipABSTRACT
Currently, artificial intelligence (AI), machine learning (ML), and deep learning (DL) are gaining increased interest in many fields, particularly in pharmaceutical research and development, where they assist in decision-making in complex situations. Numerous research studies and advancements have demonstrated how these computational technologies are used in various pharmaceutical research and development aspects, including drug discovery, personalized medicine, drug formulation, optimization, predictions, drug interactions, pharmacokinetics/ pharmacodynamics, quality control/quality assurance, and manufacturing processes. Using advanced modeling techniques, these computational technologies can enhance efficiency and accuracy, handle complex data, and facilitate novel discoveries within minutes. Furthermore, these technologies offer several advantages over conventional statistics. They allow for pattern recognition from complex datasets, and the models, typically developed from data-driven algorithms, can predict a given outcome (model output) from a set of features (model inputs). Additionally, this review discusses emerging trends and provides perspectives on the application of AI with quality by design (QbD) and the future role of AI in this field. Ethical and regulatory considerations associated with integrating AI into pharmaceutical technology were also examined. This review aims to offer insights to researchers, professionals, and others on the current state of AI applications in pharmaceutical research and development and their potential role in the future of research and the era of pharmaceutical Industry 4.0 and 5.0.
Subject(s)
Artificial Intelligence , Drug Development , Pharmaceutical Research , Pharmaceutical Research/methods , Drug Development/methods , Humans , Technology, Pharmaceutical/methods , Drug Discovery/methods , Machine Learning , Quality Control , Precision Medicine/methodsABSTRACT
Stress testing (also known as forced degradation) of pharmaceutical drug substances and products is a critical part of the drug development process, providing insight into the degradation pathways of drug substances and drug products. This information is used to support the development of stability-indicating methods (SIMs) capable of detecting pharmaceutically relevant degradation products that might potentially be observed during manufacturing, long-term storage, distribution, and use. Assessing mass balance of stressed samples is a key aspect of developing SIMs and is a regulatory expectation. However, the approaches to measure, calculate, and interpret mass balance can vary among different pharmaceutical companies. Such disparities also pose difficulties for health authorities when reviewing mass balance assessments, which may result in the potential delay of drug application approvals. The authors have gathered input from 10 pharma companies to map out a practical review of science-based approaches and technical details to assess and interpret mass balance results. Key concepts of mass balance are introduced, various mass balance calculations are demonstrated, and recommendations on how to investigate poor mass balance results are presented using real-world case studies. Herein we provide a single source reference on the topic of mass balance in pharmaceutical forced degradation for small molecule drug substances and drug products in support of regulatory submissions with the goal of facilitating a shared understanding among pharmaceutical scientists and health authorities.
Subject(s)
Drug Stability , Pharmaceutical Preparations/chemistry , Pharmaceutical Preparations/metabolism , Drug Industry/methods , Humans , Drug Development/methodsABSTRACT
The COVID-19 pandemic has highlighted the importance of efficient drug discovery in respiratory disease. The traditional set up of clinical trials is expensive and allows for significant attrition of new drugs, many of which undergo extensive safety testing before being abandoned for lack of efficacy. Phase 0 trials, named as they sit between pre-clinical research and phase I, allow for the testing of sub-clinical microdoses in humans to gather early pharmacokinetic (PK), pharmacodynamic (PD) and mechanistic data, before deciding on which drugs to advance further. This early data can improve the efficiency and cost effectiveness of drug development and reduce the extent of animal testing. Phase 0 trials traditionally have utilised sub-therapeutic microdoses of compounds administered intravenously with readouts focusing on PK - measured using highly sensitive methods such as accelerator mass spectrometry (AMS) and liquid chromatography tandem mass spectrometry (LC-MS/MS) of peripheral blood, as well as whole-body positron emission tomography (PET). Mathematical models allow for extrapolation of this PK data to support the further testing of larger, systemically effective doses. However, this extrapolation method is limited at providing robust PD or target engagement/ mode of action data. Using an Intra-Target Microdosing (ITM) approach, a small compartment of the body (about 1% or less) is exposed to potentially clinically active local concentrations. This allows for the collection of PD data, evidence of target cell engagement, as well as the opportunity to extrapolate systemic PK and PD data. This approach has the potential within the pulmonary system for the study and rapid and cost-effective development of new and repurposed drugs.
Subject(s)
Lung , Humans , Lung/diagnostic imaging , COVID-19 Drug Treatment , SARS-CoV-2 , Drug Development/methods , COVID-19 , Clinical Trials as TopicABSTRACT
Coronavirus disease 2019 (COVID-19) was declared a global pandemic in March 2020, which precipitated urgent public health responses. The causative agent, SARS-CoV-2, spreads primarily via respiratory droplets, necessitating precautions to mitigate transmission risks. Biopharmaceutical industries and academic institutions worldwide swiftly redirected their research endeavors towards developing therapeutic interventions, focusing on monoclonal antibodies, antiviral agents, and immunomodulatory therapies. The evolving body of evidence surrounding these treatments has prompted successive updates and revisions from the FDA, delineating the evolving landscape of COVID-19 therapeutics. This review comprehensively examines each treatment modality within the context of their developmental trajectories and regulatory approvals throughout the pandemic. Furthermore, it elucidates their mechanisms of action and presents clinical data underpinning their utility in combating the COVID-19 crisis.
Subject(s)
Antiviral Agents , COVID-19 Drug Treatment , COVID-19 , Drug Development , SARS-CoV-2 , Humans , Antiviral Agents/pharmacology , Antiviral Agents/therapeutic use , SARS-CoV-2/drug effects , Drug Development/methods , Antibodies, Monoclonal/therapeutic use , Antibodies, Monoclonal/pharmacology , Immunomodulating Agents/pharmacology , Immunomodulating Agents/therapeutic use , Animals , PandemicsABSTRACT
Drug development has historically relied on phase I-III clinical trials including participants sharing the same disease. However, drug development has evolved as the discovery of mechanistic drivers of disease demonstrated that the same therapeutic target may provide benefits across different diseases. A basket trial condenses evaluation of one therapy among multiple related diseases into a single trial and presents an opportunity to borrow information across them rather than viewing each in isolation. Borrowing is a statistical tool but requires a foundation of clinical and therapeutic mechanistic justification. We review the Bayesian borrowing approach, including its assumptions, and provide a framework for how this approach can be evaluated for successful use in a basket trial for drug development.
Subject(s)
Bayes Theorem , Clinical Trials as Topic , Drug Development , Humans , Clinical Trials as Topic/methods , Drug Development/methods , Research DesignABSTRACT
Increasing the levels of antiapoptotic Bcl-2 proteins is an important way that cancer cells utilize to get out of apoptosis, underscoring their significance as promising targets for anticancer therapies. Lately, a primary compound 1 bearing thiazolidine-2,4-dione was discovered to exhibit comparable Mcl-1 inhibitory activity in comparison to WL-276. Herein, thirty-nine thiazolidine-2,4-dione analogs were yielded through incorporating different biphenyl moieties (R1), amino acid side chains (R2) and sulfonamides (R3) on 1. The findings indicated that certain compounds exhibited favorable inhibitory effects against Bcl-2/Mcl-1, while demonstrating limited or negligible binding affinity towards Bcl-xL. In particular, compounds 16 and 20 exhibited greater Bcl-2/Mcl-1 inhibition compared to AT-101, WL-276 and 1. Moreover, they demonstrated notable antiproliferative effects and significantly induced apoptosis in U937 cells. The western blot and co-immunoprecipitation assays confirmed that 20 could induce alterations in the expression of apoptosis-associated proteins to result in apoptosis through on-target Bcl-2 and Mcl-1 inhibition. In addition, 20 exhibited favorable stability profiles in both rat plasma and rat liver microsomes. In total, 20 could be used as a promising compound to discover Bcl-2/Mcl-1 dual inhibitors with favorable therapeutic properties.
Subject(s)
Antineoplastic Agents , Apoptosis , Cell Proliferation , Dose-Response Relationship, Drug , Drug Discovery , Drug Screening Assays, Antitumor , Myeloid Cell Leukemia Sequence 1 Protein , Proto-Oncogene Proteins c-bcl-2 , Thiazolidinediones , Humans , Myeloid Cell Leukemia Sequence 1 Protein/antagonists & inhibitors , Myeloid Cell Leukemia Sequence 1 Protein/metabolism , Proto-Oncogene Proteins c-bcl-2/metabolism , Proto-Oncogene Proteins c-bcl-2/antagonists & inhibitors , Antineoplastic Agents/pharmacology , Antineoplastic Agents/chemistry , Antineoplastic Agents/chemical synthesis , Structure-Activity Relationship , Cell Proliferation/drug effects , Molecular Structure , Apoptosis/drug effects , Thiazolidinediones/pharmacology , Thiazolidinediones/chemistry , Thiazolidinediones/chemical synthesis , Animals , Rats , Drug DevelopmentABSTRACT
OBJECTIVE: Currently, 90% of clinical drug development fails, where 30% of these failures are due to clinical toxicity. The current extensive animal toxicity studies are not predictive of clinical adverse events (AEs) at clinical doses, while current computation models only consider very few factors with limited success in clinical toxicity prediction. We aimed to address these issues by developing a machine learning (ML) model to directly predict clinical AEs. METHODS: Using a dataset with 759 FDA-approved drugs with known AEs, we first adapted the ConPLex ML model to predict IC 50 values of these FDA-approved drugs against their on-target and off-target binding among 477 protein targets. Subsequently, we constructed a new ML model to predict clinical AEs using IC 50 values of 759 drugs' primary on-target and off-target effects along with tissue-specific protein expression profiles. RESULTS: The adapted ConPLex model predicted drug-target interactions for both on- and off-target effects, as shown by co-localization of the 6 small molecule kinase inhibitors with their respective kinases. The coupled ML models demonstrated good predictive capability of clinical AEs, with accuracy over 75%. CONCLUSIONS: Our approach provides a new insight into the mechanistic understanding of in vivo drug toxicity in relationship with drug on-/off-target interactions. The coupled ML models, once validated with larger datasets, may offer advantages to directly predict clinical AEs using in vitro/ex vivo and preclinical data, which will help to reduce drug development failure due to clinical toxicity.
Subject(s)
Drug-Related Side Effects and Adverse Reactions , Machine Learning , Humans , Protein Kinase Inhibitors/adverse effects , Drug Development/methods , AnimalsABSTRACT
This paper reviews the accelerated development of pharmaceuticals, exploring past, present, and future perspectives. It provides a historical overview of early strategies used to expedite development, beginning with initiatives from the 1990s. The work of Gardner and Byrn in accelerated development analysis during this era is highlighted. The narrative progresses to the 2000s, discussing the emergence of PK/PD in accelerating pharmaceutical development. The paper further examines case studies in the accelerated development field, including the INDIGO and Chorus programs. It concludes with an analysis of the current state of the field, referencing the NIPTE conference, which focused on the industrial perspective of accelerated development. Additionally, the paper outlines strategies for the rapid development of Solid Lipid Nanoparticle manufacturing and vaccine production.
Subject(s)
Drug Development , Nanoparticles , Humans , Drug Development/methods , Drug Development/trends , Nanoparticles/chemistry , Pharmaceutical Preparations/chemistry , History, 20th Century , History, 21st Century , Vaccines , Animals , Drug Industry/methodsABSTRACT
Aberrant or dysfunctional cellular enzymes are responsible for a wide range of diseases including cancer, neurodegenerative conditions, and metabolic disorders. Deficiencies in enzyme level or biofunction may lead to intracellular accumulation of substrate to toxic levels and interfere with overall cellular function, ultimately leading to cell damage, disease, and death. Marketed therapeutic interventions for inherited monogenic enzyme deficiency disorders include enzyme replacement therapy and small molecule chaperones. Novel approaches of in vivo gene therapy and ex vivo cell therapy are under clinical evaluation and provide promising opportunities to expand the number of available disease-modifying treatments. To support the development of these different therapeutics, assays to quantify the functional activity of protein enzymes have gained importance in the diagnosis of disease, assessment of pharmacokinetics and pharmacodynamic response, and evaluation of drug efficacy. In this review, we discuss the technical aspects of enzyme activity assays in the bioanalytical context, including assay design and format as well as the unique challenges and considerations associated with assay development, validation, and life cycle management.
Subject(s)
Biomarkers , Drug Development , Metabolism, Inborn Errors , Humans , Biomarkers/metabolism , Metabolism, Inborn Errors/drug therapy , Metabolism, Inborn Errors/diagnosis , Metabolism, Inborn Errors/genetics , Drug Development/methods , Enzyme Assays/methods , Animals , Enzyme Replacement Therapy/methodsABSTRACT
INTRODUCTION: Asthma is a common disease with a global burden of 358 million patients. Despite improvements in pharmacological and non-pharmacological treatments, many patients still do not achieve complete asthma control. Therefore, innovative pharmacotherapy is important. AREAS COVERED: Following a semi-structured search in Pubmed, an overview of advances in inhaled asthma therapy is provided, looking at innovations in digital inhalers, eco-friendly inhalers and novel inhaled biologic therapies, antibiotics and vaccines, as well as other potential novel asthma therapy targets. EXPERT OPINION: Digital inhalers, sending reminders and monitoring inhalation technique electronically, can support medication adherence and improve asthma control. To reduce the global warming potential of traditional aerosols used in pressurized metered-dose inhalers (HFA-134a, HFA-227ea), greener alternatives are under development (HFA-152a, HFO-1234ze) that are expected to be available by 2025. Current pharmacological advances in asthma therapy are mainly achieved by novel biologicals (anti-IgE, anti-IL5, anti-IL4/13, and anti-TSLP) targeting specific severe asthma phenotypes. While injection is the usual administration route for biologics and vaccines used in asthma, inhalation is an option being explored, although several (mainly formulation) challenges need to be overcome. Other potential novel future inhaled asthma therapies include anti-IL-33/ST2 biologicals and JAK inhibitors, all still requiring more clinical evidence.