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Aim To assess the potential of interleukin-6 (IL-6) signaling blockade in the lung to treat SARS-CoV-2 infection via model-based simulation by exploring soluble IL-6 receptor (sIL-6R) sequestration by tocilizumab (TCZ) and IL-6 sequestration by siltuximab (SIL). Methods Literature values of IL-6, IL-6 antagonist SIL, sIL-6R, IL-6R antagonist TCZ, and their respective binding constants were used to develop a model to predict the impact of treatment on IL-6 signaling. Models were used to generate simulated bronchoalveolar lavage fluid (BALF) concentrations for normal subjects, subjects at risk of developing acute respiratory distress syndrome (ARDS), and subjects with ARDS under four conditions: without treatment, treatment with TCZ, treatment with SIL, and treatment with TCZ + SIL. Results With TCZ intervention, IL-6 levels are unaffected and sIL-6R is reduced somewhat below the Normal case. IL-6:sIL-6R complex only slightly decreased relative to the no-intervention case. With SIL intervention, sIL-6R levels are unaffected and IL-6 is greatly reduced below the Normal case. IL-6:sIL-6R complex is greatly decreased relative to the no-intervention case. With TCZ + SIL intervention, IL-6 and sIL-6R levels are reduced below the Normal case and achieve suppression equivalent to monotherapy results for their respective targets. IL-6:sIL-6R complex reduction is predicted to be greater than that achieved with monotherapy. This reflects sequestration of both components of the complex and the nonlinear binding equilibrium. Conclusion Co-administration of both IL-6 and IL-6R sequestering products such as SIL and TCZ may be necessary to effectively treat COVID-19 patients who have or are at risk of developing ARDS.

AVB-S6-500 neutralized growth arrest-specific 6 (GAS6) protein and effectively inhibited AXL signaling in preclinical cancer models. A target-mediated drug disposition (TMDD) pharmacokinetic/pharmacodynamic (PK/PD) model was used to select first-in-human (FIH) doses for AVB-S6-500 based on predicted target (GAS6) suppression in the clinic. The effect of TMDD on AVB-S6-500 clearance was incorporated into a standard two-compartment model, providing parallel linear and nonlinear clearance. Observed AVB-S6-500 and GAS6 concentration data in cynomolgus monkeys and relevant interspecies differences were used to predict the PK (serum concentration)/PD (GAS6 suppression) relationship in humans. Human exposure and GAS6 suppression were simulated for the proposed FIH doses of 1, 2.5, 5, and 10 mg/kg. A dose of 1 mg/kg was selected to target GAS6 suppression for 2 weeks in the initial healthy volunteer study. The cynomolgus monkey:human ratios for the highest proposed FIH dose were anticipated to yield more than a 10-fold margin to the nonclinical no observed adverse event level while maintaining > 90% GAS6 suppression. In human subjects, the first dose (1 mg/kg) model-projected and clinically observed maximal concentration (Cmax ) was within 10% of predicted; repeat dosing at 5 mg/kg was within 1% (Cmax ) and 45% (area under the serum concentration-time curve from time 0 to end of dosing interval) of predicted. Predicted GAS6 suppression duration of 14 days was accurate for the 1 mg/kg dose. A PK/PD model expedited clinical development of AVB-S6-500, minimized exposure of patients with cancer to subtherapeutic doses, and rationally guided the optimal dosing in patients.

Background and Objectives Lisocabtagene maraleucel (liso-cel) is a CD19-directed, defined composition, 4-1BB chimeric antigen receptor (CAR) T-cell product administered at equal target doses of CD8+ and CD4+ CAR+ T cells. Large between-subject variability has been noted with CAR T-cell therapies; patient characteristics might contribute to CAR T-cell expansion variability. We developed a population cellular kinetic model to characterize the kinetics of the liso-cel transgene, via quantitative polymerase chain reaction assessment after intravenous infusion of liso-cel, and to understand covariates that might influence liso-cel kinetics in individual patients. Methods We employed nonlinear mixed-effects modeling to develop a population cellular kinetic model for liso-cel. The population cellular kinetic analysis was performed using 2524 post-infusion transgene observations from 261 patients with relapsed/refractory large B-cell lymphoma who were treated with a single dose of liso-cel in TRANSCEND NHL 001. Covariates for the analysis included baseline intrinsic factors such as age, baseline disease characteristics, and liso-cel and coadministration factors. Results Liso-cel cellular kinetics were well described by a piecewise model of cellular growth kinetics that featured lag, exponential growth, and biexponential decay phases. Population means (95% confidence interval) of lag phase duration, doubling time, time to maximum levels, initial decline half-life, and terminal half-life were 3.27 (2.71–3.97), 0.755 (0.667–0.821), 9.29 (8.81–9.70), 5.00 (4.15–5.90), and 352 (241–647) days, respectively. The magnitude of effect on liso-cel expansion metrics demonstrated that the covariate associations were smaller than the residual between-subject variability in the population. Conclusions The covariates tested were not considered to have a meaningful impact on liso-cel kinetics. Clinical Trial Registration NCT02631044.

During a pandemic caused by a novel pathogen (NP), drug repurposing offers the potential of a rapid treatment response via a repurposed drug (RD) while more targeted treatments are developed. Five steps of model-informed drug repurposing (MIDR) are discussed: (i) utilize RD product label and in vitro NP data to determine initial proof of potential, (ii) optimize potential posology using clinical pharmacokinetics (PK) considering both efficacy and safety, (iii) link events in the viral life cycle to RD PK, (iv) link RD PK to clinical and virologic outcomes, and optimize clinical trial design, and (v) assess RD treatment effects from trials using model-based meta-analysis. Activities which fall under these five steps are categorized into three stages: what can be accomplished prior to an NP emergence (preparatory stage), during the NP pandemic (responsive stage) and once the crisis has subsided (retrospective stage). MIDR allows for extraction of a greater amount of information from emerging data and integration of disparate data into actionable insight.

Purpose: Batiraxcept is a novel Fc fusion protein that inhibits the growth arrest-specific (GAS)/AXL signaling pathway by binding the sole activating GAS6 ligand, which reduces AXL signaled invasion and migration of highly metastatic cells in vitro and inhibits metastatic disease in nonclinical models of aggressive human cancers. We used dose-exposure (D-E) and exposure-response (E-R) modeling and simulation to identify a recommended Phase 2 dose (RP2D). The D-E modeling is expected to apply to any cancer and batiraxcept combination, while the E-R modeling may be disease specific. Patients and Methods: A population pharmacokinetic (PK)/pharmacodynamic (PD) model was applied to exposure data from healthy volunteers (n=24, Phase (P) 1 study, single ascending dose cohort [NCT03401528]) and platinum-resistant ovarian cancer (PROC) patients (n=42, P1b study [NCT03639246]) treated with either batiraxcept+paclitaxel or batiraxcept+pegylated liposomal doxorubicin to capture the D-E relationship of batiraxcept. A Cox Proportional Hazards Model was applied to progression-free survival (PFS) observed from the PROC patients, to capture the E-R relationship of batiraxcept. The models were used to study PFS in prospective studies of 5, 10, 15, and 20 mg/kg administered iv once every 2 weeks at the 10th, 50th (median), and 90th percentile of expected exposure metrics. In a separate P1b study in 2L+clear cell renal cell carcinoma (ccRCC), 23 patients were dosed with 15mg/kg or 20mg/kg batiraxcept in combination with standard of care cabozantinib [NCT04300140]. PK, PD, and clinical response data from both doses tested in ccRCC were compared to the modeling predictions generated from the PROC study. Results: The PROC E-R analysis predicted that a dose of 15mg/kg would provide exposure levels associated with longer PFS, and a 20mg/kg dose did not add additional benefit. Fifteen mg/kg was identified as the RP2D from the PROC P1b study and is the batiraxcept dose being evaluated in combination with standard of care weekly paclitaxel in the ongoing PROC P3 study [NCT04729608]. PK and PD data from the ccRCC P1b study compare favorably with simulations from the PROC D-E model. Consistent with simulations from the PROC E-R analysis, the 20mg/kg dose did not provide additional benefit above that seen with the 15mg/kg dose in the ccRCC P1b study, indicating these doses are at the plateau of drug effect. Conclusion: Consistent with emerging U.S. Food and Drug Administration guidance around a more thoughtful approach to dose selection in cancer (“Project Optimus”), E-R analysis supported the identification of batiraxcept 15mg/kg as the RP2D in the PROC P1b study. Furthermore, PK/PD and preliminary activity of batiraxcept 15mg/kg+cabozantinib are consistent with these data and support the batiraxcept RP2D of 15mg/kg across different tumor types and combinations with batiraxcept. Citation Format: Gail Mcintyre, Reshma Rangwala, Michael G. Dodds, Olivier Barriere. Exposure-response analysis of batiraxcept and application to recommended phase 2 dose in platinum-resistant ovarian and clear cell renal cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr CT506.

As the global COVID-19 pandemic continues, unabated and clinical trials demonstrate limited effective pharmaceutical interventions, there is a pressing need to accelerate treatment evaluations. Among options for accelerated development is the evaluation of drug combinations in the absence of prior monotherapy data. This approach is appealing for a number of reasons. First, combining two or more drugs with related or complementary therapeutic effects permits a multipronged approach addressing the variable pathways of the disease. Second, if an individual component of a combination offers a therapeutic effect, then in the absence of antagonism, a trial of combination therapy should still detect individual efficacy. Third, this strategy is time saving. Rather than taking a stepwise approach to evaluating monotherapies, this strategy begins with testing all relevant therapeutic options. Finally, given the severity of the current pandemic and the absence of treatment options, the likelihood of detecting a treatment effect with combination therapy maintains scientific enthusiasm for evaluating repurposed treatments. Antiviral combination selection can be facilitated by insights regarding SARS-CoV-2 pathophysiology and cell cycle dynamics, supported by infectious disease and clinical pharmacology expert advice. We describe a clinical evaluation strategy using adaptive combination platform trials to rapidly test combination therapies to treat COVID-19.

Aim: We hypothesize that the efficacy of COVID-19 therapeutic candidates will be better predicted by understanding their effects at various points on a viral cell cycle, in particular, the specific rate constants, and that drugs acting independently of these specific discrete sites may not yield expected efficacy. We hypothesize that drugs, or combinations of drugs that act at specific multiple sites on the viral life cycle have the highest probability of success in the treatment of early infection phase in COVID-19 patients. Methods: Using a target cell limited model structure that had been used to characterize viral load dynamics from COVID-19 patients, we performed simulations to show that combinations of therapeutics targeting specific rate constants have greater probability of efficacy and supportive rationale for clinical trial evaluation. Results: Based on the known kinetics of the SARS-CoV-2 life cycle, we rank ordered potential targeted approaches involving repurposed, low-potency agents. We suggest that targeting multiple points central to viral replication within infected host cells or release from those cells is a viable strategy for reducing both viral load and host cell infection. In addition, we observed that the time-window opportunity for a therapeutic intervention to effect duration of viral shedding exceeds the effect on sparing epithelial cells from infection or impact on viral load AUC. Furthermore, the impact on reduction on duration of shedding may extend further in patients who exhibit a prolonged shedder phenotype. Conclusions: Our work highlights the use of model-informed tools to better rationalize effective treatments for COVID-19.

Aim: To assess the potential of interleukin-6 (IL-6) signaling blockade in the lung to treat SARS-CoV-2 infection via model-based simulation by exploring soluble IL-6 receptor (sIL-6R) sequestration by tocilizumab (TCZ) and IL-6 sequestration by siltuximab (SIL). Methods: Literature values of IL-6, the IL-6 antagonist SIL, sIL-6R, the IL-6R antagonist TCZ, and their respective binding constants were used to develop a model to predict the impact of treatment on IL-6 signaling. Models were used to generate simulated bronchoalveolar lavage (BAL) concentrations for normal subjects, subjects at risk of developing acute respiratory distress syndrome (ARDS), and subjects with ARDS were simulated under four conditions: without treatment, treatment with TCZ, treatment with SIL, and treatment with TCZ + SIL. Results: With TCZ intervention, IL-6 levels are unaffected and sIL-6R is reduced somewhat below the Normal case. IL-6:sIL-6R complex only slightly decreased relative to the no-intervention case. With SIL intervention, sIL-6R levels are unaffected and IL-6 is greatly reduced below the Normal case. IL-6:sIL-6R complex is greatly decreased relative to the no-intervention case. With TCZ + SIL intervention, IL-6 and sIL-6R levels are reduced below the Normal case and achieve suppression equivalent to monotherapy results for their respective targets. IL-6:sIL-6R complex reduction is predicted to be greater than monotherapy. This reflects sequestration of both components of the complex and the nonlinear binding equilibrium. Conclusion: Co-administration of both IL-6 and IL-6R sequestering products such as SIL and TCZ may be necessary to effectively treat COVID-19 patients who have or are at risk of developing ARDS.

Understanding the pharmacokinetic (PK) and pharmacodynamic (PD) relationship of a therapeutic monoclonal antibody against proprotein convertase subtilisin/kexin type 9 (PCSK9) exhibiting target‐mediated drug disposition (TMDD) is critical for selecting optimal dosing regimens. We describe the PK/PD relationship of evolocumab using a mathematical model that captures evolocumab binding and removal of unbound PCSK9 as well as reduction in circulating low‐density lipoprotein cholesterol (LDL‐C). Data were pooled from 2 clinical studies: a single‐dose escalation study in healthy subjects (7‐420 mg SC; n = 44) and a multiple‐dose escalation study in statin‐treated hypercholesterolemic patients (14 mg weekly to 420 mg monthly [QM] SC; n = 57). A TMDD model described the time course of unbound evolocumab concentrations and removal of unbound PCSK9. The estimated linear clearance and volume of evolocumab were 0.256 L/day and 2.66 L, respectively, consistent with other monoclonal antibodies. The time course of LDL‐C reduction was described by an indirect response model with the elimination rate of LDL‐C being modulated by unbound PCSK9. The concentration of unbound PCSK9 associated with half‐maximal inhibition (IC50) of LDL‐C elimination was 1.46 nM. Based on simulations, 140 mg every 2 weeks (Q2W) and 420 mg QM were predicted to achieve a similar time‐averaged effect of 69% reduction in LDL‐C in patients on statin therapy, suggesting that an approximate 3‐fold dose increase is required for a 2‐fold extension in the dosing interval. Evolocumab dosing regimens of 140 mg Q2W or 420 mg QM were predicted to result in comparable reductions in LDL‐C over a monthly period, consistent with results from recently completed phase 3 studies.

Phase I studies have shown that AMG 151 activates glucokinase, a key enzyme in glucose homeostasis. The present randomized, placebo-controlled phase IIa study evaluated the dose-effect relationship of the glucokinase activator AMG 151 relative to placebo on fasting plasma glucose (FPG) in 236 patients (33-35 patients per arm) with type 2 diabetes treated with metformin. Patients received oral AMG 151 at 50, 100 or 200 mg twice daily, AMG 151 at 100, 200 or 400 mg once daily or matching placebo for 28 days. A significant linear dose-effect trend was observed with the twice-daily regimen (p = 0.004) for change in FPG to day 28. No trend was observed with the once-daily regimen. A higher incidence of hypoglycaemia and hypertriglyceridaemia was observed with AMG 151 administration. AMG 151 significantly reduced FPG when administered twice daily but not when administered once daily in patients with type 2 diabetes treated with metformin.

Targeting angiogenesis is a promising approach to the treatment of solid tumors and age-related macular degeneration (AMD). Inhibition of vascularization has been validated by the successful marketing of monoclonal antibodies (mAbs) that target specific growth factors or their receptors, but there is considerable room for improvement in existing therapies. Combination of mAbs targeting both the VEGF and PDGF pathways has the potential to increase the efficacy of anti-angiogenic therapy without the accompanying toxicities of tyrosine kinase inhibitors and the inability to combine efficiently with traditional chemotherapeutics. However, development costs and regulatory issues have limited the use of combinatorial approaches for the generation of more efficacious treatments. The concept of mediating disease pathology by targeting two antigens with one therapeutic was proposed over two decades ago. While mAbs are particularly suitable candidates for a dual-targeting approach, engineering bispecificity into one molecule can be difficult due to issues with expression and stability, which play a significant role in manufacturability. Here, we address these issues upstream in the process of developing a bispecific antibody (bsAb). Single-chain antibody fragments (scFvs) targeting PDGFRbeta and VEGF-A were selected for superior stability. The scFvs were fused to both termini of human Fc to generate a bispecific, tetravalent molecule. The resulting molecule displays potent activity, binds both targets simultaneously, and is stable in serum. The assembly of a bsAb using stable monomeric units allowed development of an anti-PDGFRB/VEGF-A antibody capable of attenuating angiogenesis through two distinct pathways and represents an efficient method for rapid engineering of dual-targeting molecules.

Recombinant interleukin-21 (rIL-21) is an immune stimulating cytokine recently tested in two Phase 1 trials for immune responsive cancers. A secondary objective of these trials was to characterize pharmacodynamic responses to rIL-21 in patients. Here, we report the effects of systemic rIL-21 on serum markers of immune stimulation.Recombinant IL-21 was administered by intravenous bolus injection at dose levels from 1 to 100 microg/kg using two distinct treatment regimens: thrice weekly ('3/w') for 6 weeks; or once daily for five consecutive days followed by nine dose-free days ('5 + 9'). In the absence of dose limiting toxicity, additional cycles of dosing were initiated immediately following the nine dose-free days. An array of 70 different proteins was profiled in subject serum samples from several time points during the course of the study. Hierarchical clustering analysis was performed on a normalized subset of these data.Systemic administration of rIL-21 affected the serum levels of several cytokines, chemokines, acute-phase proteins and cell adhesion proteins. The magnitude and duration of response were dose dependent for a subset of these biomarkers. The 5 + 9 dosing regimen generally produced cyclic changes that were of greater magnitude, as compared to a more chronic stimulation with the 3/w dosing regimen. Despite these differences, rIL-21 effects on many analytes were similar between regimens when averaged over the time of treatment. Based on similar temporal, between-subject and dose response changes, groups of analytes were identified that exhibited distinct components of the rIL-21-mediated immune activation. Biomarkers indicative of lymphocyte activation (increased IL-16, decreased RANTES), acute phase response (increased CRP, ferritin), myeloid activation (increased MDC, MIP-1 alpha), and leukocyte chemotaxis/trafficking (increased sCAMs, MCP-1) were strongly modulated in subjects treated with rIL-21.Administration of rIL-21 resulted in activation of multiple cell types and immune response pathways. The changes observed in serum proteins were consistent with coincident processes of lymphoid and myeloid cell activation and trafficking, and acute phase response.

Hemostasis in humans and other animals is a complex process that controls blood loss after a vascular injury. Factor XIII (FXIII) stabilizes clots primarily by cross-linking fibrin, thus protecting a newly formed clot from fibrinolysis by plasmin. Congenital deficiencies in humans involving FXIII are associated with delayed bleeding and wound healing and severe spontaneous hemorrhaging. These symptoms can be alleviated by intravenous administration of enriched FXIII plasma fractions. Circulating plasma FXIII is found as a heterotetramer that dissociates in the presence of calcium and thrombin into an active dimer and 2 inactive monomers. The recombinant FXIII under investigation is the active dimer alone. A 3-compartment, nonlinear population pharmacokinetic model was implemented in NONMEM V and then used to analyze data from preclinical studies in cynomolgus monkeys. The model simultaneously describes endogenous production of dimer (0.622 microg kg(-1) hr(-1)) and monomer (12.1 microg kg(-1) hr(-1)), and the administration of recombinant dimer. The model incorporates the rate and extent of complexation of recombinant dimer with available endogenous monomer (6.59 mg(-1) kg hr(-1)) to form the heterotetramer. Half-lives for dimer, heterotetramer, and monomer (3.33 hours, 2.83 days, and 3.94 hours for A(2), A(2)B(2), and B, respectively) were estimated, along with their variability in the population studied.

Advances in computer hardware and the associated computer-intensive algorithms made feasible by these advances [like Markov chain Monte Carlo (MCMC) data analysis techniques] have made possible the application of hierarchical full Bayesian methods in analyzing pharmacokinetic and pharmacodynamic (PK-PD) data sets that are multivariate in nature. Pharmacokinetic data analysis in particular has been one area that has seized upon this technology to refine estimates of drug parameters from sparse data gathered in a large, highly variable population of patients. A drawback in this type of analysis is that it is difficult to quantitatively assess convergence of the Markov chains to a target distribution, and thus, it is sometimes difficult to assess the reliability of estimates gained from this procedure. Another complicating factor is that, although the application of MCMC methods to population PK-PD problems has been facilitated by new software designed for the PK-PD domain (specifically PKBUGS), experts in PK-PD may not have the necessary experience with MCMC methods to detect and understand problems with model convergence. The objective of this work is to provide an example of a set of diagnostics useful to investigators, by analyzing in detail three convergence criteria (namely the Raftery and Lewis, Geweke, and Heidelberger and Welch methods) on a simulated problem and with a rule of thumb of 10,000 chain elements in the Markov chain. We used two publicly available software packages to assess convergence of MCMC parameter estimates; the first performs Bayesian parameter estimation (PKBUGS/WinBUGS), and the second is focused on posterior analysis of estimates (BOA). The main message that seems to emerge is that accurately estimating confidence regions for the parameters of interest is more demanding than estimating the parameter means. Together, these tools provide numerical means by which an investigator can establish confidence in convergence and thus in the estimated parameters derived from hierarchical full Bayesian pharmacokinetic data analysis.

ARRY-403 is a glucokinase activator developed for the treatment of diabetes. Less than dose-proportional exposure was observed during single ascending dose studies with ARRY-403. A physiologically based pharmacokinetic (PBPK) model for ARRY-403 was developed through integration of in vitro physicochemical data with precipitation time estimations based on results from the single ascending dose studies; PBPK modeling indicated that the primary cause of the less than dose-proportional exposure was dose-limited absorption because of pH-dependent solubility. The impact of dose, particle size, and fasted or fed state on ARRY-403 exposure was examined through sensitivity analyses and used to refine the PBPK model. On the basis of the marked pH-dependent solubility of ARRY- 403, the refined PBPK model was used to simulate the effects of acid-reducing agents (ARAs) on ARRY-403 exposure, as these agents are widely available and could be coadministered with ARRY-403. The simulations indicated that a clinical study with an ARA was warranted; in a clinical study, famotidine had a marked effect on ARRY-403 exposure. This approach, based on the "predict, learn, and confirm" paradigm, demonstrates the utility of integrating physicochemical properties, in vitro experiments, and clinical results using PBPK to inform formulation development and to guide clinical study design.

The objectives of this retrospective analysis were (1) to characterize the population pharmacokinetics (popPK) of four different monoclonal antibodies (mAbs) in a combined analysis of individual data collected during first-in-human (FIH) studies and (2) to provide a scientific rationale for prospective design of FIH studies with mAbs. The data set was composed of 171 subjects contributing a total of 2716 mAb serum concentrations, following intravenous (IV) and subcutaneous (SC) doses. mAb PK was described by an open 2-compartment model with first-order elimination from the central compartment and a depot compartment with first-order absorption. Parameter values obtained from the popPK model were further used to generate optimal sampling times for a single dose study. A robust fit to the combined data from four mAbs was obtained using the 2-compartment model. Population parameter estimates for systemic clearance and central volume of distribution were 0.20 L/day and 3.6 L with intersubject variability of 31% and 34%, respectively. The random residual error was 14%. Differences (> 2-fold) in PK parameters were not apparent across mAbs. Rich designs (22 samples/subject), minimal designs for popPK (5 samples/subject), and optimal designs for non-compartmental analysis (NCA) and popPK (10 samples/subject) were examined by stochastic simulation and estimation. Single-dose PK studies for linear mAbs executed using the optimal designs are expected to yield high-quality model estimates, and accurate capture of NCA estimations. This model-based meta-analysis has determined typical popPK values for four mAbs with linear elimination and enabled prospective optimization of FIH study designs, potentially improving the efficiency of FIH studies for this class of therapeutics.

A computer model capable of integrating mechanisms of biofilm resistance to disinfection by antimicrobial agents was developed. Resistance mechanisms considered included retarded penetration due to a stoichiometric reaction between the antimicrobial agent and biomass, incomplete penetration due to a catalytic reaction between the antimicrobial agent and the biomass, and the existence of a fraction of the cells in a resistant phenotypic state. Mathematical models of these processes were derived and solved in the computer simulation package MATLAB. Four sets of fitted experimental data on the disinfection of Pseudomonas aeruginosa biofilms were fit to each of the three models. No one model fit all of the data sets adequately. Killing of a 2-day old biofilm by tobramycin was best described by the physiological limitation model. Killing by hypochlorite was best described by the stoichiometric transport model. Killing by hydrogen peroxide was best simulated by the catalytic transport model. These results suggest that multiple mechanisms of biofilm reduced susceptibility are manifested even in biofilms of the same species and that the particular resistance mechanism depends on the biofilm age, antimicrobial agent, and biofilm thickness. The models presented in this article may be useful for diagnosing mechanisms of biofilm resistance from experimental data.

Pharmacometric approaches can assist in biosimilar development by leveraging quantitative knowledge of the originator product characteristics such as dose-exposure and exposure-response information to support a targeted approach to clinical studies. The degree to which these approaches can be applied relies on the level of information known about the originator and information that supports application of the originator model to the biosimilar. A model-based approach testing the hypothesis that the biosimilar PK and/or PK/PD profile is similar to the originator in the target patient population is aligned with the central comparability exercise required for the biosimilar approval. This Commentary details the key opportunities in study design and study analysis where pharmacometrics approaches can aid biosimilar development.

We have developed a new model to describe endogenous glucose kinetics during a labeled (hot) intravenous glucose tolerance test (IVGTT) to derive a time profile of endogenous glucose production (EGP). We reanalyzed data from a previously published study (P. Vicini, J. J. Zachwieja, K. E. Yarasheski, D. M. Bier, A. Caumo, and C. Cobelli. Am J Physiol Endocrinol Metab 276: E285–E294, 1999), in which insulin-modified [6,6-2H2]glucose-labeled IVGTTs (0.33 g/kg glucose) were performed in 10 normal subjects. In addition, a second tracer ([U-13C]glucose) was infused in a variable rate to clamp the endogenous glucose tracer-to-tracee ratio (TTR). Our new model describing endogenous glucose kinetics was incorporated into the two-compartment hot minimal-model structure. The model gave estimates of glucose effectiveness [1.54 ± 0.31 (SE) ml·kg−1·min−1], insulin sensitivity (37.74 ± 5.23 104 dl·kg−1·min−1·μU−1·ml), and a new parameter describing the sensitivity of EGP to the inhibitory effect of insulin (IC50 = 0.0195 ± 0.0046 min−1). The model additionally provided an estimate of the time course of EGP showing almost immediate inhibition, followed by a secondary inhibitory effect caused by infusion of insulin, and a large overshoot as EGP returns to its basal value. Our estimates show very good agreement with those obtained via deconvolution and the model-independent TTR clamp technique. These results suggest that the new integrated model can serve as a simple one-step approach to obtain metabolic indexes while also providing a parametric description of EGP.

One goal of large scale clinical trials is to determine how a drug is processed by, and cleared from, the human body [i.e., its pharmacokinetic (PK) properties] and how these PK properties differ between individuals in a population (i.e., its population PK properties). Due to the high cost of these studies and the limited amount of data (e.g., blood samples) available from each study subject, it would be useful to know how many measurements are needed and when those measurements should be taken to accurately quantify population PK model parameters means and variances. Previous studies have looked at optimal design strategies of population PK experiments by developing an optimal design for an individual study (i.e., no interindividual variability was considered in the design), and then applying that design to each individual in a population study (where interindividual variability is present). A more algorithmically and informationally intensive approach is to develop a population optimal design, which inherently includes the assessment of interindividual variability. We present a simulation-based evaluation of these two design methods based on nonlinear Gaussian population PK models. Specifically, we compute standard individual and population D-optimal designs and compare population PK model parameter estimates based on simulated optimal design measurements. Our results show that population and standard D-optimal designs are not significantly different when both designs have the same number of samples per individual. However, population optimal designs allow for sampling schedules where the number of samples per individual is less than the number of model parameters, the theoretical limit allowed in standard optimal design. These designs with a low number of samples per individual are shown to be nearly as robust in parameter estimation as standard D-optimal designs. In the limit of just one sample per individual, however, population D-optimal designs are shown to be inadequate.

Clinical trial simulation (CTS) and model-based meta-analysis (MBMA) can increase our understanding of small, first-in-patient (FIP) trial design performance to inform Phase 2 decision making. In this work, we compared dose-ranging designs vs. designs testing only placebo and the maximum dose for early decision making in psoriasis. Based on MBMA of monoclonal antibodies in the psoriasis space, a threshold of greater than a 50 percentage point improvement over placebo effect at the highest feasible drug dose was required for the advancement in psoriasis. Studies testing only placebo and the maximum dose made the correct advancement decision marginally more often than dose-ranging designs in the majority of the cases. However, dose-ranging studies in FIP trials offer important design advantages in the form of dose-response (D-R) information to inform Phase 2 dose selection. CTS can increase the efficiency and quality of drug development decision making by studying the limitations and benefits of study designs prospectively.CPT: Pharmacometrics & Systems Pharmacology (2013) 2, e58; doi:10.1038/psp.2013.32; published online 24 July 2013.

278 PEGYLATED INTERFERON PLUS RIBAVIRIN: AN EFFICACIOUS AND WELL-TOLERATED TREATMENT REGIMEN FOR HIV-HCVCO-INFECTED PATIENTS WITH HEPATITIS C VIRUS RELATED CIRRHOSIS M.C. Mendes-Correa, M.H. da Silva, J.F.C. Figueiredo, G. Gryninger, M. Gonzalez, T. Reuter, L.G.M. Filho, A.C.S. Santos, J.D.U. Brito, F. Nogui, R.J. Gianini, P.A. Ferreira. Hospital das Clinicas-Infectious Diseases Department, Sao Paulo University Medical School, CRTAIDS, Sao Paulo, Clinica de Especialidades, Sao Bernardo do Campo, Infectious Diseases Department, Sao Paulo University Medical School, Ribeirao Preto, CRTAIDS, Bauru, Instituto de Infectologia Emilio Ribas, Sao Paulo, Infectious Diseases Department, Medical School – Espirito Santo Federal University, Vitoria, CRTAIDS, Braśilia, CRTAIDS, Diadema, Epidemiology and Statistics Laboratory, Sao Paulo University Medical School, Infectious Diseases Department, Medical School – Sao Paulo Federal University, Sao Paulo, Brazil E-mail: cassiamc@uol.com.br

16008 Background: Despite the impact of tyrosine kinase inhibitors on the outcome for mRCC, complete responses are rare and long term survival remains poor. rIL-21, a cytokine that enhances CD8+ T ...