Dose-Response-Time Data Analysis: An Underexploited Trinity

In Vitro Inhibition of Endoplasmic Reticulum Stress: A Promising Therapeutic Strategy for Patients with Crohn's Disease

BACKGROUND

Crohn's disease (CD) is an inflammatory bowel disease marked by an abnormal immune response and excessive pro-inflammatory cytokines, leading to impaired protein processing and endoplasmic reticulum (ER) stress. This stress, caused by the accumulation of misfolded proteins, triggers the unfolded protein response (UPR) through IRE1/Xbp-1, PERK/eIF2α, and ATF6 pathways, which are linked to intestinal inflammation. This study aimed to investigate ER stress in CD patients' intestinal mucosa and evaluate phenylbutyrate (PBA) as an ER stress inhibitor.

METHODS

Colon biopsies from CD patients and controls were cultured under five conditions, including 4-PBA treatments. Real-time PCR, cytokine level, and immunohistochemistry were performed.

RESULTS

Immunohistochemistry revealed that ER stress was activated in CD patients' intestinal epithelial cells and lamina propria cells. PERK/eIF2α, but not IRE1/Xbp-1 or ATF6, was upregulated in CD patients compared to controls. UPR-related genes (STC2, CALR, HSPA5, HSP90B1) were also elevated in CD patients. PBA treatment significantly reduced ER stress and UPR markers while decreasing apoptotic markers like DDIT3. Pro-inflammatory cytokines, such as IL-1β, IL-6, IL-17, TNF- α, and sCD40L, were significantly reduced after PBA treatment.

CONCLUSION

ER stress and UPR pathways are activated in CD colonic mucosa, and PBA reduces these markers, suggesting potential therapeutic benefits for CD-related inflammation.

Dynamic changes in human brain connectivity following ultrasound neuromodulation

Non-invasive neuromodulation represents a major opportunity for brain interventions, and transcranial focused ultrasound (FUS) is one of the most promising approaches. However, some challenges prevent the community from fully understanding its outcomes. We aimed to address one of them and unravel the temporal dynamics of FUS effects in humans. Twenty-two healthy volunteers participated in the study. Eleven received FUS in the right inferior frontal cortex while the other 11 were stimulated in the right thalamus. Using a temporal dynamic approach, we compared resting-state fMRI seed-based functional connectivity obtained before and after FUS. We also assessed behavioural changes as measured with a task of reactive motor inhibition. Our findings reveal that the effects of FUS are predominantly time-constrained and spatially distributed in brain regions functionally connected with the directly stimulated area. In addition, mediation analysis highlighted that FUS applied in the right inferior cortex was associated with behavioural alterations which was directly explained by the applied acoustic pressure and the brain functional connectivity change we observed. Our study underscored that the biological effects of FUS are indicative of behavioural changes observed more than an hour following stimulation and are directly related to the applied acoustic pressure.

Orosomucoid 2 is an endogenous regulator of neuronal mitochondrial biogenesis and promotes functional recovery post-stroke

Development of functional recovery therapies is critical to reduce the global impact of stroke as the leading cause of long-term disability. Our previous studies found that acute-phase protein orosomucoid (ORM) could provide an up to 6 h therapeutic time window to reduce infarct volume in acute ischemic stroke by improving endothelial function. However, its role in neurons and functional recovery post-stroke remains largely unknown. Here, we showed that exogenous ORM administration with initial injection at 0.5 h (early) or 12 h (delayed) post-MCAO daily for consecutive 7 days significantly decreased infarct area, improved motor and cognitive functional recovery, and promoted mitochondrial biogenesis after MCAO. While neuron-specific knockout of ORM2, a dominant subtype of ORM in the brain, produced opposite effects which could be rescued by exogenous ORM. In vitro, exogenous ORM protected SH-SY5Y cells from OGD-induced damage and promoted mitochondrial biogenesis, while endogenous ORM2 deficiency worsened these processes. Mechanistically, inactivation of CCR5 or AMPK eliminated the protective effects of ORM on neuronal damage and mitochondrial biogenesis. Taken together, our findings demonstrate that ORM, mainly ORM2, is an endogenous regulator of neuronal mitochondrial biogenesis by activating CCR5/AMPK signaling pathway, and might act as a potential therapeutic target for the functional recovery post-stroke.

Ginsenoside Rg1 promotes fetal hemoglobin production in vitro: A potential therapeutic avenue for β-thalassemia

β-thalassemia, a globally prevalent genetic disorder, urgently requires innovative treatment options. Fetal hemoglobin (HbF) induction stands as a key therapeutic approach. This investigation focused on Ginsenoside Rg1 from the Panax genus for HbF induction. Employing K562 cells and human erythroid precursor cells (ErPCs) derived from neonatal cord blood, the study tested Rg1 at different concentrations. We measured its effects on γ-globin mRNA levels and HbF expression, alongside assessments of cell proliferation and differentiation. In K562 cells, Rg1 at 400 μM significantly increased γ-globin mRNA expression by 4.24 ± 1.08-fold compared to the control. In ErPCs, the 800 μM concentration was most effective, leading to an over 80% increase in F-cells and a marked upregulation in HbF expression. Notably, Rg1 did not adversely affect cell proliferation or differentiation, with the 200 μM concentration showing an increase in γ-globin mRNA by 2.33 ± 0.58-fold, and the 800 μM concentration enhancing HbF expression by 2.59 ± 0.03-fold in K562 cells. Our results underscore Rg1's potential as an effective and safer alternative for β-thalassemia treatment. By significantly enhancing HbF levels without cytotoxicity, Rg1 offers a notable advantage over traditional treatments like Hydroxyurea. While promising, these in vitro findings warrant further in vivo exploration to confirm Rg1's therapeutic efficacy and to unravel its underlying mechanistic pathways.

In vitro PK/PD modeling of tyrosine kinase inhibitors in non-small cell lung cancer cell lines

Tyrosine kinase inhibitors (TKIs) are routinely prescribed for the treatment of non-small cell lung cancer (NSCLC). As with all medications, patients can experience adverse events due to TKIs. Unfortunately, the relationship between many TKIs and the occurrence of certain adverse events remains unclear. There are limited in vivo studies which focus on TKIs and their effects on different regulation pathways. Many in vitro studies, however, that investigate the effects of TKIs observe additional changes, such as changes in gene activations or protein expressions. These studies could potentially help to gain greater understanding of the mechanisms for TKI induced adverse events. However, in order to utilize these pathways in a pharmacokinetic/pharmacodynamic (PK/PD) framework, an in vitro PK/PD model needs to be developed, in order to characterize the effects of TKIs in NSCLC cell lines. Through the use of ordinary differential equations, cell viability data and nonlinear mixed effects modeling, an in vitro TKI PK/PD model was developed with estimated PK and PD parameter values for the TKIs alectinib, crizotinib, erlotinib, and gefitinib. The relative standard errors for the population parameters are all less than 25%. The inclusion of random effects enabled the model to predict individual parameter values which provided a closer fit to the observed response. It is hoped that this model can be extended to include in vitro data of certain pathways that may potentially be linked with adverse events and provide a better understanding of TKI-induced adverse events.

Skipping a pillar does not make for strong foundations: Pharmacokinetic-pharmacodynamic reasoning behind the shape of dose-response relationships in oncology

Dose-response analysis is often applied to the quantification of drug-effect especially for slowly responding disease end points where a comparison is made across dose levels after a particular period of treatment. It has long been recognized that exposure - response is more appropriate than dose-response. However, trials necessarily are designed as dose-response experiments. Second, a wide range of functional forms are used to express relationships between dose and response. These considerations are also important for clinical development because pharmacokinetic (PK; and variability) plus pharmacokinetic-pharmacodynamic modeling may allow one to anticipate the shape of the dose-response curve and so the trial design. Here, we describe how the location and steepness of the dose response is determined by the PKs of the compound being tested and its exposure-response relationship in terms of potency (location), efficacy (maximum effect) and Hill coefficient (steepness). Thus, the location (50% effective dose [ED50 ]) is dependent not only on the potency (half-maximal effective concentration) but also the compound's PKs. Similarly, the steepness of the dose response is shown to be a function of the half-life of the drug. It is also shown that the shape of relationship varies dependent on the assumed time course of the disease. This is important in the context of drug-discovery where the in vivo potencies of compounds are compared as well as when considering an analysis of summary data (for example, model-based meta-analysis) for clinical decision making.

Generative modeling of single-cell gene expression for dose-dependent chemical perturbations

Single-cell sequencing reveals the heterogeneity of cellular response to chemical perturbations. However, testing all relevant combinations of cell types, chemicals, and doses is a daunting task. A deep generative learning formalism called variational autoencoders (VAEs) has been effective in predicting single-cell gene expression perturbations for single doses. Here, we introduce single-cell variational inference of dose-response (scVIDR), a VAE-based model that predicts both single-dose and multiple-dose cellular responses better than existing models. We show that scVIDR can predict dose-dependent gene expression across mouse hepatocytes, human blood cells, and cancer cell lines. We biologically interpret the latent space of scVIDR using a regression model and use scVIDR to order individual cells based on their sensitivity to chemical perturbation by assigning each cell a "pseudo-dose" value. We envision that scVIDR can help reduce the need for repeated animal testing across tissues, chemicals, and doses.

Turn On, Tune In, Turnover! Target Biology Impacts In Vivo Potency, Efficacy, and Clearance

Even though significant efforts have been spent in recent years to understand and define the determinants of in vivo potency and clearance, important pieces of information are still lacking. By introducing target turnover into the reasoning, we open up to further the understanding of central factors important to the optimization of translational dose-concentration-response predictions. We describe (i) new (open model) expressions of the in vivo potency and efficacy parameters, which embody target turnover, binding, and complex kinetics, also capturing full, partial, and inverse agonism and antagonism; (ii) a detailed examination of open models to show what potency and efficacy parameters have in common and how they differ; and (iii) a comprehensive literature review showing that target turnover rate varies with age, species, tissue/subregion, treatment, disease state, hormonal and nutritional state, and day-night cycle. The new open model expression, which integrates system and drug properties, shows the following. Fractional turnover rates rather than the absolute target or ligand-target complex expression determine necessary drug exposure via in vivo potency. Absolute ligand-target expression determines the need of a drug, based on the transduction ρ and in vivo efficacy parameters. The free enzyme concentration determines clearance and maximum metabolic rate. The fractional turnover rate determines time to equilibrium between substrate, free enzyme, and complex.The properties of substrate, target, and the complex demonstrate nonsaturable metabolic behavior at equilibrium. Nonlinear processes, previously referred to as capacity- and time-dependent kinetics, may occasionally have been disequilibria. Finally, the open model may pinpoint why some subjects differ in their demand of drug. SIGNIFICANCE STATEMENT: Understanding the target turnover is a central tenet in many translational dose-concentration-response predictions. New open model expressions of in vivo potency, efficacy parameter, and clearance are derived and anchored onto a comprehensive literature review showing that target turnover rate varies with age, species, tissue/subregion, treatment, disease, hormonal and nutritional state, day-night cycle, and more. Target turnover concepts will therefore significantly impact fundamental aspects of pharmacodynamics and pharmacokinetics, thereby also the basics of drug discovery, development, and optimization of clinical dosing.

Hydrocinnamic Acid and Perillyl Alcohol Potentiate the Action of Antibiotics against Escherichia coli

The treatment of bacterial infections has been troubled by the increased resistance to antibiotics, instigating the search for new antimicrobial therapies. Phytochemicals have demonstrated broad-spectrum and effective antibacterial effects as well as antibiotic resistance-modifying activity. In this study, perillyl alcohol and hydrocinnamic acid were characterized for their antimicrobial action against Escherichia coli. Furthermore, dual and triple combinations of these molecules with the antibiotics chloramphenicol and amoxicillin were investigated for the first time. Perillyl alcohol had a minimum inhibitory concentration (MIC) of 256 µg/mL and a minimum bactericidal concentration (MBC) of 512 µg/mL. Hydrocinnamic acid had a MIC of 2048 µg/mL and an MBC > 2048 µg/mL. Checkerboard and time-kill assays demonstrated synergism or additive effects for the dual combinations chloramphenicol/perillyl alcohol, chloramphenicol/hydrocinnamic acid, and amoxicillin/hydrocinnamic acid at low concentrations of both molecules. Combenefit analysis showed synergism for various concentrations of amoxicillin with each phytochemical. Combinations of chloramphenicol with perillyl alcohol and hydrocinnamic acid revealed synergism mainly at low concentrations of antibiotics (up to 2 μg/mL of chloramphenicol with perillyl alcohol; 0.5 μg/mL of chloramphenicol with hydrocinnamic acid). The results highlight the potential of combinatorial therapies for microbial growth control, where phytochemicals can play an important role as potentiators or resistance-modifying agents.

Examining the efficacy of localised gemcitabine therapy for the treatment of pancreatic cancer using a hybrid agent-based model

The prognosis for pancreatic ductal adenocarcinoma (PDAC) patients has not significantly improved in the past 3 decades, highlighting the need for more effective treatment approaches. Poor patient outcomes and lack of response to therapy can be attributed, in part, to a lack of uptake of perfusion of systemically administered chemotherapeutic drugs into the tumour. Wet-spun alginate fibres loaded with the chemotherapeutic agent gemcitabine have been developed as a potential tool for overcoming the barriers in delivery of systemically administrated drugs to the PDAC tumour microenvironment by delivering high concentrations of drug to the tumour directly over an extended period. While exciting, the practicality, safety, and effectiveness of these devices in a clinical setting requires further investigation. Furthermore, an in-depth assessment of the drug-release rate from these devices needs to be undertaken to determine whether an optimal release profile exists. Using a hybrid computational model (agent-based model and partial differential equation system), we developed a simulation of pancreatic tumour growth and response to treatment with gemcitabine loaded alginate fibres. The model was calibrated using in vitro and in vivo data and simulated using a finite volume method discretisation. We then used the model to compare different intratumoural implantation protocols and gemcitabine-release rates. In our model, the primary driver of pancreatic tumour growth was the rate of tumour cell division. We were able to demonstrate that intratumoural placement of gemcitabine loaded fibres was more effective than peritumoural placement. Additionally, we quantified the efficacy of different release profiles from the implanted fibres that have not yet been tested experimentally. Altogether, the model developed here is a tool that can be used to investigate other drug delivery devices to improve the arsenal of treatments available for PDAC and other difficult-to-treat cancers in the future.

Pharmacokinetic and Pharmacodynamic Modeling of siRNA Therapeutics - a Minireview

The approval of four small interfering RNA (siRNA) products in the past few years has demonstrated unequivocally the therapeutic potential of this novel modality. Three such products (givosiran, lumasiran and inclisiran) are liver-targeted, using tris N-acetylgalactosamine (GalNAc)₃ as the targeting ligand. Upon subcutaneous administration, GalNAc-conjugated siRNAs rapidly distribute into the liver via asialoglycoprotein receptor (ASGPR) mediated uptake in the hepatocytes, resulting in fast elimination from the systemic circulation. Patisiran, on the other hand, has been formulated in a lipid nanoparticle for optimal delivery to the liver. While several publications have described preclinical and clinical pharmacokinetic (PK) and pharmacodynamic (PD) results, including absorption, distribution, metabolism, and elimination (ADME) profiles in selected species as well as limited modeling efforts for siRNA therapeutics, there is no systematic review of the PK and PD models developed for these agents or work summarizing the utility and application(s) of such models in drug development and regulatory review. Here, we provide a mini-review of the current state of modeling efforts for siRNA therapeutics within the early preclinical, translational, and clinical stages of siRNA development. Diverse modeling methods including simple compartmental, mechanistic and systems PK/PD, physiologically-based PK (PBPK), population PK/PD, and dose-response-time models are introduced and reviewed. The utility of such models in development and regulatory review for siRNA therapeutics is also discussed with examples. Finally, the current knowledge gaps in mechanism of action of siRNA and resulting challenges in model development are summarized. The goal of this minireview is to trigger cross-functional discussion amongst all key stakeholders to generate key experimental datasets and align on current assumptions, model structures, and approaches to facilitate development and application of robust PK/PD models for siRNA therapeutics.

In silico and in vitro screening for potential anticancer candidates targeting GPR120

The G-protein coupled receptor - GPR120 has recently been implicated as a novel target for colorectal cancer (CRC) and other cancer managements. In this study, a homology model of GPR120S (short isoform) was generated to identify potential anti-cancer compounds targeting the GPR120 receptor using a combined in silico docking-based virtual screening (DBVS), structure-activity relationships (SAR) and in vitro screening approach. SPECS database of synthetic chemical compounds (~350,000) was screened using the developed GPR120S model to identify molecules binding to the orthosteric binding pocket followed by an AutoDock SMINA rigid-flexible docking protocol. The best 13 hit molecules were then tested in vitro to evaluate their cytotoxic activity against SW480 - human CRC cell line expressing GPR120. The test compound 1 (3-​(4-​methylphenyl)​-​2-​[(2-​oxo-​2-​phenylethyl)​sulfanyl]​-​5,6-​dihydrospiro(benzo[h]​quinazoline-​5,1'-​cyclopentane)​-​4(3H)​-​one) showed ~ 90% inhibitory effects on cell growth with micromolar affinities (IC₅₀ = 23.21-26.69 µM). Finally, SAR analysis of compound 1 led to the identification of a more active compound from the SPECS database showing better efficacy during cell-based cytotoxicity assay -5 (IC₅₀ = 5.89-6.715 µM), while a significant reduction in cytotoxic effects of 5 was observed in GPR120-siRNA pre-treated SW480 cells. The GPR120S homology model generated, and SAR analysis conducted by this work discovered a potential chemical scaffold, dihydrospiro(benzo[h]quinazoline-5,1'-cyclopentane)-4(3H)-one, which will aid future research on anti-cancer drug development for CRC management.

Controlled coupling of an ultrapotent auristatin warhead to cetuximab yields a next-generation antibody-drug conjugate for EGFR-targeted therapy of KRAS mutant pancreatic cancer

BACKGROUND

Antibody-drug conjugate (ADC) construction poses numerous challenges that limit clinical progress. In particular, common bioconjugation methods afford minimal control over the site of drug coupling to antibodies. Here, such difficulties are overcome through re-bridging of the inter-chain disulfides of cetuximab (CTX) with auristatin-bearing pyridazinediones, to yield a highly refined anti-epidermal growth factor receptor (EGFR) ADC.

METHODS

In vitro and in vivo assessment of ADC activity was performed in KRAS mutant pancreatic cancer (PaCa) models with known resistance to CTX therapy. Computational modelling was employed for quantitative prediction of tumour response to various ADC dosing regimens.

RESULTS

Site-selective coupling of an auristatin to CTX yielded an ADC with an average drug:antibody ratio (DAR) of 3.9, which elicited concentration- and EGFR-dependent cytotoxicity at sub-nanomolar potency in vitro. In human xenografts, the ADC inhibited tumour growth and prolonged survival, with no overt signs of toxicity. Key insights into factors governing ADC efficacy were obtained through a robust mathematical framework, including target-mediated dispositional effects relating to antigen density on tumour cells.

CONCLUSIONS

Together, our findings offer renewed hope for CTX in PaCa therapy, demonstrating that it may be reformatted as a next-generation ADC and combined with a predictive modelling tool to guide successful translation.