Nivolumab is a human monoclonal antibody that blocks the interaction between PD-1 programmed death-1 (PD-1) and its ligands, PD-L1 and PD-L2. Nivolumab demonstrated efficacy in clinical trials for various types of cancer. A time-varying clearance was identified for nivolumab. We show that the change of clearance over time is associated with the post-treatment effects: clearance decreases when disease status improves. This interaction between posttreatment effects and drug exposure may lead to a biased steep estimate of the exposure-response (E-R) relationship for efficacy. Under this scenario, simulations were performed to develop a proposed methodology to assess the causal effect of drug exposure upon clinical response. Data from nivolumab trials were subsequently used to verify the proposed methodology for E-R analysis. The results showed that E-R analysis results based on pharmacokinetic (PK) metrics derived from the first dose are more consistent with the true E-R or dose-response relationship than the steady-state PK metrics.

Predicting clinically significant drug interactions during drug development is a challenge for the pharmaceutical industry and regulatory agencies. Since the publication of the US Food and Drug Administration's (FDA's) first in vitro and in vivo drug interaction guidance documents in 1997 and 1999, researchers and clinicians have gained a better understanding of drug interactions. This knowledge has enabled the FDA and the industry to progress and begin to overcome these challenges. The FDA has continued its efforts to evaluate methodologies to study drug interactions and communicate recommendations regarding the conduct of drug interaction studies, particularly for CYP-based and transporter-based drug interactions, to the pharmaceutical industry. A drug interaction Web site was established to document the FDA's current understanding of drug interactions (http://www.fda.gov/cder/drug/drugInteractions/default.htm). This report provides an overview of the evolution of the drug interaction guidances, includes a synopsis of the steps taken by the FDA to revise the original drug interaction guidance documents, and summarizes and highlights updated sections in the current guidance document, Drug Interaction Studies-Study Design, Data Analysis, and Implications for Dosing and Labeling.

Pembrolizumab is a monoclonal antibody that targets the programmed death-1 receptor to induce immune-mediated clearance (CL) of tumor cells. Originally approved by the US Food and Drug Administration in 2014 for treating patients with unresectable or metastatic melanoma, pembrolizumab is now also used to treat patients with non-small-cell lung cancer, classical Hodgkin lymphoma, head and neck cancer, and urothelial cancer. This paper describes the recently identified feature of pembrolizumab pharmacokinetics, the time-dependent or time-varying CL. Overall results indicate that CL decreases over the treatment period of a typical patient in a pattern well described by a sigmoidal function of time with three parameters: the maximum proportion change in CL from baseline (approximately I or exactly e - 1), the time to reach I/2 (TI), and a Hill coefficient. Best overall response per response evaluation criteria in solid tumor category was found to be associated with the magnitude of I.

This FDA approval summary provides an update on approval of pembrolizumab for treatment of patients with metastatic non‐small cell lung cancer whose tumors express PD‐L1 as determined by an FDA‐approved test. The results of KEYNOTE‐010 and KEYNOTE‐024 trials are presented.

C-X-C chemokine receptor 4 (CXCR4) is frequently over-expressed in various types of cancer; many agents against CXCR4 are in clinical development currently despite variable data for the prognostic impact of CXCR4 expression. Here eighty-five studies with a total of 11,032 subjects were included to explore the association between CXCR4 and progression-free survival (PFS) or overall survival (OS) in subjects with cancer. Pooled analysis shows that CXCR4 over-expression is significantly associated with poorer PFS (HR 2.04; 95% CI, 1.72-2.42) and OS (HR=1.94; 95% CI, 1.71-2.20) irrespective of cancer types. Subgroup analysis indicates significant association between CXCR4 and shorter PFS in hematological malignancy, breast cancer, colorectal cancer, esophageal cancer, renal cancer, gynecologic cancer, pancreatic cancer and liver cancer; the prognostic effects remained consistent across age, risk of bias, levels of adjustment, median follow-up period, geographical area, detection methods, publication year and size of studies. CXCR4 over-expression predicts unfavorable OS in hematological malignancy, breast cancer, colorectal cancer, esophageal cancer, head and neck cancer, renal cancer, lung cancer, gynecologic cancer, liver cancer, prostate cancer and gallbladder cancer; these effects were independence of age, levels of adjustment, publication year, detection methods and follow-up period. In conclusion, CXCR4 over-expression is associated with poor prognosis in cancer.

Viral entry and egress are important determinants of virus infectivity and pathogenicity. β-Coronaviruses, including the COVID-19 virus SARS-CoV-2 and MHV, exploit the lysosomal exocytosis pathway for egress. Here we show that SARS-CoV-2 ORF3a, but not SARS-CoV ORF3a, promotes lysosomal exocytosis. SARS-CoV-2 ORF3a facilitates lysosomal targeting of the BORC-ARL8b complex, which mediates trafficking of lysosomes to the vicinity of the plasma membrane, and exocytosis-related SNARE proteins. The Ca 2+ channel TRPML3 is required for SARS-CoV-2 ORF3a-mediatd lysosomal exocytosis. Expression of SARS-CoV-2 ORF3a greatly elevates extracellular viral release in cells infected with the coronavirus MHV-A59 which itself lacks ORF3a. In SARS-CoV-2 ORF3a, Ser171 and Trp193 are critical for promoting lysosomal exocytosis and blocking autophagy. When these residues are introduced into SARS-CoV ORF3a, it acquires the ability to promote lysosomal exocytosis and inhibit autophagy. Our results reveal a mechanism by which SARS-CoV-2 interacts with host factors to promote its extracellular egress.

Although without clear scientific rationale, body size-based dosing is often used for administering monoclonal antibodies (mAbs). This simulation study compared the performance of body size-based and fixed dosing in reducing pharmacokinetic (PK) and/or pharmacodynamic (PD) variability in adults for 12 mAbs with published population PK and/or PD models. At the population level, 95th percentile intervals of concentration-time profiles, distribution, and variability of exposure for 1000 subjects after both dosing approaches were examined. At the individual level, the difference between the exposures of patients with extreme body sizes from the typical exposure following both approaches was compared. The results show that the 2 dosing approaches perform similarly across the mAbs investigated with fixed dosing being better for some mAbs and body size-based dosing being better for the others. Based on this finding, we recommend using fixed dosing in first-in-human (FIH) adult studies because it offers other advantages. When sufficient data become available, a full assessment of body size effect on PK/PD should be conducted to determine the optimal dosing approach for phase 3 trials. Other factors that may affect the selection of dosing approach were also discussed. Dosing approach for mAbs in the pediatric population is out of the scope of this study.

Obesity has been associated with abnormally high expression of the enzyme aromatase in the breast, increased local estrogen production, and predisposition to breast hyperplasia and cancer. Increased adiposity in postmenopausal women may trigger signaling pathways that induce aromatase expression. In breast adipose fibroblasts, increased TNF production may induce the distal aromatase promoter, whereas increased local PGE2 production may induce the proximal promoter region. We review here the mechanisms that control aromatase gene expression in breast adipose tissue, and the paracrine interactions between malignant breast epithelial cells and the surrounding adipose fibroblasts. Systematic characterization of these signaling pathways will facilitate the identification of potential drug targets to selectively reduce aromatase expression and excessive estrogen production, with therapeutic benefit.