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Objectives: To illustrate the impact of errors in documented dose administration time on therapeutic drug monitoring (TDM)-based target attainment evaluation for vancomycin and meropenem, and to explore the influence of drug and patient characteristics, and TDM sampling strategies. Methods: Bedside observations of errors in documented dose administration times were collected. Population pharmacokinetic simulations were performed for vancomycin and meropenem, evaluating different one- and two-sampling strategies for populations with estimated creatinine clearance (CLcr) of 30, 80 or 130 mL/min. The impact of errors was evaluated as the proportion of individuals incorrectly considered to have reached the target. Results: Of 143 observed dose administrations, 97% of doses were given within ±30 min of the documented time. For vancomycin, a +30 min error was predicted to result in a 0.1-3.9 percentage point increase of cases incorrectly evaluated as reaching area under the concentration-time curve during a 24-hour period (AUC24)/minimum inhibitory concentration (MIC) >400, with the largest increase for patients with augmented renal clearance and peak and trough sampling. For meropenem, a +30 min error resulted in a 1.3-6.4 and 0-20 percentage point increase of cases incorrectly evaluated as reaching 100% T>MIC, and 50% T>MIC, respectively. Overall, mid-dose and trough sampling was most favourable for both antibiotics. Conclusions: For vancomycin, simulations indicate that TDM-based target attainment evaluation is robust with respect to the observed errors in dose administration time of ±30 min; however, the errors had a potentially clinically important impact in patients with augmented renal clearance. For meropenem, extra measures to promote correct documentation are warranted when using TDM, as the impact of errors was evident even in patients with normal renal function.

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.

Publications on the exposure-effect relationships of factor concentrates for hemophilia treatment are limited, whereas such analyses give insight on treatment efficacy. Our objective was to examine the relationship between the dose, factor VIII (FVIII) levels and bleeding for rFVIII-SingleChain (lonoctocog alfa, Afstyla). Data from persons with severe hemophilia A on rFVIII-SingleChain prophylaxis from three clinical trials were combined. The published rFVIII-SingleChain population pharmacokinetic (PK) model was evaluated and expanded. The probability of bleeding was described with a parametric repeated time-to-event (RTTE) model. Data included 2080 bleeds, 2545 chromogenic stage assay, and 3052 one-stage assay FVIII levels from 241 persons (median age 19 years) followed for median 1090 days. The majority of the bleeds occurred in joints (65%) and the main bleeding reason was trauma (44%). The probability of bleeding decreased during follow-up and a FVIII level of 8.9 IU/dL (95% confidence interval: 6.9-10.9) decreased the bleeding hazard by 50% compared to a situation without FVIII in plasma. Variability in bleeding hazard between persons with similar FVIII levels was large, and the pre-study annual bleeding rate explained part of this variability. When a FVIII trough level of 1 or 3 IU/dL is targeted during prophylaxis, simulations predicted two (90% prediction interval [PI]: 0-17) or one (90% PI: 0-11) bleeds per year, respectively. In conclusion, the developed PK-RTTE model adequately described the relationship between dose, FVIII levels and bleeds for rFVIII-SingleChain. The obtained estimates were in agreement with those published for the FVIII concentrates BAY 81-8973 (octocog alfa) and BAY 94-9027 (damoctocog alfa pegol), indicating similar efficacy to reduce bleeding.

Background Little is known on how sports participation affects bleeding risk in hemophilia. This study aimed to examine associations between sports participation, factor VIII (FVIII) levels and bleeding in persons with hemophilia A. Methods In this observational, prospective, single-center study, persons with hemophilia A who regularly participated in sports were followed for 12 months. The associations of patient characteristics, FVIII levels, and type/frequency of sports participation with bleeding were analyzed by repeated time-to-event modelling. Results One hundred and twelve persons (median age: 24 years [interquartile range:16-34], 49% severe, 49% on prophylaxis) were included. During follow-up, 70 bleeds of which 20 sports-induced were observed. FVIII levels were inversely correlated with the bleeding hazard; a 50% reduction of the baseline bleeding hazard was observed at FVIII levels of 3.1 and a 90% reduction at 28.0 IU/dL. The bleeding hazard did not correlate with sports participation. In addition, severe hemophilia, prestudy annual bleeding rate, and presence of arthropathy showed a positive association with the bleeding hazard. Conclusions This analysis showed that FVIII levels were an important determinant of the bleeding hazard, but sports participation was not. This observation most likely reflects the presence of adequate FVIII levels during sports participation in our study. Persons with severe hemophilia A exhibited a higher bleeding hazard at a similar FVIII levels than nonsevere, suggesting that the time spent at lower FVIII levels impacts overall bleeding hazard. These data may be used to counsel persons with hemophilia regarding sports participation and the necessity of adequate prophylaxis.

Background: The benefit of pharmacogenetic testing before starting drug therapy has been well documented for several single gene-drug combinations. However, the clinical utility of a pre-emptive genotyping strategy using a pharmacogenetic panel has not been rigorously assessed. Methods: We conducted an open-label, multicentre, controlled, cluster-randomised, crossover implementation study of a 12-gene pharmacogenetic panel in 18 hospitals, nine community health centres, and 28 community pharmacies in seven European countries (Austria, Greece, Italy, the Netherlands, Slovenia, Spain, and the UK). Patients aged 18 years or older receiving a first prescription for a drug clinically recommended in the guidelines of the Dutch Pharmacogenetics Working Group (ie, the index drug) as part of routine care were eligible for inclusion. Exclusion criteria included previous genetic testing for a gene relevant to the index drug, a planned duration of treatment of less than 7 consecutive days, and severe renal or liver insufficiency. All patients gave written informed consent before taking part in the study. Participants were genotyped for 50 germline variants in 12 genes, and those with an actionable variant (ie, a drug-gene interaction test result for which the Dutch Pharmacogenetics Working Group [DPWG] recommended a change to standard-of-care drug treatment) were treated according to DPWG recommendations. Patients in the control group received standard treatment. To prepare clinicians for pre-emptive pharmacogenetic testing, local teams were educated during a site-initiation visit and online educational material was made available. The primary outcome was the occurrence of clinically relevant adverse drug reactions within the 12-week follow-up period. Analyses were irrespective of patient adherence to the DPWG guidelines. The primary analysis was done using a gatekeeping analysis, in which outcomes in people with an actionable drug-gene interaction in the study group versus the

Publications on the exposure-effect relationships of factor concentrates for hemophilia treatment are limited, whereas such analyses give insight on treatment efficacy. Our objective was to examine the relationship between the dose, factor VIII (FVIII) levels and bleeding for rFVIII-SingleChain (lonoctocog alfa, Afstyla). Data from persons with severe hemophilia A on rFVIII-SingleChain prophylaxis from three clinical trials were combined. The published rFVIII-SingleChain population pharmacokinetic (PK) model was evaluated and expanded. The probability of bleeding was described with a parametric repeated time-to-event (RTTE) model. Data included 2080 bleeds, 2545 chromogenic stage assay, and 3052 one-stage assay FVIII levels from 241 persons (median age 19 years) followed for median 1090 days. The majority of the bleeds occurred in joints (65%) and the main bleeding reason was trauma (44%). The probability of bleeding decreased during follow-up and a FVIII level of 8.9 IU/dL (95% confidence interval: 6.9–10.9) decreased the bleeding hazard by 50% compared to a situation without FVIII in plasma. Variability in bleeding hazard between persons with similar FVIII levels was large, and the pre-study annual bleeding rate explained part of this variability. When a FVIII trough level of 1 or 3 IU/dL is targeted during prophylaxis, simulations predicted two (90% prediction interval [PI]: 0–17) or one (90% PI: 0–11) bleeds per year, respectively. In conclusion, the developed PK-RTTE model adequately described the relationship between dose, FVIII levels and bleeds for rFVIII-SingleChain. The obtained estimates were in agreement with those published for the FVIII concentrates BAY 81-8973 (octocog alfa) and BAY 94-9027 (damoctocog alfa pegol), indicating similar efficacy to reduce bleeding.

Purpose: Empirical time-varying clearance models have been reported for several immune checkpoint inhibitors, including avelumab (anti-programmed death ligand 1). To investigate the exposure response relationship for avelumab, we explored semimechanistic pharmacokinetic (PK)-tumor growth dynamics (TGD) models. Patients and Methods: Plasma PK data were pooled from three phase I and II trials (JAVELIN Merkel 200, JAVELIN Solid Tumor, and JAVELIN Solid Tumor JPN); tumor size (TS) data were collected from patients with metastatic Merkel cell carcinoma (mMCC) enrolled in JAVELIN Merkel 200. A PK model was developed first, followed by TGD modeling to investigate interactions between avelumab exposure and TGD. A PK-TGD feedback loop was evaluated with simultaneous fitting of the PK and TGD models. Results: In total, 1,835 PK observations and 338 TS observations were collected from 147 patients. In the final PK-TGD model, which included the bidirectional relationship between PK and TGD, avelumab PK was described by a two-compartment model with a positive association between clearance and longitudinal TS, with no additional empirical time-varying clearance identified. TGD was described by first-order tumor growth/shrinkage rates, with the tumor shrinkage rate decreasing exponentially over time; the exponential time-decay constant decreased with increasing drug concentration, representing the treatment effect through tumor shrinkage inhibition. Conclusions: We developed a TGD model that mechanistically captures the prevention of loss of antitumor immunity (i.e., T-cell suppression in the tumor microenvironment) by avelumab, and a bidirectional interaction between PK and TGD in patients with mMCC treated with avelumab, thus mechanistically describing previously reported time variance of avelumab elimination.

This study tested the hypothesis that analyzing longitudinal item scores of the Unified Parkinson's Disease Rating Scale could allow a smaller trial size and describe a drug's effect on symptom progression. Two historical studies of the dopaminergic drug ropinirole were analyzed: a cross-over formulation comparison trial in 161 patients with early-stage Parkinson's disease, and a 24-week, parallel-group, placebo-controlled efficacy trial in 393 patients with advanced-stage Parkinson's disease. We applied item response theory to estimate the patients' symptom severity and developed a longitudinal model using the symptom severity to describe the time course of the placebo response and the drug effect on the time course. Similarly, we developed a longitudinal model using the total score. We then compared sample size needs for drug effect detection using these two different models. Total score modeling estimated median changes from baseline at 24 weeks (90% confidence interval) of -3.7 (-5.4 to -2.0) and -9.3 (-11 to -7.3) points by placebo and ropinirole. Comparable changes were estimated (with slightly higher precision) by item-score modeling as -2.0 (-4.0 to -1.0) and -9.0 (-11 to -8.0) points. The treatment duration was insufficient to estimate the symptom progression rate; hence the drug effect on the progression could not be assessed. The trial sizes to detect a drug effect with 80% power on total score and on symptom severity were estimated (at the type I error level of 0.05) as 88 and 58, respectively. Longitudinal item response analysis could markedly reduce sample size; it also has the potential for assessing drug effects on disease progression in longer trials.

OBJECTIVES: Pharmacogenetic panel-based testing represents a new model for precision medicine. A sufficiently powered prospective study assessing the (cost-)effectiveness of a panel-based pharmacogenomics approach to guide pharmacotherapy is lacking. Therefore, the Ubiquitous Pharmacogenomics Consortium initiated the PREemptive Pharmacogenomic testing for prevention of Adverse drug Reactions (PREPARE) study. Here, we provide an overview of considerations made to mitigate multiple methodological challenges that emerged during the design.METHODS: An evaluation of considerations made when designing the PREPARE study across six domains: study aims and design, primary endpoint definition and collection of adverse drug events, inclusion and exclusion criteria, target population, pharmacogenomics intervention strategy, and statistical analyses.RESULTS: Challenges and respective solutions included: (1) defining and operationalizing a composite primary endpoint enabling measurement of the anticipated effect, by including only severe, causal, and drug genotype-associated adverse drug reactions; (2) avoiding overrepresentation of frequently prescribed drugs within the patient sample while maintaining external validity, by capping drugs of enrolment; (3) designing the pharmacogenomics intervention strategy to be applicable across ethnicities and healthcare settings; and (4) designing a statistical analysis plan to avoid dilution of effect by initially excluding patients without a gene-drug interaction in a gatekeeping analysis.CONCLUSION: Our design considerations will enable quantification of the collective clinical utility of a panel of pharmacogenomics-markers within one trial as a proof-of-concept for pharmacogenomics-guided pharmacotherapy across multiple actionable gene-drug interactions. These considerations may prove useful to other investigators aiming to generate evidence for precision medicine.

Pharmacokinetic-based prophylaxis of replacement factor VIII products has been encouraged in the past years, but the exposure (factor VIII activity)-response (bleeding frequency) relationship remains unclear. The aim of this study was to characterize the relationship between factor VIII dose, plasma factor VIII activity, bleeding patterns and individual characteristics in severe hemophilia A patients. Pooled pharmacokinetic and bleeding data during prophylactic treatment with BAY 81-8973 (octocog alfa) were obtained from the three LEOPOLD trials. The population pharmacokinetics of factor VIII activity and longitudinal bleeding frequency, as well as bleeding severity, were described using nonlinear mixed effects modelling in NONMEM. In total, 183 patients (median age 22 years [range, 1-61]; weight 60 kg [11-124]) contributed with 1535 plasma factor VIII activity observations, 633 bleeds and 11 patient/study characteristics (median observation period 12 months [3.1-13.1]). A parametric repeated time-to-categorical bleed model, guided by plasma factor VIII activity from a 2-compartment population pharmacokinetic model, described the time to the occurrence of bleeds and their severity. Bleeding probability decreased with time of study, and a bleed was not found to affect the time of the next bleed. Several covariate effects were identified, including the bleeding history in the 12-month pre-study period increasing the bleeding hazard. However, unexplained inter-patient variability for the phenotypic bleeding pattern remained large (111%CV). Further studies to translate the model into a tool for dose individualization that considers the individual bleeding risk are required. Research based on a post-hoc analysis of the LEOPOLD studies (ClinicalTrials.gov identifiers NCT01029340, NCT01233258 and NCT01311648).