In patients with systemic lupus erythematosus (SLE), increased type I interferon signaling is associated with increased disease activity across organs, including in the kidney, which can cause lupus nephritis (LN). Anifrolumab, which abrogates type I interferon signaling, is an approved treatment for moderate to severe SLE. In a phase 2 trial in patients with LN (TULIP-LN; NCT02547922), promising clinical benefit was observed with an intensified regimen (IR) of intravenous anifrolumab (3× 900 mg Q4W, 300 mg thereafter) compared with the approved SLE dose (basic regimen [BR], 300 mg Q4W). Anifrolumab clearance was greater with higher levels of proteinuria; however, the quantitative relationship between proteinuria and anifrolumab exposure was not fully characterized. Here, we describe a mathematical model of time-varying anifrolumab pharmacokinetics, 24-hour urine protein-creatinine ratio (UPCR24), and investigational product discontinuation in patients with LN. The model evaluated both TULIP-LN anifrolumab dosing regimens (IR and BR) and revealed a temporal association between clearance and proteinuria in patients with LN, with each mg/mg UPCR reduction resulting in a 21% decrease in linear anifrolumab clearance. Our model indicated that an intensified regimen including 6 initial anifrolumab 900 mg doses provided adequate exposure and rapid UPCR24 reduction. Higher anifrolumab exposure and reduced UPCR24 were each associated with decreased risk of treatment discontinuation. These model results guided the selection of an optimized, longer intensified anifrolumab dosing regimen (6× 900 mg Q4W, 300 mg thereafter) for the ongoing phase 3 IRIS trial (NCT05138133).

AIMS:Inhaled corticosteroids (ICS) plus bronchodilator are recommended for the treatment of asthma. Targeting the JAK1-dependent pathway may be an alternative for asthma management in patients with incomplete response to ICS. The aim of this study was to investigate the safety, tolerability, pharmacokinetics (PK) and pharmacodynamics (PD) of AZD0449, a novel JAK1 selective inhibitor, following inhaled (dry powder, nebulized) and intravenous administration to healthy participants and patients with mild asthma. METHODS:This was a randomized, single-blind, placebo-controlled Phase 1 study (NCT03766399) of single- and multiple-ascending doses conducted using a three-part design. Healthy participants and patients with mild asthma aged 18-55 years were recruited. The study evaluated safety, tolerability, PK and PD of AZD0449. PD was measured as the effect on fractional exhaled nitric oxide (FeNO). Systemic target engagement was measured using phosphorylation of signal transducer and activator of transcription 6 (pSTAT6). RESULTS:A total of 125 participants were included in the study. No drug-related safety concerns emerged. Following inhaled administration, AZD0449 showed low, dose-proportional, systemic exposures and elimination from plasma was partly absorption-limited, suggesting lung retention and supporting once-daily dosing. At the dose levels evaluated (1.2-5.0 mg), there was no significant anti-inflammatory effect (reduction in FeNO) with AZD0449 vs. placebo, following repeated dosing for 14 days. Furthermore, there was no significant suppression of pSTAT6. CONCLUSIONS:AZD0449 was safely administered via inhalation, with low systemic exposure and lung retention. This study provides a greater understanding of inhaled dosing of small molecule JAK1 inhibitors for the treatment of asthma. No effect on PD biomarkers (FeNO and STAT6) was observed.

Excessive Wnt signaling contributes to the development of fibrotic diseases and cancer. Here, we report the findings of a phase 1 study evaluating AZD5055, an orally administered porcupine inhibitor, which inhibits Wnt signaling. The primary objective was to evaluate the safety and tolerability of AZD5055 in healthy volunteers. Secondary and exploratory objectives were the pharmacokinetics and pharmacodynamics of AZD5055, respectively. Sixty healthy volunteers were randomized to receive placebo or AZD5055 in single ascending doses of 7, 20, or 40 mg (part 1), or multiple ascending doses of 5, 15, or 20 mg once daily over 14 consecutive days of dosing (Part 2). AZD5055 was safe and well tolerated in both study parts. AZD5055 exposure increased dose-proportionally with a pharmacokinetic profile enabling once daily dosing. AZD5055 effectively inhibited Wnt signaling in skin, hair follicles, and serum samples. Thus, AZD5055 has therapeutic potential in Wnt-driven fibrotic diseases and cancers.

Aims Corticosteroids are the treatment of choice for many inflammatory diseases, but often lead to adverse effects, including hyperglycemia. This study investigated the mechanisms driving differential effects on glucose control for AZD9567, a novel oral, non-steroidal, selective glucocorticoid receptor modulator, versus prednisolone in 46 patients with type 2 diabetes mellitus. Methods In this randomized, double-blind, 2-way cross-over study (NCT04556760), participants received either AZD9567 72 mg and prednisolone 40 mg daily (Cohort 1); AZD9567 40 mg and prednisolone 20 mg daily (Cohort 2); or placebo and prednisolone 5 mg daily (Cohort 3). Treatment duration was 3 days with a 3-week washout between treatment periods. Glycemic control was assessed after a standardized meal and with continuous glucose monitoring. Results A significant difference between AZD9567 and prednisolone in favour of AZD9567 was observed for the change from baseline to Day 4 glucose excursions post-meal in Cohort 1 (glucose AUC0-4h -4.54%; 95% CI: -8.88, -0.01; p=0.049), but not in Cohort 2 (-5.77%; 95% CI: -20.92, 12.29; p=0.435). In Cohort 1, significant differences between AZD9567 and prednisolone were also seen for the change from baseline to Day 4 in insulin and glucagon secretion post-meal (p<0.001 and p=0.005, respectively), and change from baseline to Day 4 in GLP-1 response (p=0.022). Significant differences between AZD9567 and prednisolone for 24-hour glucose control were observed for both Cohort 1 (-1.507 mmol/L; 95% CI: -2.0820, -0.9314; p<0.001), and Cohort 2 (-1.110 mmol/L; 95% CI -1.7257, -0.4941; p<0.001). Conclusions AZD9567 significantly reduced treatment-induced hyperglycemia compared with prednisolone.

Abstract Oral corticosteroid use is limited by side effects, some caused by off‐target actions on the mineralocorticoid receptor that disrupt electrolyte balance. AZD9567 is a selective, nonsteroidal glucocorticoid receptor modulator. The efficacy, safety, and tolerability of AZD9567 and prednisolone were assessed in a phase IIa study. Anti‐inflammatory mechanism of action was also evaluated in vitro in monocytes from healthy donors. In this randomized, double‐blind, parallel‐group, multicenter study, patients with active rheumatoid arthritis were randomized 1:1 to AZD9567 40 mg or prednisolone 20 mg once daily orally for 14 days. The primary end point was change from baseline in DAS28‐CRP at day 15. Secondary end points included components of DAS28‐CRP, American College of Rheumatology (ACR) response criteria (ACR20, ACR50, and ACR70), and safety end points, including serum electrolytes. Overall, 21 patients were randomized to AZD9567 (n = 11) or prednisolone (n = 10), and all completed the study. As anticipated, AZD9567 had a similar efficacy profile to prednisolone, with no clinically meaningful (i.e., >1.0) difference in change from baseline to day 15 in DAS28‐CRP between AZD9567 and prednisolone (least‐squares mean difference: 0.47, 95% confidence interval: −0.49 to 1.43). Similar results were observed for the secondary efficacy end points. In vitro transcriptomic analysis showed that anti‐inflammatory responses were similar for AZD9567, prednisolone, and dexamethasone. Unlike prednisolone, AZD9567 had no effect on the serum sodium:potassium ratio. The safety profile was not different from that of prednisolone. Larger studies of longer duration are required to determine whether AZD9567 40 mg may in the future be an alternative to prednisolone in patients with inflammatory disease.

The type I interferon (IFN) signaling pathway is implicated in the pathogenesis of systemic lupus erythematosus (SLE). Anifrolumab is a monoclonal antibody that targets the type I IFN receptor subunit 1. Anifrolumab is approved in several countries for patients with moderate to severe SLE receiving standard therapy. The approved dosing regimen of anifrolumab is a 300-mg dose administered intravenously every 4 weeks; this was initially based on the results of the Phase 2b MUSE and further confirmed in the Phase 3 TULIP-1 and TULIP-2 trials, in which anifrolumab 300-mg treatment was associated with clinically meaningful improvements in disease activity with an acceptable safety profile. There have been several published analyses of the pharmacokinetic and pharmacodynamic profile of anifrolumab, including a population-pharmacokinetic analysis of 5 clinical studies of healthy volunteers and patients with SLE, in which body weight and type I IFN gene expression were significant covariates identified for anifrolumab exposure and clearance. Additionally, the pooled Phase 3 SLE population has been used to evaluate how serum exposure may be related to clinical responses, safety risks, and pharmacodynamic effects of the 21-gene type I IFN gene signature (21-IFNGS). The relevance of 21-IFNGS with regard to clinical efficacy outcomes has also been analyzed. Herein, the clinical pharmacokinetics, pharmacodynamics, and immunogenicity of anifrolumab as well as results of population-pharmacokinetics and exposure-response analyses are reviewed.

We characterized the population pharmacokinetics of anifrolumab, a type I interferon receptor-blocking antibody. Pharmacokinetic data were analyzed from the anifrolumab (intravenous [IV], every 4 weeks) arms from 5 clinical trials in patients with systemic lupus erythematosus (SLE) (n =664) and healthy volunteers (n = 6). Population pharmacokinetic modeling was performed using a 2-compartment model with parallel linear and nonlinear elimination pathways. The impact of covariates (demographics, interferon gene signature [IFNGS, high/low], disease characteristics, renal/hepatic function, SLE medications, and antidrug antibodies) on pharmacokinetics was evaluated. Time-varying clearance (CL) was characterized using an empirical sigmoidal time-dependent function. Anifrolumab exposure increased more than dose-proportionally from 100 to 1000 mg IV every 4 weeks. Based on population pharmacokinetics modeling, the baseline median linear CL was 0.193 L/day in IFNGS-high patients and 0.153 L/day in IFNGS-low/healthy volunteers. After a year, median anifrolumab linear CL decreased by 8.4% from baseline. Body weight and IFNGS were significant pharmacokinetic covariates, whereas age, sex, race, disease activity, SLE medications, and presence of antidrug antibodies had no significant effect on anifrolumab pharmacokinetics. Anifrolumab at a concentration of 300 mg IV every 4 weeks was predicted to be below the lower limit of quantitation in 95% of patients approximate to 10 weeks after a single dose and approximate to 16 weeks after stopping dosing at steady state. To conclude, anifrolumab exhibited nonlinear pharmacokinetics and time-varying linear CL; doses >= 300 mg IV every 4 weeks provided sustained anifrolumab concentrations. This study provides further evidence to support the use of anifrolumab 300 mg IV every 4 weeks in patients with moderate to severe SLE.

Nonlinear mixed effects (NLME) modeling is a powerful tool to analyze time-series data from several individual entities in an experiment. In this paper, we give a brief overview of a package for NLME modeling in Wolfram Mathematica entitled NLMEModeling, implementing the first-order conditional estimation method with sensitivity equation-based gradients for parameter estimation. NLMEModeling supports mixed effects modeling of dynamical systems where the underlying dynamics are described by either ordinary or stochastic differential equations combined with observation equations with flexible observation error models. Moreover, NLMEModeling is a user-friendly package with functionality for parameter estimation, model diagnostics (such as goodness-of-fit analysis and visual predictive checks), and model simulation. The package is freely available and provides an extensible add-on to Wolfram Mathematica.

A central question in drug discovery is how to select drug candidates from a large number of available compounds. This analysis presents a model-based approach for comparing and ranking combinations of radiation and radiosensitizers. The approach is quantitative and based on the previously-derived Tumor Static Exposure (TSE) concept. Combinations of radiation and radiosensitizers are evaluated based on their ability to induce tumor regression relative to toxicity and other potential costs. The approach is presented in the form of a case study where the objective is to find the most promising candidate out of three radiosensitizing agents. Data from a xenograft study is described using a nonlinear mixed-effects modeling approach and a previously-published tumor model for radiation and radiosensitizing agents. First, the most promising candidate is chosen under the assumption that all compounds are equally toxic. The impact of toxicity in compound selection is then illustrated by assuming that one compound is more toxic than the others, leading to a different choice of candidate.

Rationale: To examine the potential of TLR9 (Toll-like receptor 9) activation to modulate the type 2 immune response in asthma. Objectives: To evaluate efficacy and safety of AZD1419, an inhaled TLR9 agonist, in a phase 2a, randomized, double-blind trial. Methods: Adult patients with asthma with a history of elevated eosinophils (>250 cells/mu l) were randomized 1:1 to receive 13 onceweekly doses of inhaled AZD1419 (1, 4, or 8 mg; n= 40) or placebo (n = 41). Inhaled corticosteroids and long-acting f3 2 -agonist were tapered down and then discontinued. The last four doses of AZD1419 were given without maintenance medication, followed by a 40-week observation period. Primary endpoint was time to loss of asthma control (LOC). Measurements and Main Results: AZD1419 induced a T-helper cell type 1-type IFN response with a sustained reduction in markers of type 2 inflammation. However, there were no statistically significant differences between AZD1419 and placebo for time to LOC, proportion of patients with LOC, changes in Asthma Control Questionnaire-five-item version, exacerbations, reliever use, FEV1, peak expiratory flow, or fractional exhaled nitric oxide (FENO). LOC was predicted by an early rise in FENO in 63% of patients. Despite withdrawal of maintenance treatment, 24 patients completed the study without LOC; AZD1419 n = 11, placebo n = 13. Adverse events were balanced across groups, with no deaths or serious adverse events judged as causally related to AZD1419. Conclusions: AZD1419 was safe and well tolerated but did not lead to improved asthma control, despite reducing markers of type 2 inflammation. Results suggest that a novel accelerated step-down approach based on FENO is possible for patients with well-controlled asthma.

Introduction: The Phase 2a INCONTRO trial (NCT02898662) is a unique clinical trial that followed eosinophilic, moderate-to-severe asthma patients for up to 10 months after withdrawal of maintenance therapy. The primary endpoint of the trial – the effect of the TLR9 agonist AZD1419 on the time to loss of asthma control (LOC) – was not met. Interestingly, though, 30% (24/81) of all patients managed to complete the trial, maintaining asthma control without standard therapy. Objective: To investigate what covariates differentiate patients who lost asthma control from those maintaining control. Methods: Key baseline covariates were identified in two ways: (1) between-group comparisons (lost control vs. maintained control) and (2) Cox regression of time to LOC in combination with covariate selection. A longitudinal analysis of the relationship between fractional exhaled nitric oxide (FeNO) – measured at home by patients every second day – and LOC was also performed. Results: Baseline eosinophil and FeNO levels were significantly higher in the LOC group and positively associated to risk of LOC (p<0.05). CRP and ALK-P, on the other hand, showed an inverse association to risk of LOC and were significantly higher in patients maintaining control (p<0.05). Both the current value and relative change in FeNO over a three-week period were longitudinal features predicting LOC events (45% and 287% risk increase per two-fold change, respectively). Conclusion: Established markers of type 2 inflammation were associated to risk of LOC following withdrawal of standard asthma therapy and longitudinal changes in FeNO preceded LOC. Elevated markers of systemic inflammation were inversely associated to the risk of LOC.

Intradermal delivery of AZD8601, an mRNA designed to produce vascular endothelial growth factor A (VEGF‐A), has previously been shown to accelerate cutaneous wound healing in a murine diabetic model. Here, we develop population pharmacokinetic and pharmacodynamic models aiming to quantify the effect of AZD8601 injections on the dynamics of wound healing. A dataset of 584 open wound area measurements from 131 mice was integrated from 3 independent studies encompassing different doses, dosing timepoints, and number of doses. Evaluation of several candidate models showed that wound healing acceleration is not likely driven directly by time‐dependent VEGF‐A concentration. Instead, we found that administration of AZD8601 induced a sustained acceleration of wound healing depending on the accumulated dose, with a dose producing 50% of the maximal effect of 92 µg. Simulations with this model showed that a single dose of 200 µg AZD8601 can reduce the time to reach 50% wound healing by up to 5 days.

AZD9567 is a potent and selective nonsteroidal oral glucocorticoid receptor modulator. It is developed as an anti‐inflammatory drug with improved safety profile compared with steroids like prednisolone. Throughout the clinical development of AZD9567, dose selection and data interpretation require a method for determining doses with the same anti‐inflammatory effect as prednisolone. Equipotent doses of AZD9567 and prednisolone were defined by the same average inhibition of TNFα release, a biomarker of anti‐inflammatory effect, measured in a lipopolysaccharide‐stimulated whole blood ex vivo assay. Based on pharmacokinetic‐pharmacodynamic models, TNFα dose‐response relationships for AZD9567 and prednisolone were established. A comparison of the dose‐response curves enabled estimation of an equipotency relationship. Specifically, 20 mg prednisolone was estimated to be equipotent to 40 mg AZD9567 (95% confidence interval: 29–54 mg). Static concentration‐response analyses showed that the relative potencies for inhibition of TNFα release of AZD9567 and prednisolone were well aligned with several other pro‐inflammatory cytokines.

Nonlinear mixed effects modeling is a powerful tool when analyzing data from several entities in an experiment. In this paper, we present NLMEModeling, a package for mixed effects modeling in Wolfram Mathematica. NLMEModeling supports mixed effects modeling of dynamical systems where the underlying dynamics are described by either ordinary or stochastic differential equations combined with a flexible observation error model. Moreover, NLMEModeling is a user-friendly package with functionality for model validation, visual predictive checks and simulation capabilities. The package is freely available and provides a flexible add-on to Wolfram Mathematica.

Radiation therapy, whether given alone or in combination with chemical agents, is one of the cornerstones of oncology. We develop a quantitative model that describes tumor growth during and after treatment with radiation and radiosensitizing agents. The model also describes long-term treatment effects including tumor regrowth and eradication. We challenge the model with data from a xenograft study using a clinically relevant administration schedule and use a mixed-effects approach for model-fitting. We use the calibrated model to predict exposure combinations that result in tumor eradication using Tumor Static Exposure (TSE). The model is able to adequately describe data from all treatment groups, with the parameter estimates taking biologically reasonable values. Using TSE, we predict the total radiation dose necessary for tumor eradication to be 110 Gy, which is reduced to 80 or 30 Gy with co-administration of 25 or 100 mg kg−1 of a radiosensitizer. TSE is also explored via a heat map of different growth and shrinkage rates. Finally, we discuss the translational potential of the model and TSE concept to humans. The new model is capable of describing different tumor dynamics including tumor eradication and tumor regrowth with different rates, and can be calibrated using data from standard xenograft experiments. TSE and related concepts can be used to predict tumor shrinkage and eradication, and have the potential to guide new experiments and support translations from animals to humans.

Background Glucocorticoids are highly effective and widely used anti-inflammatory drugs, but their use is limited by serious side-effects, including glucocorticoid-induced hyperglycaemia and diabetes. AZD9567 is a non-steroidal, selective glucocorticoid receptor modulator that aims to reduce side-effects. We aimed to assess the safety, tolerability, and pharmacokinetics of AZD9567 in healthy volunteers. Methods Two phase 1 clinical studies were done. First, a randomised, placebo-controlled, single-blind, single-ascending dose study was done in healthy men who received single oral doses of AZD9567 2 mg, 10 mg, 20 mg, 40 mg, 80 mg, 100 mg, 125 mg, or 155 mg, or prednisolone 60 mg (n=8 per dose group, randomly assigned 16:2] to receive active drug or placebo). Second, a randomised, active-controlled, single-blind, multiple-ascending dose study was done, in which men and women received oral AZD9567 or prednisolone once daily for 5 days. One cohort of volunteers with prediabetes received AZ D9567 10 mg (n=7) or prednisolone 20 mg (n=2). All other cohorts comprised healthy volunteers, receiving AZD9567 20 mg, 40 mg, 80 mg, or 125 mg (n=7 per dose group), or prednisolone 5 mg (n=13), 20 mg (n=16), or 40 mg (n=13). Participants and study centre staff were masked to treatment assignment for each cohort, although data were unmasked for safety review between cohorts. The primary outcome of the single-ascending dose study was the safety, tolerability, and pharmacokinetics of single ascending doses of AZD9567; for the multiple-ascending dose study it was the safety and tolerability of AZD9567 following multiple ascending doses. As a secondary outcome, effects on glycaemic control were ascertained with oral glucose tolerance tests (OGTTs) done at baseline and on day 1 of the single-ascending dose study, and at baseline and on day 4 of the multiple-ascending dose study. These trials are registered at ClinicalTrials.gov, NCT02512575 and NCT02760316. Findings In the single-ascending dose study, between Nov 18, 2015, and Sept 26, 2016, 72 healthy white men were enrolled, and all completed the study. In the multiple-ascending dose study, between May 2, 2016, and Sept 13, 2017, 77 predominantly white male volunteers (including nine individuals with prediabetes and eight women) were enrolled and 75 completed the study. All doses of AZD9567 and prednisolone were well tolerated, with no serious adverse events or events suggesting adrenal insufficiency. In the single-ascending dose study, nine adverse events of mild intensity were reported (five with AZD9567 and four with placebo); no adverse event was reported by more than one person. In the multiple-ascending dose study, 44 adverse events of mild or moderate intensity were reported (18 with AZD9567 and 26 with prednisolone). The most common were headache and micturition. Apparent clearance, volume of distribution, and half-life of AZD9567 were consistent across doses and for single versus repeated dosing. In the multiple-ascending dose study, OGTTs showed no significant difference with AZD9567 doses up to 80 mg compared with prednisolone S mg in glucose area under the curve from 0 h to 4 h post-OGTT (AUC(0-4h)) from baseline to day 4; the increase in glucose AUC(0-4h) from baseline to day 4 was significantly lower with all AZD9567 doses versus prednisolone 20 mg (AZD9567 20 mg p<0 . 0001, 40 mg p=0.0001, 80 mg p=0 . 0001, and 125 mg p=0.0237). Interpretation AZD9567 appears to be safe and well tolerated in healthy, predominantly white male volunteers and shows promising initial evidence for improved post-prandial glucose control. Studies of longer duration, with a greater proportion of women and other ethnic groups, and in patients requiring anti-inflammatory treatment are needed to characterise the clinical efficacy and safety profile of AZD9567. (C) 2019 Elsevier Ltd. All rights reserved.

This study presents an extensive dose-response-time (DRT) meta-analysis of the nicotinic acid-induced inhibition of free fatty acids and insulin release. The purpose was to quantify the implications of lacking exposure data when analysing complex pharmacodynamic systems. The DRT model successfully characterised various response behaviours-including time-delays, rebound, feedback mechanisms, and adaptation-on both the individual and the population level. Comparing the fitted DRT model to an exposure-driven reference analysis showed that bias and uncertainty were introduced in the parameter estimates. However, most estimates were within one standard error from the reference. In both approaches, a few parameters suffered from practical identifiability issues, likely due to large differences in half-lives of the different rate processes. Moreover, the optimal dosing strategies predicted by the DRT model differed slightly from those of the exposure-driven analysis, having a lower optimal steady-state reduction of free fatty acids exposure.

III-36 Tim Cardilin Modeling of radiation therapy and radiosensitizing agents in tumor xenografts Tim Cardilin (1,2), Joachim Almquist (1), Mats Jirstrand (1), Astrid Zimmermann (3), Floriane Lignet (4), Samer El Bawab (4), and Johan Gabrielsson (5) (1) Fraunhofer-Chalmers Centre, Gothenburg, Sweden, (2) Department of Mathematical Sciences, Chalmers University of Technology and Gothenburg University, Gothenburg, Sweden, (3) Merck, Translational Innovation Platform Oncology, Darmstadt, Germany, (4) Merck, Global Early Development - Quantitative Pharmacology, Darmstadt, Germany, (5) Division of Pharmacology and Toxicology, Department of Biomedical Sciences and Veterinary Public Health, Swedish University of Agricultural Sciences, Uppsala, Sweden Objectives: To conceptually and mathematically describe the treatment effects of radiation and radiosensitizing agents on tumor volume in xenografts with respect to short- and long-term effects. Methods: Data were generated in FaDu xenograft mouse models, where animals were treated with radiation given either as monotherapy (2 Gy per dose) or together with an early-discovery radiosensitizing agent (25 or 100 mg/kg per dose) that interferes with the repair of the DNA damage induced by irradiation. Animals received treatment following a clinically-relevant administration schedule with doses five days a week for six weeks. Tumor diameters were measured by caliper twice a week for up to 140 days. A pharmacodynamic tumor model was adapted from a previously-published model [1,2]. The improved model captures both short- and long-term treatment effects including tumor eradication and tumor regrowth. Short-term radiation effects are described by allowing lethally irradiated cells up to one more cell division before apoptosis. Long-term radiation effects are described by an irreversible decrease in tumor growth rate. The radiosensitizing agent was assumed to stimulate both processes. The model also includes a natural death rate of cancer cells. The model was calibrated to the xenograft data using a mixed-effects approach based on the FOCE method that was implemented in Mathematica [3]. Between-subject variability was accounted for in initial tumor volume, as well as in the short- and long-term radiation effects. Results: Data across all treatment groups were well-described by the model. All model parameters were estimated with acceptable precision and biologically reasonable values. Vehicle growth was approximately exponential during the observed time period with an estimated tumor doubling time of approximately 5 days. Tumor growth following radiation therapy resulted in significant tumor regression followed by either tumor eradication (2 animals) or slow regrowth (7 animals). The short- and long-term effects incorporated into the tumor model were able to account for both of these scenarios. A simple analysis shows that if the tumor growth rate is decreased below the natural death rate, the tumor will be eradicated. Otherwise, the tumor will regrow but at a slower rate compared to pre-treatment. The model predicts that each fraction of radiation (2 Gy) results in lethal damage in 15 % of viable cells, and that a total dose above 120 Gy will eradicate the tumor. Tumor growth following combination therapy with a lower dose (25 mg/kg) resulted in more cases of tumor eradication (6 animals) and fewer cases of regrowth (3 animals), whereas combination therapy with the higher dose (100 mg/kg) resulted in tumor eradication in all 9 animals. When radiation therapy was complemented by radiosensitizing treatment (100 mg/kg per dose), each fraction of 2 Gy was estimated to kill 25 % of viable cells, and the total radiation dose required for tumor eradication was decreased by a factor four to 30 Gy. Conclusions: A tumor model has been developed to describe the treatment effects of radiation therapy, as well as combination therapies involving radiation, in tumor xenografts. The model distinguishes between short- and long-term effects of radiation treatment and can describe different tumor dynamics, including tumor eradication and tumor regrowth at different rates. The novel tumor model can be used to predict treatment outcomes for a broad range of treatments including radiation therapy and combination therapies with different radiosensitizing agents. References: [1] Cardilin T, Almquist J, Jirstrand M, Zimmermann A, El Bawab S, Gabrielsson J. Model-based evaluation of radiation and radiosensitizing agents in oncology. CPT: Pharmacometrics & Syst. Pharmacol. (2017). [2] Cardilin T, Zimmermann A, Jirstrand M, Almquist J, El Bawab S, Gabrielsson J. Extending the Tumor Static Concentration Curve to average doses – a combination therapy example using radiation therapy. PAGE 25 (2016) Abstr 5975 [www.page-meeting.org/?abstract=5975]. [3] Almquist J, Leander J, Jirstrand M. Using sensitivity equations for computing gradients of the FOCE and FOCEI approximations to the population likelihood. J Pharmacokinet Pharmacodyn (2015) 42: 191-209.

Mathematical models predicting in vivo pharmacodynamic effects from in vitro data can accelerate drug discovery, and reduce costs and animal use. However, data integration and modeling is non-trivial when more than one drug-target receptor is involved in the biological response. We modeled the inhibition of non-esterified fatty acid release by dual G-protein-coupled receptor 81/109A (GPR81/GPR109A) agonists in vivo in the rat, to estimate the in vivo EC50 values for 12 different compounds. We subsequently predicted those potency estimates using EC50 values obtained from concentration-response data in isolated primary adipocytes and cell systems overexpressing GPR81 or GPR109A in vitro. A simple linear regression model based on data from primary adipocytes predicted the in vivo EC50 better than simple linear regression models based on in vitro data from either of the cell systems. Three models combining the data from the overexpressing cell systems were also evaluated: two piecewise linear models defining logical OR- and AND-circuits, and a multivariate linear regression model. All three models performed better than the simple linear regression model based on data from primary adipocytes. The OR-model was favored since it is likely that activation of either GPR81 or GPR109A is sufficient to deactivate the cAMP pathway, and thereby inhibit non-esterified fatty acid release. The OR-model was also able to predict the in vivo selectivity between the two receptors. Finally, the OR-model was used to predict the in vivo potency of 1651 new compounds. This work suggests that data from the overexpressing cell systems are sufficient to predict in vivo potency of GPR81/GPR109A agonists, an approach contributing to faster and leaner drug discovery.