Category: 3. Business

Zscaler, Inc. (NASDAQ: ZS), the leader in cloud security, today announced it has acquired innovative AI security pioneer SPLX, extending the Zscaler Zero Trust Exchange^TM platform with shift-left AI asset discovery, automated red teaming, and governance, so organizations can secure their AI investments from development through deployment. 

“Today marks an important step in advancing Zscaler’s role as the trusted partner helping organizations securely adopt AI,” said Jay Chaudhry, CEO, Chairman, and Founder of Zscaler. “AI is creating enormous value, but its full potential can only be realized when it can be secured. By combining SPLX’s technology with the intelligence of the Zscaler Zero Trust Exchange and its native data protection that classifies, governs, and prevents loss of sensitive data across prompts, models, and outputs, Zscaler will secure the entire AI lifecycle on one platform. This will strengthen our industry leadership and give customers the confidence to safely embrace AI.”

As AI drives record infrastructure investments projected to exceed $250 billion by end of 2025¹, organizations face a rapidly expanding attack surface and shadow AI sprawl. Continuously evolving models, agents, and large language models (LLMs) require ongoing discovery, risk assessment, and remediation, while AI agents and Model Context Protocol (MCP) servers demand strict guardrails and new techniques to secure data and AI assets across the lifecycle.

SPLX’s innovative technology and deep expertise in AI red teaming, asset management, threat inspection, prompt hardening and governance will expand Zscaler’s current capabilities, creating a new, dedicated and natively integrated layer of AI protection within the Zscaler Zero Trust Exchange platform, that includes: 

• AI Asset Discovery and Risk Assessment: Discovery extends beyond public generative AI applications and public clouds to include AI models, workflows, code repositories and RAGs and MCP servers in both public and private deployments.
   
• Automated AI Red Teaming and Remediation: From development to production, with 5,000+ purpose-built and domain specific attack simulations to find risks and vulnerabilities, and offer remediation in real time. 
   
• AI Runtime Guardrails and Prompt Hardening: Expands Zscaler’s current AI Runtime Guardrails that protect sensitive data and block malicious attacks between AI apps and LLMs, as well as agentic workflows, to include deep visibility within development environments and automate Guardrails for risky AI assets.
   
• AI Governance and Compliance: Risk mitigation and support for organizations to shift from reactive defense to proactive protection for their valuable AI investments, and comply with governance frameworks. 

“Zscaler and SPLX share a vision to confront the vast new attack surface created by rapidly expanding AI infrastructure investments,” said Kristian Kamber, CEO and co-founder of SPLX. “By joining forces, we’ll bring our innovation to one of the most trusted security platforms in the world, securing AI innovation at the speed organizations are adopting it.” 

Source: 1) Goldman Sachs, “Technology in 2025: The Cycle Rolls On” February 2, 2025

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Forward-Looking Statements

This press release contains forward-looking statements that are based on our management’s beliefs and assumptions and on information currently available to our management. These forward-looking statements include the expected benefits of the proposed acquisition to Zscaler and its customers and plans regarding SPLX’s capabilities. These forward-looking statements are subject to the safe harbor provisions created by the Private Securities Litigation Reform Act of 1995. A significant number of factors could cause actual results to differ materially from statements made in this press release, including those factors related to Zscaler’s ability to successfully integrate SPLX technology into our cloud platform, the potential impact of the acquisition to the existing SPLX business and the retention of SPLX employees. Additional risks and uncertainties are set forth in our most recent Annual Report on Form 10-K filed with the Securities and Exchange Commission (“SEC”) on September 11, 2025, which is available on our website at ir.zscaler.com and on the SEC’s website at www.sec.gov. Any forward-looking statements in this release are based on the limited information currently available to Zscaler as of the date hereof, which is subject to change, and Zscaler will not necessarily update the information, even if new information becomes available in the future.

Expanded collaboration makes Falcon Next-Gen SIEM the foundation of EY global cyber managed services for security and non-security data, accelerating AI-driven security transformation for clients

AUSTIN, Texas – November 3, 2025 – CrowdStrike (NASDAQ: CRWD) and Ernst & Young LLP (EY US) today announced that EY US has selected CrowdStrike Falcon® Next-Gen SIEM as the foundational platform powering its global cybersecurity managed services. With Falcon Next-Gen SIEM and EY US managed services experience, enterprises worldwide can accelerate the move beyond legacy security information and event management (SIEM) and modernize security operations at scale.

Adversaries are moving at the speed of AI, scaling attacks faster than defenders can respond. Legacy SIEM, built for a different era, is too slow, noisy, and costly to stop today’s threats. Falcon Next-Gen SIEM delivers real-time speed, efficiency, and outcomes legacy platforms can’t match – and will be further strengthened by CrowdStrike’s acquisition of Onum, a real-time data pipeline platform. 

By standardizing its global managed services on Falcon Next-Gen SIEM for security and non-security data, EY will equip clients with AI-powered protection that moves faster and sees more, enabling organizations to replace outdated SIEM with a modern platform that delivers measurable outcomes at scale.

“The agentic era is accelerating everything, and legacy SIEMs simply can’t cope with threat landscape realities as well as enterprise data proliferation,” said Daniel Bernard, chief business officer at CrowdStrike. “By making Falcon Next-Gen SIEM the foundation of EY US global managed services, we’re helping clients modernize faster and achieve outcomes legacy tools could never deliver.”

Key improvements for clients include:

• Accelerated Migration: EY US professionals will help enterprises move from legacy SIEM to Falcon Next-Gen SIEM, achieving substantial efficiencies and up to 150% faster search.
• AI-Powered, Adversary-Driven Protection: Falcon Next-Gen SIEM unifies CrowdStrike first- and third-party platform data with real-time threat intelligence and AI-powered automation, delivering enterprise-wide visibility and supercharging detection and response.
• Next-Generation Operating Model: EY Managed Services helps clients turn data into a competitive edge by reducing operational burden, increasing cost certainty, accelerating AI adoption, and building smarter operating models that lower risk and unlock strategic value.
• Global Security Operations Center (SOC): The experience of EY US in SOC helps clients strengthen cyber and operational resilience by reducing attack surface exposure, securing digital identity, and managing cybersecurity risks with 24/7 advanced defense across 160 countries.
• Unified Visibility and Scale: CrowdStrike consolidates data into a single platform, delivering complete visibility and massive scale without the cost and complexity of legacy solutions.

“Our clients need security that’s faster, simpler and more effective,” said Tapan Shah, EY Global and Americas Cybersecurity Managed Services Leader. “With EY US as the first mover in building our cyber managed services on Falcon Next-Gen SIEM, we see this as more than a technology upgrade – it’s a strategic move to embrace AI security operations. EY US teams bring deep sector and AI experience, delivering high-impact cybersecurity outcomes that improve operations and efficiency across the enterprise.” 

About EY

EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets.

Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow.

EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multidisciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.

All in to shape the future with confidence.

EY refers to the global organization, and may refer to one or more, of the member firms of Ernst & Young Global Limited, each of which is a separate legal entity. Ernst & Young Global Limited, a UK company limited by guarantee, does not provide services to clients. Information about how EY collects and uses personal data and a description of the rights individuals have under data protection legislation are available via ey.com/privacy. EY member firms do not practice law where prohibited by local laws. For more information about our organization, please visit ey.com.

Ernst & Young LLP is a client-serving member firm of Ernst & Young Global Limited operating in the US.

About CrowdStrike

CrowdStrike (NASDAQ: CRWD), a global cybersecurity leader, has redefined modern security with the world’s most advanced cloud-native platform for protecting critical areas of enterprise risk – endpoints and cloud workloads, identity and data.

Powered by the CrowdStrike Security Cloud and world-class AI, the CrowdStrike Falcon® platform leverages real-time indicators of attack, threat intelligence, evolving adversary tradecraft and enriched telemetry from across the enterprise to deliver hyper-accurate detections, automated protection and remediation, elite threat hunting and prioritized observability of vulnerabilities.

Purpose-built in the cloud with a single lightweight-agent architecture, the Falcon platform delivers rapid and scalable deployment, superior protection and performance, reduced complexity and immediate time-to-value.

CrowdStrike: We stop breaches.

Learn more: https://www.crowdstrike.com/

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Cannabinoid receptor 1 (CB₁), which is majorly expressed in the central nervous system (CNS) belongs to the class A G-protein coupled receptor (GPCR) family proteins (Hua et al., 2016; Mackie, 2008; Zou and Kumar, 2018; Dutta and Shukla, 2023). GPCRs are expressed in the cellular membrane and help transduce chemical signals from the extracellular to the intracellular direction with the help of the downstream signaling proteins (G-proteins and β-arrestin) (Rosenbaum et al., 2009; Latorraca et al., 2017; Weis and Kobilka, 2018). In addition, GPCRs are the largest family of drug targets due to their substantial involvement in human pathophysiology and druggability (Hauser et al., 2017; Yang et al., 2021). Significant research efforts have been invested in the discovery of drugs targeting CB₁, which helps to maintain homeostasis in neuron signaling and physiological processes (Smith et al., 2010; An et al., 2020).

Initial drug discovery efforts, especially the design of synthetic agonists, were based on modifying the scaffolds of phytocannabinoids (e.g. ${\mathrm{\Delta }}^9$-Tetrahydrocannabinol, cannabinol) and endocannabinoids (e.g. Anandamide, 2-arachidonoylglycerol) (Figure 1; Pertwee, 2006; Pertwee and Ross, 2002; Pertwee et al., 2010). The synthetic molecules, which maintain the aromatic, pyran, and cyclohexenyl ring of the most common psychoactive phytocannabinoid ${\mathrm{\Delta }}^9$-THC, are known as classical cannabinoids (Figure 1—figure supplement 1; Razdan, 2009 Madras, 2018; Dutta et al., 2022a). However, the pharmacological potential of these molecules was diminished due to their psychological and physiological side effects (‘tetrad’ side effect) (Moore and Weerts, 2022; Wang et al., 2020; Tummino et al., 2023). One such example of a synthetic cannabinoid is 1,1-Dimethylheptyl-11-hydroxy-tetrahydrocannabinol (commonly known as HU-210), which is a Schedule I controlled substance in the United States (Farinha-Ferreira et al., 2022).

Apart from the canonical structures of synthetic cannabinoids, molecules with diverse scaffolds were also synthesized through structure-activity studies (Wiley et al., 2016; Schoeder et al., 2018; Walsh and Andersen, 2020). However, these molecules also lacked any pharmacological importance due to psychological side effects (Akram et al., 2019; Worob and Wenthur, 2020). Due to the diverse structures and psychological effects, these molecules became unregulated substitutes for traditional illicit substances (Peacock et al., 2019). These synthetic cannabinoids belong to a class of molecules known as NPS as these molecules are not scheduled under the Single Convention on Narcotic Drugs (1961) or the Convention on Psychotropic Substances (1971) (Peacock et al., 2019; Madras, 2016). Synthetic cannabinoids make up the largest category of NPS molecules (Shafi et al., 2020; Alam and Keating, 2020). NPS creates a significant challenge for drug enforcement agencies, as they appeal to drug users seeking ‘legal highs’ to avoid the legal consequences of using traditional drugs and to be undetectable in drug screenings (Worob and Wenthur, 2020).

The molecular structures of NPS synthetic cannabinoids consist of four pharmacophore components: linked, linker, core, and tail groups (Worob and Wenthur, 2020; Potts et al., 2020). The core usually consists of aromatic scaffolds (e.g. indole, indazole, carbazole, benzimidazole) (Figure 1—figure supplement 2; Schoeder et al., 2018). The tail and linker groups are connected to the core. In the tail group, long alkyl chain-like scaffolds are ubiquitous in most NPSs; however, molecules with bulkier cyclic chains (e.g. AB-CHMINACA) are also present (Potts et al., 2020). Frequently encountered scaffolds in linker groups are methanone, ethanone, carboxamide, and carboxylate ester groups (Hill et al., 2018). The linker acts as a bridge between the core and the linked group. In the initial NPS synthetic cannabinoids, the linked group included polyaromatic rings; however, non-cyclic linked groups have also been identified in NPS recently (Schoeder et al., 2018; Potts et al., 2020). Structural diversity in every component, while maintaining high binding affinity and potency for CB₁ make these molecules easier for drug manufacturers and harder to ban by drug enforcement agencies (Banister et al., 2015a; Ametovski et al., 2020; Cannaert et al., 2020; Banister et al., 2015b).

The use of NPS synthetic cannabinoids has been found to cause more physiological side effects than traditional cannabinergic ‘tetrad’ side effects (Tai and Fantegrossi, 2014). These side effects include tachycardia, drowsiness, dizziness, hypertension, seizures, convulsions, nausea, high blood pressure, and chest pain (Tai and Fantegrossi, 2014; Finlay et al., 2019). For instance, Gatch and Forster have shown that the high concentrations of AMB-FUBINACA, the molecule which caused ‘zombie outbreak’ in New York, induced tremors (Gatch and Forster, 2019; Adams et al., 2017). A recent biochemical study has linked these discriminatory effects with the differential signaling of β-arrestin (Finlay et al., 2019). According to Finlay et al., NPS shows higher β-arrestin signaling compared to the classical cannabinoids, which has also been confirmed by other β-arrestin signaling studies (Finlay et al., 2019; Grafinger et al., 2021). However, a mechanistic understanding of these differential downstream signaling effects between NPS and classical cannabinoids is still missing.

Mutagenesis studies have shown that the conserved NPxxY motif of CB₁ have a larger role in downstream β-arrestin signaling than G-protein signaling (Leo et al., 2023; Liao et al., 2023). Recently published MDMB-FUBINACA bound CB₁-β-arrestin-1 complex structure also points out the importance of the unique triad interaction (Y397^7.53-Y294^5.58-T210^3.46) involving NPxxY motif in β-arrestin-1 signaling (Liao et al., 2023). However, structural comparison of the classical cannabinoid (AM841) and NPS (MDMB-FUBINACA) bound active CB₁-G_i complex shows a conformationally similar NPxxY motif (Figure 2; Krishna Kumar et al., 2019; Hua et al., 2020). In light of these experimental observations, it can be inferred that higher β-arrestin signaling stems from higher dynamic propensity of triad interaction formation for NPS-bound CB₁. We hypothesized that distinct orthosteric pocket interactions for NPS and classical cannabinoids cause differential allosteric modulation of intracellular dynamics that facilitate triad interaction.

To study these distinct dynamic effects, we compared the (un)binding of the classical cannabinoid (HU-210) and NPS (MDMB-FUBINACA) from the receptor binding site. These molecules have nanomolar affinities. Obtaining the initial pathway of ligand unbinding from unbiased sampling will be computationally expensive. Therefore, a well-tempered metadynamics approach was used to sample the unbinding event, where a time-dependent biased potential is deposited for the faster sampling of the metastable minima along the pathway (Barducci et al., 2008). However, a detailed characterization of the unbinding processes is only possible through the thermodynamics and kinetics estimation of intermediate states. Thus, a transition operator-based approach is needed, which helps to estimate the transition timescale between the states and the stationary density of each state. Estimation from these approaches usually depends on the equilibrium between the local states, which can only be maintained by reversible sampling. For high-affinity ligands like MDMB-FUBINACA and HU-210, reversible sampling is expensive as ligands move from high energy unbound states to lower energy bound states irreversibly. Hence, we implemented a transition operator approach named the transition-based reweighting analysis (TRAM) method, which can tackle this lack of local equilibrium between states by combining unbiased and biased approaches (Wu et al., 2016). TRAM has been used in in different simulation studies for estimating thermodynamics and kinetics of processes that have high free energy barriers. For example, TRAM have been utilized for characterization of small molecule and peptide (un)binding processes (Wu et al., 2016; Paul et al., 2017; Ge et al., 2021; Spiriti et al., 2022; Ge and Voelz, 2022), protein dimerization (Meral et al., 2018), ion transportation (Hu et al., 2019). To implement TRAM for our study, extensive sampling of the (un)binding process of both ligands was performed using a combination of umbrella sampling and unbiased simulations from the pathway obtained using metadynamics (see Methods section) (Kästner, 2011). We showed that TRAM can produce consistent kinetic estimation with less unbiased simulation data compared to traditional methods like the Markov state model (Prinz et al., 2011).

Based on estimates of thermodynamics and kinetics, it was observed that both NPS and classical cannabinoids have similar unbinding pathways. However, their unbinding mechanisms differ due to the aromatic tail of the MDMB-FUBINACA compared to the alkyl side chain of HU-210. Furthermore, dynamic interaction calculations reveal a major difference with TM7 between NPS and classical cannabinoid. Specifically, the hydroxyl group in the benzopyran moiety of HU-210 forms much stronger polar interactions with S383^7.39 compared to the carbonyl oxygen of the linker group in MDMB-FUBINACA. MD simulations of other classical cannabinoids and NPS molecules bound to CB₁ also support these significant interaction differences. The ligand binding effect in intracellular signaling was estimated by measuring the probability of triad formation in the intracellular region. NPS-bound CB₁ shows higher probability of forming triad interaction compared to the classical cannabinoids, which supports the experimental observations of high $\beta$-arrestin signaling of NPS-bound receptors. To validate that the triad formation is indeed caused by the binding pocket interaction differences between the two ligands, allosteric strength binding pocket residues and NPxxY motif was estimated with the deep learning technique, Neural relational inference (NRI) (Zhu et al., 2022a). NRI network revealed that binding pocket residues of NPS-bound ensemble have higher allosteric weights for the NPxxY motif compared to classical cannabinoids. These analyses validate our hypothesis that the differential dynamic allosteric control of the NPxxY motif might lead to the $\beta$-arrestin signaling for different ligands. This study provides a foundation for additional computational and experimental research to enhance our understanding of the connection between ligand scaffolds and downstream signaling. This knowledge will assist drug enforcement agencies in proactively banning these molecules and inform policies that can protect individuals from the effects of abuse.

Introduction

Lung cancer is the second most common type of cancer in women and men, but it is the most important cause of cancer-related deaths.¹ Non-small-cell lung cancer (NSCLC) constitutes approximately 85% of all lung cancers.² Currently, immunotherapy is the main treatment modality for NSCLC cancer without driver mutation.³

Nivolumab is a human immunoglobulin G4 (IgG4) antibody targeting programmed death-1 (PD-1) receptors. It is an important treatment agent with demonstrated efficacy independent of PD-L1 score in chemotherapy-resistant NSCLC cancer without ALK, RET, or ROS1 mutations. In daily practice, a validated marker that will benefit from treatment in patients receiving Nivolumab has not yet been clearly established. In the Checkmate 227 and CheckMate 568 studies, ipilimumab, a CTLA-4 antibody, was found to be effective together with nivolumab in patients with advanced stage NSCLC patients with tumor mutation burden independent of PD-L1 score. Tumor Mutational Burden (TMB) is an important biomarker in predicting response to immunotherapy. Studies have shown that patients with a TMB greater than 10 mutations per megabase have the highest predicted objective response rate (ORR), reaching up to 38% to 42%, regardless of PD-L1 expression levels. However, despite its predictive value, TMB is not yet used as a standard test due to its high financial cost and the technical complexity of measurement.^4–6

In the inflammatory tumor microenvironment (TME), innate immune cells such as monocytes and adaptive immune cells (eg T lymphocytes) produce various inflammatory mediators in response to abnormal signals from the tumor, creating an inflammatory response.^7,8 In this process, neutrophils stand out as both effective elements of innate immunity and cellular messengers shaping the adaptive response. They not only suppress the tumor-killing activity of cytotoxic T lymphocytes (CTLs), but also trigger angiogenesis and support tumor progression by secreting numerous growth factors and chemokines, such as TGF-β, VEGF, IL-6, IL-8, IL-12, and matrix metalloproteinases. G-CSF secreted by tumor cells reinforces this tumor-supportive cycle by increasing the number of neutrophils.^9–12 Only 15–60% of patients can achieve the expected response with CTLA-4, PD-1 and PD-L1 inhibitors developed through activation of the immune system.¹³

In this study, we aimed to investigate the prognostic importance of inflammatory and nutritional markers along with clinical parameters on treatment response in metastatic NSCLC patients who received nivolumab treatment.

Materials and Methods

Patient Characteristics

In this multicenter study, data of metastatic non-small cell lung cancer (NSCLC) patients diagnosed and treated between February 2021 and November 2024 at three oncology centers (Ankara Etlik City Hospital, Nevşehir State Hospital, and Ankara Atatürk Sanatoryum Hospital) were retrospectively analyzed. Patients who had previously received 1 line of platinum-containing chemotherapy (cisplatin or carboplatin) and progressed and received second-line immunotherapy were included. (Figure 1) Patients with pathologically confirmed NSCLC who received at least 2 cycles of nivolumab treatment at the metastatic stage with 240 mg every 2 weeks or 360 mg every 3 weeks were included in the study. Patients who had another concurrent malignancy, had active infection findings, did not have driver mutations (EGFR, ALK, ROS1), and had pre-treatment blood parameters, were over 18 years of age, and had ECOG <2 before nivolumab treatment were included. PD-L1 expression was evaluated by immunohistochemical staining using the VENTANA PD-L1 (SP263) assay (Roche, Switzerland) on the BenchMark ULTRA automated staining platform. All procedures, including antigen retrieval and detection steps, were performed in accordance with the manufacturer’s protocol. The Common Terminology Criteria for Adverse Events Scoring System (CTCAE) v4.0 was used for the definition and evaluation of immune-related adverse events (irAEs). The study received approval from the local ethics board (Approval no: 2500043238 / 28.05.2025, Non-Interventional Ethics Committee of Nevsehir Haci Bektas Veli University).

Figure 1 CONSORT Flow Diagram.

Calculation of Indices

In the metastatic stage, the indices were calculated as follows by taking the complete blood count and biochemistry data obtained from the blood samples collected 7 days or earlier before the start of treatment. CRP levels were quantitatively measured using the immunoturbidimetric method, while albumin levels were determined by spectrophotometric methods.

• Neutrophil-to-Lymphocyte Ratio (NLR) = Neutrophils (10⁹/L) / Lymphocytes (10⁹/L)
• Platelet-to-Lymphocyte Ratio (PLR) = Platelets (10⁹/L) / Lymphocytes (10⁹/L)
• Lymphocyte-to-Monocyte Ratio (LMR) = Lymphocytes (10⁹/L) / Monocytes (10⁹/L)
• Systemic Immune-Inflammation Index (SII) = (Platelets (10⁹/L) × Neutrophils (10⁹/L)) / Lymphocytes (10⁹/L)
• Systemic Inflammation Response Index (SIRI) = (Neutrophils (10⁹/L) × Monocytes (10⁹/L)) / Lymphocytes (10⁹/L)
• Prognostic Nutritional Index (PNI) = Albumin (g/dL) + 0.005 × Lymphocytes (10⁹/L)
• Hemoglobin, Albumin, Lymphocyte, Platelet Score (HALP) = Hemoglobin (g/dL) × Albumin (g/dL) × Lymphocytes (10⁹/L)) / Platelets (10⁹/L)
• Neutrophil-to-Eosinophil Ratio (NER) = Neutrophils (10⁹/L) / Eosinophils (10⁹/L)
• C-Reactive Protein-to-Albumin Ratio (CAR): CRP (mg/L) / Albumin (g/dL).

Statistical Analysis

Statistical analyses were performed using SPSS 24 (SPSS Inc., Chicago, III) and Microsoft^® Excel^® 2019 (Version 2503) 32 bit and R software (R Core Team, 2024). Receiver operating characteristic (ROC) analysis was used to determine the ideal cut-off for the markers and to calculate sensitivity-specificity, and the Youden index method was used.¹⁴ In determining the ideal cut-off, long survival was considered a predictive marker. For variables that did not reach a statistically significant p value in the ROC analysis, the median cut-off value was included in the analyses. Kaplan-Meier survival analysis was used to calculate the estimated median overall survival time. Cox-regression analysis was used to calculate the univariate overall survival Hazard Ratio, and the Forward Stepwise (Likelihood Ratio) method was used for multivariate models. In the univariate Cox regression analysis for PDL1, patients with unknown PDL1 were not included, and 3 categories (< 1 vs 1–49 vs ≥ 50) were compared. All patients were included in the other univariate analyses. The proportional hazards assumption was tested using Schoenfeld residuals. The Schoenfeld residuals test was evaluated using the survival library in the R program (R Core Team, 2024).^15,16 Variables demonstrating a p-value below 0.05 were deemed statistically significant and consequently included in the final model based on the predetermined retention criteria. Situations where the P value was below 0.05 and the Type 1 error level was below 5% were interpreted as statistically significant.

Results

The study included 229 patients with metastatic non-small cell lung cancer who received nivolumab treatment. The median age of the patients was 63 (min: 41, max: 83). 84.3% (n=193) of the patients were male and 56.8% (n=130) of the tumorswere localized to the right lung. 51.1% (n=117) patients had adenocarcinoma, 40.6% had squamous histology and 8.3% (n=19) had “not otherwise specified (nos) histology”. The PDl-1 score of 49 patients (21.4%) was unknown. More than half of them (43.2%, n=122) were metastatic at the time of diagnosis and the most common metastatic site was bone metastasis (31.4%, n=72). Other clinical and pathological data are shown in Table 1.

Table 1 Clinical and Laboratory Characteristics of the Patients (n = 229)

The ideal cut-off values for inflammatory and nutrient markers to predict long survival were calculated separately. The ideal cut-off value for SII was determined as 1224 (AUC: 0.564, P=0.094), for PNI as 45.1 (AUC: 0.591, P=0.018), for HALP score as 2.0 (AUC: 0.576, P=0.046) and for CAR as 8.5 (AUC: 0.598, P=0.010) and the median values for other parameters were included in the analyses. Sensitivity and specificity are given in Table 2 with AUC 95% Confidence interval.

Table 2 ROC-Curve Analysis for Long-Term Survival and Derived Optimal Cut-off Values

The estimated median survival time of the patients was calculated as 21.2 months (95% CI: 17.4–25.0 months). The factors affecting survival were evaluated according to Univariate Cox regression analysis. Having brain metastasis at the time of diagnosis (HR: 2.08, 95% CI: 1.26–3.44, p=0.004), detection of liver metastasis (HR: 1.85, 95% CI: 1.13–3.03, p=0.014) and presence of adrenal metastasis (HR: 1.64, 95% CI: 1.01–2.66, p=0.045) were detected as negative prognostic findings. High neutrophil-lymphocyte ratio (NLR), which indirectly indicates inflammation (HR: 2.04, 95% CI: 1.42–2.92, p<0.001), high systemic immune-inflammation index (SII) (HR: 1.96, 95% CI: 1.37–2.79, p<0.001), high C-reactive protein-albumin ratio (CAR) (HR: 1.84, 95% CI: 1.29–2.61, p=0.001), high platelet-lymphocyte ratio (PLR) (HR: 1.60, 95% CI: 1.13–2.26, p=0.009) and high systemic inflammation response index (SIRI) (HR: 1.51, 95% CI: 1.07–2.15, p=0.021) were found to be poor prognostic markers predicting survival. Low prognostic nutritional index (PNI) (HR: 0.48, 95% CI: 0.34–0.69, p<0.001), low hemoglobin-albumin-lymphocyte-platelet score (HALP) (HR: 0.49, 95% CI: 0.35–0.70, p<0.001) and low lymphocyte-monocyte ratio (LMR) (HR: 0.65, 95% CI: 0.46–0.92, p=0.016) was found to be a predictive marker indicating poor prognosis. Clinically, the presence of immune-related adverse events was associated with prolonged overall survival (OS) (HR: 0.63, 95% CI: 0.41–0.97, p=0.034). Other investigated markers were tumor histological type (HR: 1.18, 95% CI: 0.98–1.41, p=0.075), disease stage at diagnosis (HR: 1.38, 95% CI: 0.97–1.97, p=0.076), PLD1 (HR: 0.88, 95% CI: 0.74–1.05, p=0.146), presence of pleural effusion (HR: 1.36, 95% CI: 0.90–2.05, p=0.145), use of hepatitis B prophylaxis (HR: 1.31, 95% CI: 0.83–2.09, p=0.250), presence of contralateral lung metastases (HR: 0.82, 95% CI: 0.55–1.20, p=0.298), tumor localization (HR: 0.84, 95% CI: 0.59–1.18, p=0.318), age group (HR: 1.18, 95% CI: 0.82–1.70, p=0.375), presence of bone metastases (HR: 0.87, 95% CI: 0.61–1.26, p=0.474), presence of extramediastinal lymphadenopathy (HR: 0.84, 95% CI: 0.50–1.43, p=0.527), gender (HR: 1.04, 95% CI: 0.64–1.68, p=0.873) and high neutrophil-eosinophil ratio (HR: 1.00, 95% CI: 0.71–1.42, p=0.986) and no statistically significant difference was found between survival (Table 3, Figure 2).

Table 3 Univariate Cox Proportional-Hazard Analysis for Overall Survival

Figure 2 Hazard ratios for clinical, pathological, and inflammatory markers in patients with metastatic non-small cell lung cancer (NSCLC) receiving nivolumab therapy. (Blue dots represent hazard ratio estimates, and horizontal lines indicate 95% confidence intervals.).

In the multivariate Cox regression analysis, the presence of brain metastasis (HR: 2.84, 95% CI: 1.68–4.79, p<0.001), the presence of adrenal metastasis (HR: 1.64, 95% CI: 1.01–2.67, p=0.046) and low PNI value (HR: 0.44, 95% CI: 0.30–0.63, p<0.001) prognosis showed the characteristic of being a prognostic model (Table 4). The findings obtained from the Cox regression analysis were tested for the proportional hazards assumption using Schoenfeld residuals. It was determined that the p-values for all variables in the model were above 0.05, indicating that the proportional hazards assumption was met. The multivariate model created in Table 4 is statistically significant (χ²= 31.93, p<0.001). To assess the fit of the model, the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) values were calculated and were obtained as 1183.73 and 1192.35, respectively. These values indicate that the overall fit of the model is acceptable VIF values were examined for multicollinearity, and no significant multicollinearity was detected (VIF<5).

Table 4 Multivariate Cox Proportional-Hazard Analysis for Overall Survival

Discussion

In this study, 229 patients with metastatic non-small cell (NSCLC) who received nivolumab immunotherapy were analyzed. In the study, in univariate analysis, the presence of brain metastasis, liver and adrenal metastasis were associated with poor prognosis. Patients who developed immune-related side effects during treatment had better treatment responses. Except for NER, the investigated inflammation markers (PLR, LMR, SII, SIRI, PNI, HALP, NER, CAR) predicted prognosis. In multivariate analysis, brain metastasis, adrenal metastasis and Prognostic nutritional index (PNI) formed a strong prognostic model.

While immunotherapy treatments for lung cancer are rapidly advancing, it is still unclear in which patients the treatment will be effective. Although the PDL-1 score is the most basic marker in clinical studies, immunotherapy treatments can be effective in patients with negative PDL-1 scores, while immunotherapy is not effective in some groups with high PDL1 scores.^17,18 With the investigation of tumor mutation burden and microsatellite instability, MSI was detected positive in only 0.33% of small cell lung cancers.¹⁹ TMB is a high-cost test and is not a routinely recommended test.²⁰ Therefore, a cheap, easily applicable marker is needed to predict immunotherapy response. In the study conducted by Lin et al, PDL-1 score did not statistically predict treatment response in patients receiving nivolumab.²¹ Phase 3 study data for nivolumab demonstrated that treatment efficacy was independent of PD-L1 levels. When we excluded the subgroup with unknown PD-L1 levels from our study analysis, there was no association between PD-L1 levels and survival (p=0.146), and these results were consistent with the literature.²²

Immune-Related Adverse Events (irAEs) are the definition of side effects caused by autoimmune or inflammatory toxins that develop due to excessive activation of the immune system in patients treated with immune checkpoint inhibitors.²³ irAEs are seen when the immune system is not limited to tumor cells but also invades normal tissues. In the study conducted by Ebi et al, it was seen to be associated with good prognosis in patients receiving ipilimumab together with nivolumab.²⁴ Zhou et al. The meta-analysis revealed that immunotherapy responses were better in patients who developed irAEs.²⁵ In our study, patients who developed irAEs had better survival, consistent with the results of the mentioned studies.

For a clearer understanding of immunotherapy biomarkers, it would be helpful to focus on neoantigen formation and presentation, the tumor microenvironment, changes in certain gene signaling pathways, MHC molecules, and T-cell receptors.²⁶ Among these pathways, the IL-6/STAT3 axis has been implicated in mediating resistance to checkpoint blockade by intrinsically impairing CD8⁺ T-cell differentiation and function, with elevated circulating IL-6 levels correlating with poor responses to anti-PD-L1 therapy.^12,27,28 Although it is technically not possible to measure these markers directly, indirectly looking at inflammation markers in the blood seems to be an easily accessible and inexpensive method. Recent studies suggest that increased lymphocytes and decreased neutrophils are associated with better prognosis in NSCLC patients treated with nivolumab. Russo et al. In their study, they demonstrated that increased neutrophil levels are poor prognostic in NSCLC patients.²⁹ The same study demonstrated that increased NLR and increased PLR are poor prognostic in nivolumab treatment.²⁹ Cao et al. In a pooled analysis of 14 retrospective studies, increased NLR was found to be a poor prognostic marker and determined the ideal cut-off value as 5.³⁰ In our study, the median cut-off was 4.3, and patients above this cut-off were considered to have poor nivolumab responses.

As a result of the immune system response that occurs together with inflammation, an increase in C-reactive protein (CRP), neutrophils, and a decrease in albumin and lymphocytes in the blood are expected results.³¹ The C-reactive protein/albumin ratio (CAR), which reflects high CRP and low albumin scores, has been suggested to be prognostic in lung cancer. Dai et al found that patients with high CAR scores had shorter OS and PFS.³² Prognostic nutritional index (PNI) is a score that evaluates serum albumin level and lymphocyte count together, and Wang et al found a 57% decrease in the risk of death in patients with low prognostic index compared to those with high prognostic index (HR:0.43).³³ HALP Score, which evaluates the combination of Hemoglobin, Albumin, Lymphocyte, Platelet, is an immune-nutritional index defined in recent years. Akgül et al found that patients with low HALP scores in lung cancer patients treated with nivolumab in the second line had a poor prognosis.³⁴ Our study is consistent with the literature, and when each was evaluated independently, high CAR (HR:1.84), low PNI (HR:0.48), and low HALP (HR:0.49) were found to be associated with poor prognosis in patients receiving nivolumab.

There were some limitations regarding our study. The retrospective nature of our study design was an important limitation. Other limitations were the small percentage of patients with brain metastases (11.4%) and the high percentage of patients with unknown pdl1 (21.4%). In addition, the inability to calculate the ideal cut-off using Roc-Curve analysis for hematological parameters that were significant in the survival analysis was a statistical weakness of our study. The evaluation of immunotherapy results in brain metastatic patients, which is an exclusion criterion in most clinical studies, and the data of a homogeneous center make the study strong.

Conclusion

In conclusion, when evaluated separately in our study, NSCLC patients treated with nivolumab had poor response to treatment in liver, brain and adrenal metastatic patients and markers (NLR, PLR, LMR, SII, SIRI, PNI, HALP, CAR) which are indirect indicators of inflammation were prognostic on their own, and PNI formed a prognostic model with brain metastasis and adrenal metastasis among these markers. Prospective data are needed in further studies.

Abbreviations

ANC, Absolute Neutrophil Count; AUC, Area Under the Curve; CAR, C-Reactive Protein-to-Albumin Ratio; CI, Confidence Interval; CRP, C-Reactive Protein; CTLA-4, Cytotoxic T-Lymphocyte Antigen-4; ECG, Eastern Cooperative Oncology Group; HALP, Hemoglobin, Albumin, Lymphocyte, Platelet Score; HR, Hazard Ratio; irAEs, Immune-related Adverse Events; LMR, Lymphocyte-to-Monocyte Ratio; NER, Neutrophil-to-Eosinophil Ratio; NLR, Neutrophil-to-Lymphocyte Ratio; NOS, Not Otherwise Specified; NSCLC, Non-Small Cell Lung Cancer; PD-1, Programmed Death-1; PD-L1, Programmed Death Ligand-1; PLR, Platelet-to-Lymphocyte Ratio; PNI, Prognostic Nutritional Index; ROC, Receiver Operating Characteristic; SCC, Squamous Cell Carcinoma; SII, Systemic Immune-Inflammation Index; SIRI, Systemic Inflammation Response Index; TMB, Tumor Mutational Burden; VEGF, Vascular Endothelial Growth Factor.

Ethics Approval and Consent to Participate

This study was reviewed and approved by the Ethics Committee of Nevsehir Haci Bektas Veli University.All participants provided written informed consent prior to treatment. The study was conducted in accordance with the principles outlined in the Declaration of Helsinki.

Disclosure

The authors declare that they have no conflicts of interest related to this work.

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Introduction

In recent years, ERCP has emerged as an essential, minimally invasive interventional procedure for diagnosing and treating biliary and pancreatic disorders.¹ Annually, over one million individuals worldwide undergo ERCP.² Nevertheless, the procedure’s complexity, duration, and invasive nature can induce anxiety, discomfort, and pain in patients. Consequently, deep sedation and general anesthesia are increasingly used in ERCP for diagnosis and treatment.³ The optimal anesthesia for ERCP should ensure that patients remain pain-free and comfortable, while maintaining respiratory and circulatory stability and facilitating rapid recovery. However, commonly employed anesthesia techniques, such as local anesthesia or traditional sedation combined with analgesia and anesthesia, present challenges, including poor patient cooperation, delayed drug onset, and an increased risk of respiratory depression.⁴ Therefore, there is an urgent need to develop more optimized anesthesia protocols.

As a novel benzodiazepine, remimazolam is characterized by a rapid onset, brief duration of action, swift metabolism, and minimal respiratory and circulatory suppression. These pharmacological attributes suggest its promising application in short-duration, minor surgical procedures, such as painless gastrointestinal endoscopy.^5–8 Its pharmacokinetic and pharmacodynamic properties render it a potentially ideal agent for anesthesia induction in ERCP. However, significant variability exists in the response to anesthetic agents among patients of different age groups. As age increases, there is a decline in the hepatic metabolic capacity, a decrease in plasma protein binding rate, and an increase in central nervous system sensitivity, all of which necessitate adjustments in drug dosage.^9–11 Currently, there is a lack of age-stratified studies on the median effective dose of remimazolam for ERCP anesthesia induction, which hinders the precision of its clinical application.

This study seeks to investigate the ED₅₀ of remimazolam for anesthesia induction during ERCP using an age-stratified method. This approach aims to establish a foundation for personalized medication strategies tailored to patients of varying ages. The findings of this research are anticipated to optimize anesthesia management for ERCP, enhance patient safety and comfort, and provide empirical support for the development of anesthesia protocols for specific populations, including elderly patients.

Methods

Ethics Approval

This study received ethical approval from the Ethics Committee of the First Affiliated Hospital of the University of Science and Technology of China (USTC) (Approval No. 2022 KY 044; Approval Date: April 6, 2022). In accordance with the Declaration of Helsinki, all participants provided written informed consent prior to their involvement in the trial. The trial was registered with the Chinese Clinical Trial Registry (ChiCTR) prior to participant enrollment (Registration No. ChiCTR2200060357; Principal Investigator: Xu Min; Enrollment Date: May 29, 2022). The research was conducted at the First Affiliated Hospital of USTC from October 2022 to December 2023. The manuscript adheres to the relevant guidelines of the Consolidated Standards of Reporting Trials (CONSORT).

Participants

This prospective study recruited a total of 165 patients aged 50 to 89 years, with ASA levels I to III and a BMI ranging from 18 kg/m² to 30 kg/m², who underwent ERCP surgery under general anesthesia. Eligible patients should be able to understand the study, voluntarily sign the informed consent, and be willing to comply with the trial protocol requirements. Exclusion criteria included: (1) individuals who are allergic to or contraindicated for benzodiazepines, opioids, propofol, flumazenil, naloxone, and other related medications; (2) Patients with severe cardiac dysfunction (eg, New York Heart Association Class III–IV), severe respiratory insufficiency (eg, chronic obstructive pulmonary disease GOLD grade 3–4, or baseline room air SpO₂ < 92%), severe renal impairment (eg, estimated glomerular filtration rate < 30 mL/min/1.73m²), or other uncontrolled chronic conditions (eg, unstable hypertension or diabetes) that, in the investigator’s judgment, would pose a significant risk for tolerating anesthesia; (3) individuals with mental illness; (4) with a history of alcoholism, opioid allergy, or drug abuse; (5) with uncontrolled severe hypertension; (6) emergency surgery patients; (7) pregnant or lactating women; (8) surgeries lasting longer than one hour; and (9) any other condition that, in the opinion of the investigator, may pose a risk to the patient or interfere with the study objectives and procedures.

Patients were categorized into four groups based on age: R1 group (50–59 years old; 27 cases), R2 group (60–69 years old; 29 cases), R3 group (70–79 years old; 30 cases), and R4 group (80–89 years old; 24 cases) (Figure 1). The first patient in the R1 group received an induction dose of remimazolam at 0.1 mg/kg. For groups R2 to R4, the initial dose for the first patient in each subsequent group was reduced by one dose gradient (0.01 mg/kg) as age increased. This study employed the Dixon up-and-down method for dose escalation/escalation design, enrolling patients in each cohort until seven crossovers were observed. This method is extensively used in determining the ED₅₀ of anesthetic drugs;¹² consequently, an a priori sample size calculation was not performed.

Figure 1 Flow diagram of patient recruitment.

Anesthesia Protocol

The patient fasted for 8 hours and abstained from drinking for 4 hours before the surgery. Upon entering the operating room, heart rate (HR), electrocardiogram (ECG), oxygen saturation (SpO₂), and bispectral index (BIS) values were continuously monitored. Radial artery puncture and catheterization were performed for invasive arterial pressure monitoring under local anesthesia. The patient received 10 mL of dyclonine hydrochloride mucilage (0.1% dyclonine hydrochloride) and supplemental oxygen (3–4 L/min) for 3 minutes. After establishing intravenous access, an anesthesiologist, blinded to the group assignment, administered sufentanil at a dosage of 0.1 µg/kg, followed by a preset dose of remimazolam injected one minute later. After 180 seconds of intravenous remimazolam injection, an ERCP examination was conducted when the MOAA/S score reached 0. If the examination proceeded smoothly, anesthesia was deemed successful, and the next patient would receive a lower dose of remimazolam (the dose was reduced by 0.01mg/kg). If the MOAA/S score remained ≥1 after 3 minutes, or if the MOAA/S score reached 0 but the ERCP examination was unsuccessful (due to movement, coughing, etc)., anesthesia was classified as a failure. Under these circumstances, emergency anesthesia using propofol at 1 mg/kg was administered, with the process repeated every 3 minutes until the MOAA/S score reached 0 and the ERCP was concluded, followed by an increased remimazolam dosage (increased by 0.01 mg/kg) for the subsequent patient. A single negative outcome and a single positive outcome were sequentially documented as a single cross. The experiment concluded after the completion of seven crosses. A different anesthesiologist documented the test outcomes and notified the nurse, who was not involved in the study, to prepare the experimental drug for the next patient. For maintenance purposes, normal saline was used as the solution, while remimazolam was employed for mixing. A 20 mL syringe was used to mix the recommended remimazolam dosage, resulting in a total volume of 20 mL.

During diagnosis and treatment, ephedrine should be administered for symptomatic relief if the systolic blood pressure (SBP) falls below 30% of the baseline value. In cases where the HR is ≤ 50 beats per minute, the intravenous administration of 0.5 mg atropine is indicated. If the SpO₂ drops to ≤93%, it is essential to maintain the patient’s jaw position and increase the oxygen flow. Should the SpO₂ decrease to ≤ 80%, the endoscopic procedure must be halted, and supplemental oxygen should be administered via a mask. Remimazolam should be discontinued immediately after surgery, and the patient should be transferred to the post-anesthesia care unit (PACU). Once the Aldrete score reaches ≥9, the patient may return to the ward, accompanied by family members.

Data Collection

The primary objective of this research was to determine the ED₅₀ and ED₉₅ of remimazolam in conjunction with 0.1 µg/kg sufentanil for patient induction. Furthermore, as a secondary outcome, HR, mean arterial pressure (MAP), peripheral SpO₂, and BIS were measured at various time points: prior to the initiation of anesthesia induction (T0), and at 10 seconds (T1), 20 seconds (T2), 40 seconds (T3), 60 seconds (T4), 90 seconds (T5), 120 seconds (T6), and 180 seconds (T7) following induction. Concurrently, adverse events and corresponding treatment measures were documented throughout the study.

Statistical Analysis

The data analysis was performed using SPSS version 27. Descriptive statistics are presented as means with standard deviations (SD) or medians with interquartile ranges, depending on whether the data distribution is normal or skewed. Categorical data are expressed as percentages. For categorical data analysis, the Chi-square test or Fisher’s exact test was employed, while the Mann–Whitney U-test was used for nonparametric statistics. A one-way analysis of variance (ANOVA) was used to compare multiple groups. A two-way ANOVA was conducted to analyze data collected at various time points across the groups. The effective doses (ED₅₀ and ED₉₅) of remimazolam, along with their corresponding CIs, were determined using probit regression analysis. All statistical tests were two-tailed, and a p-value of less than 0.05 was considered statistically significant. Sequential graphs and dose-response curves were generated using GraphPad Prism version 8.

A trio of multivariable linear regression models was formulated to evaluate the independent correlation between age and remimazolam dosage. The model I remained unchanged, while Model II underwent modifications for the gender and BMI. Model III received additional adjustments for the levels of albumin (ALB), alanine aminotransferase (ALT), serum creatinine (Scr), and blood urea nitrogen (BUN). Variables were chosen for the models when they showed possible impact factors, as evidenced by a univariate analysis p-value below 0.05. Furthermore, indices closely linked to remimazolam metabolism and the clinical functions of the liver and kidneys are integrated.^13,14 A collinearity diagnosis was conducted to prevent the inclusion of highly correlated variables in the model. To explore the linear relationship between age and remimazolam dosage, smooth curve fitting was applied after adjusting for potential confounding variables.

Results

General Data

Figure 1 shows that out of 165 patients screened for recruitment, 55 were excluded and 110 were assigned to groups R1 (n=27), R2 (n=29), R3 (n=30), and R4 (n=24). All 110 enrolled patients completed the study and were included in the primary outcome analysis. Table 1 displays the baseline characteristics of the 110 patients. Apart from age (p <0.001) and ALB (p <0.001), the four groups have similar demographic characteristics.

Table 1 Demographic Characteristics

In the investigation of effective dosing, the ED₅₀ of remimazolam for anesthesia induction was quantified using the probit regression model. The results indicated ED₅₀ values of 0.122 mg/kg (95% CI: 0.115, 0.127), 0.108 mg/kg (95% CI: 0.101, 0.115), 0.093 mg/kg (95% CI: 0.084, 0.103), and 0.078 mg/kg (95% CI: 0.070, 0.085) for groups R1 through R4, respectively. Correspondingly, the dose required to achieve ED₉₅ was determined to be 0.132 mg/kg (95% CI: 0.127, 0.161), 0.122 mg/kg (95% CI: 0.115, 0.164), 0.113 mg/kg (95% CI: 0.103, 0.172), and 0.090 mg/kg (95% CI: 0.084, 0.128) for the same groups, as presented in Table 2. Importantly, both ED₅₀ and ED₉₅ values demonstrated a statistically significant reduction with increasing age from group R1 to group R4 (p < 0.05). The results of the Dixon up-and-down method for each group are illustrated in Figure 2, and the dose-response curves for remimazolam induction across the groups are shown in Figure 3.

Table 2 ED50 and ED95 of Remimazolam for Anesthesia Induction

Figure 2 The up-and-down sequence of Remimazolam dose for anesthesia Induction. (A) R1 group; (B) R2 group; (C) R3 group; (D) R4 group; “●”represent negative reaction, patient anesthesia failed, “◯” represent positive reaction, patient successfully anesthesia.

Figure 3 The dose-response curve from the probit analysis of remimazolam dosage and probability of success anesthesia. X-axis: Remimazolam dose (mg/kg); Y-axis: Probability of successful anesthesia (probit-transformed cumulative percentage). The dashed vertical line indicates ED50 with 95% CI (shaded area). (A) R1 group; (B) R2 group; (C) R3 group; (D) R4 group. Abbreviations: ED50, median effective dose; CI, confidence interval.

Bivariate linear correlation analysis in Table 3 showed a significant negative correlation between the requirement for remimazolam and age (r = −0.829, 95% CI: −0.875 to −0.753, p < 0.001). A rise in BMI correlated with a reduced need for remimazolam (r = −0.198, 95% CI: −0.021 to −0.375, p = 0.04). On the other hand, a notable positive correlation was found between the need for remimazolam dosage and ALB levels, with statistical significance (r = 0.249, 95% CI: 0.066–0.407, p = 0.009). There were no notable links detected between other indicators of organ function and the required dosage of remimazolam. Furthermore, to clarify the direct correlation between age and the need for remimazolam dosage, a smooth curve fitting method was used, factoring in variables such as gender, BMI, ALB, ALT, Scr, and BUN, which were found to be statistically significant (Figure 4).

Table 3 Correlation Coefficients Between Age and Remimazolam Requirement

Figure 4 Adjusted dose-response linear between age and remimazolam requirement. Adjusted for gender, BMI, ALB, ALT, Scr, BUN. Abbreviations: BMI, body mass index; ALB,albumin; ALT,alanine aminotransferase; Scr, serum creatinine; BUN,blood urea nitrogen.

Model I was established as a basic model, incorporating only the age factor to initially assess its impact on the required dosage of remimazolam. Based on the results of univariate linear regression analysis, BMI and gender were identified as significant factors (p < 0.05) and were therefore included in Model II. Building on these findings, Model III was further adjusted for levels of ALB, ALT, Scr, and BUN. The diagnostic tests for collinearity showed no variables with strong interconnections that required removal from the multivariable linear regression model. The research revealed a notable correlation between advancing age and a reduced need for remimazolam (p < 0.001) in Model I. This relationship persisted and remained significant even after accounting for BMI and gender in Model II (p < 0.001), and after additional adjustments for ALB, ALT, Scr, and BUN levels in Model III (p < 0.001).

No serious adverse events occurred during induction with remimazolam combined with sufentanil across all age groups. Some patients experienced transient decreases in blood pressure or heart rate, which were promptly corrected with ephedrine or atropine. The incidence of hypoxemia (SpO₂ ≤ 93%) was low, with the following cases per group: R1: 2 case (7.4%), R2: 1 cases (3.4%), R3: 3 cases (10.0%), R4: 2 cases (8.3%). All cases were managed by jaw-thrust maneuver or increased oxygen flow without the need to interrupt the endoscopic procedure. No instances of severe respiratory depression or circulatory collapse requiring endotracheal intubation or ICU transfer occurred.

Discussion

This study is the first to employ an age-stratified design to systematically investigate the ED₅₀ of remimazolam for anesthesia induction during ERCP and its relationship with patient age. The results demonstrate a significant age-dependent decline in ED₅₀ across groups (R1 to R4: 0.122, 0.108, 0.093, and 0.078 mg/kg, respectively), with age identified as an independent predictor of dosage requirements (r = −0.829, p < 0.001). By addressing the homogeneity limitations of previous dose-finding studies, this research provides evidence-based guidance for reducing anesthetic doses in elderly patients, thereby advancing precision in clinical anesthesia management.

Notably, previous studies have also reported age-dependent reductions in remimazolam dosage requirements. For instance, Oh et al¹⁵ demonstrated a lower ED₉₅ for loss of consciousness in elderly patients compared to younger adults, while Song et al¹³ observed a significantly reduced ED₅₀ in patients aged over 65 years. Similarly, Chae et al¹⁶ suggested stratified induction doses across different age decades, corroborating the necessity of age-adjusted dosing.

Remimazolam, an ultrashort-acting benzodiazepine, exerts its effects by enhancing γ-aminobutyric acid (GABA) receptor activity in the central nervous system (CNS).¹⁷ Unlike propofol or midazolam, remimazolam undergoes rapid hydrolysis by tissue esterases to an inactive metabolite (CNS 7054), bypassing hepatic or renal metabolism.¹⁸ This pharmacokinetic profile confers unique advantages for elderly populations. However, our findings revealed a substantial reduction in ED₅₀ among older patients (11.5%–16.1% per decade of age), despite the absence of age-related metabolic impairment. This suggests that heightened CNS sensitivity to remimazolam, rather than altered metabolism, drives the observed dose reduction. Similar age-dependent patterns have been reported for propofol, with declining neuronal density, altered neurotransmitter receptor expression, and changes in blood-brain barrier permeability proposed as mechanisms.^19,20

Prior studies on remimazolam induction in elderly patients reported reduced dosage requirements but failed to fully disentangle the confounding metabolic factors.¹⁵ For instance, propofol studies identified correlations between dosage and serum ALB or glomerular filtration rate (GFR), implying that clearance variability might obscure age-related effects.²¹ To isolate the independent influence of age on remimazolam dosing, our multivariate models adjusted for hepatic (ALT, ALB) and renal (Scr, BUN) markers. Age remained a robust independent predictor of dosage, aligning with physiologically based pharmacokinetic (PBPK) frameworks that integrate organ perfusion and enzyme activity to differentiate CNS sensitivity from metabolic contributions.²² The bivariate correlation analysis revealed a notable positive link between the need for remimazolam and ALB concentrations (r = 0.249, p = 0.009), and a reverse relationship with BMI (r = −0.198, p = 0.04). Remimazolam’s pharmacokinetic analysis relies on a tripartite model, characterized by a reduced apparent volume of distribution and an increased clearance rate.²³ Nonetheless, the interaction between body mass and pharmacokinetic factors is complex.²⁴ Observational data support the idea that BMI is a statistically significant covariate in predicting the likelihood of unconsciousness in patients treated with remimazolam during general anesthesia.²⁵ Consequently, adjusting the remimazolam dosage based on BMI could mitigate the impact of body weight on drug metabolism, making this approach more logical than fixed-dose treatments. ALB serves as the principal drug-binding protein in plasma, interacting with various drugs through multiple binding sites, thereby forming a “reservoir” that influences the free concentration, distribution, and clearance of drugs.²⁶ Benzodiazepines, such as midazolam, exhibit high rates of ALB binding, with 94% of the drug bound to protein.²⁷ This characteristic can result in significant increases in free drug concentrations during states of hypoalbuminemia. In contrast, remimazolam possesses distinct pharmacokinetic properties. Its metabolism is predominantly reliant on esterase activity, which facilitates the rapid clearance of unbound drug, thereby reducing its susceptibility to fluctuations in ALB levels compared to midazolam. However, recent findings by Song et al¹³ indicate that ALB concentrations significantly influence the induction efficacy of remimazolam.

Although ERCP is performed across a wide age range, epidemiological data and clinical practice indicate that the majority of procedures are concentrated in patients aged 50 to 89 years, who are more frequently affected by biliary and pancreatic diseases requiring interventional management.^28,29 Focusing on this age range not only ensures an adequate sample size but also enhances the clinical relevance and applicability of our findings. Furthermore, as age advances, patients often exhibit diminished physiological reserves and reduced tolerance to anesthesia, necessitating more individualized dosing strategies to mitigate perioperative risks.^29–31 In this study, we stratified patients in 10-year increments, starting with an initial dose of 0.1 mg/kg. For each subsequent age group, the first patient received a 0.01 mg/kg dose reduction to determine the ED₅₀ and ED₉₅ of remimazolam in patients over 50 years old. Prior research efforts^15–17 have investigated the induction dosage of remimazolam across various age cohorts. Compared with previous studies, our findings are consistent with the dose trend reported by Oh et al¹⁵ indicating increased sensitivity to remimazolam and a significantly reduced induction dose required in elderly patients. However, the ED₉₅ values we observed were lower than reported by Oh et al. Furthermore, while Zhang et al¹⁷ noted in their systematic review that remimazolam demonstrates good hemodynamic stability and rapid recovery across different age groups, they did not provide specific age-stratified dosing recommendations. Our study addresses this gap by employing precise stratification in 10-year increments, systematically quantifying for the first time the inverse relationship between remimazolam induction dose and age in patients over 50 years old, providing evidence for personalized dosing in advanced age populations.

The study by Song et al¹³ (n=120), using a continuous infusion of remimazolam at 0.05 mg/kg/min, observed that the ED₅₀ for inducing loss of consciousness was 0.26 mg/kg and 0.19 mg/kg in patients aged 18–64 years and those ≥65 years, respectively. Chae et al¹⁶ (n=120), employing probit regression to analyze the dose-response relationship across six bolus dose groups (0.02–0.27 mg/kg), suggested that the optimal induction doses of remimazolam were 0.25–0.33 mg/kg for patients aged <40 years, 0.19–0.25 mg/kg for those aged 60–80 years, and 0.14–0.19 mg/kg for patients >80 years. In contrast, our ED₅₀ and ED₉₅ values for comparable age segments are substantially lower. This discrepancy can likely be attributed to several key methodological differences. First, we administered 0.1 μg/kg of sufentanil before remimazolam. Opioids exhibit pharmacodynamic synergy, significantly reducing remimazolam induction requirements. Substantial evidence^32,33 indicates that opioids indirectly inhibit GABA interneurons in the ventral tegmental area, disinhibiting dopaminergic pathways while potentiating the GABA effects of benzodiazepines, thereby enhancing the depth of anesthesia. In painless endoscopic procedures which typically target deep sedation, coadministration of alfentanil reduces remimazolam requirements by 20–30%.³⁴ Although the target depth differs, the synergistic principle between opioids and remimazolam is consistent. Second, the age-remimazolam dose relationship is nonlinear: (1) Elderly patients demonstrate increased CNS sensitivity to sedatives, potentially due to altered neuronal receptor density and blood-brain barrier permeability.³¹ This sensitivity may increase abruptly after the age of 65, causing a sharp reduction in anesthetic requirements. (2) Hepatic blood flow decreases by 0.3–1.5% per decade, with accelerated hepatocyte loss after the age of 60.³⁵ This nonlinear decline further reduces remimazolam clearance in elderly patients, necessitating dose adjustments beyond linear model predictions. (3) Elderly patients, particularly those with frailty or chronic diseases, often have reduced plasma ALB,³⁶ which decreases drug-binding sites and increases free drug concentrations, thereby enhancing the drug’s effects. Clinical study³⁷ shows that the relationship between remimazolam’s effect-site concentration (Ce) and BIS values follows a sigmoid curve, with a leftward shift in elderly patients, indicating that lower concentrations achieve an equivalent depth of sedation. This shift becomes more pronounced with advancing age, suggesting an inverse nonlinear correlation between age and dose requirements. Our findings confirm this phenomenon, showing an accelerated dose reduction between groups R3 and R4. Therefore, age-stratified investigations allow for the precise characterization of nonlinear age-dose relationships, avoiding the underestimation of dose variations that may occur with broader age categories. Third, our combined use of MOAA/S scores and BIS monitoring improves the accuracy of anesthetic depth assessment, reducing both false negatives and false positives, and enabling a more precise calculation of the ED₅₀ for remimazolam. This can prevent a single evaluation index from increasing the assessment bias, which could result in the overestimation or underestimation of the remimazolam dose requirement.

This study effectively determined the ED₅₀ of remimazolam in different age groups using Dixon’s up-and-down method. However, it is important to note that this method has limitations for estimating parameters at the distribution tail, such as the ED₉₅, as evidenced by the relatively wide confidence intervals we calculated for the ED₉₅ (eg, 0.103–0.172 mg/kg in group R3). This reflects the inherent challenge of precisely estimating high-percentile effective doses with a limited sample size. Therefore, when clinicians refer to the ED₉₅ values from this study for medication guidance, they should be aware of this uncertainty and cautiously perform individualized dose adjustments based on the specific circumstances of the patient. Future studies with larger sample sizes or employing different experimental designs (eg, randomized assigned dose groups) will help to more precisely determine the ED₉₅ of remimazolam.

The primary strength of this study lies in its refined age-stratified design and multivariate model adjustment, which systematically quantifies, for the first time, the significant negative linear correlation between remimazolam dosage requirements and age. Although the study enrolled patients across a broad age range of 50–89 years, the oldest group (R4, 80–89 years) was predominantly composed of individuals aged 81–84 years, with only a small proportion aged 85 years or older. This underrepresentation of the oldest-old subgroup may limit the generalizability of our findings to individuals aged 85 years and above. Additionally, although patients with severe hepatic or renal dysfunction were excluded, the cohort was not specifically designed to recruit or stratify elderly individuals with chronic comorbidities such as diabetes or neurodegenerative diseases, who may exhibit altered drug sensitivity and thus introduce potential bias in the results. Furthermore, sufentanil was administered at a fixed dose as an adjunct without individual titration or systematic dose-response analysis, potentially leading to an underestimation of its modulatory effect on remimazolam’s potency. Finally, Although our study adjusted for age, BMI, and organ function markers, we did not collect data on functional capacity (eg, metabolic equivalents, METs) or frailty indices, which are known to influence anesthetic sensitivity and perioperative outcomes. Future studies should incorporate these metrics to further refine remimazolam dosing in elderly patients.

Furthermore, it is noteworthy that although chronic comorbidities (eg, diabetes) were not used as stratification or exclusion criteria, some patients in the cohort might indeed have had such conditions. Metabolic diseases like diabetes can influence drug response through various mechanisms, including alterations in blood-brain barrier permeability, effects on hepatic and renal function, or pathological changes in the peripheral and central nervous systems, potentially increasing sensitivity to sedative drugs. Although we adjusted for liver and kidney function-related indicators (ALB, ALT, Scr, BUN) in our multivariate models, information on patient comorbidities was not systematically collected, which represents a limitation of this study. Future research should further explore the impact of comorbidities on the dose-response relationship of remimazolam to enable more precise personalized medication.

Future studies should be expanded to include extremely elderly populations (≥90 years) and those with comorbidities, while exploring multifactorial predictive models (eg, age + ALB + comorbidity burden) to optimize individualized dosing. Given remimazolam’s short-acting properties, further investigation is warranted to validate its dosing patterns in non-ERCP settings, such as day-case surgeries and ICU sedation. Integrating target-controlled infusion (TCI) technology may enable dynamic “dose-effect-age” matching, ultimately enhancing anesthesia safety in geriatric patients.

This study quantified the age-dependent reduction in the ED₅₀ of remimazolam for anesthesia induction during ERCP. The ED₅₀ decreased progressively from 0.122 mg/kg (95% CI: 0.115–0.127) in patients aged 50–59 years to 0.078 mg/kg (95% CI: 0.070–0.085) in those aged 80–89 years. Multivariable linear regression confirmed age as an independent predictor of remimazolam requirements, even after adjusting for BMI, ALB, and hepatic/renal function markers. These results emphasize the necessity of age-stratified dosing to mitigate overdosing risks in elderly populations, particularly given their heightened central nervous system sensitivity. Future studies should be expanded to include extremely elderly populations (≥90 years) and those with comorbidities to further refine personalized dosing strategies.

Data Sharing Statement

The authors state that all data in the manuscript are accessible if requested (contact e-mail address [email protected]). The authors verify that all data intended for sharing is de-identified.

Funding

This study was supported by the “Rui” Special Fund for Scientific Research from Hubei Chen Xiaoping Science and Technology Development Foundation (CXPJJH12000005-07-116); Anhui Provincial Health Care Commission Health Research Project (AHWJ2024BAc30062). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Disclosure

The authors declare no conflicts of interest in this work.

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31. Coetzee E, Absalom AR. Absalom anthony-ray. pharmacokinetic and pharmacodynamic changes in the older adults: impact on anesthetics. Clin Geriatr Med. 2025;41(1):19–35. doi:10.1016/j.cger.2024.03.004

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Opportunity to create one of the largest global copper complexes

Santiago, Chile – November 3, 2025 – Teck Resources Limited (TSX: TECK.A and TECK.B, NYSE: TECK) (“Teck”) provided an update on its roadmap to long-term value creation, including progress ramping up Quebrada Blanca (QB) and the Company’s proposed merger with Anglo American plc (“Anglo American”) inclusive of the potential benefits of combining QB and Collahuasi to create one of the largest global copper complexes, during an investor presentation and QB site tour November 3 and 4 in Chile.

“We have a clear path to creating tremendous value for shareholders by completing the transformative merger of equals with Anglo American and continuing to advance the ramp up and optimization of QB,” said Jonathan Price, President and CEO. “Completion of the merger will create a leading growth-oriented copper investment vehicle with resilience and capacity to realize significant value across the combined portfolio. Integrating QB and Collahuasi is widely recognized as one of the most compelling industrial synergy opportunities in the industry today, and will establish one of the largest global copper complexes, unlocking additional production and value for all stakeholders.”

Realizing the full value of QB
QB is a tier-one, multi-generational copper asset with state-of-the-art facilities. The current mine plan only utilizes 15% of the resource base, providing multiple pathways for long-term growth. Performance has improved with the implementation of the QB Action Plan in August, with work progressing on resolving the constraint on production posed by the slower-than-expected development of the Tailings Management Facility. Recent progress includes:
 

• Mill throughput and recoveries running in line with expectations through October
• Completing construction of three rock benches, with the fourth on track to be completed by the end of 2025 and the fifth in H1 2026 to enable ongoing production
• Replaced 59% of cyclones to date to incorporate new technology, on track to replace 100% of cyclones by the end of 2025
• Sand drainage rates improving since the first cyclone battery refit
• Targeting completion of sand wedge in H1 2026 enabling transition to steady state operations in 2026

Creation of a Top 5 Global Producer with Scale, Resilience and Financial Strength
The proposed merger of Teck and Anglo American will create long-term value growth for shareholders, establishing a global critical minerals champion and top five copper producer with more than 70% copper exposure and outstanding further growth optionality. Highlights of Anglo Teck include:
 

• Top five global copper producer with combined copper production of 1.2 million tonnes, expected to grow to c.1.35 million tonnes in 2027 from current operations
• Portfolio of operating assets includes six world class copper mines, one of the world’s largest zinc mines, and two highly cash generative premium iron ore operations
• Teck shareholders to remain fully invested in a top-tier copper-focused platform and in the future value creation at Anglo Teck
• Teck shareholders benefit from multiple value drivers: US$800 million in pre-tax recurring annual corporate synergies; near-term growth of an additional potential ~120-165 kilotonnes per annum (ktpa) copper production through asset optimization; potential ~295 ktpa additional copper production through medium-term capital efficient adjacencies (including QB-Collahuasi and Los Bronces-Andina synergies); and extensive brownfield and greenfield future growth optionality
• With increased scale and a global capital markets footprint, Anglo Teck will have access to a deeper pool of investors, creating the opportunity to re-rate towards a premium copper valuation multiple

Unlocking the potential of QB-Collahuasi
The proposed merger of Teck and Anglo American will enable a highly attractive opportunity to unlock unique industrial synergies between two flagship copper assets – QB and Collahuasi. These two operations comprise one of the largest global copper complexes and their proximity creates a compelling, capital-efficient adjacency value benefit, including:
 

• Approximately 175,000 tonnes per annum of expected incremental copper production
• Approximately US$1.4 billion (100% basis) additional EBITDA[1]
• Extremely capital-efficient growth at approximately US$11,000 per tonne of incremental production, including construction of a 15-kilometre conveyor from the Collahuasi pit to QB plant
• Estimates reflect the most up-to-date and detailed assessment of integration potential, with data from both operations, and review and validation by external advisors
• As the only shareholder in both ventures, Anglo Teck is well-positioned to work with a reduced number of partners to facilitate the capture of this substantial value upside for shareholders of both assets

“The value that will be created in combining Teck and Anglo American – for shareholders of both companies, QB-Collahuasi partners, and our customers, employees and the communities where we operate – is clear and compelling,” said Price. “We are advancing our work to realize this incredible potential and are excited to bring together two great companies to form a global critical minerals champion and top five global copper producer with leading copper exposure and growth optionality.”

Webcast Details
President and Chief Executive Officer Jonathan Price and members of Teck’s executive management team will be presenting on Monday, November 3, 2025 from 10:55 a.m. to 1:30 p.m. Eastern / 7:55 a.m. to 10:30 a.m. Pacific time as part of Teck’s QB Operations Site Visit.

A webcast to view the event will be held as follows: 

Date: Monday, November 3, 2025
Time: 10:55 a.m. ET / 7:55 a.m. PT
Listen-Only Webcast: here

An archive of the webcast will be available at teck.com within 24 hours.

Forward Looking Statements
This news release contains certain forward-looking information and forward-looking statements as defined in applicable securities laws (collectively referred to as forward-looking statements). These statements relate to future events or future performance. All statements other than statements of historical fact are forward-looking statements. The use of any of the words “anticipate”, “can”, “could”, “plan”, “continue”, “estimate”, “expect”, “may”, “will”, “would”, “project”, “predict”, “likely”, “potential”, “should”, “believe” and similar expressions is intended to identify forward-looking statements. These statements involve known and unknown risks, uncertainties and other factors that may cause actual results or events to differ materially from those anticipated in such forward-looking statements. These statements speak only as of the date of this news release. These forward-looking statements include, but are not limited to, statements regarding expansion potential of QB and pathways for long term growth; the implementation and impact of the QB action plan, including the timing, outcome, and effectiveness thereof; our ability to meet mill throughput and recovery guidance; our ability to accelerate and advance QB tailings management facility development, including expectations for the timing and completion of the construction of rock benches, replacement of cyclones, and completion of the sand dam; the anticipated benefits and synergies from the proposed Merger; the expected effects of the Merger on Anglo American and Teck; our expectations with respect to potential underlying synergies between QB and Collahuasi; the expected effects and valuation of the Merger on Anglo American and Teck; and other statements that are not historical facts.

These statements are based on a number of assumptions, including, but not limited to, assumptions regarding general business and economic conditions, future outlook and anticipated events, such as our expectations with respect to the potential of QB, including design, construction, operational capacity and expansion potential; our expectations with respect to ore grades; our ability to identify and implement solutions to enable ramp-up, accelerate and improve sand drainage, strengthen execution, and resolve other constraints on QB production, including the timeline for implementing such solutions; our expectations regarding cost, timing and completion of tailing management facility development at our QB operations; our ability to improve our planning, forecasting and reconciliation processes to support operational readiness and enable informed decision-making and risk management; our expectations with respect to the occurrence, timing and length of required maintenance shutdowns and equipment replacement; our expectations with respect our previously issued guidance, including with respect to production, sales, cost, unit cost, capital expenditure, capitalized stripping, operating outlook, recovery, mill throughput, and other guidance the ability of Anglo American and Teck to complete the Merger, including obtaining all required regulatory and shareholder approvals; expectations with respect to the strategy, production capabilities and future financial or operating performance of Teck and Anglo American following the Merger; the potential valuation of the merger of Teck and Anglo American; the expected synergies between Teck and Anglo American, including between the QB and Collahuasi operations; the expected revenue from the synergies between Teck and Anglo American; the success of the new board and management team; the satisfaction of the conditions precedent to the Merger; the potential of Teck and Anglo American following the merger to meet industry target, public profile expectations, future plans, projections, objectives, estimates and forecasts and the timing related thereto. The foregoing list of assumptions is not exhaustive. Events or circumstances could cause actual results to vary materially.

Forward-looking information is based on the information available at the time those statements are made and are of good faith belief of the officers and directors of Teck with respect to future events and are subject to risks and uncertainties that could cause actual results to differ materially from those expressed in the Forward-looking information. Factors that may cause actual results to vary materially include, but are not limited to, expectations with respect to the implementation of the QB action plan and our ability to successfully resolve constraints related to the QB tailings management facility; the possibility that the Merger will not be completed on the terms and conditions, or on the timing, currently contemplated or at all, due to a failure to obtain or satisfy, in a timely manner or otherwise, required regulatory, shareholder and court approvals and other conditions to the closing of the Merger; the risk that competing offers or acquisition proposals will be made; public perception of the Merger, market reaction to the Merger, the negative impact that the failure to complete the Merger for any reason could have on the business of Anglo American or Teck; general economic and market conditions, including interest and foreign exchange rates, global financial markets, changes in government regulations or in tax laws; industry competition; technological developments and other factors described or discussed in Teck’s disclosure materials filed with applicable securities regulatory authorities from time to time.

Teck assumes no obligation to update forward-looking statements except as required under securities laws. Further information concerning risks, assumptions and uncertainties associated with these forward-looking statements and Teck’s business can be found in Teck’s Annual Information Form for the year ended December 31, 2024 filed under our profile on SEDAR+ (www.sedarplus.ca) and on EDGAR (www.sec.gov) under cover of Form 40-F, as well as subsequent filings that can also be found under Teck’s profile.

About Teck
Teck is a leading Canadian resource company focused on responsibly providing metals essential to economic development and the energy transition. Teck has a portfolio of world-class copper and zinc operations across North and South America and an industry-leading copper growth pipeline. We are focused on creating value by advancing responsible growth and ensuring resilience built on a foundation of stakeholder trust. Headquartered in Vancouver, Canada, Teck’s shares are listed on the Toronto Stock Exchange under the symbols TECK.A and TECK.B and the New York Stock Exchange under the symbol TECK. Learn more about Teck at www.teck.com or follow @TeckResources.

Investor Contact:
Emma Chapman
Vice President, Investor Relations
+44.207.509.6576
emma.chapman@teck.com

Media Contact:
Dale Steeves
Director, External Communications
236.987.7405
dale.steeves@teck.com

25-29-TR

UK factories staged a recovery in October after the reopening of Jaguar Land Rover operations and a pick-up in consumer spending, according to a closely watched survey of the manufacturing sector.

The S&P Global purchasing managers’ index (PMI) rose to a one-year high as business optimism improved and factory output expanded.

Jaguar Land Rover, Britain’s biggest carmaker, supported the recovery after it began reopening facilities hit by a cyber-attack that some experts estimated cost the UK economy about £1.9bn.

Manufacturers were able to shake off some of the uncertainty from Donald Trump’s tariffs. Consumers also increased spending on new cars, improving the outlook for the makers of vital industrial components.

S&P Global said the PMI rose to 49.7 in October from 46.2 in September, where a figure above 50 indicates expansion. A sub-index measuring factory output jumped sharply to 51.6 from 45.7 in September, signalling a return to growth.

Martin Beck, the chief economist at the consultants WPI Strategy, said there were reasons to be optimistic about a recovery gathering pace.

“Rising real wages should underpin domestic demand for goods, while government incentives for green technologies and battery production could boost investment,” he added.

“The recent depreciation of sterling against the dollar and euro also improves UK export competitiveness. And the government’s decision to increase the discount on electricity network charges for energy-intensive industries offers some relief on costs.”

However, Mike Thornton, the head of industrials at the accountants RSM UK, said: “While the uptick in manufacturing activity in October shows a reverse on the downward trend seen in August and September, only time will tell if this is a temporary rebound in output rather than a sustained recovery.

“Following Jaguar Land Rover’s phased production restart in October, it’s likely that this has created a ripple effect throughout the supply chain, particularly as the shutdown impacted more than 5,000 middle-market businesses.”

The UK’s manufacturing sector has suffered a succession of blows since the Covid pandemic. Industry bodies have complained that a steep rise in gas and electricity costs, in addition to rising wages and higher employment taxes, have crippled many businesses.

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The British Chambers of Commerce, the CBI and Make UK, the manufacturing lobby group, have called on the chancellor to give extra support to the manufacturing sector in the budget later this month.

Rob Dobson, a director at S&P Global Market Intelligence, said: “There are concerns the forthcoming budget will exacerbate the lingering challenges created by last year’s budget, especially in relation the impact of national minimum wage and employer national insurance on costs, demand and production.

“This means that business optimism remains below its long-run average despite rising to an eight-month high in October.

“Manufacturers seem to be stuck in a holding pattern until the domestic policy and geopolitical backdrops exhibit greater clarity.”