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Insight into the development of treatment resistance can support the optimization of anticancer treatments. This study aims to characterize the tumor dynamics and development of drug resistance in patients with non-small cell lung cancer treated with erlotinib, and investigate the relationship between baseline circulating tumor DNA (ctDNA) data and tumor dynamics. Data obtained for the analysis included (1) intensively sampled erlotinib concentrations from 29 patients from two previous pharmacokinetic (PK) studies, and (2) tumor sizes, ctDNA measurements, and sparsely sampled erlotinib concentrations from 18 patients from the START-TKI study. A two-compartment population PK model was first developed which well-described the PK data. The PK model was subsequently applied to investigate the exposure-tumor dynamics relationship. To characterize the tumor dynamics, models accounting for intra-tumor heterogeneity and acquired resistance with or without primary resistance were investigated. Eventually, the model assumed acquired resistance only resulted in an adequate fit. Additionally, models with or without exposure-dependent treatment effect were explored, and no significant exposure-response relationship for erlotinib was identified within the observed exposure range. Subsequently, the correlation of baseline ctDNA data on EGFR and TP53 variants with tumor dynamics’ parameters was explored. The analysis indicated that higher baseline plasma EGFR mutation levels correlated with increased tumor growth rates, and the inclusion of ctDNA measurements improved model fit. This result suggests that quantitative ctDNA measurements at baseline have the potential to be a predictor of anticancer treatment response. The developed model can potentially be applied to design optimal treatment regimens that better overcome resistance.

Blood pressure measurements form a critical component of adverse event monitoring for tyrosine kinase inhibitors, but might also serve as a biomarker for dose titrations. This study explored the impact of various sources of within-individual variation on blood pressure readings to improve measurement practices and evaluated the utility for individual- and population-level dose selection. A pharmacokinetic-pharmacodynamic modeling framework was created to describe circadian blood pressure changes, inter- and intra-day variability, changes from dipper to non-dipper profiles, and the relationship between drug exposure and blood pressure changes over time. The framework was used to quantitatively evaluate the influence of physiological and pharmacological aspects on blood pressure measurements, as well as to compare measurement techniques, including office-based, home-based, and ambulatory 24-h blood pressure readings. Circadian changes, as well as random intra-day and inter-day variability, were found to be the largest sources of within-individual variation in blood pressure. Office-based and ambulatory 24-h measurements gave rise to potential bias (>5 mmHg), which was mitigated by model-based estimations. Our findings suggest that 5-8 consecutive, home-based, measurements taken at a consistent time around noon, or alternatively within a limited time frame (e.g., 8.00 a.m. to 12.00 p.m. or 12.00 p.m. to 5.00 p.m.), will give rise to the most consistent blood pressure estimates. Blood pressure measurements likely do not represent a sufficiently accurate method for individual-level dose selection, but may be valuable for population-level dose identification. A user-friendly tool has been made available to allow for interactive blood pressure simulations and estimations for the investigated scenarios.

Dr. Reddy's Laboratories rituximab (DRL_RI; Dr. Reddy's Laboratories SA, Basel, Switzerland) is under development as a rituximab biosimilar. Study RI-01-002 (Clinical Trials Registry - India/2012/11/003129), comparing DRL_RI to the reference medicinal product (RMP) MabThera® (Roche, Grenzach-Wyhlen, Germany), demonstrated pharmacokinetic (PK) equivalence and showed comparable pharmacodynamic, efficacy, safety, and immunogenicity profiles. We used data from the same study to perform population PK and PK–pharmacodynamic analyses: first exploring possible factors influencing the PK similarity assessment between products and then performing simulations to investigate the impact of tumor size on rituximab PK. Nonlinear mixed-effects models for PK, tumor size, tumor size–PK, and tumor response were developed independently. The final PK model included drug product as a dose-scaling parameter and predicted a 6.75% higher dose reaching the system in RMP-treated patients. However, when tumor size was included in the tumor size–PK model, the drug product effect was no longer observed. The model rather indicated that patients with larger tumor size have higher clearance. Further simulations confirmed that higher baseline tumor size is associated to slightly lower rituximab exposure. Tumor response, described by a continuous-time Markov model, did not differ between drug products. Both had higher effects during the first 20 weeks of treatment. Also, the model described a subpopulation of nonresponders to treatment (42%) with faster transitions to a worse state. The different rituximab exposure initially detected between drug products (6.75%) was shown using PK/PK–pharmacodynamic analysis to be attributed to a tumor size imbalance between treatment groups. PK/PK–pharmacodynamic analyses may contribute to PK similarity assessments.

Colistin heteroresistance (HR) refers to a bacterial population comprised of several subpopulations with different levels of resistance to colistin. In this study, we discuss the classic form of HR, in which a resistant subpopulation exists within a predominantly susceptible population. We investigated the prevalence of colistin HR and its evolution into full resistance among 173 clinical carbapenem-resistant Acinetobacter baumannii isolates and examined the effect of HR on clinical outcomes. To determine HR, we performed population analysis profiling. Our results showed a high prevalence of HR (67.1%). To examine evolution of HR strains into full resistance, the HR strains were grown in colistin-containing broth, transferred onto colistin-containing plates, and colonies on these plates were transferred into colistin-free broth. Many of the HR strains (80.2%) evolved into full resistance, 17.2% reverted to HR, and 2.6% were borderline. We used logistic regression to compare 14-day clinical failure and 14-day mortality between patients infected by HR versus susceptible non-HR carbapenem-resistant A. baumannii. In the subgroup of patients with bacteremia, HR was significantly associated with 14-day mortality.IMPORTANCE To our knowledge, this is the first large-scale study to report on HR in Gram-negative bacteria. We described the prevalence of colistin HR in a large sample of carbapenem-resistant A. baumannii isolates, the evolution of many colistin HR isolates to a resistant phenotype following colistin exposure and withdrawal, and the clinical consequences of colistin HR. We found a high prevalence of HR among clinical carbapenem-resistant A. baumannii isolates; most evolved into a resistant phenotype following colistin exposure and withdrawal. In patients treated with colistin, evolution of HR A. baumannii into full resistance could lead to higher rates of treatment failure and contribute to the reservoir of colistin-resistant pathogens in health care settings. To

Neutrophil granulocytes are key components of the host response against pathogens, and severe neutropenia, with neutrophil counts below 0.5 × 106 cells/mL, renders patients increasingly vulnerable to infections. Published in vitro (n = 7) and in vivo (n = 5) studies with time-course information on bacterial and neutrophil counts were digitized to characterize the kinetics of neutrophil-mediated bacterial killing and inform on the immune systems' contribution to the clearance of bacterial infections. A mathematical model for the in vitro dynamics of bacteria and the kinetics of neutrophil-mediated phagocytosis and digestion was developed, which was extended to in vivo studies in immune-competent and immune-compromised mice. Neutrophil-mediated bacterial killing was described by two first-order processes—phagocytosis and digestion—scaled by neutrophil concentration, where 50% of the maximum was achieved at neutrophil counts of 1.19 × 106 cells/mL (phagocytosis) and 6.55 × 106 cells/mL (digestion). The process efficiencies diminished as the phagocytosed bacteria to total neutrophils ratio increased (with 50% reduction at a ratio of 3.41). Neutrophil in vivo dynamics were captured through the characterization of myelosuppressive drug effects and postinoculation neutrophil influx into lungs and by system differences (27% bacterial growth and 9.3% maximum capacity, compared with in vitro estimates). Predictions showed how the therapeutically induced reduction of neutrophil counts enabled bacterial growth, especially when falling below 0.5 × 106 cells/mL, whereas control individuals could deal with all tested bacterial burdens (up to 109 colony forming units/g lung). The model-based characterization of neutrophil-mediated bacterial killing simultaneously predicted data across in vitro and in vivo studies and may be used to inform the capacity of host–response at the individual level., De två första författarna delar förstaförfattarskapet

FAP-4-1BBL is a bispecific antibody exerting 4-1BB-associated T-cell activation only while simultaneously bound to the fibroblast activation protein (FAP) receptor, expressed on the surface of cancer-associated fibroblasts. The trimeric complex formed when FAP-4-1BBL is simultaneously bound to FAP and 4-1BB represents a promising mechanism to achieve tumor-specific 4-1BB stimulation. We integrated in vitro data with mathematical modeling to characterize the pharmacology of FAP-4-1BBL as a function of trimeric complex formation when combined with the T-cell engager cibisatamab. This relationship was used to prospectively predict a range of clinical doses where trimeric complex formation is expected to be at its maximum. Depending on the dosing schedule and FAP-4-1BBL plasma: tumor distribution, doses between 2 and 145 mg could lead to maximum trimeric complex formation in the clinic. Due to the expected variability in both pharmacokinetic and FAP expression in the patient population, we predict that detecting a clear dose-response relationship would remain difficult without a large number of patients per dose level, highlighting that mathematical modeling techniques based on in vitro data could aid dose selection.