Clinical Drug Development Research Articles

Experimental research progress in traditional Chinese medicine prevention and treatment of diabetic peripheral neuropathy based on autophagy

Diabetic peripheral neuropathy(DPN) is a chronic complication resulted from peripheral nerve injury in the late stage of diabetes. It involves a variety of pathological changes such as oxidative stress, endoplasmic reticulum stress, neuroinflammation, and apoptosis of Schwann cells(SCs). DPN is the main factor leading to lower limb disability or amputation in diabetic patients, with high incidence, long disease course, and poor prognosis. The modern medicine treatment of DPN mainly focuses on controlling blood glucose and improving microcirculation and nerve nutrition, which can only mitigate the clinical symptoms and not fundamentally reverse the pathological changes of peripheral nerves. Autophagy is a self-clearing mechanism that maintains cellular homeostasis by removing excess metabolites. Traditional Chinese medicine(TCM), featuring the holistic concept and syndrome differentiation, can treat chronic diseases in a multi-target, multi-pathway, and wide-range manner. Modern studies have shown that the occurrence and development of DPN are related to a variety of pathological changes, and autophagy is a key mechanism associated with DPN. The environment with persistent high glucose can lead to the inhibition or over-activation of peripheral nerve cells, which causes irreversible damage of nerve cells and the occurrence and development of DPN. Therefore, restoring autophagy balance and reducing nerve damage is one of the key ways to treat DPN. The recent studies have confirmed that some active ingredients in traditional Chinese medicines and TCM compound prescriptions can inhibit the oxidative stress, endoplasmic reticulum stress, mitochondrial damage, inflammation, and apoptosis of SCs in DPN by regulating the autophagy pathway, thus playing a role in the prevention and treatment of DPN. However, the systematic induction in this field remains to be carried out. This paper reviewed the relevant literature, explained the mechanism of TCM in the prevention and treatment of DPN by regulating autophagy, and summarized the potential targets of TCM in the treatment of DPN, with a view to providing new ideas for clinical research and drug development.

Cross-Community Collaboration and Data Collection to Optimize Patient Care in Hemolytic Anemias

Background: Patient engagement is becoming increasingly important for all facets of healthcare, from drug development and approval, to ensuring equitable access and the delivery of care. It is imperative to bring the voice of those impacted by the actual disease into these processes: this is particularly true for rare diseases, such as hereditary hemolytic anemias (HHAs), where the disease burden is often high and coupled with a poor quality of life and complex treatment requirements. The Red Cell Revolution™ (RCR) advisory council arose organically as part of an Agios Pharmaceuticals-sponsored discovery process, during which a range of stakeholders including healthcare providers (HCPs), advocates, patients, and company leaders offered perspectives on how to optimize engagement with the disease communities. Insights uncovered as part of this process demonstrated that there are unifying health concerns and needs among those impacted by pyruvate kinase (PK) deficiency, sickle cell disease (SCD), and thalassemia, and that there is an opportunity to explore new patient-advocacy research, supported by the creation of a unique multi-stakeholder council. Objective: To apply a multi-stakeholder, rigorous patient-advocacy data collection approach to understand the unmet needs of patients, caregivers, and HCPs for three HHAs: PK deficiency, SCD, and thalassemia. Methods: The RCR (supported by Agios Pharmaceuticals) was established across three allied disease areas, with representation from patients (N=5), caregivers (N=1), advocates (N=3), clinicians (N=8), and Agios representatives (N=5) impacted by HHA. The patient advocacy research method commenced with a survey shared with all RCR members, which curated both qualitative and quantitative insights from the group. These insights subsequently underwent cluster analysis to determine the shared concerns experienced by those impacted by HHA. The data were also subjected to linguistic analysis whereby terminology used to describe the experiences of participants was ranked according to frequency of use to reveal the most prominent concerns. The results of these analyses were distilled into an agreed group vision by the RCR, and a specific research strategy was aligned on for the RCR to pursue. Results: RCR members provided detailed answers about unmet needs across three categories: 1) impact of disease; 2) local and regional community needs; and 3) international community needs. When applied, the analysis uncovered 12 common concerns expressed by all participants across the three disease areas. These are outlined in Table 1. These insights were distilled into four key topic areas: 1) emotional and physical fatigue, 2) timely care, 3) transition from pediatric to adult care, and 4) access disparities, which were then ranked according to four parameters, namely whether it was: 1) common across all three disease areas, 2) global in scope, 3) high potential for lasting impact, and 4) revolutionary (involving or causing a complete or dramatic change). This produced alignment on one key priority: emotional and physical fatigue. Conclusion: The commonality analysis deployed here demonstrates the ability of a multi-stakeholder council to determine priority areas for research to address unmet needs. The RCR will conduct an in-depth evidence audit of the existing research in this field to identify key knowledge gaps, enabling the design of a study that will answer outstanding research questions. This study will generate patient experience data with the potential to inform both the clinical setting and drug development. As a next step, the RCR is developing a patient advocacy research study to collect the necessary evidence to better understand fatigue and its impact on psychosocial quality of life measures, such as feelings of guilt.

A Nano-Electroporation-DNA Tensioner Platform Enhances Intracellular Delivery and Mechanical Analysis Toward Rapid Drug Assessment.

In vitro, drug assessment holds tremendous potential to success in novel drug development and precision medicine. Traditional techniques for drug assessment, however, face remarkable challenges to achieve high speed, as limited by incubation-based drug delivery (>several hours) and cell viability measurements (>1d), which significantly compromise the efficacy in clinical trials. In this work, a nano-electroporation-DNA tensioner platform is reported that shortens the time of drug delivery to less than 3s, and that of cellular mechanical force analysis to 30min. The platform adopts a nanochannel structure to localize a safe electric field for cell perforation, while enhancing delivery speed by 103 times for intracellular delivery, as compared to molecular diffusion in coculture methods. The platform is further equipped with a DNA tensioner to detect cellular mechanical force for quantifying cell viability after drug treatment. Systematic head-to-head comparison, by analyzing FDA (food and drug administration)-approved drugs (paclitaxel, doxorubicin), demonstrated the platform with high speed, efficiency, and safety, showing a simple yet powerful tool for clinical drug screening and development.

Characteristics of clinical trials of new oncology drugs approved in China.

Since reforms were introduced to incentivize drug innovation in 2015, the Chinese pharmaceutical market has experienced unprecedented prosperity, with more new drugs than ever before, especially anticancer treatments. In 2021, Chinese regulatory agencies issued the new guideline for clinical research and development of antitumor drugs, triggering a series of responses on the drug market. Limited research has outlined the nature of the original new drugs in China to understand the dynamic response of the market. The objective of this article was to map the clinical development of approved new oncology drugs in China from 2015 to 2021 and differed from previous studies by focusing on original new drugs, using the United States as a benchmark, and elaborating the endogenous features of clinical trials. Clinical trials conducted in China have risen to a level similar to that of the United States in many aspects of trial design, but there is still distance between the implementation and operational details of clinical trials. In the meantime, China has made significant breakthroughs in drug approval. Greater than 60% of novel anticancer drugs in China received accelerated approved for their first listing. Approximately 90% of the pivotal clinical trials supporting initial drug approval used surrogate measures as end points, and one half were nonrandomized or did not have a control group. However, duplicate development without evidence of a clinical advantage compared with current therapies was widely observed. By presenting a multidimensional landscape of clinical trials and approvals in the real world, this review allows interested researchers, developers, and even regulators to understand what has been done and what should be done next in anticancer drug development in China.

Use of patient-reported outcomes (PRO) data to complement exposure–response analysis in early clinical cancer drug development

BackgroundThis proof-of-concept retrospective case study investigated whether patient-reported outcomes (PRO) instruments, designed to capture symptomatic adverse event data, could identity a known exposure–response (ER) relationship for safety characterized in an original FDA analysis of an approved anti-cancer agent. PRO instruments have been designed to uniquely quantify the tolerability aspects of exposure-associated symptomatic adverse events. We explored whether standard ER analyses of clinician-reported safety data for symptomatic adverse events could be complemented by ER analysis using PRO data that capture and quantify the tolerability aspects of these same symptomatic adverse events.MethodsExposure-associated adverse event data for diarrhea were analyzed in parallel in 120 patients enrolled in a clinical trial using physician reported Common Terminology Criteria for Adverse Events (CTCAE) and patient-reported symptomatic adverse event data captured by the National Cancer Institute’s (NCI) PRO Common Terminology Criteria for Adverse Events (PRO-CTCAE) instrument. Comparative ER analyses of diarrhea were conducted using the same dataset. Results from the CTCAE and PRO-CTCAE ER analyses were assessed for consistency with the ER relationship for diarrhea established in the original NDA using a 750-patient dataset. The analysis was limited to the 120-patient subset with parallel CTCAE and PRO-CTCAE assessments.ResultsWithin the same 120-patient dataset, ER analysis using dense, longitudinal PRO-CTCAE-derived data was sensitive to identify the known ER relationship for diarrhea, whereas the standard CTCAE based ER analysis was not.ConclusionsER analysis using PRO assessed symptomatic adverse event data may be a sensitive tool to complement traditional ER analysis. Improved identification of relationships for safety, by including quantification of the tolerability aspect of symptomatic adverse events using PRO instruments, may be useful to improve the sensitivity of exposure response analysis to support early clinical trial dosage optimization strategies, where decision making occurs within limited small patient datasets.

Molecular signature to predict quality of life and survival with glioblastoma using Multiview omics model.

Glioblastoma multiforme (GBM) patients show a variety of signs and symptoms that affect their quality of life (QOL) and self-dependence. Since most existing studies have examined prognostic factors based only on clinical factors, there is a need to consider the value of integrating multi-omics data including gene expression and proteomics with clinical data in identifying significant biomarkers for GBM prognosis. Our research aimed to isolate significant features that differentiate between short-term (≤ 6 months) and long-term (≥ 2 years) GBM survival, and between high Karnofsky performance scores (KPS ≥ 80) and low (KPS ≤ 60), using the iterative random forest (iRF) algorithm. Using the Cancer Genomic Atlas (TCGA) database, we identified 35 molecular features composed of 19 genes and 16 proteins. Our findings propose molecular signatures for predicting GBM prognosis and will improve clinical decisions, GBM management, and drug development.

Artificial Intelligence: From Buzzword to Useful Tool in Clinical Pharmacology.

The advent of artificial intelligence (AI) in clinical pharmacology and drug development is akin to the dawning of a new era. Previously dismissed as merely technological hype, these approaches have emerged as promising tools in different domains, including health care, demonstrating their potential to empower clinical pharmacology decision making, revolutionize the drug development landscape, and advance patient care. Although challenges remain, the remarkable progress already made signals that the leap from hype to reality is well underway, and AI promises to offer clinical pharmacology new tools and possibilities for optimizing patient care is gradually coming to fruition. This review dives into the burgeoning world of AI and machine learning (ML), showcasing different applications of AI in clinical pharmacology and the impact of successful AI/ML implementation on drug development and/or regulatory decisions. This review also highlights recommendations for areas of opportunity in clinical pharmacology, including data analysis (e.g., handling large data sets, screening to identify important covariates, and optimizing patient population) and efficiencies (e.g., automation, translation, literature curation, and training). Realizing the benefits of AI in drug development and understanding its value will lead to the successful integration of AI tools in our clinical pharmacology and pharmacometrics armamentarium.

Inhibition of T-cell activity in alopecia areata: recent developments and new directions.

Alopecia areata (AA) is an autoimmune disease that has a complex underlying immunopathogenesis characterized by nonscarring hair loss ranging from small bald patches to complete loss of scalp, face, and/or body hair. Although the etiopathogenesis of AA has not yet been fully characterized, immune privilege collapse at the hair follicle (HF) followed by T-cell receptor recognition of exposed HF autoantigens by autoreactive cytotoxic CD8+ T cells is now understood to play a central role. Few treatment options are available, with the Janus kinase (JAK) 1/2 inhibitor baricitinib (2022) and the selective JAK3/tyrosine kinase expressed in hepatocellular carcinoma (TEC) inhibitor ritlecitinib (2023) being the only US Food and Drug Administration-approved systemic medications thus far for severe AA. Several other treatments are used off-label with limited efficacy and/or suboptimal safety and tolerability. With an increased understanding of the T-cell-mediated autoimmune and inflammatory pathogenesis of AA, additional therapeutic pathways beyond JAK inhibition are currently under investigation for the development of AA therapies. This narrative review presents a detailed overview about the role of T cells and T-cell-signaling pathways in the pathogenesis of AA, with a focus on those pathways targeted by drugs in clinical development for the treatment of AA. A detailed summary of new drugs targeting these pathways with expert commentary on future directions for AA drug development and the importance of targeting multiple T-cell-signaling pathways is also provided in this review.

Immune inhibitory receptor-mediated immune response, metabolic adaptation, and clinical characterization in patients with COVID-19

Immune inhibitory receptors (IRs) play a critical role in the regulation of immune responses to various respiratory viral infections. However, in coronavirus disease 2019 (COVID-19), the roles of these IRs in immune modulation, metabolic reprogramming, and clinical characterization remain to be determined. Through consensus clustering analysis of IR transcription in the peripheral blood of patients with COVID-19, we identified two distinct IR patterns in patients with COVID-19, which were named IR_cluster1 and IR_cluster2. Compared to IR_cluster1 patients, IR_cluster2 patients with lower expressions of immune inhibitory receptors presented with a suppressed immune response, lower nutrient metabolism, and worse clinical manifestations or prognosis. Considering the critical influence of the integrated regulation of multiple IRs on disease severity, we established a scoring system named IRscore, which was based on principal component analysis, to evaluate the combined effect of multiple IRs on the disease status of individual patients with COVID-19. Similar to IR_cluster2 patients, patients with high IRscores had longer hospital-free days at day 45, required ICU admission and mechanical ventilatory support, and presented higher Charlson comorbidity index and SOFA scores. A high IRscore was also linked to acute infection phase and absence of drug intervention. Our investigation comprehensively elucidates the potential role of IR patterns in regulating the immune response, modulating metabolic processes, and shaping clinical manifestations of COVID-19. All of this evidence suggests the essential role of prognostic stratification and biomarker screening based on IR patterns in the clinical management and drug development of future emerging infectious diseases such as COVID-19.

Evolution of Ritlecitinib Population Pharmacokinetic Models During Clinical Drug Development.

Ritlecitinib is an oral Janus kinase 3/tyrosine kinase expressed in hepatocellular carcinoma family inhibitor undergoing parallel clinical development for alopecia areata, vitiligo, ulcerative colitis, Crohn's disease, and rheumatoid arthritis. As studies read out simultaneously, strategic planning of population pharmacokinetic model development and evaluation is required to ensure timely decisions. Data from healthy participants and patients from 12 clinical trials between December 2014 and July 2021 were included: seven phase I studies in healthy participants and organ impairment, five phase II/III studies in patients with rheumatoid arthritis, ulcerative colitis, alopecia areata, and vitiligo. Population pharmacokinetic models consisted of stepwise procedures to accommodate data availability and the model's application to answering clinical development questions. At each iteration of the model update, parameters of the next model were re-estimated by leveraging previous information and new data. Three model development lifecycle iterations of the ritlecitinib population pharmacokinetic model were conducted to support alopecia areata, vitiligo, and ulcerative colitis study readouts. Initial structural modeling based on healthy participant data (and some rheumatoid arthritis and alopecia areata data) in iteration 1 provided a platform for comprehensive covariate testing during iteration 2, and model evaluation and implementation of the frequentist prior approach in iteration 3. The final model was a two-compartment model with first-order absorption and direct-response non-stationary clearance and bioavailability driven by concentrations in the peripheral compartment. The present approach demonstrated the evolution of three population pharmacokinetic models with accumulating data, addressed clinical drug development questions related to systemic exposures of ritlecitinib, and informed the approved product label. NCT02309827, NCT02684760, NCT02958865, NCT02969044, NCT03232905, NCT03732807, NCT04016077, NCT03715829, NCT04037865, NCT04004663, NCT04634565, NCT02974868.

Currently Used Methods to Evaluate the Efficacy of Therapeutic Drugs and Kidney Safety.

Kidney diseases with kidney failure or damage, such as chronic kidney disease (CKD) and acute kidney injury (AKI), are common clinical problems worldwide and have rapidly increased in prevalence, affecting millions of people in recent decades. A series of novel diagnostic or predictive biomarkers have been discovered over the past decade, enhancing the investigation of renal dysfunction in preclinical studies and clinical risk assessment for humans. Since multiple causes lead to renal failure, animal studies have been extensively used to identify specific disease biomarkers for understanding the potential targets and nephropathy events in therapeutic insights into disease progression. Mice are the most commonly used model to investigate the mechanism of human nephropathy, and the current alternative methods, including in vitro and in silico models, can offer quicker, cheaper, and more effective methods to avoid or reduce the unethical procedures of animal usage. This review provides modern approaches, including animal and nonanimal assays, that can be applied to study chronic nonclinical safety. These specific situations could be utilized in nonclinical or clinical drug development to provide information on kidney disease.

Mass spectrometry quantifies target engagement for a KRASG12C inhibitor in FFPE tumor tissue

BackgroundQuantification of drug-target binding is critical for confirming that drugs reach their intended protein targets, understanding the mechanism of action, and interpreting dose-response relationships. For covalent inhibitors, target engagement can be inferred by free target levels before and after treatment. Targeted mass spectrometry assays offer precise protein quantification in complex biological samples and have been routinely applied in pre-clinical studies to quantify target engagement in frozen tumor tissues for oncology drug development. However, frozen tissues are often not available from clinical trials so it is critical that assays are applicable to formalin-fixed, paraffin-embedded (FFPE) tissues in order to extend mass spectrometry-based target engagement studies into clinical settings.MethodsWild-type RAS and RASG12C was quantified in FFPE tissues by a highly optimized targeted mass spectrometry assay that couples high-field asymmetric waveform ion mobility spectrometry (FAIMS) and parallel reaction monitoring (PRM) with internal standards. In a subset of samples, technical reproducibility was evaluated by analyzing consecutive tissue sections from the same tumor block and biological variation was accessed among adjacent tumor regions in the same tissue section.ResultsWild-type RAS protein was measured in 32 clinical non-small cell lung cancer tumors (622–2525 amol/µg) as measured by FAIMS-PRM mass spectrometry. Tumors with a known KRASG12C mutation (n = 17) expressed a wide range of RASG12C mutant protein (127–2012 amol/µg). The variation in wild-type RAS and RASG12C measurements ranged 0–18% CV across consecutive tissue sections and 5–20% CV among adjacent tissue regions. Quantitative target engagement was then demonstrated in FFPE tissues from 2 xenograft models (MIA PaCa-2 and NCI-H2122) treated with a RASG12C inhibitor (AZD4625).ConclusionsThis work illustrates the potential to expand mass spectrometry-based proteomics in preclinical and clinical oncology drug development through analysis of FFPE tumor biopsies.

The romantic history of signaling pathway discovery in cell death: an updated review.

Cell death is a fundamental physiological process in all living organisms. Processes such as embryonic development, organ formation, tissue growth, organismal immunity, and drug response are accompanied by cell death. In recent years with the development of electron microscopy as well as biological techniques, especially the discovery of novel death modes such as ferroptosis, cuprotosis, alkaliptosis, oxeiptosis, and disulfidptosis, researchers have been promoted to have a deeper understanding of cell death modes. In this systematic review, we examined the current understanding of modes of cell death, including the recently discovered novel death modes. Our analysis highlights the common and unique pathways of these death modes, as well as their impact on surrounding cells and the organism as a whole. Our aim was to provide a comprehensive overview of the current state of research on cell death, with a focus on identifying gaps in our knowledge and opportunities for future investigation. We also presented a new insight for macroscopic intracellular survival patterns, namely that intracellular molecular homeostasis is central to the balance of different cell death modes, and this viewpoint can be well justified by the signaling crosstalk of different death modes. These concepts can facilitate the future research about cell death in clinical diagnosis, drug development, and therapeutic modalities.

Cellular Assays for Dynamic Quantification of Deubiquitinase Activity and Inhibition

Deubiquitinases (DUBs) are proteolytic enzymes that catalyze the removal of ubiquitin from protein substrates. The critical role of DUBs in regulating protein ubiquitination makes them attractive drug targets in oncology, neurodegenerative disease, and antiviral development. Biochemical assays for quantifying DUB activity have enabled characterization of substrate preferences and discovery of small molecule inhibitors. However, assessing the efficacy of these inhibitors in cellular contexts to support clinical drug development has been limited by a lack of tractable cell-based assays. To address this gap, we developed a two-color flow cytometry-based assay that allows for sensitive quantification of DUB activity and inhibition in living cells. The utility of this system was demonstrated by quantifying the potency of GRL0617 against the viral DUB SARS-CoV-2 PLpro, identifying potential GRL0617 resistance mutations, and performing structure–function analysis of the vOTU domain from the recently emerged Yezo virus. In addition, the system was optimized for cellular DUBs by modifying a GFP-targeting nanobody to recruit USP7 and USP28 to benchmark a panel of reported inhibitors and assess inhibition kinetics. Together, these results demonstrate the utility of these assays for studying DUB biology in a cellular context with potential to aid in inhibitor discovery and development.

Artificial intelligence for dementia prevention.

A wide range of modifiable risk factors for dementia have been identified. Considerable debate remains about these risk factors, possible interactions between them or with genetic risk, and causality, and how they can help in clinical trial recruitment and drug development. Artificial intelligence (AI) and machine learning (ML) may refine understanding. ML approaches are being developed in dementia prevention.We discuss exemplar uses and evaluate the current applications and limitations in the dementia prevention field. Risk-profiling tools may help identify high-risk populations for clinical trials; however, their performance needs improvement. New risk-profiling and trial-recruitment tools underpinned by ML models may be effective in reducing costs and improving future trials. ML can inform drug-repurposing efforts and prioritization of disease-modifying therapeutics. ML is not yet widely used but has considerable potential to enhance precision in dementia prevention. Artificial intelligence (AI) is not widely used in the dementia prevention field. Risk-profiling tools are not used in clinical practice. Causal insights are needed to understand risk factors over the lifespan. AI will help personalize risk-management tools for dementia prevention. AI could target specific patient groups that will benefit most for clinical trials.

Rho-Kinase Inhibitors as Emerging Targets for Glaucoma Therapy.

Glaucoma, the leading cause of irreversible blindness worldwide, is a chronic and progressive optic neuropathy characterized by damage to the optic and retinal nerve fiber layers, which can lead to permanent loss of peripheral or central vision. Reduction of intraocular pressure (IOP) is the only known modifiable risk factor for preventing and treating glaucoma. Rho kinase (ROCK) inhibitors are a new class of glaucoma drugs with a novel mechanism of action and good safety profile. They exert neuroprotective effects, act on the trabecular tissue, increase the outflow of aqueous humor, and reduce intraocular pressure. However, they also cause local adverse reactions, including common conjunctival congestion and subconjunctival bleeding; however, most are self-limiting and temporary. Netarsudil (0.02%), a ROCK inhibitor, relaxes the trabecular meshwork, increases the outflow of aqueous humor, reduces scleral venous pressure, anddirectly decreases IOP. Conjunctival congestion can be reduced if netarsudil is administered at night. The combination of these medications is always more effective than the single drug. Ripasudil (0.4%), another ROCK inhibitor, also lowers IOP; however, conjunctival hyperemia is the most common adverse drug reaction. The purpose of this review is to summarize the effects and adverse reactions of ROCK inhibitors in the experimental trial stage and in clinical treatment in recent years, providing suggestions for future clinical drug use, and research and development to reduce the side effects of these drugs, maximize the potential for reducing IOP, and improve the therapeutic effect.

Targeting PRSS23 with tipranavir induces gastric cancer stem cell apoptosis and inhibits growth of gastric cancer via the MKK3/p38 MAPK-IL24 pathway.

Gastric cancer stem cells (GCSCs) contribute to the refractory features of gastric cancer (GC) and are responsible for metastasis, relapse, and drug resistance. The key factors drive GCSC function and affect the clinical outcome of GC patients remain poorly understood. PRSS23 is a novel serine protease that is significantly up-regulated in several types of cancers and cancer stem cells, and related to tumor progression and drug resistance. In this study, we investigated the role of PRSS23 in GCSCs as well as the mechanism by which PRSS23 regulated the GCSC functions. We demonstrated that PRSS23 was critical for sustaining GCSC survival. By screening a collection of human immunodeficiency virus (HIV) protease inhibitors (PIs), we identified tipranavir as a PRSS23-targeting drug, which effectively killed both GCSC and GC cell lines (its IC50 values were 4.7 and 6.4 μM in GCSC1 cells and GCSC2 cells, respectively). Administration of tipranavir (25 mg·kg-1·d-1, i.p., for 8 days) in GCSC-derived xenograft mice markedly inhibited the growth of subcutaneous GCSC tumors without apparent toxicity. In contrast, combined treatment with 5-FU plus cisplatin did not affect the tumor growth but causing significant weight loss. Furthermore, we revealed that tipranavir induced GCSC cell apoptosis by suppressing PRSS23 expression, releasing MKK3 from the PRSS23/MKK3 complex to activate p38 MAPK, and thereby activating the IL24-mediated Bax/Bak mitochondrial apoptotic pathway. In addition, tipranavir was found to kill other types of cancer cell lines and drug-resistant cell lines. Collectively, this study demonstrates that by targeting both GCSCs and GC cells, tipranavir is a promising anti-cancer drug, and the clinical development of tipranavir or other drugs specifically targeting the PRSS23/MKK3/p38MAPK-IL24 mitochondrial apoptotic pathway may offer an effective approach to combat gastric and other cancers.

A Mitochondrial Nanoguard Modulates Redox Homeostasis and Bioenergy Metabolism in Diabetic Peripheral Neuropathy.

As a major late complication of diabetes, diabetic peripheral neuropathy (DPN) is the primary reason for amputation. Nevertheless, there are no wonder drugs available. Regulating dysfunctional mitochondria is a key therapeutic target for DPN. Resveratrol (RSV) is widely proven to guard mitochondria, yet the unsatisfactory bioavailability restricts its clinical application. Tetrahedral framework nucleic acids (tFNAs) are promising carriers due to their excellent cell entrance efficiency, biological safety, and structure editability. Here, RSV was intercalated into tFNAs to form the tFNAs-RSV complexes. tFNAs-RSV achieved enhanced stability, bioavailability, and biocompatibility compared with tFNAs and RSV alone. With its treatment, reactive oxygen species (ROS) production was minimized and reductases were activated in an in vitro model of DPN. Besides, respiratory function and adenosine triphosphate (ATP) production were enhanced. tFNAs-RSV also exhibited favorable therapeutic effects on sensory dysfunction, neurovascular deterioration, demyelination, and neuroapoptosis in DPN mice. Metabolomics analysis revealed that redox regulation and energy metabolism were two principal mechanisms that were impacted during the process. Comprehensive inspections indicated that tFNAs-RSV inhibited nitrosation and oxidation and activated reductase and respiratory chain. In sum, tFNAs-RSV served as a mitochondrial nanoguard (mito-guard), representing a viable drilling target for clinical drug development of DPN.

Antibody-drug conjugates: Recent advances in payloads.

Antibody‒drug conjugates (ADCs), which combine the advantages of monoclonal antibodies with precise targeting and payloads with efficient killing, show great clinical therapeutic value. The ADCs' payloads play a key role in determining the efficacy of ADC drugs and thus have attracted great attention in the field. An ideal ADC payload should possess sufficient toxicity, low immunogenicity, high stability, and modifiable functional groups. Common ADC payloads include tubulin inhibitors and DNA damaging agents, with tubulin inhibitors accounting for more than half of the ADC drugs in clinical development. However, due to clinical limitations of traditional ADC payloads, such as inadequate efficacy and the development of acquired drug resistance, novel highly efficient payloads with diverse targets and reduced side effects are being developed. This perspective summarizes the recent research advances of traditional and novel ADC payloads with main focuses on the structure-activity relationship studies, co-crystal structures, and designing strategies, and further discusses the future research directions of ADC payloads. This review also aims to provide valuable references and future directions for the development of novel ADC payloads that will have high efficacy, low toxicity, adequate stability, and abilities to overcome drug resistance.

Role of Polymeric Micelles in Ocular Drug Delivery: An Overview of Decades of Research.

Local drug delivery to the eye through conventional means has faced many challenges due to three essential barriers: (a) the complex structure of the cornea limiting drug absorption, (b) the capacity of ocular absorptive cells in drug metabolism, and (c) the washing effect of eye tears. Polymeric micelles (PMs) have been the focus of much interest for ocular drug delivery due to several advantages they provide for this application, including the capacity for the solubilization of hydrophobic drugs, nonirritability, nanoscopic diameter, and the clarity of their aqueous solution not interfering with vision. The potential to increase the release and residence time of incorporated medication at the site of absorption is also a bonus advantage for these delivery systems. This Review covers research conducted on single or mixed micelles prepared from small amphiphilic molecules, copolymers (diblock, triblock, and graft), and gel systems containing micelles. The purpose of this review is to provide an update on the status of micellar ocular delivery systems for different indications, with a focus on preclinical and clinical drug development. In this context, we are discussing the anatomy of the eye, various ocular barriers, different micellar formulations, and their benefits in ocular drug delivery, as well as the role of PMs in the management of ocular diseases both in preclinical models and in clinic. The encouraging preclinical effectiveness findings from experiments conducted in both laboratory settings and live animals have paved the way for the advancement of micellar systems in clinical trials for ocular administration and the first nanomicallar formulation approved for clinical use by the United States Food and Drug Administration (marketed as Cequa by Sun Pharmaceuticals).