Challenges for global antibiotic regimen planning and establishing antimicrobial resistance targets: implications for the WHO Essential Medicines List and AWaRe antibiotic book dosing.

SUMMARYThe World Health Organisation's 2022 AWaRe Book provides guidance for the use of 39 antibiotics to treat 35 infections in primary healthcare and hospital facilities. We review the evidence underpinning suggested dosing regimens. Few (n = 18) population pharmacokinetic studies exist for key oral AWaRe antibiotics, largely conducted in homogenous and unrepresentative populations hindering robust estimates of drug exposures. Databases of minimum inhibitory concentration distributions are limited, especially for community pathogen-antibiotic combinations. Minimum inhibitory concentration data sources are not routinely reported and lack regional diversity and community representation. Of studies defining a pharmacodynamic target for ß-lactams (n = 80), 42 (52.5%) differed from traditionally accepted 30%-50% time above minimum inhibitory concentration targets. Heterogeneity in model systems and pharmacodynamic endpoints is common, and models generally use intravenous ß-lactams. One-size-fits-all pharmacodynamic targets are used for regimen planning despite complexity in drug-pathogen-disease combinations. We present solutions to enable the development of global evidence-based antibiotic dosing guidance that provides adequate treatment in the context of the increasing prevalence of antimicrobial resistance and, moreover, minimizes the emergence of resistance.

An interim exploratory proteomics biomarker analysis of a phase 2 clinical trial to assess the impact of CT1812 in Alzheimer's disease.

CT1812 is a novel, brain penetrant small molecule modulator of the sigma-2 receptor (S2R) that is currently in clinical development for the treatment of Alzheimer's disease (AD). Preclinical and early clinical data show that, through S2R, CT1812 selectively prevents and displaces binding of amyloid beta (Aß) oligomers from neuronal synapses and improves cognitive function in animal models of AD. SHINE is an ongoing phase 2 randomized, double-blind, placebo-controlled clinical trial (COG0201) in participants with mild to moderate AD, designed to assess the safety and efficacy of 6 months of CT1812 treatment. To elucidate the mechanism of action in AD patients and pharmacodynamic biomarkers of CT1812, the present study reports exploratory cerebrospinal fluid (CSF) biomarker data from 18 participants in an interim analysis of the first set of patients in SHINE (part A). Untargeted mass spectrometry-based discovery proteomics detects >2000 proteins in patient CSF and has documented utility in accelerating the identification of novel AD biomarkers reflective of diverse pathophysiologies beyond amyloid and tau, and enabling identification of pharmacodynamic biomarkers in longitudinal interventional trials. We leveraged this technique to analyze CSF samples taken at baseline and after 6 months of CT1812 treatment. Proteome-wide protein levels were detected using tandem mass tag-mass spectrometry (TMT-MS), change from baseline was calculated for each participant, and differential abundance analysis by treatment group was performed. This analysis revealed a set of proteins significantly impacted by CT1812, including pathway engagement biomarkers (i.e., biomarkers tied to S2R biology) and disease modification biomarkers (i.e., biomarkers with altered levels in AD vs. healthy control CSF but normalized by CT1812, and biomarkers correlated with favorable trends in ADAS-Cog11 scores). Brain network mapping, Gene Ontology, and pathway analyses revealed an impact of CT1812 on synapses, lipoprotein and amyloid beta biology, and neuroinflammation. Collectively, the findings highlight the utility of this method in pharmacodynamic biomarker identification and providing mechanistic insights for CT1812, which may facilitate the clinical development of CT1812 and enable appropriate pre-specification of biomarkers in upcoming clinical trials of CT1812.

Model-Informed Precision Dosing: Background, Requirements, Validation, Implementation, and Forward Trajectory of Individualizing Drug Therapy.

Model-informed precision dosing (MIPD) has become synonymous with modern approaches for individualizing drug therapy, in which the characteristics of each patient are considered as opposed to applying a one-size-fits-all alternative. This review provides a brief account of the current knowledge, practices, and opinions on MIPD while defining an achievable vision for MIPD in clinical care based on available evidence. We begin with a historical perspective on variability in dose requirements and then discuss technical aspects of MIPD, including the need for clinical decision support tools, practical validation, and implementation of MIPD in health care. We also discuss novel ways to characterize patient variability beyond the common perceptions of genetic control. Finally, we address current debates on MIPD from the perspectives of the new drug development, health economics, and drug regulations.

Two-way pharmacodynamic modeling of drug combinations and its application to pairs of repurposed Ebola and SARS-CoV-2 agents.

Existing pharmacodynamic (PD) mathematical models for drug combinations discriminate antagonistic, additive, multiplicative, and synergistic effects, but fail to consider how concentration-dependent drug interaction effects may vary across an entire dose-response matrix. We developed a two-way pharmacodynamic (TWPD) model to capture the PD of two-drug combinations. TWPD captures interactions between upstream and downstream drugs that act on different stages of viral replication, by quantifying upstream drug efficacy and concentration-dependent effects on downstream drug pharmacodynamic parameters. We applied TWPD to previously published in vitro drug matrixes for repurposed potential anti-Ebola and anti-SARS-CoV-2 drug pairs. Depending on the drug pairing, the model recapitulated combined efficacies as or more accurately than existing models and can be used to infer efficacy at untested drug concentrations. TWPD fits the data slightly better in one direction for all drug pairs, meaning that we can tentatively infer the upstream drug. Based on its high accuracy, TWPD could be used in concert with PK models to estimate the therapeutic effects of drug pairs in vivo.

Translational pharmacokinetic-toxicodynamic model of myelosuppression for dose optimization in combination chemotherapy of capecitabine and oxaliplatin from rats to humans.

XELOX therapy, which comprises capecitabine and oxaliplatin, is the standard first-line chemotherapeutic regimen for colorectal cancer. However, its myelosuppressive effects pose challenges for its clinical management. Mathematical modeling combining pharmacokinetics (PK) and toxicodynamics (TD) is a promising approach for optimizing dosing strategies and reducing toxicity. This study aimed to develop a translational PK-TD model using rat data to inform dosing strategies and TD implications in humans. The rats were administered capecitabine, oxaliplatin, or XELOX combination regimen, and PK and TD data were collected. PK parameters were analyzed using sequential compartment analysis, whereas TD responses were assessed using Friberg's semi-physiological model. A toxicity intensity-based nomogram recommends optimal dosing strategies. Translational modeling techniques using the hybrid PK-TD model were employed to predict clinical responses. The PK-TD model successfully predicted the time-course profiles of hematological responses in rats following monotherapy and XELOX combination treatment. Interactive effects on lymphocytopenia were identified with the co-administration of capecitabine and oxaliplatin. A model-based recommended combination of the dose reduction rate for escaping severe lymphocytopenia was proposed as 40% and 60% doses of capecitabine and oxaliplatin, respectively. The current translational model techniques successfully simulated the time-course profiles of blood cell counts with confidence intervals in patients using rat data. Our study provides valuable insights into dose optimization strategies for each individual drug within the XELOX regimen and underscores the potential of translational modeling to improve patient outcomes. In addition to dose determination, these data will lay the groundwork for advancing drug development processes in oncology. Significance Statement This study introduced a novel translational modeling approach rooted in a rat PK-TD model to optimize dosing strategies for the XELOX regimen for colorectal cancer treatment. Our findings highlight the interactive effects on lymphocytopenia and suggest a toxicity intensity-based nomogram for dose reduction, thus advancing precision medicine. This translational modeling paradigm enhances our understanding of drug interactions, offering a tool to tailor dosing, minimize hematological toxicity, and improve therapeutic outcomes in patients undergoing XELOX therapy.

The usefulness of determining plasma and tissue concentrations of phosphorodiamidate morpholino oligonucleotides to estimate their efficacy in Duchenne muscular dystrophy patients.

Currently four kinds of phosphorodiamidate morpholino oligomers (PMOs) such as viltolarsen have been approved for the treatment of Duchenne muscular dystrophy (DMD); however, it is unclear whether human efficacy can be estimated using plasma concentrations. This study summarizes the tissue distribution of viltolarsen in mice and cynomolgus monkeys and evaluates the relationship between exposure and efficacy based on exon skipping. In the tissue distribution studies, all muscles in DMD model mice showed higher concentrations of viltolarsen than those in wild-type mice and cynomolgus monkeys, and the concentrations in skeletal muscle were correlated with the exon-skipping efficiency in mice and cynomolgus monkeys. In addition, a highly sensitive bioanalytical method using liquid chromatography with tandem mass spectrometry shows promise for determining plasma concentrations up to a later time point, and the tissue (muscle)/plasma concentration ratio (Kp) in DMD model mice was shown to be useful for predicting changes in pharmacodynamic (PD) markers in humans. Our results suggest that pharmacokinetic (PK)/PD analysis can be conducted by using the human PK profile or Kp values and skipping efficiency in DMD model mice. This information will be useful for the efficient and effective development of PMOs as therapeutic agents. Significance Statement We compare that plasma and tissue concentrations with the efficiency of exon skipping for viltolarsen as an example phosphorodiamidate morpholino oligomers in skeletal and cardiac muscle of mice and cynomolgus monkeys for pharmacokinetics/pharmacodynamics (PK/PD) analysis. Our results suggest that PK/PD analysis can be conducted by using the human PK profile or Kp values and skipping efficiency in DMD model mice.

Physiologically Based Pharmacokinetic (PBPK) Modeling of small molecules: How Much Progress Have We Made?

Physiologically based pharmacokinetic (PBPK) models of small molecules have become mainstream in drug development and academic research. The use of PBPK models is continuously expanding with the majority of work now focusing on predictions of drug-drug interactions, drug-disease interactions, and changes in drug disposition across lifespan. Recently, publications that use PBPK modeling to predict drug disposition during pregnancy and in organ impairment have increased reflecting the advances in incorporating diverse physiological changes into the models. Due to the expanding computational power and diversity of modeling platforms available, the complexity of PBPK models has also increased. Academic efforts have provided clear advances in better capturing human physiology in PBPK models and incorporating more complex mathematical concepts into PBPK models. Examples of such advances include the segregated gut model with a series gut compartments allowing modeling of physiological blood flow distribution within an organ and zonation of metabolic enzymes, and series compartment liver models allowing simulations of hepatic clearance for high extraction drugs. Despite these advances in academic research, the progress in assessing model quality and defining model acceptance criteria based on the intended use of the models has not kept pace. This review suggests that awareness of the need for predefined criteria for model acceptance has increased but many manuscripts still lack description of scientific justification and/or rationale for chosen acceptance criteria. As artificial intelligence and machine learning approaches become more broadly accepted, these tools offer promise for development of comprehensive assessment for existing observed data and analysis of model performance. Significance Statement PBPK modeling has become a mainstream application in academic literature and is broadly used for predictions, analysis and evaluation of pharmacokinetic data. Many significant advances have been made in developing advanced PBPK models that better capture human physiology but oftentimes sufficient justification for the chosen model acceptance criterion and model structure is still missing. This review provides a summary of the current landscape of PBPK applications used and highlights the needs for advancing PBPK modeling science and training in academia.

Nonclinical pharmacokinetics, pharmacodynamics and safety assessment of a FLT3L-Fc molecule for cancer immunotherapy.

FLT3L-Fc is a cytokine-Fc fusion agonizing receptor-type tyrosine-protein kinase FLT3 (fms-related tyrosine kinase 3; CD135). FLT3 is expressed on dendritic cells (DCs) as well as myeloid and lymphoid progenitors. Nonclinical pharmacokinetics, pharmacodynamics and safety of FLT3L-Fc were investigated in rats and cynomolgus monkeys. FLT3L-Fc induced robust pharmacodynamic responses, evidenced by marked expansion of peripheral blood cDC1s, cDC2s, and pDCs (up to 301-fold in rats and 378-fold in monkeys), peaking at 8-10 days after the first dose. FLT3L-Fc was well tolerated with no adverse findings at doses up to 10 mg/kg administered intravenously twice three weeks apart. In both species, major clinical pathology findings consisted of expansion of white blood cell (WBC) populations including lymphocytes, monocytes, neutrophils, basophils, and large unstained cells, which were pronounced after the first dose. The WBC findings were associated microscopically with histiocytic and mononuclear cell infiltrates in multiple organs. Tissue immunohistochemistry in monkeys showed that the leukocyte infiltrates consisted of hematopoietic progenitor cells and histiocytes with a reactive morphology and were associated with a slight stimulation of regional T and B cell populations. Additional FLT3L-Fc-associated changes included decreases in red blood cell (RBC) mass, increases in RBC distribution width, variable changes in reticulocytes, and transient alterations in platelet counts (rats only). The RBC and WBC findings were associated microscopically with increased hematopoietic cellularity of the bone marrow in both species and increased splenic megakaryocytic extramedullary hematopoiesis in rats. The totality of nonclinical safety data support the clinical development of FLT3L-Fc.

Pharmacokinetic-Pharmacodynamic Analysis of pH-Responsive Doxorubicin-Releasing Micelles with Anticancer Activity.

This study aimed to investigate the effect of in vivo pH-responsive doxorubicin (DOX) release and the targetability of pilot molecules in folic acid (FA)-modified micelles using a pharmacokinetic-pharmacodynamic (PK-PD) model. The time profiles of intratumoral DOX concentrations in Walker256 tumor-bearing rats were monitored using a microdialysis probe, followed by compartmental analysis, to evaluate intratumoral tissue pharmacokinetics. Maximal DOX was released from micelles 350 min after the administration of pH-responsive DOX-releasing micelles. However, FA modification of the micelles shortened the time to peak drug concentration to 150 min. Additionally, FA modification resulted in a 27-fold increase in the tumor inflow rate constant. Walker256 tumor-bearing rats were subsequently treated with DOX, pH-responsive DOX-releasing micelles, and pH-responsive DOX-releasing FA-modified micelles to monitor the tumor growth-time profiles. An intratumoral threshold concentration of DOX (55-64 ng/g tumor) was introduced into the drug efficacy compartment to construct a PD model, followed by PK-PD analysis of the tumor growth-time profiles. Similar results of threshold concentration and drug potency of DOX were obtained across all three formulations. Cell proliferation was delayed as the drug delivery ability of DOX was improved. The PK model, which was developed using the microdialysis method, revealed the intratumoral pH-responsive DOX distribution profiles. This facilitated the estimation of intratumoral PK parameters. The PD model with threshold concentrations contributed to the estimation of PD parameters in the three formulations, with consistent mechanisms observed. We believe that our PK-PD model can objectively assess the contributions of pH-responsive release ability and pilot molecule targetability to pharmacological effects.

The development and evaluation of dose-prediction tools for allopurinol therapy (Easy-Allo tools).

AIMS: Dose escalation at the initiation of allopurinol therapy can be protracted and resource intensive. Tools to predict the allopurinol doses required to achieve target serum urate concentrations would facilitate the implementation of more efficient dose-escalation strategies. The aim of this research was to develop and externally evaluate allopurinol dosing tools, one for use when the pre-urate-lowering therapy serum urate is known (Easy-Allo1) and one for when it is not known (Easy-Allo2). METHODS: A revised population pharmacokinetic-pharmacodynamic model was developed using data from 653 people with gout. Maintenance doses to achieve the serum urate target of <0.36 mmol L-1 in >80% of individuals were simulated and evaluated against external data. The predicted and observed allopurinol doses were compared using the mean prediction error (MPE) and root mean square error (RMSE). The proportion of Easy-Allo predicted doses within 100 mg of the observed was quantified. RESULTS: Allopurinol doses were predicted by total body weight, baseline urate, ethnicity and creatinine clearance. Easy-Allo1 produced unbiased and suitably precise dose predictions (MPE 2 mg day-1 95% confidence interval [CI] -13-17, RMSE 91%, 90% within 100 mg of the observed dose). Easy-Allo2 was positively biased by about 70 mg day-1 and slightly less precise (MPE 70 mg day-1 95% CI 52-88, RMSE 131%, 71% within 100 mg of the observed dose). CONCLUSIONS: The Easy-Allo tools provide a guide to the allopurinol maintenance dose requirement to achieve the serum urate target of <0.36 mmol L-1 and will aid in the development of novel dose-escalation strategies for allopurinol therapy.

Prediction of C-reactive protein dynamics during meropenem treatment in neonates and infants.

AIMS: C-reactive protein (CRP) is used to determine the effect of antibiotic treatment on sepsis in neonates/infants. We aimed to develop pharmacokinetic-pharmacodynamic (PKPD) model of meropenem and CRP in neonates/infants and evaluate its predictive performance of CRP dynamics. METHODS: Data from neonates/infants treated with meropenem in 3 previous studies were analysed. To the previously developed meropenem PK models, the addition of turnover, transit or effect compartment, delay differential equation PD models of CRP as a function of meropenem concentration or its cumulative area under the curve (AUC) were evaluated. The percentage of neonates/infants (P0.1 , P0.2 ) in whom the ratio of the fifth day CRP to its peak value was predicted with an error of <0.1 (<0.2) was calculated. RESULTS: A total of 60 meropenem treatment episodes (median [range] gestational age 27.6 [22.6-40.9] weeks, postnatal age 13 [2-89] days) with a total of 351 CRP concentrations (maximum value 65.5 [13-358.4] mg/L) were included. Turnover model of CRP as a function of meropenem cumulative AUC provided the best fit and included CRP at the start of treatment, use of prior antibiotics, study and causative agent Staphylococcus aureus or enterococci as covariates. Using meropenem population predictions and data available at 0, 24, 48, 72 h after the start of treatment, P0.1 (P0.2 ) was 36.4, 36.4, 60.6 and 66.7% (70.0, 66.7, 72.7 and 78.7%), respectively. CONCLUSION: The developed PKPD model of meropenem and CRP as a function of meropenem cumulative AUC incorporating several patient characteristics predicts CRP dynamics with an error of <0.2 in most neonates/infants.

Model-based dose optimization framework for bedaquiline, pretomanid and linezolid for the treatment of drug-resistant tuberculosis.

AIMS: Bedaquiline, pretomanid and linezolid (BPaL) combination treatment against Mycobacterium tuberculosis is promising, yet safety and adherence concerns exist that motivate exploration of alternative dosing regimens. We developed a mechanistic modelling framework to compare the efficacy of the current and alternative BPaL treatment strategies. METHODS: Pharmacodynamic models for each drug in the BPaL combination treatment were developed using in vitro time-kill data. These models were combined with pharmacokinetic models, incorporating body weight, lesion volume, site-of-action distribution, bacterial susceptibility and pharmacodynamic interactions to assemble the framework. The model was qualified by comparing the simulations against the observed clinical data. Simulations were performed evaluating bedaquiline and linezolid approved (bedaquiline 400 mg once daily [QD] for 14 days followed by 200 mg three times a week, linezolid 1200 mg QD) and alternative dosing regimens (bedaquiline 200 mg QD, linezolid 600 mg QD). RESULTS: The framework adequately described the observed antibacterial activity data in patients following monotherapy for each drug and approved BPaL dosing. The simulations suggested a minor difference in median time to colony forming unit (CFU)-clearance state with the bedaquiline alternative compared to the approved dosing and the linezolid alternative compared to the approved dosing. Median time to non-replicating-clearance state was predicted to be 15 days from the CFU-clearance state. CONCLUSIONS: The model-based simulations suggested that comparable efficacy can be achieved using alternative bedaquiline and linezolid dosing, which may improve safety and adherence in drug-resistant tuberculosis patients. The framework can be utilized to evaluate treatment optimization approaches, including dosing regimen and duration of treatment predictions to eradicate both replicating- and non-replicating bacteria from lung and lesions.

Cassia angustifolia and tacrolimus interaction in a liver transplant patient, a case report.

Cassia angustifolia is a species of plant from the Senna family that has traditionally been used as a laxative in different herbal products and commercial medicines. Even though there are few documented drug-plant interactions, the use of C. angustifolia with different drugs may have additive effects, such as with other laxatives or potassium-depleting diuretics. Its use also increases peristalsis which, may reduce drug absorption. The combination with digoxin has been associated with an increased risk of digoxin toxicity, probably due to an increase in plasma digoxin concentrations and hypokalaemia. We present a case with supratherapeutic trough concentration of tacrolimus, an immunosuppressive agent, and a herbal product in a liver transplant patient after concomitant intake of tacrolimus and a herbal product based on C. angustifolia, suggesting a possible drug-lant interaction through by P-glycoprotein. We observed an increase in the patient's blood concentration 2.8-fold and the area under the curve at steady state 2.1-fold. This interaction could be of clinical relevance, given the dose-dependent side effects of tacrolimus, such as nephrotoxicity, neurotoxicity, hypertension, hyperglycaemia, or electrolyte alterations.

Combined translational pharmacometrics approach to support the design and conduct of the first-in-human study of DWP16001.

AIMS: The objective of this study was to characterize the pharmacokinetics (PK)/pharmacodynamics (PD) of DWP16001, a novel sodium-glucose cotransporter 2 inhibitor, and predict efficacious doses for the first-in-human study using various translational approaches. METHODS: A mechanistic PK/PD model was developed for DWP16001 using nonlinear mixed-effect modelling to describe animal PK/PD properties. Using allometry and in silico physiologically based equations, human PK parameters were predicted. Human PD parameters were scaled by applying interspecies difference and in vitro drug-specific factors. Human parameters were refined using early clinical data. Model-predicted PK and PD outcomes were compared to observations before and after parameter refinement. RESULTS: The PK/PD model of DWP16001 was developed using a 2-compartment model with first-order absorption and indirect response. Efficacious doses of 0.3 and 2 mg of DWP16001 were predicted using human half-maximal inhibitory concentration values translated from Zucker Diabetic Fatty rats and normal rats, respectively. After parameter refinement, doses of 0.2 and 1 mg were predicted to be efficacious for each disease model, which improved the prediction results to within a 1.2-fold difference between the model prediction and observation. CONCLUSIONS: This study predicted efficacious human doses of DWP16001 using population PK/PD modelling and a combined translational pharmacometrics approach. Early clinical data allowed the methods used to translate in vitro and in vivo findings to clinical PK/PD values for DWP16001 to be optimized. This study has shown that a refinement step can be readily applied to improve model prediction and further support the study design and conduct of a first-in-human study.

Determinants of early change in serum creatinine after initiation of dolutegravir-based antiretroviral therapy in South Africa.

AIMS: Dolutegravir increases serum creatinine by inhibiting its renal tubular secretion and elimination. We investigated determinants of early changes in serum creatinine in a southern African cohort starting first-line dolutegravir-based antiretroviral therapy (ART). METHODS: We conducted a secondary analysis of data from participants in a randomized controlled trial of dolutegravir, emtricitabine and tenofovir disoproxil fumarate (TDF) or tenofovir alafenamide fumarate (TAF) (ADVANCE, NCT03122262). We assessed clinical, pharmacokinetic and genetic factors associated with change in serum creatinine from baseline to Week 4 using linear regression models adjusted for age, sex, baseline serum creatinine, HIV-1 RNA concentration, CD4 T-cell count, total body weight and co-trimoxazole use. RESULTS: We included 689 participants, of whom 470 had pharmacokinetic data and 315 had genetic data. Mean change in serum creatinine was 11.3 (SD 9.9) µmol.L-1. Factors that were positively associated with change in serum creatinine at Week 4 were increased log dolutegravir area under the 24-h concentration-time curve (change in creatinine coefficient [ß] = 2.78 µmol.L-1 [95% confidence interval (CI) 0.54, 5.01]), TDF use (ß = 2.30 [0.53, 4.06]), male sex (ß = 5.20 [2.92, 7.48]), baseline serum creatinine (ß = -0.22 [-0.31, -0.12]) and UGT1A1 rs929596 A→G polymorphism with a dominant model (ß = -2.33 [-4.49, -0.17]). The latter did not withstand correction for multiple testing. CONCLUSIONS: Multiple clinical and pharmacokinetic factors were associated with early change in serum creatinine in individuals initiating dolutegravir-based ART. UGT1A1 polymorphisms may play a role, but further research on genetic determinants is needed.

Belantamab mafodotin concentration-QTc relationships in patients with relapsed or refractory multiple myeloma from the DREAMM-1 and -2 studies.

AIMS: To evaluate relationships between plasma concentrations of belantamab mafodotin, total monoclonal antibody, and its payload and changes in electrocardiogram (ECG) parameters in patients with relapsed or refractory multiple myeloma from the DREAMM-1 and DREAMM-2 studies. METHODS: Hysteresis plots and linear regression analyses of pharmacokinetic (PK) analyte (belantamab mafodotin, total monoclonal antibody, and cytotoxic cysteine-maleimidocaproyl monomethyl auristatin F payload) concentrations vs. time-matched ECG parameters (absolute/change from baseline in QT interval corrected for RR interval [QTc/ΔQTc] and QT interval corrected for heart rate by Fridericia's formula [QTcF/ΔQTcF]) were performed. Concentrations of PK analyte required for a 10-ms increase in QTc in DREAMM-2 were calculated via simulation, as was the probability of ΔQTc/ΔQTcF exceeding 10 ms for the expected Cmax of PK analyte concentrations associated with the doses (2.5 and 3.4 mg/kg) administered in DREAMM-2. RESULTS: Time-matched PK and ECG data from 290 patients (DREAMM-1, n = 73; DREAMM-2, n = 217) were analysed. Hysteresis plots did not clearly indicate any concentration-related prolongation in QTc or QTcF; regression analyses indicated a very small rate of increase in ΔQTc and ΔQTcF with increasing concentrations of PK analytes. Calculated concentrations of PK analyte required for a 10-ms prolongation in QTc were higher than the maximum analyte concentrations observed following treatment with belantamab mafodotin in DREAMM-2; the probability that each dose would prolong ΔQTc and ΔQTcF by >10 ms was 0 and <0.25%, respectively. CONCLUSION: This study of belantamab mafodotin and its payload did not provide evidence of QT prolongation in patients with relapsed or refractory multiple myeloma at clinically relevant doses.

Pharmacokinetic-pharmacodynamic modelling and simulation of methotrexate dosing in patients with rheumatoid arthritis.

AIMS: To develop a non-linear mixed-effects population pharmacokinetic and pharmacodynamic (PK-PD) model describing the change in the concentration of methotrexate polyglutamates in erythrocytes (ery-MTX-PGn with "n" number of glutamate, representing PK component) and how this relates to modified 28-joint Disease Activity Score incorporating erythrocyte sedimentation rate (DAS-28-3) for rheumatoid arthritis (RA), representing PD component. METHODS: An existing PK model was fitted to data from a study consisting of 117 RA patients. The estimation of population PK-PD parameters was performed using stochastic approximation expectation maximisation algorithm in Monolix 2021R2. The model was used to perform Monte Carlo simulations of a loading dose regimen (50mg subcutaneous methotrexate as loading doses, then 20mg weekly oral methotrexate) compared to a standard dosing regimen (10mg weekly oral methotrexate for 2 weeks, then 20mg weekly oral methotrexate). RESULTS: Every 40 nmol/L increase in ery-MTX-PG3-5 total concentration correlated with 1-unit reduction in DAS-28-3. Significant covariate effects on the therapeutic response of methotrexate included the use of prednisolone in the first 4 weeks (positive use correlated with 25% reduction in DAS-28-3 when other variables were constant) and patient age (every 10-year increase in age correlated with 3.4% increase in DAS-28-3 when other variables were constant). 4 methotrexate loading doses led to a higher percentage of patients achieving a good/moderate response compared to the standard regimen (Week 4: 87.6% vs. 39.8%; Week 10: 64.7% vs. 57.0%). CONCLUSIONS: A loading dose regimen was more likely to achieve higher ery-MTX-PG concentration and better therapeutic response after 4 weeks of methotrexate treatment.

Ceftazidime-related neurotoxicity in a patient with renal impairment: a case report and literature review.

PURPOSE: We present the case of a 67-year-old woman with severely reduced renal clearance suffering from ceftazidime-induced encephalopathy. Subsequently, we search the literature to review and describe the neurotoxicity of ceftazidime. METHODS: A search string was developed to search PubMed for relevant cases from which relevant information was extracted. Using the collected data a ROC analysis was performed in R to determine a neurotoxicity threshold. RESULTS: Our patient suffered from progressive loss of consciousness and myoclonic seizures, with improvements noted a few days after discontinuation of treatment. The dose was not appropriately reduced to take into account her reduced renal function. The highest ceftazidime concentration recorded was 234.9 mg/mL. Using the Naranjo score we found a probable relationship between our patient's encephalopathy and ceftazidime administration. In the literature we found a total of 32 similar cases, most of which also had some form of renal impairment. Using our collected data and ceftazidime concentrations provided in the literature, a ROC analysis provided a neurotoxicity threshold of 78 mg/L for ceftazidime neurotoxicity. CONCLUSION: Ceftazidime-related neurotoxicity is a known issue, especially in patients with severe renal impairment. Yet no concrete toxicity threshold has been reported so far. We propose the first toxicity threshold for ceftazidime of 78 mg/L. Future prospective studies are needed to validate and optimize the neurotoxicity threshold as upper limit for ceftazidime therapeutic drug monitoring.

Concentration-resistance relationship and PK/PD evaluation of danofloxacin against emergence of resistant Pasteurella multocida in an in vitro dynamic model.

AIMS: This study aimed to assess the pharmacokinetic/pharmacodynamic (PK/PD) targets of danofloxacin to minimize the risk of selecting resistant Pasteurella multocida mutants and to identify the mechanisms underlying their resistance in an in vitro dynamic model, attaining the optimum dosing regimen of danofloxacin to improve its clinical efficacy based on the mutant selection window (MSW) hypothesis. METHODS AND RESULTS: Danofloxacin at seven dosing regimens and 5 days of treatment were simulated to quantify the bactericidal kinetics and enrichment of resistant mutants upon continuous antibiotic exposure. The magnitudes of PK/PD targets associated with different efficacies were determined in the model. The 24 h area under the concentration-time curve (AUC) to minimum inhibitory concentration (MIC) ratios (AUC24h/MIC) of danofloxacin associated with bacteriostatic, bactericidal and eradication effects against P. multocida were 34, 52, and 64 h. This translates to average danofloxacin concentrations (Cav) over 24 h being 1.42, 2.17, and 2.67 times the MIC, respectively. An AUC/MIC-dependent antibacterial efficacy and AUC/mutant prevention concentration (MPC)-dependent enrichment of P. multocida mutants in which maximum losses in danofloxacin susceptibility occurred at a simulated AUC24h/MIC ratio of 72 h (i.e. Cav of three times the MIC). The overexpression of efflux pumps (acrAB-tolC) and their regulatory genes (marA, soxS, and ramA) was associated with reduced susceptibility in danofloxacin-exposed P. multocida. The AUC24h/MPC ratio of 19 h (i.e. Cav of 0.8 times the MPC) was determined to be the minimum mutant prevention target value for the selection of resistant P. multocida mutants. CONCLUSIONS: The emergence of P. multocida resistance to danofloxacin exhibited a concentration-dependent pattern and was consistent with the MSW hypothesis. The current clinical dosing regimen of danofloxacin (2.5 mg kg-1) may have a risk of treatment failure due to inducible fluoroquinolone resistance.

Second-Order Effects of Chemotherapy Pharmacodynamics and Pharmacokinetics on Tumor Regression and Cachexia.

Drug dose response curves are ubiquitous in cancer biology, but these curves are often used to measure differential response in first-order effects: the effectiveness of increasing the cumulative dose delivered. In contrast, second-order effects (the variance of drug dose) are often ignored. Knowledge of second-order effects may improve the design of chemotherapy scheduling protocols, leading to improvements in tumor response without changing the total dose delivered. By considering treatment schedules with identical cumulative dose delivered, we characterize differential treatment outcomes resulting from high variance schedules (e.g. high dose, low dose) and low variance schedules (constant dose). We extend a previous framework used to quantify second-order effects, known as antifragility theory, to investigate the role of drug pharmacokinetics. Using a simple one-compartment model, we find that high variance schedules are effective for a wide range of cumulative dose values. Next, using a mouse-parameterized two-compartment model of 5-fluorouracil, we show that schedule viability depends on initial tumor volume. Finally, we illustrate the trade-off between tumor response and lean mass preservation. Mathematical modeling indicates that high variance dose schedules provide a potential path forward in mitigating the risk of chemotherapy-associated cachexia by preserving lean mass without sacrificing tumor response.