A new PKPD model to characterize the inoculum effect of Acinetobacter baumannii on polymyxin B in vitro

The inoculum effect (i.e., reduction in antimicrobial activity at large starting inoculum) is a phenomenon described for various pathogens. Since limited data exist regarding inoculum effect of Acinetobacter baumannii , we evaluated killing of A. baumannii by polymyxin B, a last-resort antibiotic, at several starting inocula and developed a PKPD model to capture this phenomenon. In vitro static time-kill experiments were performed using polymyxin B at concentrations ranging from 0.125 to 128 mg/L against a clinical A. baumannii isolate at four starting inocula from 10 5 to 10 8 CFU/mL. Samples were collected up to 30 h to quantify the viable bacterial burden and were simultaneously modeled in the NONMEM software program. The expression of polymyxin B resistance genes ( lpxACD , pmrCAB and wzc ), and genetic modifications were studied by RT-qPCR and DNA sequencing experiments, respectively. The PKPD model included a single homogeneous bacterial population with adaptive resistance. Polymyxin B effect was modelled as a sigmoidal E max model and the inoculum effect as an increase of polymyxin B EC 50 with increasing starting inoculum using a power function. Polymyxin B displayed a reduced activity as the starting inoculum increased: a 20-fold increase of polymyxin B EC 50 was observed between the lowest and the highest inoculum. No effects of polymyxin B and inoculum size were observed on the studied genes. The proposed PKPD model successfully described and predicted the pronounced in vitro inoculum effect of A. baumannii on polymyxin B activity. These results should be further validated using other bacteria/antibiotic combinations and in vivo models.

Investigating myotoxicity following Australian red-bellied black snake (Pseudechis porphyriacus) envenomation

Background Myotoxicity is one of the common clinical manifestations of red-bellied black snake (Pseudechis porphyriacus) envenomation characterised by elevated creatine kinase (CK) concentrations of greater than 1000 U/L. This study aimed to investigate the occurrence of myotoxicity in patients following envenomation. Methods/Principal findings Patient characteristics and serial blood samples (timed venom concentrations and CK concentrations, pre- and post- antivenom) from 114 patients (median age 41, 2-90y; 80 male) were extracted from the Australian Snakebite Project database. Patients were categorised into three groups based on peak CK concentrations [no myotoxicity (<1000 U/L), mild (1000–10,000 U/L) and severe (>10,000 U/L)]. The odds of (mild or severe) myotoxicity was lower in patients that received early antivenom (within 6 hours post-bite) compared to those that received late or no antivenom (odd ratio was 0.186; 95% confidence interval, 0.052–0.664). A population pharmacokinetic-pharmacodynamic (PKPD) model was developed to describe the relationship between the time course of venom (a mixture of toxins) and effect (elevated CK). In addition, a kinetic-pharmacodynamic (KPD) model was developed to describe the relationship between time course of a theoretical toxin and effect. Model development and parameter estimation was performed using NONMEM v7.3. No single set of parameter values from either the PKPD or KPD models were found that could accurately describe the time course of different levels of severity of myotoxicity. The predicted theoretical toxin half-life from the KPD model was 11 ± 3.9 hours compared to the half-life of venom of 5.3 ± 0.36 hours. This indicates that the putative causative toxin’s concentration-time profile does not parallel that of venom. Conclusion Early antivenom administration reduces the incidence of myotoxicity. The venom concentration profile does not appear to be the driver for myotoxicity following envenomation. Additional factors that affect the sensitivity of the patient to snake venom/toxins must be explored to understand the relationship with myotoxicity.

Pharmacokinetic-pharmacodynamic modelling of atazanavir in hair among adolescents on antiretroviral treatment in Zimbabwe

Background Drug potency is a pharmacological parameter defining dose or concentration of drug required to obtain 50% of the drug’s maximal effect. Pharmacokinetic-pharmacodynamic modelling and simulation allows estimation of potency and evaluate strategies improving treatment outcome. The objective of our study is to determine potency of atazanavir in hair, defined as atazanavir level in hair associated with 50% probability of failing to achieve viral load below 1000 copies/ml among adolescents, and explore the effect of participant specific variables on potency. Methods A secondary analysis was performed on data from a previous study conducted in HIV-infected adolescents failing 2nd line ART from Harare central hospital, Zimbabwe, between 2015 and 2016. We simulated atazanavir concentrations in hair using NONMEM (version 7.3) ADVAN 13, based on a previously established pharmacokinetic model. Logistic regression methods were used for PKPD analysis. Simulations utilising PKPD model focused on estimation of potency and exploring the effect of covariates. Results The potency of atazanavir in hair was found to be 4.5 ng/mg hair before adjusting for covariate effects. Participants at three months follow-up, reporting adequate adherence, having normal BMI-for-age, and cared for by mature guardians had increased potency of atazanavir in hair of 2.6 ng/mg, however the follow-up event was the only statistically significant factor at 5% level. Conclusion Atazanavir in hair in the range 2.6 to 4.5 ng/mg is associated with above 50% probability of early viral load suppression. Adherence monitoring to adolescents with lower potency of atazanavir is recommended. The effect self-reported adherence level, BMI-for-age, and caregiver status require further evaluation.

Towards Evidence-Based Weaning: a Mechanism-Based Pharmacometric Model to Characterize Iatrogenic Withdrawal Syndrome in Critically Ill Children

For the management of iatrogenic withdrawal syndrome (IWS) in children, a quantitative understanding of the dynamics of IWS of commonly used opioids and sedatives is lacking. Here, we introduce a new mechanism-based pharmacokinetic-pharmacodynamic (PKPD) modeling approach for studying IWS in pediatric clinical datasets. One thousand seven hundred eighty-two NRSwithdrawal scores of IWS severity were analyzed, which were collected from 81 children (age range: 1 month–18 years) that received opioids or sedatives by continuous infusion for 5 days or more. These data were successfully fitted with a PKPD model consisting of a plasma and a dependence compartment that well characterized the dynamics of IWS from morphine, fentanyl, and ketamine. The results suggest that (1) instead of decreasing the infusion rate by a set percentage at set intervals, it would be better to lengthen the weaning period when higher infusion rates are administered prior to weaning; (2) for fentanyl specifically, the risk of IWS might be lower when weaning with smaller dose reductions every 12 h instead of weaning with greater dose reductions every 48 h. The developed PKPD model can be used to evaluate the risk of IWS over time and the extent to which it is affected by different weaning strategies. The results yield hypotheses that could guide future clinical research on optimal weaning strategies. The mechanism-based PKPD modeling approach can be applied in other datasets to characterize the IWS dynamics of other drugs used in pediatric intensive care. Graphical abstract

Extrapolation and Justification of Nplate Dosing to Improve Overall Survival in Acute Radiation Syndrome

Background: Acute Radiation Syndrome (ARS) is an acute illness caused by exposure to a high dose of penetrating radiation over a short period of time. Hematopoietic subsyndrome of ARS (HS-ARS) is characterized by dose dependent bone marrow depression leading to lymphopenia, neutropenia, thrombocytopenia, and anemia. Death due to HS-ARS from infection or excessive bleeding usually occurs within 2 to 3 weeks. Duration of thrombocytopenia is a predictor of overall survival (OS) in irradiated animal models, suggesting that a treatment for thrombocytopenia may increase survival in humans with HS-ARS. Romiplostim, a thrombopoietin receptor agonist, treatment resulted in prevention of severe thrombocytopenia and increased OS in irradiated animals. As human clinical trials for HS-ARS are not feasible or ethical, a romiplostim pharmacokinetic/pharmacodynamic (PKPD)-OS model for irradiated humans was developed. The model, informed by PKPD data in healthy/irradiated rhesus monkeys (RM) and healthy volunteers (HV), was subsequently used to predict the survival benefit of romiplostim relative to placebo in humans with HS-ARS. Methods: A PKPD model of romiplostim exposure-platelet response in healthy RM was developed and updated with radiation parameters to estimate the radiation effects on thrombopoiesis, on PKPD of romiplostim, and on differences in platelet response due to sex and body weight (Pritchard-Bell, ACoP11, 2020). A parametric time-to-event model relating platelet time course to OS in irradiated RM with/without romiplostim treatment was developed to quantify the impact of platelet response on OS (Jones, ACoP11, 2020). To extrapolate radiation effects to humans, romiplostim PKPD radiation parameters and radiation effects estimated from irradiated RM were applied to a romiplostim HV PKPD model. The extrapolated irradiated human PKPD model and irradiated RM OS model were combined and calibrated against published historical mortality data of humans exposed to acute radiation (Scott BR 1990). Following calibration, the extrapolated irradiated human PKPD and OS models were used to conduct simulations of OS in irradiated humans receiving romiplostim or placebo treatment. Relative survival benefit (RSB) of romiplostim, proportion of romiplostim treated humans surviving relative to placebo treated humans post radiation exposure, was summarized for various romiplostim doses (1 [initiation dose per label], 3, or 10 µg/kg [maximum dose per label]) and treatment scenarios (time after irradiation, adult vs pediatric) based on simulations of 10,000 humans/scenario randomized 1:1 to receive romiplostim or placebo. Results: An HV PKPD model of thrombopoiesis was updated to incorporate radiation specific scaling factors estimated from irradiated RM on romiplostim pharmacokinetic parameters and platelet lifespan, nonlinear inhibitory effect of radiation dose on megakaryocyte production, treatment effect of romiplostim on platelet lifespan, radiation sensitivity and radiation intensity. The extrapolated PKPD model for irradiated humans combined with the OS model from irradiated RM was calibrated with a scaling factor of 1.24 on radiation parameters to result in 50% survival 60 days post radiation exposure for humans exposed to a 3.07 Gy radiation dose (1 Gy/hr over 3.07 hr) consistent with published data. The calibrated OS model was used to simulate OS following romiplostim treatment 24 hours post irradiation and predicted 75% (RSB: 1.5), 80% (RSB: 1.6), and 87% (RSB: 1.7) survival on day 60, for romiplostim doses of at 1, 3, and 10 µg/kg, respectively compared to 50% survival for placebo. Percent survival was &gt;75% when 10 µg/kg romiplostim was administered 24, 48, or 72 hours post irradiation and when administered to pediatric sub-groups (0-2, &gt;2-6, &gt;6-12, &gt;12-18). Conclusions: A PKPD model of romiplostim exposure-response in irradiated humans was used to predict platelet response in humans with HS-ARS with/without treatment with romiplostim and was combined with an OS model to simulate 60-day survival in humans with HS-ARS. Simulations demonstrated the robust survival benefit of a single 10 µg/kg romiplostim dose compared with placebo in both adult and pediatric humans with HS-ARS following an acute radiation event. Selection of a romiplostim dose for treatment of HS-ARS is pending review of the irradiated RM studies and subsequent modeling and simulation analyses by the FDA. Disclosures Doshi: Amgen Inc: Current Employment. Jones:Amgen Inc: Current Employment. Pritchard-Bell:Amgen Inc: Current Employment. Park:Amgen Inc: Current Employment. Olsson Gisleskog:POG Pharmacometrics Ltd: Current Employment.

A Minimal PKPD Interaction Model for Evaluating Synergy Effects of Combined NSCLC Therapies

This paper introduces a mathematical compartmental formulation of dose-effect synergy modelling for multiple therapies in non small cell lung cancer (NSCLC): antiangiogenic, immuno- and radiotherapy. The model formulates the dose-effect relationship in a unified context, with tumor proliferating rates and necrotic tissue volume progression as a function of therapy management profiles. The model accounts for inter- and intra-response variability by using surface model response terms. Slow acting peripheral compartments such as fat and muscle for drug distribution are not modelled. This minimal pharmacokinetic-pharmacodynamic (PKPD) model is evaluated with reported data in mice from literature. A systematic analysis is performed by varying only radiotherapy profiles, while antiangiogenesis and immunotherapy are fixed to their initial profiles. Three radiotherapy protocols are selected from literature: (1) a single dose 5 Gy once weekly; (2) a dose of 5 Gy × 3 days followed by a 2 Gy × 3 days after two weeks and (3) a dose of 5 Gy + 2 × 0.075 Gy followed after two weeks by a 2 Gy + 2 × 0.075 Gy dose. A reduction of 28% in tumor end-volume after 30 days was observed in Protocol 2 when compared to Protocol 1. No changes in end-volume were observed between Protocol 2 and Protocol 3, this in agreement with other literature studies. Additional analysis on drug interaction suggested that higher synergy among drugs affects up to three-fold the tumor volume (increased synergy leads to significantly lower growth ratio and lower total tumor volume). Similarly, changes in patient response indicated that increased drug resistance leads to lower reduction rates of tumor volumes, with end-volume increased up to 25–30%. In conclusion, the proposed minimal PKPD model has physiological value and can be used to study therapy management protocols and is an aiding tool in the clinical decision making process. Although developed with data from mice studies, the model is scalable to NSCLC patients.

4512 Allopregnanolone Dose Finding for Status Epilepticus Treatment by Pharmacokinetic-Pharmacodynamic Modeling using Quantitative EEG in Dogs

OBJECTIVES/GOALS: Allopregnanolone (ALLO), a modulator of GABAA receptors, may be useful as a treatment for human and canine benzodiazepine-refractory status epilepticus (SE). Our objective was to develop a phamacokinetic-pharmacodynamic (PKPD) model relating ALLO plasma concentrations to electroencephalographic (EEG) effects in dogs. METHODS/STUDY POPULATION: Four healthy dogs and one dog with epilepsy that had implanted intracranial electrodes were utilized. ALLO doses ranging from 1-6 mg/kg were administered IV over 5 min. EEG data were collected during four IM doses (1-2 mg/kg). Blood samples were collected up to 6 hr following dosing. ALLO concentrations were measured using HPLC-MS/MS. Power density was determined in EEG bands using a custom algorithm. A two-compartment link PKPD model was developed to describe the relation between ALLO plasma concentration and change in EEG power in the alpha, beta, delta and theta bands. RESULTS/ANTICIPATED RESULTS: ALLO caused a rapid increase in absolute power density in all EEG bands measured (1-4, >4 – 8, >8 – 12, >12 – 25, and >25 – 100 Hz). The onset of effect was rapid (1-3 min) and demonstrated by frequency band and dose analysis. Concentration-EEG data were best fit by a two-compartment PK model and sigmoidal Emax PD indirect link model. The beta frequency band was most sensitive, showing increases in power at the lowest ALLO concentrations. The EC50 concentration for the beta frequency was ~270 ng/mL. The EC50 values for effects on the other frequency bands were ~500-700 ng /mL. In conclusion, IV ALLO causes a rapid effect on EEG that can be used to determine minimal plasma concentrations associated with target engagement. DISCUSSION/SIGNIFICANCE OF IMPACT: Dose selection for future clinical trials will use the effective concentrations determined here in conjunction with studies in animal status epilepticus models. Studies are planned in client owned dogs with epilepsy to evaluate clinical efficacy in dogs and as nonclinical proof-of-concept evidence supporting translational studies in people. CONFLICT OF INTEREST DESCRIPTION: Michael Rogawski and Dorota Zolkowska are named as inventors on patent applications claiming use of neuroactive steroids including allopregnanolone and ganaxolone in the treatment of status epilepticus.

A novel mechanism-based pharmacokinetic–pharmacodynamic (PKPD) model describing ceftazidime/avibactam efficacy against β-lactamase-producing Gram-negative bacteria

Background Diazabicyclooctanes (DBOs) are an increasingly important group of non β-lactam β-lactamase inhibitors, employed clinically in combinations such as ceftazidime/avibactam. The dose finding of such combinations is complicated using the traditional pharmacokinetic/pharmacodynamic (PK/PD) index approach, especially if the β-lactamase inhibitor has an antibiotic effect of its own. Objectives To develop a novel mechanism-based pharmacokinetic–pharmacodynamic (PKPD) model for ceftazidime/avibactam against Gram-negative pathogens, with the potential for combination dosage simulation. Methods Four β-lactamase-producing Enterobacteriaceae, covering Ambler classes A, B and D, were exposed to ceftazidime and avibactam, alone and in combination, in static time–kill experiments. A PKPD model was developed and evaluated using internal and external evaluation, and combined with a population PK model and applied in dosage simulations. Results The developed PKPD model included the effects of ceftazidime alone, avibactam alone and an ‘enhancer’ effect of avibactam on ceftazidime in addition to the β-lactamase inhibitory effect of avibactam. The model could describe an extensive external Pseudomonas aeruginosa data set with minor modifications to the enhancer effect, and the utility of the model for clinical dosage simulation was demonstrated by investigating the influence of the addition of avibactam. Conclusions A novel mechanism-based PKPD model for the DBO/β-lactam combination ceftazidime/avibactam was developed that enables future comparison of the effect of avibactam with other DBO/β-lactam inhibitors in simulations, and may be an aid in translating PKPD results from in vitro to animals and humans.

3552 Advancing Glioblastoma (GBM) drug regimen development to support combination therapy through integrated PKPD modeling and simulation-based predictions

OBJECTIVES/SPECIFIC AIMS: Despite advancements in therapies, such as surgery, irradiation (IR) and chemotherapy, outcome for patients suffering from glioblastoma remains fatal; the median survival rate is only about 15 months. Even with novel therapeutic targets, networks and signaling pathways being discovered, monotherapy with such agents targeting such pathways has been disappointing in clinical trials. Poor prognosis for GBM can be attributed to several factors, including failure of drugs to cross the blood-brain-barrier (BBB), tumor heterogeneity, metastasis and angiogenesis. Development of tumor resistance, particularly to temozolomide (TMZ), creates a substantial clinical challenge.The primary focus of our work is to rationally develop novel combination therapies and dose regimens that mitigate resistance development. Specifically, our aim is to combine TMZ with small molecule inhibitors that are either currently in clinical trials or are approved drugs for other cancer types, and which target the disease at various resistance signaling pathways that are induced in response to TMZ monotherapy. METHODS/STUDY POPULATION: To accomplish this objective, an integrated PKPD modeling approach is used. The approach is largely based on the work of Cardilin, et al, 2018. A PK model for each drug is first defined. This is subsequently linked to a PD model description of tumor growth dynamics in the presence of a single drug or combinations of drugs. A key outcome of these combined PKPD models are tumor static concentration (TSC) curves of dual or triple combination drug regimens that identify combination drug exposures predicted to arrest tumor growth. This approach has been applied to TMZ in combination with abemaciclib (a dual CDK4/6 small molecule inhibitor) based on data from a published study evaluating abemaciclib efficacy in combination with TMZ in a glioblastoma xenograft model (Raub, et al, 2015). RESULTS/ANTICIPATED RESULTS: A PKPD model was developed to predict tumor growth kinetics for TMZ and abemaciclib monotherapy, as well as combination therapy. Population PK models in immune deficient NSG mice for temozolomide and abemaciclib were developed based on data obtained from original and published studies. Subsequently, the PK model was linked to tumor volume data obtained from U87-MG GBM subcutaneous xenografts, again using both original data as well as data from the Raub, et al, 2015 study. Model parameters quantifying tumor volume dynamics were precisely estimated (coefficient of variation < 30%). The developed PKPD model was used to calculate plasma concentrations of TMZ and abemaciclib that would arrest tumor growth, as well as combinations of concentrations of the two drugs that would accomplish the same endpoint. This so-called TSC curve for the TMZ and abemaciclib combination pair evidenced an additive effect of the two agents when administered together. These results will be presented. In addition, results from on-going PKPD studies of TMZ in combination with two other small molecule inhibitors, RG7388, an MDM2 inhibitor, and GDC0068, an AKT inhibitor, will also be presented. DISCUSSION/SIGNIFICANCE OF IMPACT: Our long-term goals are to further elucidate SOC-induced responses in GBM and establish combination treatment regimens that are safe and significantly improve therapeutic efficacy. Collectively, our studies will broadly influence chemotherapy of GBM by establishing a process to rationally design combination approaches that mitigate resistance development. These studies will ultimately provide opportunities to study other targeted agents tailored to individual molecular signatures of GBM, as well as other tumor types.

Hierarchical Stochastic Model in Bayesian Inference for Engineering Applications: Theoretical Implications and Efficient Approximation

Hierarchical Bayesian models (HBMs) have been increasingly used for various engineering applications. We classify two types of HBM found in the literature as hierarchical prior model (HPM) and hierarchical stochastic model (HSM). Then, we focus on studying the theoretical implications of the HSM. Using examples of polynomial functions, we show that the HSM is capable of separating different types of uncertainties in a system and quantifying uncertainty of reduced order models under the Bayesian model class selection framework. To tackle the huge computational cost for analyzing HSM, we propose an efficient approximation scheme based on importance sampling (IS) and empirical interpolation method (EIM). We illustrate our method using two engineering examples—a molecular dynamics simulation for Krypton and a pharmacokinetic/pharmacodynamics (PKPD) model for cancer drug.