Dose-fractionation studies of a Plasmodium phosphatidylinositol 4-kinase inhibitor in a humanized mouse model of malaria.

UCT594 is a 2-aminopyrazine carboxylic acid Plasmodium phosphatidylinositol 4-kinase inhibitor with potent asexual blood-stage activity, the potential for interrupting transmission, as well as liver-stage activities. Herein, we investigated pharmacokinetic/pharmacodynamic (PK/PD) relationships relative to blood-stage activity toward predicting the human dose. Dose-fractionation studies were conducted in the Plasmodium falciparum NSG mouse model to determine the PK/PD indices of UCT594, using the in vivo minimum parasiticidal concentration as a threshold. UCT594 demonstrated concentration-dependent killing in the P. falciparum-infected NSG mouse model. Using this data and the preclinical pharmacokinetic data led to a low predicted human dose of <50 mg. This makes UCT594 an attractive potential antimalarial drug.

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.

Pharmacodynamic mechanism-based interaction model for the haemodynamic effects of remifentanil and propofol in healthy volunteers.

BACKGROUND: Propofol and remifentanil are frequently combined for the induction and maintenance of general anaesthesia. Both propofol and remifentanil cause vasodilation and potentially reduce arterial BP. We aimed to develop a mechanism-based model that characterises the haemodynamic interactions between remifentanil and propofol. METHODS: Data from two clinical trials in healthy volunteers were analysed using remifentanil-alone, propofol-alone, and combination groups. We evaluated remifentanil effects on haemodynamics using a previously developed mechanism-based haemodynamic model of propofol. The interaction between propofol and remifentanil was explored using the principles of the general pharmacodynamic interaction (GPDI) model. RESULTS: Remifentanil alone increased the dissipation rate of total peripheral resistance by 50% at 3.0 ng ml-1. Additionally, the dissipation rates of HR and stroke volume were attenuated by 4.8% and 4.9% per 1 ng ml-1 increase in remifentanil concentration, respectively. The maximal effect of propofol alone in decreasing the production rate of total peripheral resistance was 78%, which decreased to 32% when combined with remifentanil 4 ng ml-1. The effects of remifentanil on HR and stroke volume were attenuated by propofol with maximum decreases of 11.9% and 21.2%, respectively. Goodness-of-fit plots and prediction-corrected visual predictive check plots showed good predictive performance of the models. CONCLUSIONS: The structure of the previous mechanism-based haemodynamic model for propofol was able to describe the effects of remifentanil alone on haemodynamic variables. The GPDI model provided a good framework for characterising the pharmacodynamic interaction between remifentanil and propofol on haemodynamic properties. CLINICAL TRIAL REGISTRATION: NCT02043938; NCT03143972.

Development of a pharmacokinetic and pharmacodynamic model for intranasal administration of midazolam in older adults: a single-site two-period crossover study.

BACKGROUND: Intranasal midazolam can produce procedural sedation in frail older patients with dementia who are unable to tolerate necessary medical or dental procedures during domiciliary medical care. Little is known about the pharmacokinetics and pharmacodynamics of intranasal midazolam in older (>65 yr old) people. The aim of this study was to understand the pharmacokinetic/pharmacodynamic properties of intranasal midazolam in older people with the primary goal of developing a pharmacokinetic/pharmacodynamic model to facilitate safer domiciliary sedation care. METHODS: We recruited 12 volunteers: ASA physical status 1-2, aged 65-80 yr, and received midazolam 5 mg intravenously and 5 mg intranasally on two study days separated by a 6 day washout period. Concentrations of venous midazolam and 1'-OH-midazolam, Modified Observer's Assessment of Alertness/Sedation (MOAA/S) score, bispectral index (BIS), arterial pressure, ECG, and respiratory parameters were measured for 10 h. RESULTS: Time to peak effect of intranasal midazolam for BIS, MAP, and SpO2 were 31.9 (6.2), 41.0 (7.6), and 23.1 (3.0) min, respectively. Intranasal bioavailability was lower compared with intravenous administration (Fabs 95%; 95% confidence interval: 89-100%). A three-compartment model best described midazolam pharmacokinetics following intranasal administration. A separate effect compartment linked to the dose compartment best described an observed time-varying drug-effect difference between intranasal and intravenous midazolam, suggesting direct nose-to-brain transport. CONCLUSIONS: Intranasal bioavailability was high and sedation onset was rapid, with maximum sedative effects after 32 min. We developed a pharmacokinetic/pharmacodynamic model for intranasal midazolam for older persons and an online tool to simulate changes in MOAA/S, BIS, MAP, and SpO2 after single and additional intranasal boluses. CLINICAL TRIAL REGISTRATION: EudraCT (2019-004806-90).

Assessing the relative importance of bacterial resistance, persistence and hyper-mutation for antibiotic treatment failure.

To curb the rising threat of antimicrobial resistance, we need to understand the routes to antimicrobial treatment failure. Bacteria can survive treatment by using both genetic and phenotypic mechanisms to diminish the effect of antimicrobials. We assemble empirical data showing that, for example, Pseudomonas aeruginosa infections frequently contain persisters, transiently non-growing cells unaffected by antibiotics (AB) and hyper-mutators, mutants with elevated mutation rates, and thus higher probability of genetic resistance emergence. Resistance, persistence and hyper-mutation dynamics are difficult to disentangle experimentally. Hence, we use stochastic population modelling and deterministic fitness calculations to investigate the relative importance of genetic and phenotypic mechanisms for immediate treatment failure and establishment of prolonged, chronic infections. We find that persistence causes 'hidden' treatment failure with very low cell numbers if antimicrobial concentrations prevent growth of genetically resistant cells. Persister cells can regrow after treatment is discontinued and allow for resistance evolution in the absence of AB. This leads to different mutational routes during treatment and relapse of an infection. By contrast, hyper-mutation facilitates resistance evolution during treatment, but rarely contributes to treatment failure. Our findings highlight the time and concentration dependence of different bacterial mechanisms to escape AB killing, which should be considered when designing 'failure-proof' treatments.

Mechanism-based pharmacodynamic model for propofol haemodynamic effects in healthy volunteers☆.

BACKGROUND: The adverse haemodynamic effects of the intravenous anaesthetic propofol are well known, yet few empirical models have explored the dose-response relationship. Evidence suggests that hypotension during general anaesthesia is associated with postoperative mortality. We developed a mechanism-based model that quantitatively characterises the magnitude of propofol-induced haemodynamic effects during general anaesthesia. METHODS: Mean arterial pressure (MAP), heart rate (HR) and pulse pressure (PP) measurements were available from 36 healthy volunteers who received propofol in a step-up and step-down fashion by target-controlled infusion using the Schnider pharmacokinetic model. A mechanistic pharmacodynamic model was explored based on the Snelder model. To benchmark the performance of this model, we developed empirical models for MAP, HR, and PP. RESULTS: The mechanistic model consisted of three turnover equations representing total peripheral resistance (TPR), stroke volume (SV), and HR. Propofol-induced changes were implemented by Emax models on the zero-order production rates of the turnover equations for TPR and SV. The estimated 50% effective concentrations for propofol-induced changes in TPR and SV were 2.96 and 0.34 µg ml-1, respectively. The goodness-of-fit for the mechanism-based model was indistinguishable from the empirical models. Simulations showed that predictions from the mechanism-based model were similar to previously published MAP and HR observations. CONCLUSIONS: We developed a mechanism-based pharmacodynamic model for propofol-induced changes in MAP, TPR, SV, and HR as a potential approach for predicting haemodynamic alterations. CLINICAL TRIAL REGISTRATION: NCT02043938.

Understanding and applying pharmacometric modelling and simulation in clinical practice and research.

Understanding the dose-concentration-effect relationship is a fundamental component of clinical pharmacology. Interpreting data arising from observations of this relationship requires the use of mathematical models; i.e. pharmacokinetic (PK) models to describe the relationship between dose and concentration and pharmacodynamic (PD) models describing the relationship between concentration and effect. Drug development requires several iterations of pharmacometric model-informed learning and confirming. This includes modelling to understand the dose-response in preclinical studies, deriving a safe dose for first-in-man, and the overall analysis of Phase I/II data to optimise the dose for safety and efficacy in Phase III pivotal trials. However, drug development is not the boundary at which PKPD understanding and application stops. PKPD concepts will be useful to anyone involved in the prescribing and administration of medicines for purposes such as determining off-label dosing in special populations, individualising dosing based on a measured biomarker (personalised medicine) and in determining whether lack of efficacy or unexpected toxicity maybe solved by adjusting the dose rather than the drug. In clinical investigator-led study design, PKPD can be used to ensure the optimal dose is used, and crucially to define the expected effect size, thereby ensuring power calculations are based on sound prior information. In the clinical setting the most likely people to hold sufficient expertise to advise on PKPD matters will be the pharmacists and clinical pharmacologists. This paper reviews fundamental PKPD principles and provides some real-world examples of PKPD use in clinical practice and applied clinical research.

A Phase II pilot trial to evaluate safety and efficacy of ferroquine against early Plasmodium falciparum in an induced blood-stage malaria infection study.

BACKGROUND: Ferroquine (SSR97193) is a candidate anti-malarial currently undergoing clinical trials for malaria. To better understand its pharmacokinetic (PK) and pharmacodynamic (PD) parameters the compound was tested in the experimentally induced blood stage malaria infection model in volunteers. METHODS: Male and non-pregnant female aged 18-50 years were screened for this phase II, controlled, single-centre clinical trial. Subjects were inoculated with ~1800 viable Plasmodium falciparum 3D7A-infected human erythrocytes, and treated with a single-dose of 800 mg ferroquine. Blood samples were taken at defined time-points to measure PK and PD parameters. The blood concentration of ferroquine and its active metabolite, SSR97213, were measured on dry blood spot samples by ultra-performance liquid chromatography with tandem mass spectrometry (LC-MS/MS). Parasitaemia and emergence of gametocytes were monitored by quantitative PCR. Safety was determined by recording adverse events and monitoring clinical laboratory assessments during the course of the study. RESULTS: Eight subjects were enrolled into the study, inoculated with infected erythrocytes and treated with 800 mg ferroquine. Ferroquine was rapidly absorbed with maximal exposure after 4-8 and 4-12 h exposure for SSR97213. Non-compartmental PK analysis resulted in estimates for half-lives of 10.9 and 23.8 days for ferroquine and SSR97213, respectively. Parasite clearance as reported by parasite reduction ratio was 162.9 (95 % CI 141-188) corresponding to a parasite clearance half-life of 6.5 h (95 % CI: 6.4-6.7 h). PK/PD modelling resulted in a predicted minimal parasiticidal concentration of 20 ng/mL, and the single dosing tested in this study was predicted to maintain an exposure above this threshold for 454 h (37.8 days). Although ferroquine was overall well tolerated, transient elevated transaminase levels were observed in three subjects. Paracetamol was the only concomitant treatment among the two out of these three subjects that may have played a role in the elevated transaminases levels. No clinically significant ECG abnormalities were observed. CONCLUSIONS: The parameters and PK/PD model derived from this study pave the way to the further rational development of ferroquine as an anti-malarial partner drug. The safety of ferroquine has to be further explored in controlled human trials. Trial registration anzctr.org.au (registration number: ACTRN12613001040752), registered 18/09/2013.

Model-based exposure-response analysis to quantify age related differences in the response to scopolamine in healthy subjects.

AIM: Subjects with increasing age are more sensitive to the effects of the anti-muscarinic agent scopolamine, which is used (among other indications) to induce temporary cognitive dysfunction in early phase drug studies with cognition enhancing compounds. The enhanced sensitivity has always been attributed to incipient cholinergic neuronal dysfunction, as a part of the normal aging process. The aim of the study was to correlate age-dependent pharmacodynamic neuro-physiologic effects of scopolamine after correcting for differences in individual exposure. METHODS: We applied a pharmacokinetic and pharmacodynamic modelling approach to describe individual exposure and neurocognitive effects of intravenous scopolamine administration in healthy subjects. RESULTS: A two-compartment linear kinetics model best described the plasma concentrations of scopolamine. The estimated scopolamine population mean apparent central and peripheral volume of distribution was 2.66 ± 1.050 l and 62.10 ± 10.100 l, respectively and the clearance was 1.09 ± 0.096 l min(-1) . Age was not related to a decrease of performance in the tests following scopolamine administration in older subjects. Only the saccadic peak velocity showed a positive correlation between age and sensitivity to scopolamine. Age was, however, correlated at baseline with an estimated slower reaction time while performing the cognitive tests and to higher global δ and frontal θ frequency bands measured with the surface EEG. CONCLUSIONS: Most of the differences in response to scopolamine administration between young and older subjects could be explained by pharmacokinetic differences (lower clearance) and not to an enhanced sensitivity when corrected for exposure levels.

Celecoxib interferes to a limited extent with aspirin-mediated inhibition of platelets aggregation.

AIMS: The aim of the study was to analyze the interaction between celecoxib and low dose aspirin for COX-1 binding and its consequences on the aspirin-mediated antiplatelet effects. METHODS: We investigated ex vivo the interaction between celecoxib and aspirin for COX-1 binding and measured the resulting antiplatelet effects. We applied mechanism-based pharmacokinetic-pharmacodynamic (PKPD) modelling to analyze these data and to predict in vivo platelet aggregation for different doses and administration schedules of aspirin and celecoxib. RESULTS: The predictions of the PK-PD model were consistent with results from previous studies that investigated interaction between aspirin and celecoxib. The modelling results indicate that celecoxib can attenuate to a limited extent the in vivo antiplatelet effects of low dose aspirin. The extent of this interaction can be substantial (up to 15% increase in platelet aggregation by 200 mg day(-1) celecoxib when combined with low dose aspirin) during the first days of aspirin administration in patients who are already treated with celecoxib, and it cannot be prevented by separate administration of the interacting drugs. CONCLUSIONS: At the recommended therapeutic doses, celecoxib can attenuate to a limited extent the in vivo antiplatelet effects of low dose aspirin. Patients receiving a combination of low dose aspirin and the recommended doses of celecoxib were not identified to have increased risk of cardiovascular and cerebrovascular events due to competition between these drugs for COX-1 binding. Interaction between low dose aspirin and other COX-2 inhibitors and its clinical consequences requires further investigation.

Pharmacokinetic-pharmacodynamic modelling of acute N-terminal pro B-type natriuretic peptide after doxorubicin infusion in breast cancer.

AIMS: The aim of the present study was to develop a pharmacokinetic-pharmacodynamic (PK-PD) model to characterize the relationship between plasma doxorubicin and N-terminal pro B-type natriuretic peptide (NT-proBNP) concentrations within 48 h of doxorubicin treatment. METHODS: The study enrolled 17 female patients with stages 1-3 breast cancer and receiving adjuvant doxorubicin (60 mg m(-2) ) and cyclophosphamide (600 mg m(-2) ) every 14 days for four cycles. In two consecutive cycles, plasma concentrations of doxorubicin, doxorubicinol, troponin and NT-proBNP were collected before infusion, and up to 48 h after the end of doxorubicin infusion. Nonlinear mixed-effects modelling was used to describe the PK-PD relationship of doxorubicin and NT-proBNP. RESULTS: A three-compartment parent drug with a one-compartment metabolite model best described the PK of doxorubicin and doxorubicinol. Troponin concentrations remained similar to baseline. An indirect PD model with transit compartments best described the relationship of doxorubicin exposure and acute NT-proBNP response. Estimated PD parameters were associated with large between-subject variability (total assay variability 38.8-73.9%). Patient clinical factors, including the use of enalapril, were not observed to be significantly associated with doxorubicin PK or NT-proBNP PD variability. CONCLUSION: The relationship between doxorubicin concentration and the acute NT-proBNP response was successfully described with a population PK-PD model. This model will serve as a valuable framework for future studies to identify clinical factors associated with the acute response to doxorubicin. Future studies are warranted to examine the relationship between this acute response and subsequent heart failure. Should such a relationship be established, this model could provide useful information on patients' susceptibility to doxorubicin-induced long-term cardiotoxicity.

Pharmacokinetics and concentration-effect relationship of adalimumab in rheumatoid arthritis.

AIMS: This study aimed at describing adalimumab pharmacokinetics (PK) and the concentration-effect relationship of adalimumab using pharmacokinetic-pharmacodynamic (PK-PD) modelling in patients with rheumatoid arthritis (RA). METHODS: Adalimumab PK and PK-PD data were obtained from a multicentric observational study. Adalimumab (40 mg) was administered subcutaneously every other week, and its pharmacokinetics was described using a one-compartment model. The relationship between adalimumab concentration and C-reactive protein (CRP) concentration was described using an indirect response model with inhibition of CRP input, whereas the relationship between adalimumab concentration and disease activity score in 28 joints (DAS28) was described using a direct inhibition model. Dose regimens that included a loading dose of adalimumab were simulated. RESULTS: Thirty patients treated for RA were analysed. The following pharmacokinetic and PK-PD parameters were estimated (interidividual coefficient of variation): apparent volume of distribution (Vd /F) = 10.8 l (92%); apparent clearance (CL/F) = 0.32 l day(-1) (17%); first-order absorption rate (ka ) = 0.28 day(-1) ; CRP input (kin ) = 22.0 mg l(-1) day(-1) (65%); adalimumab concentration leading to a 50% decrease in kin (C50 ) = 3.6 mg l(-1) (88%); baseline DAS28 (DAS0 ) = 5.5 mg l(-1) (11%); and adalimumab concentration leading to 50% decrease of DAS0 (IC50 ) = 11.0 mg l(-1) (71%). Simulations showed that a 160 mg loading dose should reduce the time to reach efficacy in terms of both CRP and DAS28 after the first injection. CONCLUSIONS: This is the first study to describe adalimumab pharmacokinetics and the concentration-effect relationship in RA. A 160 mg loading dose may lead to an increased benefit from treatment in RA patients.

Model-based evaluation of drug-induced QTc prolongation for compounds in early development.

AIMS: Significant differences between dogs and humans have been observed in the concentration-QTc effect relationship of compounds with known pro-arrhythmic properties. These findings suggest that interspecies differences must be considered when evaluating drug effects. The aim of this study was to evaluate the performance of a model-based approach to assess the risk of QTc prolongation for three investigational compounds (NCE01, NCE02 and NCE03). METHODS: Pharmacokinetic and pharmacodynamic data from experiments in conscious dogs and healthy subjects were included in this analysis. Pharmacokinetic modelling and deconvolution methods were applied to derive drug concentrations at the time of each QT measurement. An integrated pharmacokinetic-pharmacodynamic (PKPD) model was then used to describe QT prolongation. A threshold of ≥10 ms was used to characterize the probability of QTc prolongation. RESULTS: The PKPD relationships of all three compounds were successfully described in both species. A strong effect was observed after administration of NCE01 to dogs and humans, with a slope of 0.0061 and 0.0662 ms nm(-1), respectively, and maximal probability of QTc prolongation ≥10 ms at peak concentration. For NCE02 and NCE03, QTc-shortening and borderline QT effects were observed both in dogs and humans, as described by negative or very shallow slopes (NCE02, -0.00098 and -0.01 ms nm(-1); NCE03, 0.00064 and -0.0002 ms nm(-1)). CONCLUSIONS: Whilst NEC01 shows clear pro-arrhythmic effects, the liability for QT/QTc prolongation for NCE02 and NCE03 can be deemed low at the expected therapeutic exposure. Moreover, our results show the advantages of an integrated PKPD approach as the basis for translating pro-arrhythmic effects from dogs to humans.

Integration of PKPD relationships into benefit-risk analysis.

AIM: Despite the continuous endeavour to achieve high standards in medical care through effectiveness measures, a quantitative framework for the assessment of the benefit-risk balance of new medicines is lacking prior to regulatory approval. The aim of this short review is to summarise the approaches currently available for benefit-risk assessment. In addition, we propose the use of pharmacokinetic-pharmacodynamic (PKPD) modelling as the pharmacological basis for evidence synthesis and evaluation of novel therapeutic agents. METHODS: A comprehensive literature search has been performed using MESH terms in PubMed, in which articles describing benefit-risk assessment and modelling and simulation were identified. In parallel, a critical review of multi-criteria decision analysis (MCDA) is presented as a tool for characterising a drug's safety and efficacy profile. RESULTS: A definition of benefits and risks has been proposed by the European Medicines Agency (EMA), in which qualitative and quantitative elements are included. However, in spite of the value of MCDA as a quantitative method, decisions about benefit-risk balance continue to rely on subjective expert opinion. By contrast, a model-informed approach offers the opportunity for a more comprehensive evaluation of benefit-risk balance before extensive evidence is generated in clinical practice. CONCLUSIONS: Benefit-risk balance should be an integral part of the risk management plan and as such considered before marketing authorisation. Modelling and simulation can be incorporated into MCDA to support the evidence synthesis as well evidence generation taking into account the underlying correlations between favourable and unfavourable effects. In addition, it represents a valuable tool for the optimization of protocol design in effectiveness trials.

Pharmacokinetic/pharmacodynamic evaluation of tigecycline dosing in a hollow fiber infection model against clinical bla-KPC producing Klebsiella Pneumoniae isolates.

The FDA announced a boxed warning for tigecycline due to progression of infections caused by Gram-negative bacteria and increased risk of mortality during treatment. Plasma exposure of tigecycline might not prevent bacteraemia in these cases from the focuses. Hence, we evaluated intensified dosing regimens and breakpoints that might suppress bloodstream infections, caused by progression of infection by e.g., Gram-negatives. A pharmacometric model was built from tigecycline concentrations (100-600 mg daily doses) against clinical Klebsiella pneumoniae isolates (MIC 0.125-0.5 mg/L). Regrowth occurred at clinically used doses and stasis was only achieved with 100 mg q8h for the strain with the lowest studied MIC of 0.125 mg/L. Stasis at 24 h was related to fAUC/MIC of 38.5. Our study indicates that even intensified dosing regimens might prevent bloodstream infections only for MIC values ≤0.125 mg/L for tigecycline. This indicates an overly optimistic breakpoint of 1 mg/L for Enterobacterales, which are deemed to respond to the tigecycline high dose regimen (EUCAST Guidance Document on Tigecycline Dosing 2022).

Not-in-trial simulation I: Bridging cardiovascular risk from clinical trials to real-life conditions.

AIMS: The assessment of heart rate-corrected QT (QTc) interval prolongation relies on the evidence of drug effects in healthy subjects. This study demonstrates the relevance of pharmacokinetic-pharmacodynamic (PKPD) relationships to characterize drug-induced QTc interval prolongation and explore the discrepancies between clinical trials and real-life conditions. METHODS: d,l-Sotalol data from healthy subjects and from the Rotterdam Study cohort were used to assess treatment response in a phase I setting and in a real-life conditions, respectively. Using modelling and simulation, drug effects at therapeutic doses were predicted in both populations. RESULTS: Inclusion criteria were shown to restrict the representativeness of the trial population in comparison to real-life conditions. A significant part of the typical patient population was excluded from trials due to weight and baseline QTc interval criteria. Relative risk was significantly different between sotalol users with and without heart failure, hypertension, diabetes and myocardial infarction (P < 0.01). Although drug effects do cause an increase in the relative risk of QTc interval prolongation, the presence of diabetes represented an increase from 4.0 [95% confidence interval (CI) 2.7-5.8] to 6.5 (95% CI 1.6-27.1), whilst for myocardial infarction it increased from 3.4 (95% CI 2.3-5.13) to 15.5 (95% CI 4.9-49.3). CONCLUSIONS: Our findings show that drug effects on QTc interval do not explain the observed QTc values in the population. The prevalence of high QTc values in the real-life population can be assigned to co-morbidities and concomitant medications. These findings substantiate the need to account for these factors when evaluating the cardiovascular risk of medicinal products.

Corrigendum: Guidance for the treatment of adult growth hormone deficiency with somapacitan, a long-acting growth hormone preparation.

[This corrects the article DOI: 10.3389/fendo.2022.1040046.].

FOLFIRINOX Pharmacodynamic Interactions in 2D and 3D Pancreatic Cancer Cell Cultures.

The multi-drug combination regime, FOLFIRINOX, is a standard of care chemotherapeutic therapy for pancreatic cancer patients. However, systematic evaluation of potential pharmacodynamic interactions among multi-drug therapy has not been reported previously. Here, pharmacodynamic interactions of the FOLFIRINOX agents (5-fluorouracil (5-FU), oxaliplatin (Oxa) and SN-38, the active metabolite of irinotecan) were assessed across a panel of primary and established pancreatic cancer cells. Inhibition of cell proliferation was quantified for each drug, alone and in combination, to obtain quantitative, drug-specific interaction parameters and assess the nature of drug interactions. The experimental data were analysed assuming Bliss independent interactions, and nonlinear regression model fitting was conducted in SAS. Estimates of the drug interaction term, psi (ψ), revealed that the Oxa/SN-38 combination appeared synergistic in PANC-1 (ψ = 0.6, 95% CI = 0.4, 0.9) and modestly synergistic, close to additive, in MIAPaCa-2 (ψ = 0.8, 95% CI = 0.6, 1.0) in 2D assays. The triple combination was strongly synergistic in MIAPaCa-2 (ψ = 0.2, 95% CI = 0.1, 0.3) and modestly synergistic/borderline additive in PANC-1 2D (ψ = 0.8, 95% CI = 0.6, 1.0). The triple combination showed antagonistic interactions in the primary PIN-127 and 3D PANC-1 model (ψ > 1). Quantitative pharmacodynamic interactions have not been described for the FOLFIRINOX regimen; this analysis suggests a complex interplay among the three chemotherapeutic agents. Extension of this pharmacodynamic analysis approach to clinical/translational studies of the FOLFIRINOX combination could reveal additional pharmacodynamic interactions and guide further refinement of this regimen to achieve optimal clinical responses.

Guidance for the treatment of adult growth hormone deficiency with somapacitan, a long-acting growth hormone preparation.

Adult growth hormone deficiency (AGHD) is a rare endocrine disorder characterized by an abnormal body composition, metabolic abnormalities associated with increased cardiovascular diseases, bone loss, and impaired quality of life. Daily subcutaneous injections with recombinant growth hormone (GH) can alleviate the abnormalities associated with AGHD. Several long-acting GH (LAGH) preparations are currently in development that aim to reduce treatment burden for patients receiving daily GH injections. Somapacitan (Sogroya®; Novo Nordisk, Denmark) is the first LAGH preparation that has been approved for treatment of AGHD in the United States, Europe, and Japan. The recent approval of somapacitan and anticipated approval of other LAGH molecules presents new questions for physicians planning to treat AGHD with LAGH in the future. Differences in the technologies used to prolong the half-life of recombinant GH are expected to result in variations in pharmacokinetic and pharmacodynamic profiles between preparations. Therefore, it is essential that physicians understand and consider such variations when treating patients with these novel GH replacement therapies. Here, we present a set of treatment recommendations that have been created to guide physicians initiating therapy with somapacitan in patients with AGHD who are eligible for GH replacement. Furthermore, we will review the published data that underlie these recommendations to explain the rationale for the treatment and monitoring advice provided.