Clinical Drug Development Research Articles

Review article: New developments in biomarkers and clinical drug development in alpha-1 antitrypsin deficiency-related liver disease.

Alpha-1 antitrypsin liver disease (AATLD) occurs in a subset of patients with alpha-1 antitrypsin deficiency. Risk factors for disease progression and specific pathophysiologic features are not well known and validated non-invasive assessments for disease severity are lacking. Currently, there are no approved treatments for AATLD. To outline existing understanding of AATLD and to identify knowledge gaps critical to improving clinical trial design and development of new treatments. This report was developed following a multi-stakeholder forum organised by the Alpha-1 Antitrypsin Deficiency Related Liver Disease Expert Panel in which experts presented an overview of the available literature on this topic. AATLD results from a 'gain of toxic function' and primarily manifests in those with the homozygous Pi*ZZ genotype. Accumulation of misfolded 'Z' AAT protein in liver cells triggers intracellular hepatocyte injury which may ultimately lead to hepatic fibrosis. Male gender, age over 50 years, persistently elevated liver tests, concomitant hepatitis B or C virus infection, and metabolic syndrome, including obesity and type 2 diabetes mellitus, are known risk factors for adult AATLD. While the gold standard for assessing AATLD disease activity is liver histology, less invasive measures with low intra- and inter-observer variability are needed. Measurement of liver stiffness shows promise; validated thresholds for staging AATLD are in development. Such advances will help patients by enabling risk stratification and personalised surveillance, along with streamlining the development process for novel therapies. This inaugural forum generated a list of recommendations to address unmet needs in the field of AATLD.

Pediatric Formulations Developed by Extrusion-Based 3D Printing: From Past Discoveries to Future Prospects.

Three-dimensional printing (3DP) technology in pharmaceutical areas is leading to a significant change in controlled drug delivery and pharmaceutical product development. Pharmaceutical industries and academics are becoming increasingly interested in this innovative technology due to its inherent inexpensiveness and rapid prototyping. The 3DP process could be established in the pharmaceutical industry to replace conventional large-scale manufacturing processes, particularly useful for personalizing pediatric drugs. For instance, shape, size, dosage, drug release and multi-drug combinations can be tailored according to the patient's needs. Pediatric drug development has a significant global impact due to the growing needs for accessible age-appropriate pediatric medicines and for acceptable drug products to ensure adherence to the prescribed treatment. Three-dimensional printing offers several significant advantages for clinical pharmaceutical drug development, such as the ability to personalize medicines, speed up drug manufacturing timelines and provide on-demand drugs in hospitals and pharmacies. The aim of this article is to highlight the benefits of extrusion-based 3D printing technology. The future potential of 3DP in pharmaceuticals has been widely shown in the last few years. This article summarizes the discoveries about pediatric pharmaceutical formulations which have been developed with extrusion-based technologies.

Abstract 4884: Evaluating the utility of in silico variant annotation tools for cancer driver detection

Abstract In cancer genomics, precise variant annotation is crucial for clinical decisions, drug development, and research. The burgeoning genomic data offers an opportunity to use data-driven approaches to generate knowledge that supports clinical decisions. Particularly machine learning (ML) and Deep learning (DL), are becoming essential, as their application is fast, scalable, simple to implement, and generates reproducible results. The methods ranging from simple sequence-based alignment scoring to advanced algorithms like Logistic regression, Support vector machine, and Recurrent neural networks, have been employed by multiple variant annotation tools. This study compares in-silico methods available in Ensembl's Variant Effect Predictor (VEP) using a test dataset with COSMIC annotations. ML/DL success relies on robust training sets with comprehensive genomic variants features, including effects on transcription/translation, genomic context, annotation resources, in silico pathogenicity predictions, and population allele frequency. The training set, composed of known benign or pathogenic variants, serves as a reference for these algorithms to classify new and unseen variants. Our analysis reveals a limited concordance between the prediction algorithms. Despite comparable true/false positives/negatives, discrepancies persist in variant classification. Certain algorithms exhibit a propensity to over or under-call deleterious mutations. Some demonstrate a tendency to classify random variants in non-cancer genes as deleterious. Challenges include the absence of consensus on informative features, diverse training datasets, and restriction to well annotated proteins/transcripts. Balancing the sensitivity and false positives in detecting cancer drivers is crucial. Integrating individual prediction scores with ML algorithms enhances tool performance but comes with risk of error propagation, and limited accuracy. The study emphasises the need for context-specific variant classification tools, as many variants' impacts are cancer-type specific, and some may drive disease synergistically. Existing tools, designed for a "one variant - one score approach," struggle to capture complex associations, especially those dependent on changes in the tumour microenvironment. Highlighting areas for improvement, the study addresses the "black box" problem in decision processes. While limited interpretability might not hinder practical applications, tools should evolve to assess more complex associations guided by biology. Formal consensus, reference training datasets, and standards are deemed essential for developing next-generation tools. The envisioned context-dependent tools aim to streamline feature complexity, thereby mitigating the black box problem and advancing the accuracy and interpretability of cancer variant annotation. Citation Format: Madhumita, Zbyslaw Sondka, Jon Teague. Evaluating the utility of in silico variant annotation tools for cancer driver detection [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4884.

Abstract 1459: The immuno-AVI-PDX, am innovative patient-derived xenograft model for preclinical immuno-oncology studies

Abstract Over the last decade, the success of immunotherapy in treating numerous solid and hematological tumors is unprecedent. However, the poor preclinical predictive power of current model systems explains in part the failures during late-stages clinical drug development for the numerous potential immunotherapies. Thus, there is a crucial need for innovative technologies offering fast and reliable evaluation of immunotherapies on patient-derived models. Using its proprietary process of micro-implantation of patient tumor cells within selected organs of series of avian embryos, Oncofactory developed two humanized avian xenograft models, namely IMMUNO-AVI-patient derived xenograft (iAVI-PDXTM) and IMMUNO-AVI-cell line derived xenograft (iAVI-cellDXTM). These models, consisting in the co-implantation of human peripheral-blood mononuclear cells (PBMC) and human cancer cells were validated through a sequence of experimental steps. First, we found that transplantation of PBMCs into avian tissues exhibited good survival and low allogenicity against the avian embryonic organism. Second, in embryos engrafted with tumoral cells, we established that intravenously injected PBMCs successfully populated the tumor. Third, to reduce the dilution of immune cells in the embryonic tissues and to better standardize the number of implanted cells in between embryos, we optimized the process by direct co-implantation of both PBMCs and cancer cells. We analyzed the immune cell contingent sorted from dissected tumors and found that all major immune cells populations, including T and B lymphocytes, monocytes as well as NK cells were preserved post-grafting, when compared to pre-grafted PBMCs. The AVI-cellDXTM and AVI-PDXTM models initially developed by Oncofactory allows fast and reproducible tumor growth with statistical evaluation of molecule efficacy already at 24 hours post-injection. To assess whether our humanized models retain these advantages, we analyzed the outcome of anti-PD1 antibody (Pembrolizumab) intravenous injection in series of avian embryos co-engrafted with human PBMCs and PDL1-expressing breast and colorectal cancer cell lines. Twenty-four hours post vehicle or Pembrolizumab exposure, we analyzed the tumor volumes in grafted embryos using light sheet microscopy. In all three cancer models, we found a statistically significant reduction of the volume upon pembrolizumab, compared with vehicle. Using a panel of molecular markers in flow cytometry, we found that the Pembrolizumab efficiently targeted T lymphocytes in the tumors. Finally, we validated the efficiency of Pembrolizumab treatment in models of co-implantation of human PBMCs with melanoma and colorectal patient samples. Thus, humanized iAVI-cellDXTM or -PDXTM technology bring powerful and fast alternative to mouse models, to strongly accelerate preclinical developments in immuno-oncology. Citation Format: Marjorie Lacourrege, Clélia Costechareyre, Loraine Jarrosson, Romain Teinturier, Frédéric Berget, Céline Delloye-Bourgeois, Valérie Castellani. The immuno-AVI-PDX, am innovative patient-derived xenograft model for preclinical immuno-oncology studies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1459.

Establishment of RWS guidance reflecting contributions of China to regulatory science

ABSTRACT China’s accession to the ICH has accelerated the advancement of its regulatory science. To foster innovation and improve the efficiency of pharmaceutical research and development, the China National Medical Products Administration (NMPA) encourages the use of real-world evidence (RWE) to support drug regulatory decision-making and has constructed a series of real-world study (RWS) related guidance, reflecting the contribution of the NMPA to the field of RWS in drug clinical development. Based on the four guidelines on RWE, real-world data (RWD), RWS design and protocol development, and communication with regulatory authorities, the guidance has been extended to more specific clinical applications, such as oncology, rare diseases, pediatric drugs, and traditional Chinese medicine. This paper reviews the core content and features of the series of RWS guidelines, presents their role in promoting drug development, and discusses challenges of using RWE in support of drug regulatory decision-making in China.

Repurposing Drugs for Senotherapeutic Effect: Potential Senomorphic Effects of Female Synthetic Hormones.

Repurposing previously approved drugs may fast track the route to the clinic for potential senotherapeutics and improves the inefficiency of the clinical drug development pipeline. We performed a repurposing screen of 240 clinically approved molecules in human primary dermal fibroblasts for their effects on CDKN2A expression. Molecules demonstrating effects on CDKN2A expression underwent secondary screening for senescence-associated beta galactosidase (SAB) activity, based on effect size, direction, and/or molecule identity. Selected molecules then underwent a more detailed assessment of senescence phenotypes including proliferation, apoptosis, DNA damage, senescence-associated secretory phenotype (SASP) expression, and regulators of alternative splicing. A selection of the molecules demonstrating effects on senescence were then used in a new bioinformatic structure-function screen to identify common structural motifs. In total, 90 molecules displayed altered CDKN2A expression at one or other dose, of which 15 also displayed effects on SAB positivity in primary human dermal fibroblasts. Of these, 3 were associated with increased SAB activity, and 11 with reduced activity. The female synthetic sex hormones-diethylstilboestrol, ethynyl estradiol and levonorgestrel-were all associated with a reduction in aspects of the senescence phenotype in male cells, with no effects visible in female cells. Finally, we identified that the 30 compounds that decreased CDKN2A activity the most had a common substructure linked to this function. Our results suggest that several drugs licensed for other indications may warrant exploration as future senotherapies, but that different donors and potentially different sexes may respond differently to senotherapeutic compounds. This underlines the importance of considering donor-related characteristics when designing drug screening platforms.

Master protocols and other innovative trial designs in inflammation and immunology to expedite clinical drug development

Master protocol designs, such as umbrella and basket studies, allow multiple compounds or multiple target populations to be evaluated simultaneously within a single protocol, and have been widely adopted in oncology clinical trials. These novel designs can also be applied in other therapeutic areas, where they could have several benefits over conducting traditional randomized controlled trials. Here, we detail Pfizer’s recent implementations of master protocol designs in inflammation and immunology clinical studies, focusing on the opportunities for cost and resource savings and how these designs can expedite the time required to bring new treatments to patients in need.

Using Social Media as a Source of Real-World Data for Pharmaceutical Drug Development and Regulatory Decision Making.

While pharmaceutical companies aim to leverage real-world data (RWD) to bridge the gap between clinical drug development and real-world patient outcomes, extant research has mainly focused on the use of social media in a post-approval safety-surveillance setting. Recent regulatory and technological developments indicate that social media may serve as a rich source to expand the evidence base to pre-approval and drug development activities. However, use cases related to drug development have been largely omitted, thereby missing some of the benefits of RWD. In addition, an applied end-to-end understanding of RWD rooted in both industry and regulations is lacking. We aimed to investigate how social media can be used as a source of RWD to support regulatory decision making and drug development in the pharmaceutical industry. We aimed to specifically explore the data pipeline and examine how social-media derived RWD can align with regulatory guidance from the US Food and Drug Administration and industry needs. A machine learning pipeline was developed to extract patient insights related to anticoagulants from X (Twitter) data. These findings were then analysed from an industry perspective, and complemented by interviews with professionals from a pharmaceutical company. The analysis reveals several use cases where RWD derived from social media can be beneficial, particularly in generating hypotheses around patient and therapeutic area needs. We also note certain limitations of social media data, particularly around inferring causality. Social media display considerable potential as a source of RWD for guiding efforts in pharmaceutical drug development and pre-approval settings. Although further regulatory guidance on the use of social media for RWD is needed to encourage its use, regulatory and technological developments are suggested to warrant at least exploratory uses for drug development.

Development and validation of a brain fog scale for coeliac disease.

Brain fog is a subjective cognitive impairment commonly reported in coeliac disease. A standardised tool to define and assess it is an important unmet need. To develop a patient-informed tool to assess brain fog in coeliac disease to support clinical care, research and drug development. A pilot online study defined patient descriptors of brain fog. A second study evaluated the factor structure and performance of the scale across two-time points ('Now' and in the 'Past week'). One month later, participants were invited to repeat the study with two online cognitive processing tests, the Stroop task and the trail making test. Among adults with treated coeliac disease, 37 (91.9% F) participated in the pilot study and 510 (88.8% F) in the second study of whom 99 repeated the study 1 month later with 51 completing cognitive testing. The most common brain fog descriptors were 'difficulty focusing', 'difficulty thinking' and 'difficulty finding the right words and communicating'. The 12-item scale reflects 'cognitive impairment' and 'somatic and affective experience' and demonstrates strong psychometric properties. It tracked with patients report of brain fog being present or absent across two-time points. It did not significantly correlate with the cognitive tests. The brain fog assessment and severity scale is the first patient-informed clinical outcomes assessment tool measuring brain fog in coeliac disease. It is brief and validated for two time-based formats. Further research coupling it with biomarker discovery is needed to confirm its validity as a predictor of cognitive performance.

Draft Guidance for Industry Duchenne Muscular Dystrophy, Becker Muscular Dystrophy, and Related Dystrophinopathies - Developing Potential Treatments for the Entire Spectrum of Disease.

Duchenne muscular dystrophy (DMD) and related dystrophinopathies are neuromuscular conditions with great unmet medical needs that require the development of effective medical treatments. To aid sponsors in clinical development of drugs and therapeutic biological products for treating DMD across the disease spectrum by integrating advancements, patient registries, natural history studies, and more into a comprehensive guidance. This guidance emerged from collaboration between the FDA, the Duchenne community, and industry stakeholders. It entailed a structured approach, involving multiple committees and boards. From its inception in 2014, the guidance underwent revisions incorporating insights from gene therapy studies, cardiac function research, and innovative clinical trial designs. The guidance provides a deeper understanding of DMD and its variants, focusing on patient engagement, diagnostic criteria, natural history, biomarkers, and clinical trials. It underscores patient-focused drug development, the significance of dystrophin as a biomarker, and the pivotal role of magnetic resonance imaging in assessing disease progression. Additionally, the guidance addresses cardiomyopathy's prominence in DMD and the burgeoning field of gene therapy. The updated guidance offers a comprehensive understanding of DMD, emphasizing patient-centric approaches, innovative trial designs, and the importance of biomarkers. The focus on cardiomyopathy and gene therapy signifies the evolving realm of DMD research. It acts as a crucial roadmap for sponsors, potentially leading to improved treatments for DMD.

Air-pollutant particulate matter 2.5 (PM2.5)-induced inflammation and oxidative stress in diseases: Possible therapeutic approaches

Today, air pollution is one of the greatest threats to organismal healthspan. The environmental air of earth is contaminated with a wide variety of artificially generated pollutants like fine particulate matter (PM2.5) emitting from industry, fuel engine vehicles, biomass combustion, fumes from blasting, crop residue burning, and wildfire. The air pollutant PM2.5 induces massive oxidative stress and inflammation, the major contributors in initiation and progression of numerous diseases including pulmonary, cardiovascular, renal, hepatic, reproductive, neurological, mental, and accelerated biological aging. The provocative question is the following: how can we solve this air pollution associated problem? As it is not realistic to clean the environment at once from artificially generated toxic pollution, initiatives have been undertaken to develop novel therapeutic approaches to control air-pollutant-induced oxidative stress and inflammation and associated devastating diseases. The primary goal of this review article is to discuss systematically the key findings of numerous recent preclinical studies documenting first, the role of air pollutant PM2.5 in augmentation of inflammation, oxidative stress, and associated diseases; and second, the efficacies of different natural and synthetic compounds in amelioration of PM2.5-induced oxidative stress, inflammation, pyroptosis, and associated pathologies. Further investigation on the safety of these compounds will be helpful to select effective and non-toxic compound(s) for clinical trial and drug development.

A Comprehensive Review on the Traditional Uses, Phytochemical Compositions and Pharmacological Properties of an Ethnomedicinal Herb, Paederia foetida

Background:: Paederia foetida L. (Family – Rubiaceae) is a common herb found available in the temperate and tropical Asia. The ethnomedicinal applications of this plant are widely elaborated In Chinese Traditional Medicine, Ayurveda, and other ancient scriptures throughout the world. Different ethnic groups use this plant in the treatment of alimentary and digestive disorders, bone related diseases like rheumatoid arthritis, bone fractures as well as in the ailments of diabetes, coughs, asthma, itches, wounds, body ache, toothache, cancer etc. Objectives:: This comprehensive review aims to provide an insightful understanding of traditional uses, chemical composition, and pharmacological properties of P. foetida (from 1976 up to 2023), which may provide a foundation for further study and for the proper utilization of P. foetida resources. Methods:: Literature survey was conducted using known databases and the relevant keywords. Results:: P. foetida has been widely used in Chinese traditional medicine (CTM) for the treatment of dyspepsia, jaundice, pains, diarrhea and others. Several ethnic groups throughout the world used this plant to cure common health complaints namely, abdominal pain, gastritis, dysentery, diarrhoea, constipation, joint pain, etc. A total of 24 bioactive phytocompounds, such as asperuloside, paederosidic acid, sitosterols, stigmasterol, campesterol, ellagic acid, iridoids, ursolic acid, epifriedelinol, and others are reported to possess antiulcer, antidiarrheal, antihyperglycemic, antioxidant, antitussive, anthelmintic, and hepatoprotective activities. Conclusion:: The present review not only summarizes the alternative approaches using this herb by ethnic people for treating various disorders, but also focuses on the latest scientific investigations to elucidate different bioactivities of this plant, thereby facilitating the understanding of its correlation with contemporary pharmacology. However, till date, very few studies elucidated the biological properties of these phytochemicals that were isolated exclusively from this particular plant. Moreover, the correlation between phytocompounds from P. foetida and its pharmacological activities aiming towards clinical drug development is still lacking. Finally, further research should be oriented towards determining the optimal dosage and toxicological limits, and thereby providing guidance for clinical applications.

Adverse Drug Reactions prediction by combining wide & deep learning and POLY2

Accurate prediction of Adverse Drug Reactions (ADRs) holds immense importance in the field of clinical medicine and drug development. The requirement of accurate prediction spans various stages, ranging from drug design and clinical trials to marketing monitoring. The traditional ADR forecasting method has the disadvantage that it requires a lot of computing resources and is not suitable for large-scale forecasting. To address this issue, this study introduces the Wide & Deep model. This model combines the abilities of memorization and generalization to enhance the accuracy of ADR predictions. Additionally, we identify a shortcoming in the wide component of the traditional Wide & Deep model the lack of nonlinear transformation. Therefore, we propose the inclusion of POLY2 in the Wide & Deep model to rectify this shortcoming. By incorporating POLY2, our aim is to retain the models memorization and generalization abilities, leverage the nonlinear relationship between features, and capture the interaction effect between drug chemical substructures for better model performance. To validate our proposed method, we conduct experiments on two datasets: the FDA Adverse Event Reporting System (FAERS) and PubChem. The evaluation metric utilized is the Area Under the Curve (AUC) score, which demonstrates that our method outperforms the original model. The results indicate that by combining POLY2 feature crosses with the Wide & Deep model, we have achieved significant improvements in the prediction of ADRs.

2-(Difluoromethyl)-1,3,4-oxadiazoles: The Future of Selective Histone Deacetylase 6 Modulation?

Histone deacetylase 6 (HDAC6) is an important target for the treatment of oncological and non-oncological diseases. Established HDAC6 inhibitors feature a hydroxamic acid as a zinc-binding group (ZBG) and thus possess mutagenic and genotoxic potential. Recently, the 2-(difluoromethyl)-1,3,4-oxadiazole (DFMO) group emerged as a novel ZBG. In this Viewpoint, we summarize the discovery of the mode of action of DFMOs. Additionally, we discuss opportunities and challenges in the journey toward the clinical development of DFMO-based drugs for the treatment of HDAC6-driven diseases.

Conjugated Oligoelectrolyte with DNA Affinity for Enhanced Nuclear Imaging and Precise DNA Quantification.

Precise DNA quantification and nuclear imaging are pivotal for clinical testing, pathological diagnosis, and drug development. The detection and localization of mitochondrial DNA serve as crucial indicators of cellular health. We introduce a novel conjugated oligoelectrolyte (COE) molecule, COE-S3, featuring a planar backbone composed of three benzene rings and terminal side chains. This unique amphiphilic structure endows COE-S3 with exceptional water solubility, a high quantum yield of 0.79, and a significant fluorescence Stokes shift (λex = 366 nm, λem = 476 nm), alongside a specific fluorescence response to DNA. The fluorescence intensity correlates proportionally with DNA concentration. COE-S3 interacts with double-stranded DNA (dsDNA) through an intercalation binding mode, exhibiting a binding constant (K) of 1.32 × 106 M-1. Its amphiphilic nature and strong DNA affinity facilitate its localization within mitochondria in living cells and nuclei in apoptotic cells. Remarkably, within 30 min of COE-S3 staining, cell vitality can be discerned through real-time nuclear fluorescence imaging of apoptotic cells. COE-S3's high DNA selectivity enables quantitative intracellular DNA analysis, providing insights into cell proliferation, differentiation, and growth. Our findings underscore COE-S3, with its strategically designed, shortened planar backbone, as a promising intercalative probe for DNA quantification and nuclear imaging.

Review of lipocalin-2-mediated effects in diabetic retinopathy.

Studies have uncovered LCN2 as a marker of inflammation strongly related to obesity, insulin resistance, and abnormal glucose metabolism in humans, and is involved in vascular diseases, inflammatory diseases, and neurological diseases. In recent years, studies have shown that elevated levels of LCN2 have a strong association with diabetic retinopathy (DR), but the pathogenesis is unknown. Here, we reviewed the relevant literature and compiled the pathogenesis associated with LCN2-induced DR. We searched PubMed and Web of Science electronic databases using "lipocalin-2, diabetic retinopathy, retinal degeneration, diabetic microangiopathies, diabetic neuropathy and inflammation" as subject terms. In diabetic retinal neuropathy, LCN2 causes impaired retinal photoreceptor function and retinal neurons; in retinal microangiopathy, LCN2 induces apoptosis of retinal vascular endothelial cells and promotes angiogenesis; in retinal inflammation, increased secretion of LCN2 recruits inflammatory cells and induces pro-inflammatory cytokines. Moreover, LCN2 has the potential as a biomarker for DR. Recent studies have shown that retinal damage can be attenuated by silencing LCN2, which may be associated with the inhibition of caspase-1-mediated pyroptosis, and LCN2 may be a new target for the treatment of DR. In conclusion, LCN2, involved in the development of diabetic retinopathy, is a key factor in diabetic retinal microangiopathy, neurodegeneration, and retinal inflammation. LCN2 is likely to be a novel molecular target leading to DR, and a more in-depth study of the pathogenesis of DR caused by LCN2 may provide considerable benefits for clinical research and potential drug development.

WDR12/RAC1 axis promoted proliferation and anti-apoptosis in colorectal cancer cells.

WD repeat domain 12 (WDR12) plays a crucial role in the ribosome biogenesis pathway. However, its biological function in colorectal cancer (CRC) remains poorly understood. Therefore, this study aims to investigate the roles of WDR12 in the occurrence and progression of CRC, as well as its underlying mechanisms. The expression of WDR12 was assessed through The Cancer Genome Atlas (TCGA) and the Human Protein Atlas (HPA) database. Functional experiments including Celigo assay, MTT assay, and Caspase-3/7 assay were conducted to validate the role of WDR12 in the malignant progression of CRC. Additionally, mRNA chip-sequencing and ingenuity pathway analysis (IPA) were performed to identify the molecular mechanism. WDR12 expression was significantly upregulated in CRC tissues compared to normal colorectal tissues. Knockdown of WDR12 reduced proliferation and promoted apoptosis of CRC cell lines in vitro and in vivo experiments. Furthermore, WDR12 expression had a significantly inverse association with diseases and functions, including cancer, cell cycle, DNA replication, recombination, cellular growth, proliferation and repair, as revealed by IPA analysis of mRNA chip-sequencing data. Moreover, the activation of cell cycle checkpoint kinases proteins in the cell cycle checkpoint control signaling pathway was enriched in the WDR12 knockdown CRC cell lines. Additionally, downregulation of rac family small GTPase 1 (RAC1) occurred upon WDR12 knockdown, thereby facilitating the proliferation and anti-apoptosis of CRC cells. Our study demonstrates that the WDR12/RAC1 axis promotes tumor progression in CRC. Therefore, WDR12 may serve as a novel oncogene and a potential target for individualized therapy in CRC. These findings provide an experimental foundation for the clinical development of drugs targeting the WDR12/RAC1 axis.

Accelerating drug development for amyotrophic lateral sclerosis: construction and application of a disease course model using historical placebo group data

BackgroundAmyotrophic lateral sclerosis (ALS) is an irreversible degenerative disease. Placebo-controlled randomized trials are currently the main trial design to assess the clinical efficacy of drugs for ALS treatment. The aim of this study was to establish models to quantitatively describe the course of ALS, explore influencing factors, and provide the necessary information for ALS drug development.MethodsWe conducted a comprehensive search of PubMed and the Cochrane Library Central Register for placebo-controlled trials that evaluated treatments for ALS. From these trials, we extracted the clinical and demographic characteristics of participants in the placebo group, as well as outcome data, which encompassed overall survival (OS) and Amyotrophic Lateral Sclerosis Functional Rating Scale (ALSFRS-R) scores, at various time points.ResultsIn total, 47 studies involving 6118 participants were included. Disease duration and the proportion of patients receiving riluzole were identified as significant factors influencing OS in the placebo group. Specifically, the median OS was 35.5 months for a disease duration of 9 months, whereas it was 20.0 months for a disease duration of 36 months. Furthermore, for every 10% increase in the proportion of patients treated with riluzole (100 mg daily), there was an association with a median OS extension of approximately 0.4 months. The estimated time for the ALSFRS-R score in the placebo group to decrease to 50% of its maximum effect from baseline level was approximately 17.5 months, and the time to reach a plateau was about 40 months.ConclusionsThe established disease course model of the historical placebo group is valuable in the decision-making process for the clinical development of ALS drugs. It serves not only as an external control to evaluate the efficacy of the tested drug in single-arm trials but also as prior information that aids in accurately estimating the posterior distribution of the disease course in the placebo group during small-sample clinical trials.

Early Stage Preclinical Formulation Strategies to Alter the Pharmacokinetic Profile of Two Small Molecule Therapeutics.

Early stage chemical development presents numerous challenges, and achieving a functional balance is a major hurdle, with many early compounds not meeting the clinical requirements for advancement benchmarks due to issues like poor oral bioavailability. There is a need to develop strategies for achieving the desired systemic concentration for these compounds. This will enable further evaluation of the biological response upon a compound-target interaction, providing deeper insight into the postulated biological pathways. Our study elucidates alternative drug delivery paradigms by comparing formulation strategies across oral (PO), intraperitoneal (IP), subcutaneous (SC), and intravenous (IV) routes. While each modality boasts its own set of merits and constraints, it is the drug's formulation that crucially influences its pharmacokinetic (PK) trajectory and the maintenance of its therapeutic levels. Our examination of model compounds G7883 and G6893 highlighted their distinct physio-chemical attributes. By harnessing varied formulation methods, we sought to fine-tune their PK profiles. PK studies showcased G7883's extended half-life using an SC oil formulation, resulting in a 4.5-fold and 2.5-fold enhancement compared with the IP and PO routes, respectively. In contrast, with G6893, we achieved a prolonged systemic coverage time above the desired target concentration through a different approach using an IV infusion pump. These outcomes underscore the need for tailored formulation strategies, which are dictated by the compound's innate properties, to reach the optimal in vivo systemic concentrations. Prioritizing formulation and delivery optimization early on is pivotal for effective systemic uptake, thereby facilitating a deeper understanding of biological pathways and expediting the overall clinical drug development timeline.

User Centered Rare Disease Clinical Trial Knowledge Graph (RCTKG).

Drug development in rare diseases is challenging due to the limited availability of subjects with the diseases and recruiting from a small patient population. The high cost and low success rate of clinical trials motivate deliberate analysis of existing clinical trials to understand status of clinical development of orphan drugs and discover new insight for new trial. In this project, we aim to develop a user centered Rare disease based Clinical Trial Knowledge Graph (RCTKG) to integrate publicly available clinical trial data with rare diseases from the Genetic and Rare Disease (GARD) program in a semantic and standardized form for public use. To better serve and represent the interests of rare disease users, user stories were defined for three types of users, patients, healthcare providers and informaticians, to guide the RCTKG design in supporting the GARD program at NCATS/NIH and the broad clinical/research community in rare diseases.