Changes in metabolic overweight phenotypes over time and risk of nephrolithiasis: a cohort study.

BACKGROUND: Overweight/obesity is considered an independent risk factor for nephrolithiasis, but little is known about its effect on nephrolithiasis according to metabolic health status. OBJECTIVES: We aimed to investigate the association between various metabolic overweight phenotypes and the occurrence of nephrolithiasis. It also explores whether changes in these phenotypes over time influence the risk of nephrolithiasis. MATERIALS AND METHODS: A total of 10,315 participants free of nephrolithiasis who underwent an annual health checkup from 2017 to 2022 were included in our prospective cohort study. They were categorized into four groups according to the presence of overweight and metabolic abnormalities (MA). The primary endpoint was the occurrence of renal stones. Multivariable Cox analysis was conducted to elucidate the relationship between metabolic overweight phenotypes and incident nephrolithiasis. RESULTS: During a median follow-up duration of 4.02 years, nephrolithiasis occurred in 1,468 (14.23%) participants. In the full cohort, we observed that the 5-year cumulative incidences of nephrolithiasis were highest in the metabolically healthy overweight (MHO) and metabolically abnormal overweight (MAO) groups. The hazard ratios (HRs) for nephrolithiasis, relative to metabolically healthy normal weight (MHNW), ranged from 1.19 (95% CI:1.03-1.37; MHO) to 1.32 (95% CI:1.15-1.51; MAO). Furthermore, individuals with persistent MHO throughout follow-up were at a 1.42-fold increased risk of nephrolithiasis (P < 0.001), and 32.17% of individuals experienced changes in phenotype during follow-up. Among MAO subjects, those who transitioned to MHO and MHNW had a 26% and 45% lower risk of incident nephrolithiasis, respectively, compared to those who persisted in the MAO phenotype. CONCLUSION: Individuals in the MHO and MAO groups exhibit an elevated risk of incident nephrolithiasis in this prospective cohort study. A significant proportion of nephrolithiasis cases may be potentially preventable through the appropriate management of metabolic risk factors for MAO subjects.

Implications of Immunogenicity Testing for Therapeutic Monoclonal Antibodies: A Quantitative Pharmacology Framework.

The interpretation of immunogenicity results for a mAb product and prediction of its clinical consequences remain difficult, despite enormous advances in methodologies and efforts toward the best practice for consistent data generation and reporting. To this end, the contribution from the clinical pharmacology discipline has been largely limited to comparing descriptively the pharmacokinetic (PK) profiles by antidrug antibodies (ADA) status or testing the significance of ADA as a covariate in a population PK setting, similar to the practice for small-molecule drugs in investigating the effect of an intrinsic/extrinsic factor on the drug disposition. There is a need for a mAb disposition framework that captures the dynamics of ADA formation and drug's interactions with the ADA and target as parts of the drug distribution and elimination. Here we describe such a framework and examine it against the PK, ADA, and clinical response data from a phase 3 trial in patients treated with adalimumab. The proposed framework offered a generalized understanding of how the dose, target affinity, and drug/ADA analyte forms affects the manifestation of ADA response with regard to its detections and alterations of drug disposition and effectiveness. Furthermore, as an example, its utility for dose considerations was demonstrated through predicting for late-stage trials of a PCSK9 inhibitor in terms of development in ADA incidence and titers, and consequences on the drug disposition, interaction with target, and downstream lowering effect on LDL-C.

Oncology Combination Dose-Finding Study Design for Targeted and Immuno-Oncology Therapies.

Combination therapies are often evaluated during the clinical development of oncology investigational agents. A new investigational agent may be combined with one or more approved agent(s) or investigational agent(s). As the initial step to test combination therapies, combination dose escalation of an investigational agent and an approved drug is generally conducted using one of the following designs: sequential design, parallel (staggered) design, healthy participant first-in-human prior to first-in-patient combination escalation, monotherapy lead-in (intra-patient "crossover"), and potentially combination escalation (no monotherapy component). Dose-finding studies for the combinations of two investigational agents may follow similar principles and considerations, and a more conservative approach may be required. A comparison of the characteristics of these designs indicates an efficient design should consider factors including the predicted difference in dose/exposure-response relationships between monotherapy and combination therapy, any potential for pharmacokinetic and pharmacodynamic interactions between the combinatory agents, and the benefit/risk to study participants, etc. In this report, we propose application scenarios for each trial design based on the above considerations and a review of the internal database and published external studies. Generation of robust exposure-response data via an appropriate design will assist the selection of appropriate doses for further assessment to support optimal dose selection as encouraged by the US Food and Drug Administration based on Project Optimus.

Realizing the promise of Project Optimus: Challenges and emerging opportunities for dose optimization in oncology drug development.

Project Optimus is a US Food and Drug Administration Oncology Center of Excellence initiative aimed at reforming the dose selection and optimization paradigm in oncology drug development. This project seeks to bring together pharmaceutical companies, international regulatory agencies, academic institutions, patient advocates, and other stakeholders. Although there is much promise in this initiative, there are several challenges that need to be addressed, including multidimensionality of the dose optimization problem in oncology, the heterogeneity of cancer and patients, importance of evaluating long-term tolerability beyond dose-limiting toxicities, and the lack of reliable biomarkers for long-term efficacy. Through the lens of Totality of Evidence and with the mindset of model-informed drug development, we offer insights into dose optimization by building a quantitative knowledge base integrating diverse sources of data and leveraging quantitative modeling tools to build evidence for drug dosage considering exposure, disease biology, efficacy, toxicity, and patient factors. We believe that rational dose optimization can be achieved in oncology drug development, improving patient outcomes by maximizing therapeutic benefit while minimizing toxicity.

A comprehensive regulatory and industry review of modeling and simulation practices in oncology clinical drug development.

Exposure-response (E-R) analyses are an integral component in the development of oncology products. Characterizing the relationship between drug exposure metrics and response allows the sponsor to use modeling and simulation to address both internal and external drug development questions (e.g., optimal dose, frequency of administration, dose adjustments for special populations). This white paper is the output of an industry-government collaboration among scientists with broad experience in E-R modeling as part of regulatory submissions. The goal of this white paper is to provide guidance on what the preferred methods for E-R analysis in oncology clinical drug development are and what metrics of exposure should be considered.

PK/PD model-informed dose selection for oncology phase I expansion: Case study based on PF-06939999, a PRMT5 inhibitor.

The optimal dose for targeted oncology therapeutics is often not the maximum tolerated dose. Pharmacokinetic/pharmacodynamic (PK/PD) modeling can be an effective tool to integrate clinical data to help identify the optimal dose. This case study shows the utility of population PK/PD modeling in selecting the recommended dose for expansion (RDE) for the first-in-patient (FIP) study of PF-06939999, a small-molecule inhibitor of protein arginine methyltransferase 5. In the dose escalation part of the FIP trial (NCT03854227), 28 patients with solid tumors were administered PF-06939999 at 0.5 mg, 4 mg, 6 mg, or 8 mg once daily (q.d.) or 0.5 mg, 1 mg, 2 mg, 4 mg, or 6 mg twice daily (b.i.d.). Tolerability, safety, PK, PD biomarkers (plasma symmetrical dimethyl-arginine [SDMA]), and antitumor response were assessed. Semimechanistic population PK/PD modeling analyses were performed to characterize the time-courses of plasma PF-06939999 concentrations, plasma SDMA, and platelet counts collected from 28 patients. Platelet counts were evaluated because thrombocytopenia was the treatment-related adverse event with clinical safety concern. The models adequately described the PK, SDMA, and platelet count profiles both at individual and population levels. Simulations suggested that among a range of dose levels, 6 mg q.d. would yield the optimal balance between achieving the PD target (i.e., 78% reduction in plasma SDMA) and staying below an acceptable probability of developing grade ≥3 thrombocytopenia. As a result, 6 mg q.d. was selected as the RDE. The model-informed drug development approach informed the rational dose selection for the early clinical development of PF-06939999.

Association between serum uric acid/HDL-cholesterol ratio and chronic kidney disease: a cross-sectional study based on a health check-up population.

OBJECTIVE: Evidence suggests that both serum uric acid (SUA) and high-density lipoprotein cholesterol (HDL-C) are risk factors for chronic kidney disease (CKD). The SUA-to-HDL-C ratio (UHR) has recently attracted attention as a new biomarker to evaluate the role between inflammatory and anti-inflammatory substances. Thus, we explored the association between UHR and CKD in a large Chinese population. DESIGN: A cross-sectional study. SETTING: Annual health check-up population in Nanjing. PARTICIPANTS: 19 458 individuals who underwent an annual health check-up in 2019 were included in our study. MAIN OUTCOME MEASURE: CKD was diagnosed according to an estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2. RESULTS: Correlation analysis showed that UHR was negatively associated with eGFR after adjusting for confounding factors (r=-0.34). In addition, participants in the highest quartile of UHR had a higher risk of CKD than those in the lowest quartiles (OR=9.28, p<0.001). CONCLUSION: We found that high UHR values were positively associated with CKD risk in health check-up population. An increased UHR may be a useful measure by which to assess CKD risk in the preclinical stage.

Oncology dose optimization paradigms: knowledge gained and extrapolated from approved oncology therapeutics.

There has been increasing attention to dose optimization in the development of targeted oncology therapeutics. The current report has analyzed the dose selection approaches for 116 new molecular entities (NMEs) approved for oncology indications by the US FDA from 2010 to August 2021, with the goal to extract learnings about the ways to select the optimal dose. The analysis showed that: (1) the initial label dose was lower than the maximum tolerated dose (MTD) or maximum studied dose (MSD) in Phase 1 for the majority of approved NMEs, and that the MTD approach is no longer the mainstay for dose selection; (2) there was no dose ranging or optimization beyond Phase 1 dose escalation for ~ 80% of the NMEs; (3) integrated dose/exposure-response analyses were commonly used to justify the dose selection; (4) lack of dose optimization led to dose-related PMRs/PMCs in 14% of cases, but 82% of these did not result in change of the initial label dose; and (5) depending on properties of the NME and specific benefit/risk considerations for the target patient population, there could be different dose selection paradigms leading to identification of the appropriate clinical dose. The analysis supports the need to incorporate more robust dose optimization during oncology clinical development, through comparative assessment of benefit/risk of multiple dose levels, over a wide exposure range using therapeutically relevant endpoints and adequate sample size. On the other hand, in certain cases, data from FIP dose escalation may be adequate to support the dose selection.

Joint Disposition Properties and Comprehensive Pharmacokinetic Characterization of Antibody-Drug Conjugates.

Antibody-drug conjugates (ADCs) comprise 3 distinct parts: a specific antibody carrier (mAb), a linker, and a cytotoxic payload. Typical pharmacokinetic (PK) characterization of ADCs remains fragmented using separate noncompartmental analyses (NCA) of individual analytes, offering little insight into the dynamic relationships among the ADC components, and the safety and efficacy implications. As a result, it is exceedingly difficult to compare ADCs in terms of favorable PK characteristics. Therefore, there is a need for characterizing ADCs using the joint disposition properties critical for understanding the fate of an ADC complex and clinical implications. In this communication, we describe 3 joint disposition metrics (JDMs) for integrated NCA of ADCs based on a combination of common analytes of ADC, payload, conjugated payload, and total mAb. These JDMs were derived, each in a simple form of a ratio between appropriate PK parameters of two analytes, from the presumed drug delivery scheme behind typical ADC designs, in terms of (1) linker stability, (2) therapeutic exposure ratio, and (3) effective drug-to-antibody ratio in vivo. The validity of the JDM-based PK characterization was examined against model-based analyses via their applications to 3 clinical candidates: PF-06650808, PF-06647020, and PF-06664178. For instance, the linker stability estimates for PF-06650808, PF-06647020, and PF-06664178 were 0.31, 0.14, and 0.096, respectively, from the JDM-based analyses vs. 0.23, 0.11, and 0.086 by the model-based approach. Additionally, the JDMs were estimated for a number of FDA-approved or otherwise well-documented ADCs, showing their utilities in comparing ADCs in terms of favorable PK characteristics.

Starting dose selection and dose escalation for oncology small molecule first-in-patient trials: learnings from a survey of FDA-approved drugs.

The ideal starting dose for an oncology first-in-patient (FIP) trial should be low enough to be safe but not too far removed from therapeutically relevant doses. A low starting dose combined with small dose increments could lead to a lengthy dose escalation and could expose patients unnecessarily to sub-therapeutic dosing. In the current analyses, we reviewed 59 approved small molecule oncology drugs (SMOD) with the overarching goals to assess the current approaches of FIP starting dose selection and dose escalation, and to identify potential opportunities for improving trial efficiency and minimizing number of patients receiving sub-therapeutic dose levels. Of 59 SMODs, the majority (~ 66%) were kinase inhibitors and ~ 73% were approved for solid tumor indications. Most of the trials used a 3 + 3 design for dose escalation and had a median (range) of 4 cohorts (0-11) to reach MTD from the starting dose. The maximum tolerated dose (MTD) or recommended phase 2 dose (RP2D) to starting dose ratio was highly variable with a median (range) of 8 (0.25-125). About 71% of the FIP trials had < 6 dose escalation steps to reach MTD or RP2D (with 15% ≤ 2 dose escalations), but the remaining 29% of trials had ≥ 6 dose escalation steps to reach MTD or RP2D suggesting that there is still room for increasing efficiency by reducing the number of dose escalation steps, reducing the variability in MTD to starting dose ratio, and consequently reducing significant number of patients exposed at sub-therapeutic doses in the dose escalation phase of FIP study.

A mechanistic pharmacokinetic model with drug and antidrug antibody interplay, and its application for assessing the impact of immunogenicity response on bioequivalence testing.

AIMS: Single-dose pharmacokinetic (PK) studies in healthy subjects have been the design of choice for bioequivalence determination for decades. This preference has been recently extended to PK similarity studies of proposed biosimilars. However, PK similarity studies can be complicated by the effect of immunogenicity response on drug disposition. The impact is exacerbated when there is an imbalance in host-specific immunological characteristics of subjects between the test and reference groups. Such complications remain poorly understood. The purpose of this communication is to show that the impact of immunogenicity response on PK similarity determination can be critical, using adalimumab as an example. METHODS: Data for adalimumab concentrations and immunogenicity response over 10 weeks were obtained from 133 healthy subjects receiving a 40 mg dose of Humira® in a PK similarity study. Also, a population PK model with a mechanistic construct for delineating the interplay between adalimumab disposition and antidrug antibodies response was utilized to estimate via simulation the probability that a PK similarity study would fail in typical study settings. RESULTS: The simulations showed that the immunogenicity response can have a profound impact on the outcome of PK similarity determination. As such, the probability of failing to achieve the similarity conclusion increased to 51.9%, from 13.8% in the absence of immunogenicity response. CONCLUSION: This study provides a model-based framework for better understanding of how a PK similarity study can be optimally designed and for interpretation of the outcome of PK similarity determination when the drug disposition is affected in the presence of immunogenicity response.

Phase 1b study of a small molecule antagonist of human chemokine (C-C motif) receptor 2 (PF-04136309) in combination with nab-paclitaxel/gemcitabine in first-line treatment of metastatic pancreatic ductal adenocarcinoma.

Background In pancreatic ductal adenocarcinoma (PDAC), the chemokine (C-C motif) ligand 2 (CCL2)/chemokine (C-C motif) receptor 2 (CCR2) axis plays a key role in immunosuppressive properties of the tumor microenvironment, patient prognosis, and chemoresistance. This phase Ib study assessed the effects of the orally administered CCR2 inhibitor PF-04136309 in combination with nab-paclitaxel and gemcitabine in patients with previously untreated metastatic PDAC. Methods Patients received PF-04136309 twice daily (BID) continuously plus nab-paclitaxel (125 mg/m2) and gemcitabine (1000 mg/m2) administered on days 1, 8, and 15 of each 28-day cycle. The primary objectives were to evaluate safety and tolerability, characterize dose-limiting toxicities (DLTs), and determine the recommended phase II dose (RP2D) of PF-04136309. Results In all, 21 patients received PF-04136309 at a starting dose of 500 mg or 750 mg BID. The RP2D was identified to be 500 mg BID. Of 17 patients treated at the 500 mg BID starting dose, three (17.6%) experienced a total of four DLTs, including grade 3 dysesthesia, diarrhea, and hypokalemia and one event of grade 4 hypoxia. Relative to the small number of patients (n = 21), a high incidence (24%) of pulmonary toxicity was observed in this study. The objective response rate for 21 patients was 23.8% (95% confidence interval: 8.2-47.2%). Levels of CD14 + CCR2+ inflammatory monocytes (IM) decreased in the peripheral blood, but did not accumulate in the bone marrow. Conclusions PF-04136309 in combination with nab-paclitaxel plus gemcitabine had a safety profile that raises concern for synergistic pulmonary toxicity and did not show an efficacy signal above nab-paclitaxel and gemcitabine. ClinicalTrials.gov identifier: NCT02732938.

Correction to: Population pharmacokinetics of PF­05280014 (a trastuzumab biosimilar) and reference trastuzumab (Herceptin®) in patients with HER2­positive metastatic breast cancer.

The article "Population pharmacokinetics of PF-05280014 (a trastuzumab biosimilar) and reference trastuzumab (Herceptin®) in patients with HER2-positive metastatic breast cancer" written by Xiaoying Chen, Cheryl Li, Reginald Ewesuedo, Donghua Yin was originally published electronically on the publisher's internet portal (currently SpringerLink) on 3rd May 2019 without open access.

Population pharmacokinetics of PF-06438179/GP1111 (an infliximab biosimilar) and reference infliximab in patients with moderately to severely active rheumatoid arthritis.

Background: PF-06438179/GP1111 (PF-SZ-IFX) is an infliximab (IFX) biosimilar. Pharmacokinetic (PK) similarity of PF-SZ-IFX and reference IFX authorized in the European Union (ref-IFX-EU) and in the US (ref-IFX-US) was demonstrated in healthy subjects. Safety and efficacy of PF-SZ-IFX were investigated in a multinational, double-blind, randomized study in rheumatoid arthritis (RA) patients. This work aims to evaluate the population pharmacokinetics (PopPK) of ref-IFX-EU and PF-SZ-IFX in RA patients. Research design and methods: Patients with moderately to severely active RA (N = 650) were randomized 1:1 to PF-SZ-IFX or ref-IFX-EU. PopPK modeling with data collected from the study was performed using a nonlinear mixed-effects approach (NONMEM 7.2.0). Results: The PK of ref-IFX-EU and PF-SZ-IFX were adequately described using a two-compartment model with linear elimination. Clearance (CL) estimates were 0.014 L/h and 0.015 L/h for PF-SZ-IFX and ref-IFX-EU, with inter-individual variability (IIV) on CL of 43.1% and 40.1%, respectively. Volumes of distribution in the central compartment (V1) were 3.38 L and 3.57 L, with IIV on V1 of 28.1% and 23.7%, respectively. The same covariates of sex and antidrug antibody titers on CL, and body weight on V1, influenced the PK variability of ref-IFX-EU and PF-SZ-IFX. Conclusions: PopPK analysis revealed no appreciable differences between the PK of ref-IFX-EU and PF-SZ-IFX in RA patients. Trial registration: The trial is registered at ClinicalTrials.gov (CT.gov identifier: NCT02222493).

Time trend of cardiometabolic risk factors over a 10-year period in the office-working population in China.

OBJECTIVES: Recent dramatic increases in cardiovascular disease mortality in China can be mostly explained by adverse changes in hypertension, dyslipidaemia, diabetes and obesity, known as cardiometabolic risk factors. Our study aimed to assess the trend of these four signatures by a 10-year lag in Nanjing, China. METHODS: 8017 subjects attended the routine health examination in 2008, and 9379 subjects in 2017, from multiple work units of Nanjing, were included in the present study. The prevalence and trend of four cardiometabolic risk factors: hypertension, dyslipidaemia, diabetes and obesity were analysed. RESULTS: From 2008 to 2017, the prevalence of hypertension declined, while the prevalence of dyslipidaemia, diabetes and obesity increased. Besides, the population in 2008 and 2017 had an average of 0.66 and 0.78 risk factors, respectively. CONCLUSION: Cardiometabolic risk factors are common for the staff in administrative agencies and institutions of Nanjing, China. Effective screening and interventions against these risk factors should be adopted in high-risk populations such as the office-working population in China.

Population pharmacokinetics of PF-05280014 (a trastuzumab biosimilar) and reference trastuzumab (Herceptin®) in patients with HER2-positive metastatic breast cancer.

PURPOSE: PF-05280014 is a biosimilar to trastuzumab (Herceptin®). Following demonstration of pharmacokinetic (PK) similarity in healthy volunteers, a comparative clinical study in patients with HER2-positive metastatic breast cancer (mBC) compared the efficacy, safety and immunogenicity of PF-05280014 and trastuzumab sourced from the EU (trastuzumab-EU), both with paclitaxel. METHODS: Population PK of PF-05280014 and trastuzumab-EU was evaluated. RESULTS: Overall, 702 patients were treated: PF-05280014 (n = 349) and trastuzumab-EU (n = 353). Peak-and-trough serum drug concentration samples were collected (selected doses) following repeated intravenous administration of PF-05280014 or trastuzumab-EU. Population PK analysis was performed with drug concentration-time data to cycle 17 for each compound, using nonlinear mixed effect modeling. Potential baseline covariates (circulating HER2 concentrations, body weight, Japanese race, Eastern Cooperative Oncology Group status, number of metastatic sites and antidrug antibody status) were evaluated. Concentration-time data of PF-05280014 and trastuzumab-EU were adequately described by a two-compartment model with first-order elimination, with inter-individual variability (IIV) on clearance (CL), volumes of distribution in central compartment (V1) and peripheral compartments, and intercompartment clearance. Similar estimated PK parameters and IIV were obtained for both treatments. For PF-05280014 and trastuzumab-EU, baseline body weight was an influential covariate on CL and V1; the magnitude was comparable between treatments. PK was consistent between the limited number of Japanese and non-Japanese patients for both compounds. CONCLUSIONS: PF-05280014 and trastuzumab-EU had similar PK parameters and influential PK covariates in patients with HER2-positive mBC. These results provided further evidence in patients for PK similarity between PF-05280014 and trastuzumab-EU. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, NCT01989676.

PF-05280014 (a trastuzumab biosimilar) plus paclitaxel compared with reference trastuzumab plus paclitaxel for HER2-positive metastatic breast cancer: a randomised, double-blind study.

BACKGROUND: This randomised, double-blind study compared PF-05280014 (a trastuzumab biosimilar) with reference trastuzumab (Herceptin®) sourced from the European Union (trastuzumab-EU), when each was given with paclitaxel as first-line treatment for HER2-positive metastatic breast cancer. METHODS: Between 4 April 2014 and 22 January 2016, 707 participants were randomised 1:1 to receive intravenous PF-05280014 plus paclitaxel (PF-05280014 group; n = 352) or trastuzumab-EU plus paclitaxel (trastuzumab-EU group; n = 355). PF-05280014 or trastuzumab-EU was administered weekly (first dose 4 mg/kg, subsequent doses 2 mg/kg), with the option to change to a 3-weekly regimen (6 mg/kg) from Week 33. Treatment with PF-05280014 or trastuzumab-EU could continue until disease progression. Paclitaxel (starting dose 80 mg/m2) was administered on Days 1, 8 and 15 of 28-day cycles for at least six cycles or until maximal benefit of response. The primary endpoint was objective response rate (ORR), evaluating responses achieved by Week 25 and confirmed by Week 33, based on blinded central radiology review. RESULTS: The risk ratio for ORR was 0.940 (95% CI: 0.842-1.049). The 95% CI fell within the pre-specified equivalence margin of 0.80-1.25. ORR was 62.5% (95% CI: 57.2-67.6%) in the PF-05280014 group and 66.5% (95% CI: 61.3-71.4%) in the trastuzumab-EU group. As of data cut-off on 11 January 2017 (using data up to 378 days post-randomisation), there were no notable differences between groups in progression-free survival (median: 12.16 months in the PF-05280014 group vs. 12.06 months in the trastuzumab-EU group; 1-year rate: 54% vs. 51%) or overall survival (median: not reached in either group; 1-year rate: 89.31% vs. 87.36%). Safety outcomes and immunogenicity were similar between the treatment groups. CONCLUSION: When given as first-line treatment for HER2-positive metastatic breast cancer, PF-05280014 plus paclitaxel demonstrated equivalence to trastuzumab-EU plus paclitaxel in terms of ORR. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, NCT01989676.