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Murine tumors are indispensable model systems in preclinical immuno-oncology research. While immunologic heterogeneity is well-known to be an important factor that can influence treatment outcome, there is a severe paucity of data concerning the nature of this heterogeneity in murine tumor models. Using serial sectioning methodology combined with IHC analysis and whole-slide image analysis, the depth-dependent variation in immune-cell abundance in tumor specimens was investigated at single-cell resolution. Specifically, intra- and intertumor variability in cell density of nine immune-cell biomarkers was quantified in multiple murine tumor models. The analysis showed that intertumor variability was typically the dominant source of variation in measurements of immune-cell densities. Statistical power analysis revealed the effect of group size and variance in immune-cell density on the predictive power of detecting a statistically meaningful fold-change in immune-cell density. Intertumor variability in the ratio of immune-cell densities showed distinct patterns in select tumor models and revealed the existence of strong correlations between select biomarker pairs. Furthermore, the relative proportion of immune cells at different depths across tumor samples was preserved in some but not all tumor models, thereby revealing the existence of compositional heterogeneity. Taken together, these results reveal novel insights into the nature of immunologic heterogeneity, which is not accessible through typical omics approaches.

Nonclinical immunotoxicity evaluation is an important component of safety assessment for pharmaceuticals. One in vitro assay that can be applied in a weight of evidence assessment is the human lymphocyte activation (HuLA) assay, an antigen recall assay, similar in many respects to the in vivo T-cell-dependent antibody response (TDAR) in that cooperation of multiple immune cell types are needed to produce responses. This assay uses human cells and is more amenable than the TDAR to compound ranking and mechanistic studies. The HuLA assay requires less time and drug than TDAR assays, uses a relevant antigen (influenza), reflects a human immune response, and applies principles of the 3Rs to non-clinical safety assessment. Peripheral blood mononuclear cells (PBMC) from flu-immunized donors are re-stimulated with flu-vaccine in the presence of test articles, and proliferation is measured. Published data demonstrate the applicability of the HuLA assay, but it has not been evaluated for reproducibility across testing sites. To evaluate assay reproducibility, scientists from a consortium of institutions conducted the assay in parallel, using a common pool of donor PBMC, influenza vaccine, and known immunosuppressant compounds (cyclosporine A and mycophenolic acid). The HuLA assay was highly reproducible in identification of inhibition of antigen-specific responses, and there was significant agreement across testing sites in the half maximal inhibitory concentration (IC50) values. Intra-site variability was the largest contributor to the variability observed within the assay. The HuLA assay was demonstrated to be ideally suited to comparing multiple compounds (i.e. compound ranking or benchmarking) within the same assay. Overall, the data reported herein support the HuLA assay as a useful tool in mechanistic evaluations of antigen-specific immune responses.

Clinical pathology and body weight information for the cynomolgus monkey in the literature is primarily derived from a small number of animals with limited age ranges, varying geographic origins, and mixed genders.This study aimed to summarize the age- and sex-related changes in clinical pathology analytes and body weights in cynomolgus monkeys of Mauritian origin.Pre-study age and body weight data were reviewed in 1819 animals, and pre-study hematologic, coagulation, and serum biochemical analytes were reviewed in 1664 animals.Body weights were statistically higher (P 0.01) in males than females in all age groups (2-10 years). These measurements became prominent after 4 years of age and peaked at 7 to 8 years of age in both sexes. Sex-related differences were noted in reticulocyte (RETIC) counts, creatinine, cholesterol, and triglyceride concentrations, and alkaline phosphatase (ALP) and gamma-glutamyl transferase (GGT) activities. Age-related differences were noted in RETIC and lymphocyte counts, creatinine, triglyceride, phosphorus, and globulin concentrations, and ALP and GGT activities. The youngest (2 to3 year) age group had the fewest number of clinical pathologic analyte differences including ALP and GGT activity differences which occurred in all age groups from 2 to 10 years; they also had age-related lower globulin concentrations. There were no age- or sex-related differences in coagulation measurands.Sexual dimorphism in body weight was apparent for all ages from 2 to 10 years of age. The only difference in clinical pathology analytes unique to the 2 to3 years of age group were age-related lower globulin levels.

Human induced pluripotent stem cell derived cardiomyocytes (hIPSC-CM's) play an increasingly important role in the safety profiling of candidate drugs. For such models to have utility a clear understanding of clinical translation is required. In the present study we examined the ability of our hIPSC-CM model to predict the clinically observed effects of a diverse set of compounds on several electrocardiogram endpoints, including changes in QT and QRS intervals. To achieve this, compounds were profiled in a novel high throughput voltage-sensitive dye platform. Measurements were taken acutely (30 min) and chronically (24 h) to ensure that responses from compounds with slow onset kinetics or that affected surface ion channel expression would be captured. In addition, to avoid issues associated with changes in free drug levels due to protein binding, assays were run in serum free conditions. Changes in hIPSC-CM threshold APD90 values correlated with compound plasma exposures that produced a +10 ms change in clinical QTc (Pearson r2 = 0.80). In addition, randomForest modeling showed high predictivity in defining TdP risk (AUROC value = 0.938). Risk associated with QRS prolongation correlated with an increase in action potential rise-time (AUROC value = 0.982). The in-depth understanding of the clinical translatability of our hIPSC-CM model positions this assay to play a key role in defining cardiac risk early in drug development. Moreover, the ability to perform longer term studies enables the detection of compounds that may not be highlighted by more acute assay formats, such as inhibitors of hERG trafficking.

Cardiovascular (CV) safety-related attrition is an important contributor to the loss of promising drug candidates during development. CV safety pharmacology studies are conducted to identify these safety effects. Understanding translation of CV endpoints (specifically, heart rate [HR], and blood pressure [BP]) across preclinical animal models and to the clinic is critical in developing a robust CV derisking strategy. To this end, we investigated translation of HR and BP endpoints using data from 83 compounds that were tested in telemetry studies in rat and large animal (LA; dog or monkey) and 79 compounds that were tested in LA telemetry studies and human phase I clinical trials. Sensitivity, specificity as well as predictive values were calculated for rat to LA model comparison and for LA to human studies comparison. The rat CV model showed good concordance (sensitivity = 84% and specificity = 71%) for LA BP and HR changes. Similarly, LA CV measures of HR and BP showed good concordance (sensitivity = 78% and specificity = 79%) to clinical changes. The CV effects generally occurred within 0.3-3× free plasma concentration across species. Directionality of BP and HR change was conserved between LA to humans. However, for rat to LA comparisons the directionality of change was opposite for 23%-26% compounds. In conclusion, these data establish the translation of HR and BP from preclinical to clinical studies and emphasize the importance of preclinical animal models in the examination of CV safety of drugs.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Evidence suggests that bio-activation of drugs to generate chemically reactive metabolites (RM) that act as haptens to form immunogenic protein conjugates may be an important cause of immune-mediated drug hypersensitivity reactions (IDHR). Although many drugs that form RMs raise concerns about producing IDHR, standard non-clinical testing methods are rarely able to identify compounds with the potential to produce IDHR in humans. The objective of this study was to develop a predictive assay for IDHR that involves: (1) the use of an in vitro drug-metabolizing system to generate the RM that is captured by GSH, (2) conjugating the RM-GSH conjugate to mouse serum albumin (MSA) by using a chemical cross-linker, (3) immunization of mice with RM-GSH-MSA adducts, and (4) ex vivo challenge with RM-GSH-MSA adduct and measurement of lymphocyte proliferation to determine if the RM is immunogenic. The predictivity of the assay was evaluated by using drugs that produce RM and have been strongly, weakly, or not associated with IDHRs in the clinic. While this method requires additional validation with more drugs, the results demonstrate the feasibility of identifying drugs strongly associated with IDHR and the utility of the assay for rank ordering drugs with respect to their potential to cause IDHR.

Cardiovascular (CV) toxicity and related attrition are a major challenge for novel therapeutic entities and identifying CV liability early is critical for effective derisking. CV safety pharmacology studies in rats are a valuable tool for early investigation of CV risk. Thorough understanding of data analysis techniques and statistical power of these studies is currently lacking and is imperative for enabling sound decision-making. Methods Data from 24 crossover and 12 parallel design CV telemetry rat studies were used for statistical power calculations. Average values of telemetry parameters (heart rate, blood pressure, body temperature, and activity) were logged every 60 s (from 1 h predose to 24 h post-dose) and reduced to 15 min mean values. These data were subsequently binned into super intervals for statistical analysis. A repeated measure analysis of variance was used for statistical analysis of crossover studies and a repeated measure analysis of covariance was used for parallel studies. Statistical power analysis was performed to generate power curves and establish relationships between detectable CV (blood pressure and heart rate) changes and statistical power. Additionally, data from a crossover CV study with phentolamine at 4, 20 and 100 mg/kg are reported as a representative example of data analysis methods. Results Phentolamine produced a CV profile characteristic of alpha adrenergic receptor antagonism, evidenced by a dose-dependent decrease in blood pressure and reflex tachycardia. Detectable blood pressure changes at 80% statistical power for crossover studies (n = 8) were 4–5 mm Hg. For parallel studies (n = 8), detectable changes at 80% power were 6–7 mm Hg. Detectable heart rate changes for both study designs were 20–22 bpm. Discussion Based on our results, the conscious rat CV model is a sensitive tool to detect and mitigate CV risk in early safety studies. Furthermore, these results will enable informed selection of appropriate models and study design for early stage CV studies.

This chapter provides a survey of key nonclinical safety assays. For each study type, we discuss the typical study designs employed, including a summary of the type of endpoints collected. We then provide an overview of common statistical approaches in each setting. There are some general themes that are common across the study types (e.g., trend testing). At the same time, the different study types may have features that require special consideration (e.g., cross-over designs for safety pharmacology studies, intra-litter correlation in reproductive toxicology studies). While some of the design aspects of these studies are to some extent “fixed” by precedent across the industry, we do address sample size and power considerations, as this information can be valuable to understanding how statistical results can contribute to the overall interpretation of these studies. Finally, for any discussion of statistical approaches, there are likely to be multiple reasonable approaches. We’ve attempted to cover some of the more common approaches in detail, but we recognize that our treatment is not exhaustive. Where possible, we have provided references for further reading.

To assess the potential of individual bile acids (IBA) and their profiles as mechanistic biomarkers of liver injury for humans in real world situations, we interrogated samples collected under minimum controlled conditions (ie subjects were not fasted). Total bile acids (TBA) have been considered to be biomarkers of liver injury for decades, and more recently, monitoring of IBA has been proposed for differentiation of variety of etiologies of liver injury. We established a LC-MS/MS methodology to analyze nine IBA, generated reference ranges, and examined effects of age, gender, and ethnicity for each IBA. Furthermore, we evaluated the ability of IBA and their profiles to detect hepatic injury in subjects with a broad range of liver impairments. To date, our study utilized the largest total cohort of samples (N = 645) that were divided into 2 groups, healthy or liver impaired, to evaluate IBA as biomarkers. The TBA serum levels in the Asian ethnic group trended higher when compared to other ethnic groups, and the serum concentrations of IBA, such as glycocholic acid (GCA), glycochenodeoxycholic acid (GCDCA), chenodeoxycholic acid (CDCA), and taurochenoxycholic acid (TCDCA) were significantly increased. To our knowledge, this report is the first to describe ethnic differences in serum concentrations of IBAs. In patients with hepatic impairments, with the exception of deoxycholic acid (DCA), the concentrations of IBAs were significantly elevated when compared with healthy subjects. The conjugated bile acids displayed greater differences between healthy subjects and subjects with hepatic impairments than non-conjugated bile acids. Furthermore, the subjects with hepatic impairments exhibited distinct profiles (signatures) of IBAs that clustered subjects according the nature of their liver impairments. Although additional studies are needed, our data suggested that the analysis of IBA has the potential to become useful for differentiation of various forms of liver injury.

Purpose It has recently been shown that differences between the marginal predictability associated with scalp electrodes adjacent to and remote from the site of a seizure focus are able to distinguish between epochs temporally distant from and just prior to (within about 20 min) the onset of a seizure in patients with temporal lobe epilepsy. The purpose of this paper is to show that these differences of marginal predictability intervals are independent of the state of consciousness of the patient. Methods We have studied a data set encompassing 33 preictal epochs (within 1 h prior to a seizure) and 61 interictal epochs (defined as at least 1 h away from any seizure) from 14 patients. Each 30 s interval of each epoch was categorized into one of seven different states of consciousness. Statistical models were used to search for relationships (in aggregated data) between the values of differences of marginal predictabilities and state of consciousness. Results It was not possible to reject the null hypothesis of no relationship between differences of marginal predictabilities and state of consciousness. Conclusions The values of the differences between marginal predictabilities on aggregated data are apparently insensitive to the state of consciousness. This conclusion, coupled with the fact that the differences between marginal predictabilities do depend on time to seizure, suggests the potential utility of these measures as the basis for ambulatory, non-invasive methods of seizure anticipation. However, the development of a practical non-invasive method for seizure anticipation requires further extensive study on disaggregated data from individual patients.

In this paper we discuss an approach, using methods of non-linear time series analysis applied to scalp electrode recordings, which is able to distinguish between epochs temporally distant from and just prior to, the onset of a seizure in patients with temporal lobe epilepsy. The method involves a comparison of recordings taken from electrodes adjacent to and remote from the site of ictal onset. In particular, we define a non-linear quantity which we call 'marginal predictability'. This quantity is computed using data from remote and from adjacent electrodes. We find that the difference between the marginal predictabilities computed for the remote and adjacent electrodes decreases several tens of minutes prior to seizure onset, compared to its value interictally.

The Organization for Economic Co-operation and Development (OECD) has recently adopted Test Guideline 487 (TG487) for conducting the in vitro micronucleus (MNvit) assay. The purpose of this study is to evaluate and validate treatment conditions for the use of p53 competent TK6 human lymphoblastoid cells in a TG487 compliant MNvit assay. The ten reference compounds suggested in TG487 (mitomycin C, cytosine arabinoside, cyclophosphamide, benzo-a-pyrene, vinblastine sulphate, colchicine, sodium chloride, nalidixic acid and di(2-ethylhexyl)phthalate and pyrene) and noscapine hydrochloride were chosen for this study. In order to optimize the micronucleus response after treatment with some positive substances, we extended the recovery time after pulse treatment from 2 cell cycles recommended in TG487 to 3 cell cycles for untreated cells (40h). Each compound was tested in at least one of four exposure conditions: a 4h exposure followed by a 40h recovery, a 4h exposure followed by a 24h recovery, a 4h exposure in the presence of an exogenous metabolic activation system followed by a 40h recovery period, and a 27h continuous direct treatment. Results show that the direct acting clastogens, clastogens requiring metabolic activation and aneugens caused a robust increase in micronuclei in at least one test condition whereas the negative compounds did not induce micronuclei. The negative control cultures exhibited reproducibly low and consistent micronucleus frequencies ranging from 0.4 to 1.8% (0.8±0.3% average and standard deviation). Furthermore, extending the recovery period from 24h to 40h produced a 2-fold higher micronucleus frequency after a 4h pulse treatment with mitomycin C. In summary, the protocol described in this study in TK6 cells produced the expected result with model compounds and should be suitable for performing the MNvit assay in accordance with guideline TG487.

Certain compounds that induce liver injury clinically are not readily identified from earlier preclinical studies. Novel biomarkers are being sought to be applied across the pharmaceutical pipeline to fill this knowledge gap and to add increased specificity for detecting drug-induced liver injury in combination with aminotransferases (alanine and aspartate aminotransferase) – the current reference-standard biomarkers used in the clinic. The gaps in the qualification process for novel biomarkers of regulatory decision-making are assessed and compared with aminotransferase activities to guide the determination of safe compound margins for drug delivery to humans where monitoring for potential liver injury is a cause for concern. Histopathologic observations from preclinical studies are considered the principal reference standard to benchmark and assess subtle aminotransferase elevations. This approach correlates quite well for many developmental compounds, yet cases of discordance create dilemmas regarding which standard(s) indicates true injury. Concordance amongst a broader set of biomarker injury signals in a qualification paradigm will increase confidence, leading to accepted and integrated translational biomarker signals during safety assessment processes across the pharmaceutical industry, with academia, in government and in contractor laboratories.

Introduction Adrenergic blockade as a treatment for chronic heart failure (CHF) has proved effective, but its pharmacological mechanism on CHF remains unclear. In the past two decades, studies on heart rate variability (HRV) have reported that CHF patients generally have a reduced temporal complexity in heart rate variability. On the other hand, adrenergic blockers have been shown to restore such complexity. Fractal analysis is a novel and efficient tool to explore the adrenergic blockade effect on HRV. This paper applies the detrended fluctuation analysis (DFA) and multifractal DFA (MF-DFA) methods in an attempt to understand the effect of adrenergic blockade on cardiac dynamics in conscious beagle dogs. Methods DFA and MF-DFA analysis are conducted on RR interval data generated from telemetry instrumented dogs receiving a combination of 15 mg/kg nadolol and 5 mg/kg phenoxybenzamine orally administered at the 22nd and 34th hour in a parallel design ( n = 12). All dogs had approximately 48 h of beat-to-beat heart rate measurements recorded in the left ventricle. Complexity measures for heartbeat series are compared between the blocker and vehicle group. We also compute traditional statistics for HRV and spectral parameters and examine their correlation with fractal analysis. Results When compared to the vehicle group, the adrenergic blocker group had: 1) longer RR intervals ( p = 0.02) and lower beat-to-beat variability ( p = 0.04); 2) decreased low frequency (LF) and high frequency (HF) power ( p = 0.03), and higher LF-to-HF ratio; 3) larger middle-range scaling exponents ( p p = 0.03) with higher dominant singularity indices ( p = 0.02). Discussion Our results show that 1) adrenergic blockade alters the sympathovagal balance; 2) adrenergic blockers enhance the complexity of the cardiac dynamics; 3) the adrenergic blockade effect on cardiac dynamics is primarily the attenuation of small fluctuations in RR intervals. Fractal analysis also has the potential to be applied to early QT diagnosis.

In a recent paper, we showed that the value of a nonlinear quantity computed from scalp electrode data was correlated with the time to a seizure in patients with temporal lobe epilepsy. In this paper we study the relationship between the linear and nonlinear content and analyses of the scalp data. We do this in two ways. First, using surrogate data methods, we show that there is important nonlinear structure in the scalp electrode data to which our methods are sensitive. Second, we study the behavior of some simple linear metrics on the same set of scalp data to see whether the nonlinear metrics contain additional information not carried by the linear measures. We find that, while the nonlinear measures are correlated with time to seizure, the linear measures are not, over the time scales we have defined. The linear and nonlinear measures are themselves apparently linearly correlated, but that correlation can be ascribed to the influence of a small set of outliers, associated with muscle artifact. A remaining, more subtle relation between the variance of the values of a nonlinear measure and the expectation value of a linear measure persists. Implications of our observations are discussed.

Using a measure of nonlinear dynamical changes we term marginal predictability, we report evidence of robust changes in this parameter on scalp EEG in a cohort of patients with medically refractory mesiobasal temporal lobe epilepsy (MBTLE). In the baseline (interictal) state there are distinct differences in this nonlinear measure between epileptic and neurologically normal subjects. At baseline, in patients with MBTLE there are differences in these measures between electrodes adjacent to the ictal onset zone and more remotely placed electrodes. The character of these differences evolves over a period of approximately 30 min before a seizure. We discuss and integrate our findings with two emerging concepts in epileptology, first, the concept of a preictal or transition phase rather than an abrupt movement from interictal to ictal activity, and second, the notion of an epileptic neural network with changes in areas of brain remote from what has traditionally been considered the ictal onset zone influencing “ictogenesis.”

The authors review their work in applying nonlinear dynamics to predict onset of seizures in patients with medically refractory temporal lobe epilepsy. The underlying mathematical methodology is presented in some detail. To illustrate their approach, they present an extensive discussion of the analysis of preictal data from two seizures of one patient, and from one disease-free subject. They find similar behavior in some nonlinear measures across seizures, which suggests the possibility of forming a robust method of seizure prediction. However, despite clinical and electrographic preictal and ictal similarity, they have also found marked heterogeneity in other nonlinear measures of preictal activity across seizures arising out of stage 2 nonrapid eye movement sleep. The underlying basis for this variation remains uncertain and needs to be the subject of further intense study to gain a better understanding of the dynamic basis of epilepsy. The origin of these heterogeneities may or may not be related to the much larger differences in nonlinear measures between patients and disease-free subjects. To understand these differences, the authors think it is crucial to pay close attention to potentially confounding factors such as behavioral and other state changes, and to study and report in detail the ways in which relevant nonlinear measures behave in the presence of such changes, independent of seizure onset.

We present a comprehensive theoretical description of quantum well exciton-polaritons imbedded in a planar semiconductor microcavity. The exact non-local dielectric response of the quantum well exciton is treated in detail. The 4-spinor structure of the hole subband in the quantum well is considered, including the pronounced band mixing effect. The scheme is self-contained and can be used to treat different semiclassical aspects of the microcavity properties. As an example, we analyze the "selection" rules for the exciton-cavity mode coupling for different excitons., Comment: 30 pages,Latex, 2 figures, to be appreared in Interbational Journal of Modern Physics B

Herpesviruses such as cytomegalovirus (CMV) and Epstein Barr virus (EBV) often cause disease under conditions of immunosuppression, such as transplant or AIDS. Loss of control of herpesvirus infections occurs at least in part due to loss or dysfunction of virus-specific T cells. An increasing array of immunosuppressive therapeutics are being developed that target different subsets of T cells or their functions. To better understand effects of therapeutics on antiviral T cells, we have used ELISPOT and ICS to measure T cell responses against CMV and lymphcryptovirus (LCV; analogous to EBV) in cynomolgus macaques. Our work has shown that nearly all monkeys respond against both viruses, although the numbers of T cells specific for CMV are larger than those against LCV. We have also characterized the variability in the magnitude of the T responses to both viruses over time. In addition, we have examined the effects of immunosuppressive agents on the numbers and function of antiviral T cells. Our work reveals remarkable stability of herpesvirus-specific T cells, even under conditions where drugs abolish T cell stimulation for a period of several weeks.