Dose-response Data Research Articles

An investigation to improve a nonlinear mixed-effects approach for EC50 estimation based on multi-donor dose–response data

ABSTRACT Dose–response relationships are important in assessing the efficacy and potency of compounds, which can usually be characterized by a 4-parameter logistic (4-PL) model estimating EC50, slope factor, lower asymptote, and upper asymptote. EC50, the concentration of a compound that induces a response halfway between the baseline and maximum, is a key quantity to evaluate compound potency. For multi-donor dose–response data, it is often of interest to estimate the overall EC50 (i.e. the average EC50 of the population of donors) and its 95% confidence interval (CI). A few multi-donor EC50 estimation methods have been proposed in the literature. Jiang and Kopp-Schneider (2014) systematically compared the meta-analysis approach and the nonlinear mixed-effects approach and concluded that the meta-analysis approach is simple and robust to summarize EC50 estimates from multiple experiments, especially suited in the case of a small number of experiments, while the nonlinear mixed-effects approach has the issue of convergence failures probably due to overparameterization. In this article, we propose a modification of the nonlinear mixed-effects approach by using the stochastic approximation expectation-maximization (SAEM) algorithm to estimate model parameters and using multiple starting points to search for globally optimal values, which can substantially alleviate the issue of convergence failures even for small number of donors (e.g. n = 3), and achieve a smaller absolute median bias and better coverage probability of 95% confidence interval than the meta-analysis approach when the number of donors is not too small (e.g. n ≥ 7).

Computational model for policy simulation and prediction of the regulatory impact of front-of-package food labels

Non-communicable diseases (NCDs), a significant cause of global mortality, necessitate targeted policy measures to reduce exposure to risk factors, particularly nutrition-related ones. Front-of-pack food labeling aims to shape consumer behavior and decrease exposure to nutritional risk factors. There are various forms of this policy, including traffic light (TL), nutrient profile model (NPM), and reference value (RV) labels. Mathematical models incorporating experimental and dose–response data support determining the most effective form. When selecting a modeling method, it is essential to consider the uncertainty involved in estimating risk factors. This study aims to create a computational model to predict the health and economic impacts of different policy options using an improved version of the Scarborough algorithm, incorporating a validation process to address potential uncertainties. The model shows that NPM was the most effective, reducing the estimated annual mortality rate from 514,247 cases to 447,394 cases (13% reduction). The following labels were TL (11% reduction) and RV (6% reduction). Economically, the RV label affects consumer spending the least, predicting an 8% increase in monthly spending per individual from the baseline. When assessed from both health and economic perspectives, the RV label has emerged as the most advantageous front-of-pack food labeling policy. The proposed model can aid policymakers in evaluating policy alternatives and thus selecting the most advantageous policies based on health and economic outcomes while ensuring the model's accuracy and applicability for the community.

A novel 3D polymer gel dosimeter based on polymethyl methacrylate gel (PMMAG) for radiotherapy: Ultrasonic evaluation

This study investigates the characteristics of a novel polymer gel dosimeter (PMMAG) for radiotherapy applications, focusing on its radiation absorption and sensitivity properties. The PMMAG dosimeters were evaluated using both UV–vis spectrophotometry and ultrasonic techniques. The results of the study, UV–vis analysis revealed a significant increase in dose response with the introduction of a cross-linker, peaking at a monomer-to-cross-linker ratio of 5:3. Sensitivity analysis indicated optimal sensitivity at this ratio, with values reaching 0.021 a.u./Gy. Ultrasound evaluation showed that the speed of sound and attenuation coefficient demonstrated a linear relationship and a strong positive correlation with an increase in the applied radiation dose, with the highest sensitivity observed at 8 Gy. The optimal sample exhibited the highest dose-response values at both 4 Gy and 8 Gy doses. Sensitivity values ranged from 2.1 to 2.75. The ultrasonic measurements demonstrated a significantly larger dynamic range in dose response curves compared to UV–vis dose-response data. It is concluded that ultrasound shows great potential as a technique for the evaluation of polymer gel dosimeters. The PMMAG can be introduced as a novel dosimeter for ionizing radiation dosimetry, validated through both optical and ultrasound assessment methods. The consistent and reliable performance of the PMMAG dosimeters makes them suitable for various applications in radiation therapy.

New Drug Development Strategy in Japan: Flexibility in Guideline Adherence.

Recently, a new type of drug lag, known as "drug loss" has emerged in Japan. It is a condition where the development of a drug approved in other countries has not been initiated in Japan. For 265 new drugs approved in the United States or Europe during 2010-2020, only 31% had commenced development in Japan as of December 31, 2020. A characteristic feature of Japanese guidelines on new drug development is that, in principle, clinical trial data in Japanese participants are required in each study phase. Given key players in new drug development are shifting from large pharmaceutical companies to emerging biopharma companies, primarily based outside Japan, the necessity for Japanese data may contribute to the drug lag. This study aimed to clarify the guideline adherence to new drug applications in Japan. Of the 159 new drugs approved in Japan between April 2019 and March 2024, the clinical data packages for almost all drugs included both pharmacokinetic (PK) data and efficacy and safety data in Japanese participants, irrespective of the study phase or design. We identified three flexible development approaches: the absence of Japanese dose-response data (39.6%), absence of Japanese confirmatory data generated from phase III randomized controlled trials (35.2%), and post-hoc Japanese PK data (43.0%, 34/79). Biologics, orphan drug designation, antineoplastic agents, and same applicant and originator were identified as factors significantly associated with these flexibilities. The results will help foreign companies, including emerging biopharmas, in formulating effective new drug development strategies, potentially alleviating the drug lag in Japan.

Urinary Biomarkers of Strawberry and Blueberry Intake.

Introduction There is increasing interest in food biomarkers to address the shortcomings of self-reported dietary assessments. Berries are regarded as important fruits worldwide; however, there are no well-validated biomarkers of berry intake. Thus, the objective of this study is to identify urinary biomarkers of berry intake. Methods For the discovery study, participants consumed 192 g strawberries with 150 g blueberries, and urine samples were collected at 2, 4, 6, and 24 h post-consumption. A dose-response study was performed, whereby participants consumed three portions (78 g, 278 g, and 428 g) of mixed strawberries and blueberries. The urine samples were profiled by an untargeted LC-MS metabolomics approach in the positive and negative modes. Results Statistical analysis of the data revealed that 39 features in the negative mode and 15 in the positive mode significantly increased between fasting and 4 h following mixed berry intake. Following the analysis of the dose-response data, 21 biomarkers showed overall significance across the portions of berry intake. Identification of the biomarkers was performed using fragmentation matches in the METLIN, HMDB, and MoNA databases and in published papers, confirmed where possible with authentic standards. Conclusions The ability of the panel of biomarkers to assess intake was examined, and the predictability was good, laying the foundations for the development of biomarker panels.

Expression of sensitized β2 nAChR subunits in VTA neurons enhances intravenous nicotine self-administration in male rats

Ventral tegmental area (VTA) nicotinic acetylcholine receptors (nAChRs) are important for nicotine reinforcement. To determine whether and to what extent these receptors are sufficient for nicotine reinforcement, we expressed β2Leu9′Ser (i.e. sensitized) nAChR subunits in the VTA of adult male rats and assessed the nicotine dose-response relationship in intravenous self-administration (SA). β2Leu9′Ser rats self-administered nicotine doses 50–100 fold lower than the lowest doses that control rats would respond for. Expression of WT β2 subunits confirmed that this enhanced sensitivity to nicotine was due to the Leu9′Ser mutation in β2. Higher unit doses were associated with strong escalation in β2Leu9′Ser rats over 17 fixed ratio sessions. Escalation was minimal or absent in control rats at the same unit doses. In progressive ratio SA, β2Leu9′Ser rats exhibited higher breakpoints than control rats when the nicotine unit dose was 1.5 μg/kg/inf or higher. In intermittent access SA, β2Leu9′Ser rats exhibited response patterns very similar to control rats. By adding nicotine dose-response data, progressive ratio assays, and intermittent access results that rule out stereotypy, these data significantly extend our previous finding that nicotine activation of the mesolimbic dopamine pathway is sufficient for nicotine reinforcement.

Leveraging multiple data types for improved compound-kinase bioactivity prediction

Machine learning provides efficient ways to map compound-kinase interactions. However, diverse bioactivity data types, including single-dose and multi-dose-response assay results, present challenges. Traditional models utilize only multi-dose data, overlooking information contained in single-dose measurements. Here, we propose a machine learning methodology for compound-kinase activity prediction that leverages both single-dose and dose-response data. We demonstrate that our two-stage approach yields accurate activity predictions and significantly improves model performance compared to training solely on dose-response labels. This superior performance is consistent across five diverse machine learning methods. Using the best performing model, we carried out extensive experimental profiling on a total of 347 selected compound-kinase pairs, achieving a high hit rate of 40% and a negative predictive value of 78%. We show that these rates can be improved further by incorporating model uncertainty estimates into the compound selection process. By integrating multiple activity data types, we demonstrate that our approach holds promise for facilitating the development of training activity datasets in a more efficient and cost-effective way.

A systematic review and BMD modeling approach to develop an AOP for humidifier disinfectant-induced pulmonary fibrosis and cell death

Dosimetry modeling and point of departure (POD) estimation using in vitro data are essential for mechanism-based hazard identification and risk assessment. This study aimed to develop a putative adverse outcome pathway (AOP) for humidifier disinfectant (HD) substances used in South Korea through a systematic review and benchmark dose (BMD) modeling. We collected in vitro toxicological studies on HD substances, including polyhexamethylene guanidine hydrochloride (PHMG-HCl), PHMG phosphate (PHMG-p), a mixture of 5-chloro-2-methyl-4-isothiazolin-3-one and 2-methyl-4-isothiazolin-3-one (CMIT/MIT), CMIT, and MIT from scientific databases. A total of 193 sets of dose-response data were extracted from 34 articles reporting in vitro experimental results of HD toxicity. The risk of bias (RoB) in each study was assessed following the office of health assessment and translation (OHAT) guideline. The BMD of each HD substance at different toxicity endpoints was estimated using the US Environmental Protection Agency (EPA) BMD software (BMDS). Interspecies- or interorgan differences or most critical effects in the toxicity of the HD substances were analyzed using a 95% lower confidence limit of the BMD (BMDL). We found a critical molecular event and cells susceptible to each HD substance and constructed an AOP of PHMG-p- or CMIT/MIT-induced damage. Notably, PHMG-p induced ATP depletion at the lowest in vitro concentration, endoplasmic reticulum (ER) stress, epithelial-to-mesenchymal transition (EMT), inflammation, leading to fibrosis. CMIT/MIT enhanced mitochondrial reactive oxygen species (ROS) production, oxidative stress, mitochondrial dysfunction, resulting in cell death. Our approach will increase the current understanding of the effects of HD substances on human health and contribute to evidence-based risk assessment of these compounds.

Assessing the genotoxicity of N-nitrosodiethylamine with three in vivo endpoints in male Big Blue® transgenic and wild-type C57BL/6N mice.

The detection of N-nitrosamines in drug products has raised global regulatory interest in recent years due to the carcinogenic potential of some nitrosamines in animals and a need to identify a testing strategy has emerged. Ideally, methods used would allow for the use of quantitative analysis of dose-response data from in vivo genotoxicity assays to determine a compound-specific acceptable intake for novel nitrosamines without sufficient carcinogenicity data. In a previous study we compared the dose-response relationships of N-nitrosodiethylamine (NDEA) in three in vivo genotoxicity endpoints in rats. Here we report a comparison of NDEA's genotoxicity profile in mice. Big Blue® mice were administered NDEA at doses of 0.001, 0.01, 0.1, 1 and 3 mg/kg/day by oral gavage for 28 days followed by 3 days of expression. Statistically significant increases in the NDEA induced mutations were detected by both the transgenic rodent mutation assay (TGR) using the cII endpoint and by duplex sequencing in the liver but not bone marrow of mice. In addition, administration of NDEA for two consecutive days in male C57BL/6N mice caused elevated DNA damage levels in the liver as measured by % tail DNA in comet assay. The benchmark dose (BMD) analysis shows a BMDL50 of 0.03, 0.04 and 0.72 mg/kg/day for TGR, duplex sequencing and comet endpoints, respectively. Overall, this study demonstrated a similar genotoxicity profile of NDEA between mice and rats and provides a reference that can be used to compare the potential potency of other novel nitrosamines for the induction of gene mutations.

A detailed quartz and feldspar luminescence chronology for the Khonako II loess section (Southern Tajikistan)

Parts of Central Asia have been dominated by high dust flux since the start of the Quaternary. The resulting loess-palaeosol deposits are important archives for landscape and climate changes, but there is a lack of chronological data for the subaerial deposits of Southern Tajikistan. Our study presents a high-resolution luminescence chronology for the Khonako II section in the Khovaling region. Thirty-seven samples were collected from the first ∼8 m of the section, corresponding to the Holocene soil and the upper part of the Loess 1 (L1) unit. We applied quartz OSL dating to the coarse-silt fraction (40–63 μm) and polymineral pIRIR200,290 dating to the very fine sand fraction (63–90 μm). The polymineral pIRIR200,290 signal has satisfactory characteristics. The quartz dose response curve displays a non-single exponential growth above ∼100 Gy, thus, the De values were estimated by fitting a single exponential function plus linear component to the dose response data. To assess the pIRIR200,290 residual dose at deposition, we used the offset between our quartz and polymineral chronologies from Khonako II and equivalent doses measured on modern dust samples from Tajikistan and Uzbekistan. The resulting 9.2 ± 0.4 Gy dose was then subtracted from the pIRIR200,290 doses for final age calculation. The quartz OSL and pIRIR ages are then generally consistent. The obtained high-resolution luminescence chronology shows that the upper part of the L1 unit accumulated during the end of marine isotope stage (MIS) 3 and through MIS 2 (39–20 ka). The average dust accumulation rates (DAR) increased from ∼31 cm ka−1 to 41 cm ka−1 between MIS 3 and MIS 2. The DAR reached a peak of ∼71 cm ka−1 at 21 ka. A hiatus of ∼7–9 ka was then identified between the end of the last glacial maximum (LGM) and the beginning of the Holocene, and the average DAR decreased during the Holocene. Our results indicate a continuous high dust flux in the Khovaling plateau over the last 39 ka, but reworking processes and potential deflation events mark the LGM-Holocene transition. High-resolution luminescence dating studies in Tajikistan are therefore important to detect potential discontinuities in the sequences and provide an independent timescale for interpreting the climate proxies and calculating dust accumulation rates.

Prediction of therapeutic response and cancer outcomes in solid tumours via in silico clinical trials.

e13603 Background: Oncology therapeutic development has high failure rates with substantial costs. Advances in technology, including molecular characterisations of cancer and computational power, provide the opportunity to better model therapeutic response for existing and emerging therapies. Methods: Concr adapted Bayesian statistical principles used by astrophysicists to effectively integrate multi-dimensional data (genomic & transcriptomic) for accurate modelling of cancer biology. Our proprietary computational framework was applied to predict clinical response and survival through construction of digital twins and in silico simulations of clinical trials. Predicted log odds ratios (LOR) were generated for drug response and compared to published data from 8 suitable historical clinical trials. Three distinct models underpin this framework: Drug Efficacy, Treatment Response & Overall Survival (OS). Three publicly available datasets were used for training: Cancer Therapeutic Response Portal ( in vitro dose-response data), Cancer Cell Line Encyclopaedia and TCGA. Results: For all 8 clinical studies, the digital twin model accurately simulated both trial arms, compared drug efficacy across arms and predicted which treatment was most active. Unblinded evaluation: Our model accurately predicted gemcitabine would have greater clinical benefit than 5-FU (LOR -0.10, P <0.0001) in metastatic pancreatic cancer. In advanced breast cancer, the model predicted docetaxel had a higher response rate than doxorubicin, and carboplatin response rates were similar to docetaxel in BRCA wild-type patients. In platinum-sensitive recurrent ovarian cancer, the model predicted cisplatin-based combination had a higher response rate than paclitaxel. Blinded evaluation: Using data for paclitaxel, the model correctly predicted that nab-paclitaxel+gemcitabine response rates were higher than gemcitabine in metastatic pancreatic cancer (predicted LOR -0.090, p = <0.001). In all 3 early breast cancer studies, predictions mirrored clinical trial results, adjuvant ECF > CMF, adjuvant TC > AC and adjuvant tamoxifen was superior to capecitabine. The underlying pan-tumour Overall Survival model used a Random Survival Forest approach, trained on 23 cancers with predictive accuracy of 0.78 AUC ROC and C-index 0.71. To enable cohort enrichment for drug response, the model segmented patient cohorts into treatment responder and non-responder. Using this approach, the log odds increased for drug response rate for 16 of the 19 different cancers and 14 of the different 17 drugs. Conclusions: Our digital twin model represents transformative technology for clinical trial simulation with strong potential for accelerating and de-risking clinical drug development, and utility for synthetic control arms.

ETD001: A novel inhaled ENaC blocker with an extended duration of action in vivo

BackgroundInhibiting ENaC in the airways of people with cystic fibrosis (pwCF) is hypothesized to enhance mucociliary clearance (MCC) and provide clinical benefit. Historically, inhaled ENaC blockers have failed to show benefit in pwCF challenging this hypothesis. It is however unknown whether the clinical doses were sufficient to provide the required long duration of action in the lungs and questions whether a novel candidate could offer advantages where others have failed? MethodsDose-responses with the failed ENaC blockers (VX-371, BI 1265162, AZD5634, QBW276) together with ETD001 (a novel long acting inhaled ENaC blocker) were established in a sheep model of MCC and were used to predict clinically relevant doses that would provide a long-lasting enhancement of MCC in pwCF. In each case, dose predictions were compared with the selected clinical dose. ResultsEach of the failed candidates enhanced MCC in the sheep model. Translating these dose-response data to human equivalent doses, predicted that substantially larger doses of each candidate, than were evaluated in clinical studies, would likely have been required to achieve a prolonged enhancement of MCC in pwCF. In contrast, ETD001 displayed a long duration of action (≥16 h) at a dose level that was well tolerated in Phase 1 clinical studies. ConclusionsThese data support that the ENaC blocker hypothesis is yet to be appropriately tested in pwCF. ETD001 has a profile that enables dosing at a level sufficient to provide a long duration of action in a Phase 2 clinical study in pwCF scheduled for 2024.

Abstract PO4-14-09: A computational model of the mechanisms of action of combined endocrine therapy and CDK4/6 inhibition predicts outcome in patients with Luminal B breast cancer

Abstract Background: Hormone receptor-positive/HER2-negative (HR+/HER2-) breast cancer (BC) is clinically and biologically heterogeneous. CDK4/6 inhibitors (CDK4/6i) are proven to be effective in different molecular subtypes of HR+/HER2- BC, including the PAM50 luminal B. However, not all patients benefit to the same extent and new biomarkers for response are needed. The aim of this study was to develop a computational workflow to predict the response of patients with luminal B BC to treatment with CDK4/6i in combination with endocrine therapy (ET). Methods: The main part of the workflow is a computational model representing the mechanisms of action of the drugs and their influence on protein signaling and cell proliferation in the tumor. The model was trained on publicly available data from BC cell lines (Western blot time courses and viability dose-response data). The model was then used to predict response in patients by incorporating gene expression profiles obtained at baseline. The output of the model was a score indicating how strongly the tumor responded to the treatment. Gene expression data determined using the nCounter BC360 panel was available at baseline from two patient cohorts: 1) the CORALLEEN phase II trial which evaluated neoadjuvant ribociclib plus letrozole vs multi-agent chemotherapy in postmenopausal patients with luminal B by PAM50, HR+/HER2- early BC (Prat et al. Lancet Oncology. 2020), 2) a retrospective study of postmenopausal patients with HR+/HER2-/Luminal B advanced BC treated with CDK4/6i plus ET in the first line setting at Hospital Clinic Barcelona (hereafter CDK cohort). PAM50 risk of relapse (ROR) and Ki67 levels were considered as outcome for the CORALLEEN patients. Progression free survival (PFS) was available in the CDK cohort. Area under the ROC Curve (AUC) was used to estimate the discrimination performance of the model. Differences were tested for statistical significance using Wilcoxon rank-sum test. Hazard ratios were estimated using Cox regression to investigate the association with PFS. Results: The computational model used here describes the dynamics of relevant protein-protein and drug-protein interactions to the treatment of CDK4/6i plus ET. The model showed high agreement with the training data obtained from cell lines (Pearson correlation of 0.88 and 0.95). The ability of the trained model to predict treatment outcome in patients was validated in baseline samples of the CDK4/6i arm (n=51) and the chemotherapy arm (n=52) of the CORALLEEN trial, and baseline Luminal B primary tumors of the CDK cohort (n=19). For each patient, a response score was calculated by the model using the expression of 6 genes at baseline as input. This response score was significantly associated with patient response in both cohorts. The model identified patients with high Ki67 (AUC of 0.80 (95% CI 0.64 - 0.92)) and high ROR (AUC of 0.78 (95% CI 0.64 - 0.89)) after treatment in the CDK4/6i arm of the CORALLEEN cohort and was used to stratify patients into different response groups. The AUC in the chemotherapy arm of CORALLEEN for identifying high Ki67 was 0.44 (95% CI 0.29 - 0.58), indicating that the predictions are specific to CDK4/6i plus ET treatment. Additionally, stratification of patients in the CDK cohort into either two or three groups based on the response score was linked to PFS (HR=3.71 (95% CI 0.97 - 14.16), p=0.055 and HR=2.92 (95% CI 1.08 - 7.86), p=0.034, respectively). Conclusion: A mechanistic model was developed, trained on cell line data, and then used to predict treatment outcome of patients with HR+/HER2-/PAM50 Luminal B BC treated with CDK4/6i plus ET. This approach showed significant association with observed outcome and could be used to assign patients to different response groups, indicating the usefulness of the model as a potential marker for response. Citation Format: Leonard Schmiester, Fara Brasó-Maristany, Vessela Kristensen, Arnoldo Frigessi, Aleix Prat, Alvaro Köhn-Luque. A computational model of the mechanisms of action of combined endocrine therapy and CDK4/6 inhibition predicts outcome in patients with Luminal B breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-14-09.

Role of L-type Ca2+ channels in the differential response to oxytocin of uteri from virgin and proven breeder rats

Introduction: The experience of pregnancy affects uterine function well beyond delivery. For instance, the likelihood of accelerated parturitions, spontaneous delivery, and risk of hemorrhage in future pregnancies is increased with parity. While epidemiological evidence for these phenomena is abundant, mechanistic explanations of these and other changes are still being investigated. We previously demonstrated that the response to oxytocin is more robust in the uteri of proven breeder rats and that T-type calcium channels, although slightly more expressed in proven breeder samples had a rather limited impact in this mechanism. Hypothesis: Here, we tested the hypothesis that voltage gated L-type calcium channels contribute more significantly than T-type calcium channels in the differential response to oxytocin in the myometrium from virgin (V) and proven breeder (PB) rats. Methods: V and PB non pregnant female 18-week-old rats were euthanized at proestrus. Uterine strips were suspended in a tissue bath containing Krebs solution (in mM, NaCl 117, KCl 4.7, NaHCO3 25, MgCl2 1.2, KH2PO4 1.2, CaCl2 2.5, glucose 11, pH= 7.4) at 37°C in 95% O2 and 5% CO2. Dose response curves to the L-type calcium channel blocker Verapamil (10E-8 to 10E-5 M) and dose responses to oxytocin in the presence of either 10 E-6 or 10E-5 Verapamil were recorded. Area under the curve, frequency, amplitude, and duration of contractions were measured. L-type channels expression was evaluated with qRT-PCR. T-tests and ANOVA two ways were used for statistical analysis. Results: Compared to control, both doses of Verapamil suppressed 100% of spontaneous and 50% of oxytocin-evoked contractility in V and PB samples. The maximal response to oxytocin was significantly stronger in PB than in V (p<0.001). Thus, blocking L-type Ca2+ channels does not alter the differential response to oxytocin observed in the absence of verapamil. The difference in Expression of the L-type calcium channel revealed a 2-fold increase in PB compared to V uteri. These findings closely align with oxytocin dose response data in the presence of the T-type calcium channels blocker Mibefradil and with the T-type channels expression. Conclusions: Neither L-type or T-type Ca2+ channels appear to be key players in the differential response to oxytocin of V and PB uteri. Instead, it is more likely that other elements of the intracellular calcium control are involved in this phenomenon. Acknowledgements: This study was supported by a Kenneth Suarez Fellowship to RP and an MWU intramural fund to MP. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Effect of changing the radiation dose range on the in vitro cytogenetic dose response to gamma-rays

Purpose To examine the distortion of the linear quadratic (LQ) model of in vitro cytogenetic dose response over an extended range of γ-ray doses by analyzing the available literature data, and to establish the dose ranges, in which the LQ dose response curve (DRC) can be most accurately fitted for biological dosimetry. Materials and methods Data on yields of dicentrics (Dic) or dicentrics plus centric rings (Dic + CR) induced in vitro in human lymphocytes by acute γ-rays were extracted from 108 open sources. The overall dose response dataset in the dose range up to 50 Gy was fitted to a fractional-rational (FR) model, which included a ‘basic’ LQ function in the numerator, and a reduction factor dependent on the square of the dose in the denominator. Cytogenetic dose response data obtained at Grigoriev Institute for Medical Radiology, Kharkiv, Ukraine (GIMRO) in the range 0.1 − 20.3 Gy acute γ-rays were fitted to the LQ model with the progressive changing minimum or maximum radiation dose. Results The overall dose response, as expected, followed the LQ function in the dose range ≤5 Gy, but in the extended dose range appeared to be S-shaped, with intensive saturation and a plateau at doses ≥22 Gy. Coefficients of the ‘basic’ LQ equation in FR model were very close to many published DRCs; calculated asymptote was 17. Fitting of the GIMRO dataset to the LQ model with the shift of the dose range showed the increase in linear coefficient with the increment of either minimum or maximum radiation dose, while the decline of the quadratic coefficient was regulated mostly by the increase of the highest dose. The best goodness of fit, assessed by lower χ2 values, occurred for dose ranges 0.1 − 1.0 Gy; 0.5 − 5.9 Gy; 1.0 − 7.8 Gy; 2.0 − 9.6 Gy, 3.9 − 16.4 Gy and 5.9 − 20.3 Gy. The ‘see-saw’ effect in changes of LQ coefficients was confirmed by re-fitting datasets published by other laboratories. Conclusions The classical LQ model with fixed coefficients appears to have limited applicability for cytogenetic dosimetry at radiation doses >5 Gy due to the saturation of the dose response. Different response of the LQ coefficients to the changes of the dose range must be considered during the DRC construction. Proper selection of minimum and maximum dose in calibration experiments makes it possible to improve the goodness of fit of the LQ DRC.

Valuing the health benefits of nature-based recreational physical activity in England

Physical activity (PA) reduces the risk of several non-communicable diseases (NCDs). Natural environments support recreational PA. Using data including a representative cross-sectional survey of the English population, we estimated the annual value of nature-based PA conducted in England in 2019 in terms of avoided healthcare and societal costs of disease.Population-representative data from the Monitor of Engagement with the Natural Environment (MENE) survey (n = 47,580; representing 44,386,756) were used to estimate the weekly volume of nature-based recreational PA by adults in England in 2019. We used epidemiological dose–response data to calculate incident cases of six NCDs (ischaemic heart disease (IHD), ischaemic stroke (IS), type 2 diabetes (T2D), colon cancer (CC), breast cancer (BC) and major depressive disorder (MDD)) prevented through nature-based PA, and estimated associated savings using published costs of healthcare, informal care and productivity losses. We investigated additional savings resulting from hypothetical increases in: (a) visitor PA and (b) visitor numbers.In 2019, 22million adults > 16 years of age in England visited natural environments at least weekly. At reported volumes of nature-based PA, we estimated that 550 cases of IHD, 168 cases of IS, 1,410 cases of T2D, 41 cases of CC, 37 cases of BC and 10,552 cases of MDD were prevented, creating annual savings of £108.7million (95 % uncertainty interval: £70.3million; £150.3million).Nature-based recreational PA in England results in reduced burden of disease and considerable annual savings through prevention of priority NCDs. Strategies that increase nature-based PA could lead to further reductions in the societal burden of NCDs.

The dosing regimen for 17-hydroxyprogesterone caproate was suboptimal: lessons for future pharmacotherapy for pregnant women

BackgroundMakena (17-hydroxyprogesterone caproate) was FDA approved for prevention of recurrent spontaneous preterm birth in 2011 under the accelerated approval pathway but fundamental pharmacokinetic or pharmacodynamic (phase1 and phase 2) studies were not performed. At the time, there were no dose-response or concentration-response data. The therapeutic concentration was not known. The lack of such data questions whether the dosing regimen for 17-hydroxyprogesterone caproate was optimized. ObjectiveThe purpose of this study was to evaluate the dosing regimen for 17-hydroxyprogesterone by analyzing three data sets that evaluated 17-hydroxyprogesterone caproate pharmacology: the Maternal-Fetal Medicine Omega 3 study, the Obstetric-Fetal Pharmacology Research Units study and the Obstetrical-Fetal Pharmacology Research Centers study. If an inappropriate dosing regimen could be identified, such information could inform future studies of pharmacotherapy in pregnancy. Study DesignData from the Omega 3 study were utilized to determine if plasma concentration was related to spontaneous preterm birth risk and if a threshold concentration could be identified. Data from the Obstetric-Fetal Pharmacology Research Units study were used to determine the half-life of 17-hydroxyprogesterone caproate and to develop a model to simulate drug concentrations with various dosing regimens. Data from the Obstetrical-Fetal Pharmacology Research Centers study were used to determine the relationship between dose and safety outcomes. ResultsAnalysis of the Omega 3 dataset indicated that the risk of spontaneous preterm birth decreased as the log of 17-hydroxyprogesterone caproate increased [odds ratio (95%CI) 0.04 (0.00 - 0.90)]. A steady state concentration> 9 ng/ml (equivalent to > 8 ng/ml at 25-28 weeks) was associated with the lowest risk of spontaneous preterm birth [hazard ratio (95%CI) 0.52 (0.27-0.98, p=0.04)]; this concentration was not achieved in 25% of subjects receiving the 250 mg weekly dose. In the Obstetrical-Fetal Pharmacology Research Units study, the adjusted half-life (median and IQR) of 17-hydroxyprogesterone caproate was 14.0 (11.5-17.2) days. Simulations indicated that with the 250 mg weekly dose, > 5 weekly injections were required to reach the 9 ng/ml target; however, those with the shortest half-life (corresponding to higher clearance), never reached the targeted 9 ng/ml concentration. In 75% of subjects, a loading dose of 500 mg weekly for 2 weeks followed by 250 mg weekly achieved and maintained the 9 ng/ml concentration within two weeks but in those 25% with the shortest half-life, concentrations exceeded the 9 ng/ml target for only 3 weeks. In the Obstetrical-Fetal Pharmacology Research Centers study, all 65 subjects receiving a weekly dose of 500 mg exceeded the 9 ng/ml steady state. ConclusionsThe dosing regimen for 17-hydoxyprogesterone caproate was inadequate. There is a significant inverse relationship between drug concentration and spontaneous preterm birth. Risk is lowest when concentration exceeds 9 ng/ml but 25% of women receiving the 250 mg weekly dose will never reach and maintain this concentration. The drug’s long half-life necessitates a loading dose to achieve therapeutic concentrations rapidly. The omission of basic pharmacologic studies to determine the proper dosing may have compromised the effectiveness of 17-hydroxyprogesterone caproate. Future pharmacotherapy trials in pregnancy must first complete fundamental pharmacology studies.

Multi-institutional study of osimertinib dose-optimization in non-small cell lung cancer patients with EGFR activating mutation aged 70years or older ('MONEY' trial).

Osimertinib is the standard of care for patients with epidermal growth factor receptor-activating mutation-positive non-small cell lung cancer. Dose-toxicity has been previously reported, but no dose-response data within the range of 20-240mg daily (mg/d). Thus, the current 80mg/d dosing might be too high for elderly Japanese patients with an average body weight of only 50kg, resulting in excessive toxicity and cost. We therefore initiated a study to investigate whether osimertinib at 40mg/d is non-inferior to 80mg/d in patients with advanced or recurrent epidermal growth factor receptor-activating mutation-positive non-small cell lung cancer aged ≥70years, using a regression discontinuity design. Osimertinib is administered at 40mg/d for body weight ≤50kg, and 80mg/d for body weight >50kg. The primary endpoint is progression-free survival. Sample size is 550 patients, based on a non-inferiority margin of the progression-free survival hazard ratio 1.333, 0.10 one-sided type I error and 80% power.

Abstract 1670: Mechanistic insight into mTOR signaling identifies RNA splicing machinery as a potential therapeutic target for cancer

Abstract Aberrant signal transduction regulating cell growth and proliferation is a hallmark of many cancers. Activation of mTOR signaling is common and is an attractive therapeutic target with mechanistically different mTOR inhibitors in clinical use. One consequence of exposure to the mTOR inhibitor rapamycin is an alteration of gene expression through a global increase in alternative exon inclusion (Cheng et al. 2022, doi.org/10.3390/ijms232012416). To examine the mechanisms underlying this effect, we utilized the TempO-Seq targeted sequencing platform to profile both the whole transcriptome and a selection of alternatively spliced RNA targets in the rapamycin sensitive and resistant breast cancer cell lines MCF-7 and MDA MB 231 following exposure to 13 mTOR inhibitors, some closely related and some from distinct chemical classes. Recent publications have demonstrated that high quality dose response data can be obtained using this sequencing platform (Harrill et al. 2021, doi: 10.1093/toxsci/kfab009; Ramaiahgari et al. 2019, doi: 10.1093/toxsci/kfz065) and TempO-Seq has been widely adopted in toxicology for deriving compound-specific expression signatures to identify mechanisms of action and long-term toxicity. Treated cells were also profiled using TempO-LINC, a novel high-throughput single-cell assay based on the same platform. We observed that certain mTOR inhibitors induced both common and cell-specific differential expression as well as widespread alternative exon inclusion, as expected. Intriguingly, transcripts with the most significant changes in splicing upon treatment were those encoding members of the SR family of splicing factors, often overexpressed or amplified in breast cancers (Park, et al. 2019, doi: 10.1016/j.celrep.2019.10.110). This is significant because SR protein expression is autoregulated by alternative inclusion of an exon containing a premature stop codon in a feedback loop leading to nonsense-mediated decay (NMD) and lowered protein levels. Indeed, NMD is known to be inhibited by rapamycin (Martinez-Nunez, et al. 2017, doi: 10.1093/nar/gkw1109), which would lead to the observed accumulation of these transcripts. Thus, monitoring a targeted selection of alternative splicing events and regulators revealed mTOR regulation of mRNA isoform abundance consistent with regulation of the NMD RNA turnover process and with overexpression of SR proteins in breast cancers. Importantly, targeted bulk and single-cell TempO-Seq assays enable efficient sequencing and simplified data analysis without the expense and bioinformatic burden of RNAseq, making them particularly well-suited for drug discovery. These results support the use of this approach for further characterization of cell-specific effects of mTOR inhibitors and their mechanisms of action. Citation Format: Gaelle Rondeau, Megan Opichka, Kevin White, Joanne M. Yeakley, Dennis J. Eastburn, Bruce Seligmann. Mechanistic insight into mTOR signaling identifies RNA splicing machinery as a potential therapeutic target for cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1670.

Predicting the in vivo developmental toxicity of fenarimol from in vitro toxicity data using PBTK modelling-facilitated reverse dosimetry approach

In vitro methods are widely used in modern toxicological testing; however, the data cannot be directly employed for risk assessment. In vivo toxicity of chemicals can be predicted from in vitro data using physiologically based toxicokinetic (PBTK) modelling-facilitated reverse dosimetry (PBTK-RD). In this study, a minimal-PBTK model was constructed to predict the in-vivo kinetic profile of fenarimol (FNL) in rats and humans. The model was verified by comparing the observed and predicted pharmacokinetics of FNL for rats (calibrator) and further applied to humans. Using the PBTK-RD approach, the reported in vitro developmental toxicity data for FNL was translated to in vivo dose-response data to predict the assay equivalent oral dose in rats and humans. The predicted assay equivalent rat oral dose (36.46 mg/kg) was comparable to the literature reported in vivo BMD10 value (22.8 mg/kg). The model was also employed to derive the chemical-specific adjustment factor (CSAF) for interspecies toxicokinetics variability of FNL. Further, Monte Carlo simulations were performed to predict the population variability in the plasma concentration of FNL and to derive CSAF for intersubject human kinetic differences. The comparison of CSAF values for interspecies and intersubject toxicokinetic variability with their respective default values revealed that the applied uncertainty factors were adequately protective.