A 12-gene pharmacogenetic panel to prevent adverse drug reactions: an open-label, multicentre, controlled, cluster-randomised crossover implementation study.

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 control group were compared, and only if the difference was statistically significant was an analysis done that included all of the patients in the study. Outcomes were compared between the study and control groups, both for patients with an actionable drug-gene interaction test result (ie, a result for which the DPWG recommended a change to standard-of-care drug treatment) and for all patients who received at least one dose of index drug. The safety analysis included all participants who received at least one dose of a study drug. This study is registered with ClinicalTrials.gov, NCT03093818 and is closed to new participants. FINDINGS: Between March 7, 2017, and June 30, 2020, 41 696 patients were assessed for eligibility and 6944 (51·4 % female, 48·6% male; 97·7% self-reported European, Mediterranean, or Middle Eastern ethnicity) were enrolled and assigned to receive genotype-guided drug treatment (n=3342) or standard care (n=3602). 99 patients (52 [1·6%] of the study group and 47 [1·3%] of the control group) withdrew consent after group assignment. 652 participants (367 [11·0%] in the study group and 285 [7·9%] in the control group) were lost to follow-up. In patients with an actionable test result for the index drug (n=1558), a clinically relevant adverse drug reaction occurred in 152 (21·0%) of 725 patients in the study group and 231 (27·7%) of 833 patients in the control group (odds ratio [OR] 0·70 [95% CI 0·54-0·91]; p=0·0075), whereas for all patients, the incidence was 628 (21·5%) of 2923 patients in the study group and 934 (28·6%) of 3270 patients in the control group (OR 0·70 [95% CI 0·61-0·79]; p <0·0001). INTERPRETATION: Genotype-guided treatment using a 12-gene pharmacogenetic panel significantly reduced the incidence of clinically relevant adverse drug reactions and was feasible across diverse European health-care system organisations and settings. Large-scale implementation could help to make drug therapy increasingly safe. FUNDING: European Union Horizon 2020.

Characterization of anti-drug antibody dynamics using a bivariate mixed hidden-markov model by nonlinear-mixed effects approach.

Biological therapies may act as immunogenic triggers leading to the formation of anti-drug antibodies (ADAs). Population pharmacokinetic (PK) models can be used to characterize the relationship between ADA and drug disposition but often rely on the ADA bioassay results, which may not be sufficiently sensitive to inform on this characterization.In this work, a methodology that could help to further elucidate the underlying ADA production and impact on the drug disposition was explored. A mixed hidden-Markov model (MHMM) was developed to characterize the underlying (hidden) formation of ADA against the biologic, using certolizumab pegol (CZP), as a test drug. CZP is a PEGylated Fc free TNF-inhibitor used in the treatment of rheumatoid arthritis and other chronic inflammatory diseases.The bivariate MHMM used information from plasma drug concentrations and ADA measurements, from six clinical studies (n = 845), that were correlated through a bivariate Gaussian function to infer about two hidden states; production and no-production of ADA influencing PK. Estimation of inter-individual variability was not supported in this case. Parameters associated with the observed part of the model were reasonably well estimated while parameters associated with the hidden part were less precise. Individual state sequences obtained using a Viterbi algorithm suggested that the model was able to determine the start of ADA production for each individual, being a more assay-independent methodology than traditional population PK. The model serves as a basis for identification of covariates influencing the ADA formation, and thus has the potential to identify aspects that minimize its impact on PK and/or efficacy.

Population pharmacokinetics of cefotaxime in intensive care patients.

PURPOSE: To characterise the pharmacokinetics and associated variability of cefotaxime in adult intensive care unit (ICU) patients and to assess the impact of patient covariates. METHODS: This work was based on data from cefotaxime-treated patients included in the ACCIS (Antibiotic Concentrations in Critical Ill ICU Patients in Sweden) study. Clinical data from 51 patients at seven different ICUs in Sweden, given cefotaxime (1000-3000 mg given 2-6 times daily), were collected from the first day of treatment for up to three consecutive days. In total, 263 cefotaxime samples were included in the population pharmacokinetic analysis. RESULTS: A two-compartment model with linear elimination, proportional residual error and inter-individual variability (IIV) on clearance and central volume of distribution best described the data. The typical individual was 64 years, with body weight at ICU admission of 92 kg and estimated creatinine clearance of 94 mL/min. The resulting typical value of clearance was 11.1 L/h, central volume of distribution 5.1 L, peripheral volume of distribution 18.2 L and inter-compartmental clearance 14.5 L/h. The estimated creatinine clearance proved to be a significant covariate on clearance (p < 0.001), reducing IIV from 68 to 49%. CONCLUSION: A population pharmacokinetic model was developed to describe cefotaxime pharmacokinetics and associated variability in adult ICU patients. The estimated creatinine clearance partly explained the IIV in cefotaxime clearance. However, the remaining unexplained IIV is high and suggests a need for dose individualisation using therapeutic drug monitoring where the developed model, after evaluation of predictive performance, may provide support.

Pharmacometrics-Based Considerations for the Design of a Pharmacogenomic Clinical Trial Assessing Irinotecan Safety.

PURPOSE: Pharmacometric models provide useful tools to aid the rational design of clinical trials. This study evaluates study design-, drug-, and patient-related features as well as analysis methods for their influence on the power to demonstrate a benefit of pharmacogenomics (PGx)-based dosing regarding myelotoxicity. METHODS: Two pharmacokinetic and one myelosuppression model were assembled to predict concentrations of irinotecan and its metabolite SN-38 given different UGT1A1 genotypes (poor metabolizers: CLSN-38: -36%) and neutropenia following conventional versus PGx-based dosing (350 versus 245 mg/m2 (-30%)). Study power was assessed given diverse scenarios (n = 50-400 patients/arm, parallel/crossover, varying magnitude of CLSN-38, exposure-response relationship, inter-individual variability) and using model-based data analysis versus conventional statistical testing. RESULTS: The magnitude of CLSN-38 reduction in poor metabolizers and the myelosuppressive potency of SN-38 markedly influenced the power to show a difference in grade 4 neutropenia (<0.5·109 cells/L) after PGx-based versus standard dosing. To achieve >80% power with traditional statistical analysis (χ2/McNemar's test, α = 0.05), 220/100 patients per treatment arm/sequence (parallel/crossover study) were required. The model-based analysis resulted in considerably smaller total sample sizes (n = 100/15 given parallel/crossover design) to obtain the same statistical power. CONCLUSIONS: The presented findings may help to avoid unfeasible trials and to rationalize the design of pharmacogenetic studies.

Generating evidence for precision medicine: considerations made by the Ubiquitous Pharmacogenomics Consortium when designing and operationalizing the PREPARE study.

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.

Relationship between factor VIII activity, bleeds and individual characteristics in severe hemophilia A patients.

Pharmacokinetic-based prophylaxis of replacement factor VIII (FVIII) products has been encouraged in recent years, but the relationship between exposure (factor VIII activity) and response (bleeding frequency) remains unclear. The aim of this study was to characterize the relationship between FVIII dose, plasma FVIII activity, and 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 FVIII activity and longitudinal bleeding frequency, as well as bleeding severity, were described using non-linear mixed effects modeling in NONMEM. In total, 183 patients [median age 22 years (range, 1-61); weight 60 kg (11-124)] contributed with 1,535 plasma FVIII 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 FVIII 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 in 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 was based on a post-hoc analysis of the LEOPOLD studies registered at clinicaltrials.gov identifiers: 01029340, 01233258 and 01311648.

Model-based evaluation of low-dose factor VIII prophylaxis in haemophilia A.

INTRODUCTION: The optimal treatment modality for haemophilia A is lifelong prophylaxis which is expensive and may not be implementable everywhere where factor VIII (FVIII) availability is limited. A less costly alternative to prophylaxis is low-dose prophylaxis (LDP) which was compared to conventional prophylaxis in this model-based simulation study. AIM: To explore whether LDP is motivated where standard prophylaxis is not implementable, including evaluating LDP efficacy compared to high-dose prophylaxis and investigating the potential economic benefit of individualized dosing. METHODS: For a virtual adult haemophilia A population, FVIII activity levels were simulated following alternative treatment regimens, based on a published population PK model. The regimens included very LDP, LDP and conventional prophylaxis twice and thrice weekly. The annual probability of bleeding was predicted based on the weekly time spent below 1 IU/dL, using a previously published relationship. Additionally, PK-based dose individualization was evaluated to determine FVIII savings using Bayesian forecasting. RESULTS: A treatment regimen of 10 IU/kg administered thrice weekly cost 75% less than a standard high-dose regimen and was predicted to have a 5% higher median probability of annual bleeds. PK-based dose individualization may result in further cost-savings, but implementation needs benefit versus feasibility consideration. CONCLUSION: Based on simulations, a promising LDP regimen was identified that decreased treatment costs compared with standard high-dose prophylaxis at a small increase in bleeding risk. The results indicate that LDP is advocated where the standard-of-care is on-demand treatment; however, the results should be considered in the context of any limitations of the applied models.

Handling interoccasion variability in model-based dose individualization using therapeutic drug monitoring data.

AIMS: This study aims to assess approaches to handle interoccasion variability (IOV) in a model-based therapeutic drug monitoring (TDM) context, using a population pharmacokinetic model of coagulation factor VIII as example. METHODS: We assessed 5 model-based TDM approaches: empirical Bayes estimates (EBEs) from a model including IOV, with individualized doses calculated based on individual parameters either (i) including or (ii) excluding variability related to IOV; and EBEs from a model excluding IOV by (iii) setting IOV to zero, (iv) summing variances of interindividual variability (IIV) and IOV into a single IIV term, or (v) re-estimating the model without IOV. The impact of varying IOV magnitudes (0-50%) and number of occasions/observations was explored. The approaches were compared with conventional weight-based dosing. Predictive performance was assessed with the prediction error percentiles. RESULTS: When IOV was lower than IIV, the accuracy was good for all approaches (50th percentile of the prediction error [P50] <7.4%), but the precision varied substantially between IOV magnitudes (P97.5 61-528%). Approach (ii) was the most precise forecasting method across a wide range of scenarios, particularly in case of sparse sampling or high magnitudes of IOV. Weight-based dosing led to less precise predictions than the model-based TDM approaches in most scenarios. CONCLUSIONS: Based on the studied scenarios and theoretical expectations, the best approach to handle IOV in model-based dose individualization is to include IOV in the generation of the EBEs but exclude the portion of unexplained variability related to IOV in the individual parameters used to calculate the future dose.

Exploring Factors Causing Low Brain Penetration of the Opioid Peptide DAMGO through Experimental Methods and Modeling.

To advance the development of peptide analogues for improved treatment of pain, we need to learn more about the blood-brain barrier transport of these substances. A low penetration into the brain, with an unbound brain to blood ratio, Kp,uu, of 0.08, is an important reason for the lack of effect of the enkephalin analogue DAMGO (H-Tyr-d-Ala-Gly-MePhe-Gly-ol) according to earlier findings. The aim of this study was to investigate the role of efflux transporters, metabolism in the brain, and/or elimination through interstitial fluid bulk flow for the brain exposure of DAMGO. The in vivo brain distribution of DAMGO was evaluated using microdialysis in the rat. Data were analyzed with population modeling which resulted in a clearance into the brain of 1.1 and an efflux clearance 14 µL/min/g_brain. The efflux clearance was thus much higher than the bulk flow known from the literature. Coadministration with the efflux transporter inhibitors cyclosporin A and elacridar in vivo did not affect Kp,uu. The permeability of DAMGO in the Caco-2 assay was very low, of the same size as mannitol. The efflux ratio was <2 and not influenced by cyclosporin A or elacridar. These results indicate that the well-known efflux transporters Pgp and Bcrp are not responsible for the higher efflux of DAMGO, which opens up for an important role of other transporters at the BBB.

Treatment with subcutaneous and transdermal fentanyl: results from a population pharmacokinetic study in cancer patients.

PURPOSE: Transdermal fentanyl is effective for the treatment of moderate to severe cancer-related pain but is unsuitable for fast titration. In this setting, continuous subcutaneous fentanyl may be used. As data on the pharmacokinetics of continuous subcutaneous fentanyl are lacking, we studied the pharmacokinetics of subcutaneous and transdermal fentanyl. Furthermore, we evaluated rotations from the subcutaneous to the transdermal route. METHODS: Fifty-two patients treated with subcutaneous and/or transdermal fentanyl for moderate to severe cancer-related pain participated. A population pharmacokinetic model was developed and evaluated using non-linear mixed-effects modelling. For rotations from subcutaneous to transdermal fentanyl, a 1:1 dose conversion ratio was used while the subcutaneous infusion was continued for 12 h (with a 50 % tapering after 6 h). A 6-h scheme with 50 % tapering after 3 h was simulated using the final model. RESULTS: A one-compartment model with first-order elimination and separate first-order absorption processes for each route adequately described the data. The estimated apparent clearance of fentanyl was 49.6 L/h; the absorption rate constant for subcutaneous and transdermal fentanyl was 0.0358 and 0.0135 h(-1), respectively. Moderate to large inter-individual and inter-occasion variability was found. Around rotation from subcutaneous to transdermal fentanyl, measured and simulated plasma fentanyl concentrations rose and increasing side effects were observed. CONCLUSIONS: We describe the pharmacokinetics of subcutaneous and transdermal fentanyl in one patient cohort and report several findings that are relevant for clinical practice. Further research is warranted to study the optimal scheme for rotations from the subcutaneous to the transdermal route.

Population pharmacokinetics of edoxaban in patients with symptomatic deep-vein thrombosis and/or pulmonary embolism--the Hokusai-VTE phase 3 study.

AIMS: This study characterized the population pharmacokinetics of edoxaban in patients with symptomatic deep-vein thrombosis and/or pulmonary embolism in the Hokusai-VTE phase 3 study. The impact of the protocol-specified 50% dose reductions applied to patients with body weight ≤ 60 kg, creatinine clearance (CL(cr)) of 30 to 50 ml min(-1) or concomitant P-glycoprotein inhibitor on edoxaban exposure was assessed using simulations. METHODS: The sparse data from Hokusai-VTE, 9531 concentrations collected from 3707 patients, were pooled with data from 13 phase 1 studies. In the analysis, the covariate relationships used for dose reductions were estimated and differences between healthy subjects and patients as well as additional covariate effects of age, race and gender were explored based on statistical and clinical significance. RESULTS: A linear two-compartment model with first order absorption preceded by a lag time best described the data. Allometrically scaled body weight was included on disposition parameters. Apparent clearance was parameterized as non-renal and renal. The latter increased non-linearly with increasing CL(cr). Compared with healthy volunteers, inter-compartmental clearance and the CL(cr) covariate effect were different in patients (+64.6% and +274%). Asian patients had a 22.6% increased apparent central volume of distribution. The effect of co-administration of P-glycoprotein inhibitors seen in phase 1 could not be confirmed in the phase 3 data. Model-based simulations revealed lower exposure in dose-reduced compared with non-dose-reduced patients. CONCLUSIONS: The adopted dose-reduction strategy resulted in reduced exposure compared with non-dose-reduced, thereby overcompensating for covariate effects. The clinical impact of these differences on safety and efficacy remains to be evaluated.

Therapeutic drug monitoring of vancomycin and meropenem: Illustration of the impact of inaccurate information in dose administration time.

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.

A time-to-event model for acute rejections in paediatric renal transplant recipients treated with ciclosporin A.

AIMS: Ciclosporin A (CsA) dosing in immunosuppression after paediatric kidney transplantation remains challenging, and appropriate target CsA exposures (AUCs) are controversial. This study aimed to develop a time-to-first-acute rejection (AR) model and to explore predictive factors for therapy outcome. METHODS: Patient records at the Children's Hospital in Helsinki, Finland, were analysed. A parametric survival model in NONMEM was used to describe the time to first AR. The influences of AUC and other covariates were explored using stepwise covariate modelling, bootstrap-stepwise covariate modelling and cross-validated stepwise covariate modelling. The clinical relevance of the effects was assessed with the time at which 90% of the patients were AR free (t90). RESULTS: Data from 87 patients (0.7-19.8 years old, 54 experiencing an AR) were analysed. The baseline hazard was described with a function changing in steps over time. No statistically significant covariate effects were identified, a finding substantiated by all methods used. Thus, within the observed AUC range (90% interval 1.13-8.40 h mg l⁻¹), a rise in AUC was not found to increase protection from AR. Dialysis time, sex and baseline weight were potential covariates, but the predicted clinical relevance of their effects was low. For the strongest covariate, dialysis time, median t90 was 5.8 days (90% confidence interval 5.1-6.8) for long dialysis times (90th percentile) and 7.4 days (6.4-11.7) for short dialysis times (10th percentile). CONCLUSIONS: A survival model with discrete time-varying hazards described the data. Within the observed range, AUC was not identified as a covariate. This feedback on clinical practice may help to avoid unnecessarily high CsA dosing in children.

Relationship between factor VIII levels and bleeding for rFVIII-SingleChain in severe hemophilia A: A repeated time-to-event analysis.

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.

Association between Sports Participation, Factor VIII Levels and Bleeding in Hemophilia A.

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. CONCLUSION: 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.

A model-based approach leveraging in vitro data to support dose selection from the outset: A framework for bispecific antibodies in immuno-oncology.

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.

A multistate modeling and simulation framework to learn dose-response of oncology drugs: Application to bintrafusp alfa in non-small cell lung cancer.

The dose/exposure-efficacy analyses are often conducted separately for oncology end points like best overall response, progression-free survival (PFS) and overall survival (OS). Multistate models offer to bridge these dose-end point relationships by describing transitions and transition times from enrollment to response, progression, and death, and evaluating transition-specific dose effects. This study aims to apply the multistate pharmacometric modeling and simulation framework in a dose optimization setting of bintrafusp alfa, a fusion protein targeting TGF-ß and PD-L1. A multistate model with six states (stable disease [SD], response, progression, unknown, dropout, and death) was developed to describe the totality of endpoints data (time to response, PFS, and OS) of 80 patients with non-small cell lung cancer receiving 500 or 1200 mg of bintrafusp alfa. Besides dose, evaluated predictor of transitions include time, demographics, premedication, disease factors, individual clearance derived from a pharmacokinetic model, and tumor dynamic metrics observed or derived from tumor size model. We found that probabilities of progression and death upon progression decreased over time since enrollment. Patients with metastasis at baseline had a higher probability to progress than patients without metastasis had. Despite dose failed to be statistically significant for any individual transition, the combined effect quantified through a model with dose-specific transition estimates was still informative. Simulations predicted a 69.2% probability of at least 1 month longer, and, 55.6% probability of at least 2-months longer median OS from the 1200 mg compared to the 500 mg dose, supporting the selection of 1200 mg for future studies.

Non-linear mixed effects modelling of positron emission tomography data for simultaneous estimation of radioligand kinetics and occupancy in healthy volunteers.

The aim of this work was to develop a model simultaneously estimating (11)C-AZD9272 radioligand kinetics and the relationship between plasma concentration of AZD9272 and receptor occupancy in the human brain. AZD9272 is a new chemical entity pharmacologically characterised as a noncompetitive antagonist at the metabotropic glutamate receptor subtype 5 (mGluR5). Positron emission tomography (PET) was used to measure the time course of ((11)C-AZD9272) in the brain. The study included PET measurements in six healthy volunteers where the radioligand was given as a tracer dose alone as well as post oral treatment with different doses of unlabelled AZD9272. Estimation of radioligand kinetics, including saturation of receptor binding was performed by use of non-linear mixed effects modelling. Data from the regions with the highest (ventral striatum) and lowest (cerebellum) radioligand concentrations were included in the analysis. It was assumed that the extent of non-displaceable brain uptake was the same in both regions while the rate of CNS uptake and the receptor density differed. The results of the analysis showed that AZD9272 binding at the receptor is saturable with an estimated plasma concentration corresponding to 50% occupancy of approximately 200 nM. The density of the receptor binding sites was estimated to 800 nM and 200 nM in ventral striatum and cerebellum respectively. By simultaneously analysing data from several PET measurements and different brain regions in a non-linear mixed effects framework it was possible to estimate parameters of interest that would otherwise be difficult to quantify.

Model-Based Characterization of the Bidirectional Interaction Between Pharmacokinetics and Tumor Growth Dynamics in Patients with Metastatic Merkel Cell Carcinoma Treated with Avelumab.

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.

Population pharmacokinetic analysis of etrolizumab in patients with moderately-to-severely active ulcerative colitis.

Etrolizumab is an IgG1-humanized monoclonal antibody that specifically targets the ß7 subunit of α4ß7 and α4Eß7 integrins, and it has been evaluated for the treatment of moderately-to-severely active ulcerative colitis (UC). Population pharmacokinetic (PK) analysis was performed to characterize etrolizumab PK properties in patients with moderately-to-severely active UC and evaluate covariate impacts on exposure. The population PK model was developed based on etrolizumab serum concentrations from patients with moderately-to-severely active UC enrolled in six studies (one phase I, one phase II, and four phase III) and validated using another phase III clinical trial. Stepwise covariate modeling was used to evaluate the impact of 23 prespecified covariates. Etrolizumab PK was best described by a two-compartment model with first-order absorption, with clearance decreasing over time. Population typical values were 0.260 L/day for clearance (CL) during the first dosing internal, 2.61 L for central volume, 71.2% for bioavailability, and 0.193/day for absorption rate. CL reduced over the study duration, the typical maximum reduction was 26% with an onset half-life of 4.8 weeks. Consequently, the predicted mean terminal half-life was shorter after a single dose (13.0 days) compared to that at steady-state (17.1 days). Baseline body weight and albumin were the most impactful covariates for etrolizumab exposure. Final population PK model well characterized the PK properties of etrolizumab in patients with moderately-to-severely active UC and identified influential covariate effects.