Application of Deep Learning for Studying NMDA Receptors.

Artificial intelligence underwent remarkable advancement in the past decade, revolutionizing our way of thinking and unlocking unprecedented opportunities across various fields, including drug development. The emergence of large pretrained models, such as ChatGPT, has even begun to demonstrate human-level performance in certain tasks.However, the difficulties of deploying and utilizing AI and pretrained model for nonexpert limited its practical use. To overcome this challenge, here we presented three highly accessible online tools based on a large pretrained model for chemistry, the Uni-Mol, for drug development against CNS diseases, including those targeting NMDA receptor: the blood-brain barrier (BBB) permeability prediction, the quantitative structure-activity relationship (QSAR) analysis system, and a versatile interface of the AI-based molecule generation model named VD-gen. We believe that these resources will effectively bridge the gap between cutting-edge AI technology and NMDAR experts, facilitating rapid and rational drug development.

Accelerating Process Development and Product Formulation.

Currently, the lengthy time needed to bring new drugs to market or to implement postapproval changes causes multiple problems, such as delaying patients access to new lifesaving or life-enhancing medications and slowing the response to emergencies that require new treatments. However, new technologies are available that can help solve these problems. The January 2023 NIPTE pathfinding workshop on accelerating drug product development and approval included a session in which participants considered the current state of product formulation and process development, barriers to acceleration of the development timeline, and opportunities for overcoming these barriers using new technologies. The authors participated in this workshop, and in this article have shared their perspective of some of the ways forward, including advanced manufacturing techniques and adaptive development. In addition, there is a need for paradigm shifts in regulatory processes, increased pre-competitive collaboration, and a shared strategy among regulators, industry, and academia.

Another string to your bow: machine learning prediction of the pharmacokinetic properties of small molecules.

INTRODUCTION: Prediction of pharmacokinetic (PK) properties is crucial for drug discovery and development. Machine-learning (ML) models, which use statistical pattern recognition to learn correlations between input features (such as chemical structures) and target variables (such as PK parameters), are being increasingly used for this purpose. To embed ML models for PK prediction into workflows and to guide future development, a solid understanding of their applicability, advantages, limitations, and synergies with other approaches is necessary. AREAS COVERED: This narrative review discusses the design and application of ML models to predict PK parameters of small molecules, especially in light of established approaches including in vitro-in vivo extrapolation (IVIVE) and physiologically based pharmacokinetic (PBPK) models. The authors illustrate scenarios in which the three approaches are used and emphasize how they enhance and complement each other. In particular, they highlight achievements, the state of the art and potentials of applying machine learning for PK prediction through a comphrehensive literature review. EXPERT OPINION: ML models, when carefully crafted, regularly updated, and appropriately used, empower users to prioritize molecules with favorable PK properties. Informed practitioners can leverage these models to improve the efficiency of drug discovery and development process.

Innovative peptide architectures: advancements in foldamers and stapled peptides for drug discovery.

INTRODUCTION: Peptide foldamers play a critical role in pharmaceutical research and biomedical applications. This review highlights recent (post-2020) advancements in novel foldamers, synthetic techniques, and their applications in pharmaceutical research. AREAS COVERED: The authors summarize the structures and applications of peptide foldamers such as α, ß, γ-peptides, hydrocarbon-stapled peptides, urea-type foldamers, sulfonic-γ-amino acid foldamers, aromatic foldamers, and peptoids, which tackle the challenges of traditional peptide drugs. Regarding antimicrobial use, foldamers have shown progress in their potential against drug-resistant bacteria. In drug development, peptide foldamers have been used as drug delivery systems (DDS) and protein-protein interaction (PPI) inhibitors. EXPERT OPINION: These structures exhibit resistance to enzymatic degradation, are promising for therapeutic delivery, and disrupt crucial PPIs associated with diseases such as cancer with specificity, versatility, and stability, which are useful therapeutic properties. However, the complexity and cost of their synthesis, along with the necessity for thorough safety and efficacy assessments, necessitate extensive research and cross-sector collaboration. Advances in synthesis methods, computational modeling, and targeted delivery systems are essential for fully realizing the therapeutic potential of foldamers and integrating them into mainstream medical treatments.

Premix technologies for drug delivery: manufacturing, applications, and opportunities in regulatory filing.

Active pharmaceutical ingredients (APIs) and excipients can be carefully combined in premix-based materials before being added to dosage forms, providing a flexible platform for the improvement of drug bioavailability, stability, and patient compliance. This is a promising and transformative approach in novel and generic product development, offering both the potential to overcome challenges in the delivery of complex APIs and viable solutions for bypassing patent hurdles in generic product filing. We discuss the different types of premixes; manufacturing technologies such as spray drying, hot melt extrusion, wet granulation, co-crystal, co-milling, co-precipitation; regulatory filing opportunities; and major bottlenecks in the use of premix materials in different aspects of pharmaceutical product development.

Thyroid receptor ß: A promising target for developing novel anti-androgenetic alopecia drugs.

Androgenetic alopecia (AGA) significantly impacts the self-confidence and mental well-being of people. Recent research has revealed that thyroid receptor ß (TRß) agonists can activate hair follicles and effectively stimulate hair growth. This review aims to comprehensively elucidate the specific mechanism of action of TRß in treating AGA from various perspectives, highlighting its potential as a drug target for combating AGA. Moreover, this review provides a thorough summary of the research advances in TRß agonist candidates with anti-AGA efficacy and outlines the structure-activity relationships (SARs) of TRß agonists. We hope that this review will provide practical information for the development of effective anti-alopecia drugs.

Hypoxia-induced pulmonary hypertension in adults and newborns: implications for drug development.

Chronic hypoxia-induced pulmonary hypertension (CHPH) presents a complex challenge, characterized by escalating pulmonary vascular resistance and remodeling, threatening both newborns and adults with right heart failure. Despite advances in understanding the pathobiology of CHPH, its molecular intricacies remain elusive, particularly because of the multifaceted nature of arterial remodeling involving the adventitia, media, and intima. Cellular imbalance arises from hypoxia-induced mitochondrial disturbances and oxidative stress, reflecting the diversity in pulmonary hypertension (PH) pathology. In this review, we highlight prominent mechanisms causing CHPH in adults and newborns, and emerging therapeutic targets of potential pharmaceuticals.

Exploiting Cell-Based Assays to Accelerate Drug Development for G Protein-Coupled Receptors.

G protein-coupled receptors (GPCRs) are relevant targets for health and disease as they regulate various aspects of metabolism, proliferation, differentiation, and immune pathways. They are implicated in several disease areas, including cancer, diabetes, cardiovascular diseases, and mental disorders. It is worth noting that about a third of all marketed drugs target GPCRs, making them prime pharmacological targets for drug discovery. Numerous functional assays have been developed to assess GPCR activity and GPCR signaling in living cells. Here, we review the current literature of genetically encoded cell-based assays to measure GPCR activation and downstream signaling at different hierarchical levels of signaling, from the receptor to transcription, via transducers, effectors, and second messengers. Singleplex assay formats provide one data point per experimental condition. Typical examples are bioluminescence resonance energy transfer (BRET) assays and protease cleavage assays (e.g., Tango or split TEV). By contrast, multiplex assay formats allow for the parallel measurement of multiple receptors and pathways and typically use molecular barcodes as transcriptional reporters in barcoded assays. This enables the efficient identification of desired on-target and on-pathway effects as well as detrimental off-target and off-pathway effects. Multiplex assays are anticipated to accelerate drug discovery for GPCRs as they provide a comprehensive and broad identification of compound effects.

From molecules to visuals: Empowering drug discovery and development with mass spectrometry imaging.

Over the past three decades, mass spectrometry imaging (MSI) has emerged as a valuable tool for the spatial localization of drugs and metabolites directly from tissue surfaces without the need for labels. MSI offers molecular specificity, making it increasingly popular in the pharmaceutical industry compared to conventional imaging techniques like quantitative whole-body autoradiography (QWBA) and immunohistochemistry, which are unable to distinguish parent drugs from metabolites. Across the industry, there has been a consistent uptake in the utilization of MSI to investigate drug and metabolite distribution patterns, and the integration of MSI with omics technologies in preclinical investigations. To continue the further adoption of MSI in drug discovery and development, we believe there are two key areas that need to be addressed. First, there is a need for accurate quantification of analytes from MSI distribution studies. Second, there is a need for increased interactions with regulatory agencies for guidance on the utility and incorporation of MSI techniques in regulatory filings. Ongoing efforts are being made to address these areas, and it is hoped that MSI will gain broader utilization within the industry, thereby becoming a critical ingredient in driving drug discovery and development.

Advances in sarcopenia: mechanisms, therapeutic targets, and intervention strategies.

Sarcopenia is a multifactorial condition characterized by loss of muscle mass. It poses significant health risks in older adults worldwide. Both pharmacological and non-pharmacological approaches are reported to address this disease. Certain dietary patterns, such as adequate energy intake and essential amino acids, have shown positive outcomes in preserving muscle function. Various medications, including myostatin inhibitors, growth hormones, and activin type II receptor inhibitors, have been evaluated for their effectiveness in managing sarcopenia. However, it is important to consider the variable efficacy and potential side effects associated with these treatments. There are currently no drugs approved by the Food and Drug Administration for sarcopenia. The ongoing research aims to develop more effective strategies in the future. Our review of research on disease mechanisms and drug development will be a valuable contribution to future research endeavors.

Development and therapeutic implications of small molecular inhibitors that target calcium-related channels in tumor treatment.

Calcium ion dysregulation exerts profound effects on various physiological activities such as tumor proliferation, migration, and drug resistance. Calcium-related channels play a regulatory role in maintaining calcium ion homeostasis, with most channels being highly expressed in tumor cells. Additionally, these channels serve as potential drug targets for the development of antitumor medications. In this review, we first discuss the current research status of these pathways, examining how they modulate various tumor functions such as epithelial-mesenchymal transition (EMT), metabolism, and drug resistance. Simultaneously, we summarize the recent progress in the study of novel small-molecule drugs over the past 5 years and their current status.

Recent advances in the development of DprE1 inhibitors using AI/CADD approaches.

Tuberculosis (TB) is a global lethal disease caused by Mycobacterium tuberculosis (Mtb). The flavoenzyme decaprenylphosphoryl-ß-d-ribose 2'-oxidase (DprE1) plays a crucial part in the biosynthesis of lipoarabinomannan and arabinogalactan for the cell wall of Mtb and represents a promising target for anti-TB drug development. Therefore, there is an urgent need to discover DprE1 inhibitors with novel scaffolds, improved bioactivity and high drug-likeness. Recent studies have shown that artificial intelligence/computer-aided drug design (AI/CADD) techniques are powerful tools in the discovery of novel DprE1 inhibitors. This review provides an overview of the discovery of DprE1 inhibitors and their underlying mechanism of action and highlights recent advances in the discovery and optimization of DprE1 inhibitors using AI/CADD approaches.

Antibiotic Development: Lessons from the Past and Future Opportunities.

The challenge of antimicrobial resistance is broadly appreciated by the clinical and scientific communities. To assess progress in the development of medical countermeasures to combat bacterial infections, we deployed information gleaned from clinical trials conducted from 2000 to 2021. Whereas private sector interest in cancer grew dramatically over this period, activity to combat bacterial infections remained stagnant. The comparative ambivalence to antimicrobial resistance is reflected in the number of investigative drugs under clinical investigation, their stage of development and most troublingly, a declining number of organizations that are actively involved in the development of new products to treat bacterial infections. This drop reflects the exits of many companies that had previously developed antibacterial agents.

DTKGIN: Predicting drug-target interactions based on knowledge graph and intent graph.

Knowledge graph intent graph attention mechanism Predicting drug-target interactions (DTIs) plays a crucial role in drug discovery and drug development. Considering the high cost and risk of biological experiments, developing computational approaches to explore the interactions between drugs and targets can effectively reduce the time and cost of drug development. Recently, many methods have made significant progress in predicting DTIs. However, existing approaches still suffer from the high sparsity of DTI datasets and the cold start problem. In this paper, we develop a new model to predict drug-target interactions via a knowledge graph and intent graph named DTKGIN. Our method can effectively capture biological environment information for targets and drugs by mining their associated relations in the knowledge graph and considering drug-target interactions at a fine-grained level in the intent graph. DTKGIN learns the representation of drugs and targets from the knowledge graph and the intent graph. Then the probabilities of interactions between drugs and targets are obtained through the inner product of the representation of drugs and targets. Experimental results show that our proposed method outperforms other state-of-the-art methods in 10-fold cross-validation, especially in cold-start experimental settings. Furthermore, the case studies demonstrate the effectiveness of DTKGIN in predicting potential drug-target interactions. The code is available on GitHub: https://github.com/Royluoyi123/DTKGIN.

Essential considerations towards development of effective nasal antibiotic formulation: features, strategies, and future directions.

INTRODUCTION: Intranasal antibiotic products are gaining popularity as a promising method of administering antibiotics, which provide numerous benefits, e.g. enhancing drug bioavailability, reducing adverse effects, and potentially minimizing resistance threats. However, some issues related to the antibiotic substances and nasal route challenges must be addressed to prepare effective formulations. AREAS COVERED: This review focuses on the valuable points of nasal delivery as an alternative route for administering antibiotics, coupled with the challenges in the nasal cavity that might affect the formulations. Moreover, this review also highlights the application of nasal delivery to introduce antibiotics for local therapy, brain targeting, and systemic effects that have been conducted. In addition, this viewpoint provides strategies to maintain antibiotic stability and several crucial aspects to be considered for enabling effective nasal formulation. EXPERT OPINION: In-depth knowledge and understanding regarding various key considerations with respect to the antibiotic substances and nasal route delivery requirement in preparing effective nasal antibiotic formulation would greatly improve the development of nasally administered antibiotic products, enabling better therapeutic outcomes of antibiotic treatment and establishing appropriate use of antibiotics, which in turn might reduce the chance of antibiotic resistance and enhance patient comfort.

Patient-Derived Xenografts: A Valuable Preclinical Model for Drug Development and Biomarker Discovery.

Patient-derived xenografts (PDXs), established by implanting patient tumor cells into immunodeficient mice, offer a platform for faithfully replicating human tumors. They closely mimic the histopathology, genomics, and drug sensitivity of patient tumors. This chapter highlights the versatile applications of PDXs, including studying tumor biology, metastasis, and chemoresistance, as well as their use in biomarker identification, drug screening, and personalized medicine. It also addresses challenges in using PDXs in cancer research, including variations in metastatic potential, lengthy establishment timelines, stromal changes, and limitations in immunocompromised models. Despite these challenges, PDXs remain invaluable tools guiding patient treatment and advancing preclinical drug development.

Patient-Derived Xenograft Models for Translational Prostate Cancer Research and Drug Development.

Patient-derived xenografts (PDXs) are a valuable preclinical research platform generated through transplantation of a patient's resected tumor into an immunodeficient or humanized mouse. PDXs serve as a high-fidelity avatar for both precision medicine and therapeutic testing against the cancer patient's disease state. While PDXs show mixed response to initial establishment, those that successfully engraft and can be sustained with serial passaging form a useful tool for basic and translational prostate cancer (PCa) research. While genetically engineered mouse (GEM) models and human cancer cell lines, and their xenografts, each play beneficial roles in discovery science and initial drug screening, PDX tumors are emerging as the gold standard approach for therapeutic proof-of-concept prior to entering clinical trial. PDXs are a powerful platform, with PCa PDXs shown to represent the original patient tumor cell population and architecture, histopathology, genomic and transcriptomic landscape, and heterogeneity. Furthermore, PDX response to anticancer drugs in mice has been closely correlated to the original patient's susceptibility to these treatments in the clinic. Several PDXs have been established and have undergone critical in-depth characterization at the cellular and molecular level across multiple PCa tumor subtypes representing both primary and metastatic patient tumors and their inherent levels of androgen responsiveness and/or treatment resistance, including androgen-sensitive, castration resistant, and neuroendocrine PCa. Multiple PDX networks and repositories have been generated for the collaborative and shared use of these vital translational cancer tools. Here we describe the creation of a PDX maintenance colony from an established well-characterized PDX, best practice for PDX maintenance in mice, and their subsequent application in preclinical drug testing. This chapter aims to serve as a go to resource for the preparation and adoption of PCa PDX models in the research laboratory and for their use as a valuable preclinical platform for translational research and therapeutic agent development.

The landscape of small-molecule prodrugs.

Prodrugs are derivatives with superior properties compared with the parent active pharmaceutical ingredient (API), which undergo biotransformation after administration to generate the API in situ. Although sharing this general characteristic, prodrugs encompass a wide range of different chemical structures, therapeutic indications and properties. Here we provide the first holistic analysis of the current landscape of approved prodrugs using cheminformatics and data science approaches to reveal trends in prodrug development. We highlight rationales that underlie prodrug design, their indications, mechanisms of API release, the chemistry of promoieties added to APIs to form prodrugs and the market impact of prodrugs. On the basis of this analysis, we discuss strengths and limitations of current prodrug approaches and suggest areas for future development.