Pharmacological Models Research Articles

A Highly Selective and Versatile Probe Platform for Visualization of Monoacylglycerol Lipase.

Monoacylglycerol lipase (MAGL) is a key enzyme for signal termination in the endocannabinoid system (ECS). MAGL inhibition results in indirect activation of the cannabinoid receptors, which offers unique advantages for the treatment of, e.g., multiple sclerosis, epilepsy, and other neurological disorders. Molecular imaging techniques are valuable tools to overcome the current poor understanding of MAGL's distribution and role in patho- and physiological processes within ECS signaling. Herein, we report the design, synthesis, and validation of highly selective versatile fluorescent and click-chemistry probes for MAGL. Structure-based design combined with a reverse-design approach allowed the development of a structural unit that selectively and effectively recognizes MAGL while offering a versatile platform to attach different fluorophores and further reporter units. In this way, labeled probes with sub-nanomolar potency carrying diverse fluorescent dyes were obtained. Probe affinity and selectivity remained invariant to changes in the fluorophore subunit, showing the remarkable robustness of this platform in delivering tailor-made probes. Highly consistent inhibition across species supports pharmacological model translatability. Extensive profiling and validation in various cellular systems shows the ability of these highly potent and selective probes to elucidate the complex role of MAGL in ECS cellular signaling, inflammatory processes, and disease progression.

Aligning Large Language Models with Humans: A Comprehensive Survey of ChatGPT's Aptitude in Pharmacology.

Due to the lack of a comprehensive pharmacology test set, evaluating the potential and value of large language models (LLMs) in pharmacology is complex and challenging. This study aims to provide a test set reference for assessing the application potential of both general-purpose and specialized LLMs in pharmacology. We constructed a pharmacology test set consisting of three tasks: drug information retrieval, lead compound structure optimization, and research trend summarization and analysis. Subsequently, we compared the performance of general-purpose LLMs GPT-3.5 and GPT-4 on this test set. The results indicate that GPT-3.5 and GPT-4 can better understand instructions for information retrieval, scheme optimization, and trend summarization in pharmacology, showing significant potential in basic pharmacology tasks, especially in areas such as drug pharmacological properties, pharmacokinetics, mode of action, and toxicity prediction. These general LLMs also effectively summarize the current challenges and future trends in this field, proving their valuable resource for interdisciplinary pharmacology researchers. However, the limitations of ChatGPT become evident when handling tasks such as drug identification queries, drug interaction information retrieval, and drug structure simulation optimization. It struggles to provide accurate interaction information for individual or specific drugs and cannot optimize specific drugs. This lack of depth in knowledge integration and analysis limits its application in scientific research and clinical exploration. Therefore, exploring retrieval-augmented generation (RAG) or integrating proprietary knowledge bases and knowledge graphs into pharmacology-oriented ChatGPT systems would yield favorable results. This integration will further optimize the potential of LLMs in pharmacology.

New insights into anti-depression effects of bioactive phytochemicals.

Depression is one of the most common psychological disorders, and due to its high prevalence and mortality rates, it imposes a significant disease burden. Contemporary treatments for depression involve various synthetic drugs, which have limitations such as side effects, single targets, and slow onset of action. Unlike synthetic medications, phytochemicals offer the benefits of a multi-target and multi-pathway mode of treatment for depression. In this literature review, we describe the pharmacological actions, experimental models, and clinical trials of the antidepressant effects of various phytochemicals. Additionally, we summarize the potential mechanisms by which these phytochemicals prevent depression, including regulating neurotransmitters and their receptors, the HPA axis, inflammatory responses, managing oxidative stress, neuroplasticity, and the gut microbiome. Phytochemicals exert therapeutic effects through multiple pathways and targets, making traditional Chinese medicine (TCM) a promising adjunctive antidepressant for the prevention, alleviation, and treatment of depression. Therefore, this review aims to provide robust evidence for subsequent research into developing phytochemical resources as effective antidepressant agents.

Quantitative Systems Pharmacology (QSP) modeling based head-to-head comparison of agalsidase-beta and migalastat therapy in a virtual population of Fabry disease patients

Quantitative Systems Pharmacology (QSP) modeling based head-to-head comparison of agalsidase-beta and migalastat therapy in a virtual population of Fabry disease patients

A Mechanistic Pharmacological Model to Predict and Inform Effective Buprenorphine Treatment Induction Strategies in the Era of Synthetic Opioids

A Mechanistic Pharmacological Model to Predict and Inform Effective Buprenorphine Treatment Induction Strategies in the Era of Synthetic Opioids

The Kinetics of Cystatin C and Serum Creatinine in Acute Kidney Injury.

Acute kidney injury (AKI) is a common condition affecting a significant portion of hospitalized and critically ill patients. Current AKI diagnosis relies on serum creatinine (sCr), which has several recognized limitations that impact the timely detection and response to AKI management. Serum cystatin C (sCys) has characteristics that can overcome the limitations of sCr, but head-to-head comparisons of these biomarkers is difficult to study prospectively. A quantitative assessment of the kinetics of sCys and sCr during AKI is necessary to support clinical workflow implementation for AKI diagnosis and management. A quantitative systems pharmacology (QSP) model was developed using MATLAB and Simbiology (The MathWorks, Natick, MA), to simulate the concentration-time profiles of sCr and sCys under varying degrees of AKI across a spectrum of baseline kidney function. The model incorporated parameters from existing literature and used a contemporary sCr and sCys GFR equation to assess the time to reach AKI diagnostic criteria for both biomarkers. The model demonstrated that sCys achieves steady-state concentration and meets AKI diagnostic thresholds significantly faster than sCr, with an advantage of six to 48 hours, depending on CKD stage. sCys exhibited greater sensitivity in detecting GFR reductions, with the ability to detect AKI within 12-24 hours post-AKI, compared to 12-72 hours for sCr. The study also identified that for sCys, absolute value diagnostic cutoffs are more effective than percentage-based thresholds and can provide consistent detection across different CKD stages. sCys has superior kinetics for early AKI detection compared to sCr, making it a valuable addition to AKI diagnostic protocols, particularly in high-risk populations. Daily monitoring of sCys in patients at risk for AKI would facilitate more timely detection and potentially improve clinical outcomes. Future research should focus on validating sCys diagnostic criteria and integrating it with other biomarkers to enhance AKI management.

Evaluating Salidroside as a Therapeutic Agent for Vascular Calcification Using Network Pharmacology and Experimental Rat Models

Evaluating Salidroside as a Therapeutic Agent for Vascular Calcification Using Network Pharmacology and Experimental Rat Models

P1097 Phase 1/2 study to assess safety, tolerability, and efficacy of XmAb942 (anti-TL1A) in healthy participants and participants with ulcerative colitis

Abstract Background Tumour necrosis factor-like ligand 1A (TL1A) mediates a broad spectrum of pro-inflammatory and pro-fibrotic effects that have been linked to the pathogenesis of inflammatory bowel disease (IBD), as well as other autoimmune disorders. Recent clinical trials have demonstrated that antagonist antibodies that interfere with the interaction between TL1A and its cognate receptor, Death Receptor 3, can result in clinical remission in the two primary variants of IBD, ulcerative colitis and Crohn’s disease. XmAb942 is an anti-TL1A IgG1 antibody with ablated Fc-mediated effector function that incorporates the Xtend™ half-life extension technology. XmAb942 binds trimeric TL1A with high affinity and specificity and is highly potent across multiple preclinical assays. Allometric scaling of the non-human primate half-life of 23 days predicts a half-life of ≥ 70 days in humans. Quantitative systems pharmacology modelling supports the potential for superior drug exposure with less frequent dosing as compared to first-generation anti-TL1A antibodies. We now present details of the ongoing seamless Phase 1/2 study in healthy participants and participants with ulcerative colitis. Methods Phase 1 (Parts A and B) is a single ascending dose administered intravenously or subcutaneously followed by repeat dosing in healthy participants. Phase 2 (Part C) is in participants with ulcerative colitis with emerging Phase 1 data to determine dosing. Results The primary objectives of Parts A and B are to assess the safety and tolerability of single and repeat doses of XmAb942. Secondary objectives include assessment of pharmacokinetics (PK). Exploratory objectives include assessment of immunogenicity and pharmacodynamics. The primary objective of Part C is to evaluate the effect of repeat doses of XmAb942 on clinical remission in participants with moderately to severely active ulcerative colitis. Secondary objectives include evaluation of endoscopic improvement, endoscopic remission, clinical response, histologic-endoscopic improvement, histologic-endoscopic remission, as well as safety and PK assessments. Exploratory objectives include assessment of immunogenicity and pharmacodynamic effects. Conclusion The seamless Phase 1/2 study is designed to assess XmAb942 as a next-generation, potent, and long-acting anti-TL1A antibody therapeutic with potential best-in-class drug exposure and less frequent dosing. This study is currently enrolling in Australia, with Phase 2 to be expanded globally. Interim data are expected in the first half of 2025. References Clinical trials identification: NCT06619990

Understanding molecular mechanisms behind the anti-inflammatory effects of Machilus macrantha (Gulmavu) by network pharmacology and molecular modelling approach

Understanding molecular mechanisms behind the anti-inflammatory effects of <i>Machilus macrantha</i> (Gulmavu) by network pharmacology and molecular modelling approach

A physiologically-based quantitative systems pharmacology model for mechanistic understanding of the response to alogliptin and its application in patients with renal impairment.

Alogliptin is a highly selective inhibitor of dipeptidyl peptidase-4 and primarily excreted as unchanged drug in the urine, and differences in clinical outcomes in renal impairment patients increase the risk of serious adverse reactions. In this study, we developed a comprehensive physiologically-based quantitative systematic pharmacology model of the alogliptin-glucose control system to predict plasma exposure and use glucose as a clinical endpoint to prospectively understand its therapeutic outcomes with varying renal function. Our model incorporates a PBPK model for alogliptin, DPP-4 activity described by receptor occupancy theory, and the crosstalk and feedback loops for GLP-1-GIP-glucagon, insulin, and glucose. Based on the optimization of renal function-dependent parameters, the model was extrapolated to different stages renal impairment patients. Ultimately our model adequately describes the pharmacokinetics of alogliptin, the progression of DPP-4 inhibition over time and the dynamics of the glucose control system components. The extrapolation results endorse the dose adjustment regimen of 12.5mg once daily for moderate patients and 6.25mg once daily for severe and ESRD patients, while providing additional reflections and insights. In clinical practice, our model could provide additional information on the in vivo fate of DPP4 inhibitors and key regulators of the glucose control system.

Simulation of clinical trials of oral treprostinil in pulmonary arterial hypertension using a virtual population

Challenges in drug development for rare diseases such as pulmonary arterial hypertension can be addressed through the use of mathematical modeling. In this study, a quantitative systems pharmacology model of pulmonary arterial hypertension pathophysiology and pharmacology was used to predict changes in pulmonary vascular resistance and six-minute walk distance in the context of oral treprostinil clinical studies. We generated a virtual population that spanned the range of clinical observations and then calibrated virtual patient-specific weights to match clinical trials. We then used this virtual population to predict the results of clinical trials on the basis of disease severity, dosing regimen, time since diagnosis, and co-administered background therapies. The virtual population captured the effect of changes in trial design and patient subpopulation on clinical response. We also demonstrated the virtual trial workflow’s potential for enriching populations based on clinical biomarkers to increase likelihood of trial success.

A Multiple-Model-Informed Drug-Development Approach for Optimal Regimen Selection of an Oncolytic Virus in Combination With Pembrolizumab.

The antitumor efficacy of an intratumoral injection of a genetically engineered oncolytic vaccinia virus carrying human IL-7 and murine IL-12 genes (hIL-7/mIL-12-VV) was demonstrated in CT26.WT-bearing mice. In the CT26.WT-bearing mouse model, the efficacy of the combination of hIL-7/mIL-12-VV plus the anti-programmed cell death protein (PD)-1 antibody was determined to be correlated with the timing of administration: greater efficacy was observed when hIL-7/mIL-12-VV was administered before the anti-PD-1 agent instead of simultaneous administration. To identify an optimal dosing regimen for first-in-human clinical trials, a multiple model-informed drug-development (MIDD) approach was used through development of a quantitative systems pharmacology (QSP) model and an agent-based model (ABM). All models were built and verified using available literature and preclinical study data. Multiple dosing scenarios were explored using virtual populations by altering the interval between hIL-7/hIL-12-VV and pembrolizumab administration. In contrast with observations from preclinical studies, both the QSP and the ABM models demonstrated no antagonistic effect on the dose-dependent antitumor efficacy of hIL-7/hIL-12-VV by pembrolizumab in simulations of clinical therapy. Based on the MIDD strategy, it was recommended that the highest dose of hIL-7/hIL-12-VV and pembrolizumab should be administered on the same day, but with pembrolizumab administration following hIL-7/hIL-12-VV administration. Multiple different modeling approaches uniquely supported and informed the first-in-human clinical trial design by guiding the optimal dose and regimen selection.

NI-3201 Is a Bispecific Antibody Mediating PD-L1-Dependent CD28 Co-stimulation on T Cells for Enhanced Tumor Control.

Despite advances in cancer immunotherapy, such as targeting the PD-1/PD-L1 axis, a substantial number of patients harbor tumors that are resistant or relapse. Selective engagement of T-cell co-stimulatory molecules with bispecific antibodies may offer novel therapeutic options by enhancing signal 1-driven activation occurring via T-cell receptor engagement. In this study, we report the development and preclinical characterization of NI-3201, a PD-L1×CD28 bispecific antibody generated on the κλ-body platform that was designed to promote T-cell activity and antitumor function through a dual mechanism of action. We confirmed that NI-3201 blocks the PD-L1/PD-1 immune checkpoint pathway and conditionally provides T-cell co-stimulation via CD28 (signal 2) when engaging PD-L1+ tumors or immune cells. In systems with signal 1-primed T cells, NI-3201 enhanced potent effector functionality: in vitro through antigen-specific recall assays with cytomegalovirus-specific T cells and in vivo by inducing tumor regression and immunologic memory in tumor-associated antigen-expressing MC38 syngeneic mouse models. When T-cell engagers were used to provide synthetic signal 1, the combination with NI-3201 resulted in synergistic T cell-dependent cytotoxicity and potent antitumor activity in two humanized mouse tumor models. Nonhuman primate safety assessments showed favorable tolerability and pharmacokinetics at pharmacologically active doses. Quantitative systems pharmacology modeling predicted that NI-3201 exposure results in antitumor activity in patients, but this remains to be investigated. Overall, this study suggests that by combining PD-L1 blockade with safe and effective CD28 co-stimulation, NI-3201 has the potential to improve cancer immunotherapy outcomes, and the clinical development of NI-3201 for PD-L1+ solid tumors is planned.

Neuroprotection by chronic administration of Fluoroethylnormemantine (FENM) in mouse models of Alzheimer's disease

BackgroundFluoroethylnormemantine (FENM), a new Memantine (MEM) derivative, prevented amyloid-β[25–35] peptide (Aβ25–35)-induced neurotoxicity in mice, a pharmacological model of Alzheimer's disease (AD) with high predictive value for drug discovery. Here, as drug infusion is likely to better reflect drug bioavailability due to the interspecies pharmacokinetics variation, we analyzed the efficacy of FENM after chronic subcutaneous (SC) infusion, in comparison with IP injections in two AD mouse models, Aβ25–35-injected mice and the transgenic APPswe/PSEN1∂E9 (APP/PS1) line.MethodsIn Aβ25–35-treated mice, FENM was infused at 0.03–0.3 mg/kg/day during one week after Aβ25–35 injection. For comparison, FENM and MEM were administered IP daily at 0.03–0.3 mg/kg. In 10-month-old APP/PS1 mice, FENM was administered during four weeks by daily IP injections at 0.3 mg/kg or chronic SC infusion at 0.1 mg/kg/day. Memory deficits, spatial working memory and recognition memory, were analysed. Markers of neuroinflammation, apoptosis, oxidative stress, and amyloid burden in APP/PS1 mice, were quantified. Markers of synaptic plasticity such as PSD-95 and GluN2A/B/D subunits expression in hippocampus homogenates or synaptosomes were quantified in Aβ25–35-treated mice and synaptic long-term potentiation (LTP) in hippocampal slices was analysed in APP/PS1 mice.ResultsDeficits in spontaneous alternation and object recognition in Aβ25–35 mice were prevented by infused FENM at all doses tested. Similar effects were observed with the daily FENM or MEM treatments. Animals infused with 0.1 mg/kg/day FENM showed prevention of Aβ25–35-induced neuroinflammation, oxidative stress and apoptosis. FENM infusion restored Aβ25–35-induced alterations in synaptosomal PSD-95, GluN2A and P-GluN2B levels. GluN2D levels were unchanged whatever the treatment. In APP/PS1 mice, FENM infused or administered IP alleviated spontaneous alternation deficits, neuroinflammation, increases in Aβ1-40/Aβ1-42 and hippocampal LTP alteration.ConclusionThese data confirmed the neuroprotective potential of FENM in the pharmacological Aβ25–35 and transgenic APP/PS1 mouse models of AD, with a superiority to MEM, and showed that the drug can be efficiently infused chronically.

Exploring the efficacy of Wenshentiaojing decoction in PCOS: Network pharmacology and mouse model insights.

Wenshentiaojing Decoction (WSTJD), a traditional Chinese herbal prescription, was first recorded in the "Ye Tianshi female department secret recipe for diagnosis and treatment ". It has been proven effective in treating polycystic ovary syndrome (PCOS). However, the active ingredients and molecular mechanism of WSTJD against PCOS remain unclear. To explore the therapeutic effect and molecular mechanism of WSTJD against PCOS by using network pharmacology and mouse model. Network pharmacology were used to predict active ingredients, potential targets, and pathways of WSTJD against PCOS. Female mice were injected subcutaneously with DHEA (6mg/100g body weight) daily to establish a PCOS model and administered with WSTJD and quercetin to observe its therapeutic effect. Thereafter, mouse phenotypes, indicators related to oxidative stress and ferroptosis, and hub genes were determined. We identified 144 potential targets for WSTJD in the treatment of PCOS, which were enriched in immune-related signaling pathways such as reactive oxygen species, TNF and IL-17 signaling pathway. Thirteen hub genes were identified by proteinprotein interaction network (PPI) and algorithmic analysis, all of which were oxidative stress-related genes, and five of which, IL6, PTGS2, HIF1A, MTOR and EGFR, were ferroptosis-related genes. Further analysis revealed that quercetin was a key ingredient for WSTJD and that it had superior binding effects with the hub genes. Moreover, WSTJD and quercetin could significantly depress oxidative stress-related indicators and ferroptosis-related gene expression in PCOS mice. Finally, mouse models showed that the expression of the hub genes were consistent with the analysis results. WSTJD and quercetin alleviated PCOS by suppressing oxidative stress and ferroptosis. Quercetin was the key ingredient for WSTJD against PCOS.

Network Pharmacology Combined with Animal Models to Investigate the Mechanism of ChangPu YuJin Tang in the Treatment of Tourette Syndrome.

ChangPu YuJin Tang (CPYJT) is a Chinese herbal formula that has been shown to be an effective therapeutic strategy for pediatric patients with Tourette Syndrome (TS). Using an integrated strategy of network pharmacology and animal model, the aim of this study was to investigate the mechanism of CPYJT in the treatment of TS. Compound libraries of CPYJT were established using databases, such as the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). The TCMSP database and Swiss Target Prediction database were used to predict the targets. The above results were constructed into a CPYJT-Drug-Component-Target network. Moreover, TS targets were predicted using GeneCards and other databases. The targets corresponding to the potential ingredients in CPYJT and the targets corresponding to TS were taken as the intersections to construct the CPYJT-TS network. The target network was analysed by PPI using the string database. GO and KEGG enrichment analyses were performed on the target network. The whole process was performed using Cytoscape 3.7.2 to make visual network diagrams of the results. CPYJT was characterised by Ultra-Performance Liquid Chromatography-Tandem Mass Spectrometry (UHPLC-MS). Transmission Electron Microscopy (TEM) was used to observe the structural changes of CPYJT on the neuronal cells of the IDPN model rats. RT-PCR and Western Blot were used to analyse the changes in the mRNA and protein expression levels of BDNF, TrkB, PI3K, and AKT in the cortex, striatum, and thalamus brain regions after CPYJT administration in IDPN model rats. Network pharmacology and UHPLC-MS studies revealed that CPYJT acted on the TS through multiple neurotransmitters and the BDNF/TrkB and PI3K/AKT signalling pathways. CPYJT ameliorated neurocellular structural damage in the cortex, striatum, and thalamus of TS model rats. Additionally, CPYJT up-regulated the levels of BDNF, TrkB, PI3k, and AKT in the cortex, striatum, and thalamus of TS model rats. It was found that CPYJT protected neuronal cells from structural damage in multiple brain regions and affected the expression levels of BDNF, TrkB, PI3K, and Akt in the cortex, striatum, and thalamus during TS treatment.

Modulation of Angiogenesis through Endogenous Leptin Signalling: Network Pharmacology and Resonant Recognition Model Approaches in Cardiovascular Therapy.

Modulation of Angiogenesis through Endogenous Leptin Signalling: Network Pharmacology and Resonant Recognition Model Approaches in Cardiovascular Therapy.

Quantitative Systems Pharmacology Modeling in Immuno-Oncology: Hypothesis Testing, Dose Optimization, and Efficacy Prediction.

Despite an increasing number of clinical trials, cancer is one of the leading causes of death worldwide in the past decade. Among all complex diseases, clinical trials in oncology have among the lowest success rates, in part due to the high intra- and inter-tumoral heterogeneity. There are more than a thousand cancer drugs and treatment combinations being investigated in ongoing clinical trials for various cancer subtypes, germline mutations, metastasis, etc. Particularly, treatments relying on the (re)activation of the immune system have become increasingly present in the clinical trial pipeline. However, the complexities of the immune response and cancer-immune interactions pose a challenge to the development of these therapies. Quantitative systems pharmacology (QSP), as a computational approach to predict tumor response to treatments of interest, can be used to conduct in silico clinical trials with virtual patients (and emergent use of digital twins) in place of real patients, thus lowering the time and cost of clinical trials. In line with improved mechanistic understanding of the human immune system and promising results from recent cancer immunotherapy, QSP models can play critical roles in model-informed drug development in immuno-oncology. In this chapter, we discuss how QSP models were designed to serve different study objectives, including hypothesis testing, dose optimization, and efficacy prediction, via case studies in immuno-oncology.

QSP modeling of a transiently inactivating antibody-drug conjugate highlights benefit of short antibody half life

Antibody drug conjugates (ADC) are a promising class of oncology therapeutics consisting of an antibody conjugated to a payload via a linker. DYP688 is a novel ADC comprising of a signaling protein inhibitor payload (FR900359) that undergoes unique on-antibody inactivation in plasma, resulting in complex pharmacology. To assess the impact of FR inactivation on DYP688 pharmacology and clinical developability, we performed translational modeling of preclinical PK and tumor growth inhibition (TGI) data, accompanied by mechanistic Krogh cylinder tumor modeling. Using a PK-TGI model, we identified a composite exposure-above-tumorostatic concentration (AUCTSC) metric as the PK-driver of efficacy. To underpin the mechanisms behind AUCTSC as the driver of efficacy, we performed quantitative systems pharmacology (QSP) modeling of DYP688 intratumoral pharmacokinetics and pharmacodynamics. Through exploratory simulations, we show that by deviating from canonical ADC design dogma, DYP688 has optimal FR900359 activity despite its transient inactivation. Finally, we performed the successful preclinical to clinical translation of DYP688 PK, including the payload inactivation kinetics, evidenced by good agreement of the predicted PK to the observed interim clinical PK. Overall, this work highlights early quantitative pharmacokinetics as a missing link in the ADC design-developability chasm.

Application of Quantitative Systems Pharmacology Approaches to Support Pediatric Labeling in Rare Diseases.

Quantitative Systems Pharmacology (QSP) models offer a promising approach to extrapolate drug efficacy across different patient populations, particularly in rare diseases. Unlike conventional empirical models, QSP models can provide a mechanistic understanding of disease progression and therapeutic response by incorporating current disease knowledge into the descriptions of biomarkers and clinical endpoints. This allows for a holistic representation of the disease and drug response. The mechanistic nature of QSP models is well suited to pediatric extrapolation concepts, providing a quantitative method to assess disease and drug response similarity between adults and pediatric patients. The application of a QSP-based assessment of the disease and drug similarity in adult and pediatric patients in the clinical development program of olipudase alfa, a treatment for Acid Sphingomyelinase Deficiency (ASMD), illustrates the potential of this approach.