Eli Lilly (United States)

Capillary electrophoresis (CE) often provides superior separation of macromolecules such as monoclonal antibodies (mAbs), a major biopharmaceutical class, compared with liquid chromatography. However, electropherograms frequently exhibit complex baselines and peak shapes that are not reliably handled by integration algorithms designed for chromatographic data, and manual integration is often required. Many concepts have been proposed to improve peak integration, ranging from incremental algorithmic refinements and signal-to-noise (S/N)-based approaches to artificial intelligence (AI)-driven strategies, but objective performance comparisons are not possible without shared reference data sets and agreed peak limits. To address this gap, we initiated a multinational collaboration involving industrial and academic laboratories to create a comprehensive reference data set for CE peak integration. A total of 227 challenging and practically relevant electropherograms were collected from diverse applications, converted to a standardized format, and independently integrated by multiple experts. Using dedicated software tools and a structured consensus process, mutually accepted reference integration limits were established for each data set. These reference electropherograms, together with the underlying integration rules, are now made available to the scientific community. Analysis of the reference data set identified general principles for reliable peak integration, including the importance of standardized zoom levels and consistent handling of small peaks near the noise level. The data set provides a common foundation for benchmarking commercial chromatography data systems (CDS) and for developing and validating new algorithmic and AI-based integration methods. We expect this work to speed up the development of practical, automated integration strategies for CE and that these core concepts can be applied to other separation techniques.

Introduction and Objectives: Lebrikizumab received U.S. Food and Drug Administration approval on September 13, 2024, for adults and adolescents (≥12 years, ≥40 kg) with moderate-to-severe atopic dermatitis (AD). The recommended dosing regimen consists of a 500-mg loading dose (two 250-mg injections) at Week 0 and Week 2, followed by 250 mg every 2 weeks (Q2W) until Week 16 or adequate clinical response. The approved maintenance dose is lebrikizumab 250 mg every 4 weeks (Q4W). Due to prescribing information (PI) flexibility and clinician discretion, real-world evidence describing the proportion of patients who transition to lebrikizumab Q4W dosing is warranted. Methods: We assessed the proportion of patients treated with lebrikizumab who transitioned from Q2W to Q4W dosing using the IQVIA Longitudinal Access and Adjudication Data (LAAD) database. Patients who initiated lebrikizumab between September 13, 2024, and August 31, 2025 were identified; only final paid claims were included. The index date was defined as the date of the first paid lebrikizumab prescription. Patients were required to be ≥12 years old and to have pharmacy activity for ≥6 months following the index date. Data from weeks 16, 20, and 24 were assessed. If a patient receives five lebrikizumab prescriptions (28-day supply), the first, consistent opportunity to move to Q4W dosing per the label is at Week 16. However, the first opportunity to identify an Q4W dosing interval in the data would be between fills five and six, Week 16 and 20. Results: Overall, 2,948 patients were included had pharmacy activity for ≥6 months and were ≥12 years old. The mean age of the study population was 44.1 years (SD 18.9). The majority (78.6%) of patients utilizing lebrikizumab were 18–64 years. Among patients who initiated lebrikizumab, Q2W dosing, and had ≥5 lebrikizumab claims (n = 1,717) over 6 months, 72.7% had transitioned from Q2W to Q4W dosing by Week 16, 83.3% by Week 20, and 88.1% by Week 24. Of the 83.3% of patients that transitioned from Q2W to Q4W dosing by Week 20, the average time (mean) to dosing transition (Q2W to Q4W) was 13.3 weeks. Conclusion: By Week 20, 83.3% of patients receiving lebrikizumab transitioned to Q4W maintenance dosing, a proxy for adequate clinical response. This analysis was restricted to patients with consistent lebrikizumab fills and is subject to the inherent limitations of claims administrative data. Additional research will further elucidate broader lebrikizumab treatment patterns. Funding sources: this study was funded by Eli Lilly and Company.

This paper proposes a propensity score (PS)-based stratified win ratio method to address challenges of small patient populations in clinical trials, especially for rare or pediatric diseases, by incorporating external control data. Our approach enhances traditional win ratio analysis by leveraging PS stratification to account for heterogeneity between the current and external studies. Additionally, down-weighting based on the overlapping coefficient of PS distributions of current treatment and external control groups further mitigates the patient bias due to heterogeneity. Simulations show significant improvements in statistical power for detecting treatment effects within the composite endpoint combining continuous and time-to-event components, over nonborrowing and pooling methods, with utilizing Mantel-Haenszel (MH)-type weights achieving the highest power. The proposed methods are also applied to an amyotrophic lateral sclerosis (ALS) study incorporating the external control arm from a prior ALS trial. The proposed PS-based stratified win ratio method thus provides a rigorous framework for borrowing external data and analyzing composite endpoints with limited patient availability.

Recent clinical success for RNA therapeutics supports the promise of these modalities to unlock additional drug targets with pharmacodynamic responses that are considerably more durable than other drug classes. Metabolic clearance in tissue is a key determinant of dosing requirements and therapeutic durability. To build our understanding of the mechanisms of RNA metabolic clearance, we quantified the catalytic efficiency of 3'- and 5'-exonucleases, and endonucleases in S9 fractions from various rat tissues using novel fluorescent RNA probes. We validated the specificity of these probes using recombinant nucleases and rat liver S9 fractions, demonstrating their ability to accurately report enzyme activity without cross-reactivity between nuclease classes. Key experimental parameters, such as solution pH and enzyme-substrate ratios, were optimized to maximize dynamic range. Profiling nuclease activity across various rat tissues revealed tissue-specific variations, with kidney, muscle, and plasma showing the highest catalytic efficiency for 3' exonuclease, 5' exonuclease, and endonuclease, respectively. Using a model siRNA targeting hypoxanthine phosphoribosyltransferase, comparative degradation studies in rat liver homogenate, liver S9 fractions, and liver tritosomes revealed divergent metabolic profiles; S9 fractions and homogenate processed both double-stranded siRNA and single-stranded antisense RNA to a similar extent, whereas in tritosomes single-stranded RNA was observed to be degraded more rapidly than a double-stranded form. These differences are consistent with distinct nuclease activities in each compartment, reflecting both enzyme identity and relative abundance as revealed by the probe analyses. Collectively, these findings offer critical mechanistic insights into RNA metabolism and establish a robust platform to improve the development and predictability of siRNA therapeutics. SIGNIFICANT STATEMENT: Metabolic clearance of RNA therapeutics is a critical determinant of their pharmacological durability and potency. This work quantitatively describes the activity of 3 major classes of ribonucleases within various tissues and subcellular compartments, revealing specific patterns of RNA metabolism and enable discovery of novel RNA therapeutics with improved pharmacokinetic properties.

To assess the relationship between haemoglobin A1c (HbA1c) levels and incidence of long-term complications in patients with type 2 diabetes (T2D). This long-term, retrospective study acquired patient data from the Swedish National Diabetes Registry and linked national registers between 1 January 1998 and 31 December 2019. The incidence rates (IR) of microvascular/macrovascular outcomes and cardiovascular death were reported for the overall study population. The hazard ratios (HR) for these outcomes were compared across HbA1c ranges assessed over time and between the early HbA1c control groups: early tight control (HbA1c ≤6.5%), no early tight control (HbA1c >6.5%), and early adverse control (HbA1c >7%), from 18 months after diagnosis. 57.2% of the overall population were male and a median age of 60 years. The IR per 100-patient-years of any microvascular complication remained relatively stable (2005: 8.75; 2014: 10.95; 2019: 8.71), while cardiovascular death increased from 2005 (IR: 0.12) to 2018 (IR: 0.46). Incidences of any macrovascular complication increased with HbA1c ranges (8.0% to <9.0%, HR:1.16 [95%CI: 1.12-1.20]; 7.0% to <8.0%, HR:1.08 [95%CI: 1.05-1.11]) compared to reference (6.0 to <7.0%). Between early HbA1c control groups, the rates of any microvascular/macrovascular complication, and cardiovascular death were reduced in the reference early tight control group compared to the no early tight control group (HR:0.84 [95%CI: 0.80-0.89]; HR:0.86 [95%CI: 0.79-0.93]; and HR:0.60 [95%CI: 0.46-0.79], respectively), with similar results achieved compared to the early adverse control group. Elevated HbA1c levels were closely associated with long-term complications, while early tight control of HbA1c corresponded to significantly improved clinical outcomes in patients with T2D.

The ICH Guideline M10, adopted by the EMA in July 2022 and implemented in January 2023, recommends that stability testing of quality controls (QCs) should match actual sample analyte concentrations, prompting adjustments in QC levels when samples exceed analytical ranges. Laboratories continue long-term stability (LTS) testing on ultra-high concentration quality controls (UHQCs) which are often defined by multiples of the upper limit of quantification (ULOQ) rather than observed maximum concentrations (Cmax). Based on recommendations for implementation of the M10 Guideline regarding Phase 3 clinical trials, we questioned the need for further LTS testing at UHQC levels beyond Phase 2. To address LTS timeline challenges, incurred sample reproducibility (ISR) data from clinical studies were compiled, evaluating their relevance to Cmax and utilizing a Random Intercept Model (RIM) as a tool for establishing stability profiles for drug analytes. Analysis showed most UHQCs estimated using simple ULOQ multiples may not accurately reflect Cmax. Clinical ISR data provided evidence of stability across analyte concentrations within patient matrices with a high degree of confidence. Predictive tools based on ISR data were proposed as a practical approach to demonstrate stability. ISR data can support claims of analyte stability including at ultra-high concentrations, consistent with the M10 guideline and established LTS from validation testing. Using ISR from clinical reports reduces reliance on lengthy LTS testing, offering a robust, efficient method for establishing stability profiles from real-world samples to accomplish regulatory expectations while optimizing workflows.