Assessing goodness-of-fit for evaluation of dose-proportionality.

For the clinical development of a new drug, the determination of dose-proportionality is an essential part of the pharmacokinetic evaluations, which may provide early indications of non-linear pharmacokinetics and may help to identify sub-populations with divergent clearances. Prior to making any conclusions regarding dose-proportionality, the goodness-of-fit of the model must be assessed to evaluate the model performance. We propose the use of simulation-based visual predictive checks to improve the validity of dose-proportionality conclusions for complex designs. We provide an illustrative example and include a table to facilitate review by regulatory authorities.

The rat bone marrow micronucleus test: Statistical considerations on historical negative control data.

Recent updates of the OECD Guidelines for the Testing of Chemicals (Section 4: Health Effects) on genotoxicity testing emphasize the use of appropriate statistical methods for data analysis and proficiency proof. Updates also concern the mammalian erythrocyte micronucleus test (OECD 474), as the currently most often performed regulatory in vivo test. As the updated guideline gives high importance to adequate statistical assessment of historical negative control data to estimate validity of experiments and judge results, the present study evaluated statistical methodologies for handling of historical negative control data sets, and comes forward with respective proposals and reference data. Therefore, the working group "Statistics" within the German-speaking "Gesellschaft für Umwelt-Mutationsforschung e.V." (GUM) compiled a data set of 891 negative control rats from valid OECD 474-studies of four laboratories. Based on these data, Analysis-of-Variance (ANOVA) identified "laboratory" and "strain", but not "gender" as relevant stratification parameters, and argued for approximately normally distributed micronucleus frequencies in polychromatic erythrocytes per animal. This assumption provided the basis for further specifying one-sided parametric tolerance intervals for determination of corresponding upper historical negative control limits. Finally, the stability of such limits was investigated as a function of the number of experiments performed, using a simulation-based statistical strategy.

Model selection based on combined penalties for biomarker identification.

The growing role of targeted medicine has led to an increased focus on the development of actionable biomarkers. Current penalized selection methods that are used to identify biomarker panels for classification in high-dimensional data, however, often result in highly complex panels that need careful pruning for practical use. In the framework of regularization methods, a penalty that is a weighted sum of the L1 and L0 norm has been proposed to account for the complexity of the resulting model. In practice, the limitation of this penalty is that the objective function is non-convex, non-smooth, the optimization is computationally intensive and the application to high-dimensional settings is challenging. In this paper, we propose a stepwise forward variable selection method which combines the L0 with L1 or L2 norms. The penalized likelihood criterion that is used in the stepwise selection procedure results in more parsimonious models, keeping only the most relevant features. Simulation results and a real application show that our approach exhibits a comparable performance with common selection methods with respect to the prediction performance while minimizing the number of variables in the selected model resulting in a more parsimonious model as desired.

Redefining the role of biomarkers in heart failure trials: expert consensus document.

Heart failure is a growing cardiovascular disease with significant epidemiological, clinical, and societal implications and represents a high unmet need. Strong efforts are currently underway by academic and industrial researchers to develop novel treatments for heart failure. Biomarkers play an important role in patient selection and monitoring in drug trials and in clinical management. The present review gives an overview of the role of available molecular, imaging, and device-derived digital biomarkers in heart failure drug development and highlights capabilities and limitations of biomarker use in this context.

AKT1 (E17K) mutation profiling in breast cancer: prevalence, concurrent oncogenic alterations, and blood-based detection.

BACKGROUND: The single hotspot mutation AKT1 [G49A:E17K] has been described in several cancers, with the highest incidence observed in breast cancer. However, its precise role in disease etiology remains unknown. METHODS: We analyzed more than 600 breast cancer tumor samples and circulating tumor DNA for AKT1 (E17K) and alterations in other cancer-associated genes using Beads, Emulsions, Amplification, and Magnetics digital polymerase chain reaction technology and targeted exome sequencing. RESULTS: Overall AKT1 (E17K) mutation prevalence was 6.3 % and not correlated with age or menopausal stage. AKT1 (E17K) mutation frequency tended to be lower in patients with grade 3 disease (1.9 %) compared with those with grade 1 (11.1 %) or grade 2 (6 %) disease. In two cohorts of patients with advanced metastatic disease, 98.0 % (n = 50) and 97.1 % (n = 35) concordance was obtained between tissue and blood samples for the AKT1 (E17K) mutation, and mutation capture rates of 66.7 % (2/3) and 85.7 % (6/7) in blood versus tissue samples were observed. Although AKT1-mutant tumor specimens were often found to harbor concurrent alterations in other driver genes, a subset of specimens harboring AKT1 (E17K) as the only known driver alteration was also identified. Initial follow-up survival data suggest that AKT1 (E17K) could be associated with increased mortality. These findings warrant additional long-term follow-up. CONCLUSIONS: The data suggest that AKT1 (E17K) is the most likely disease driver in certain breast cancer patients. Blood-based mutation detection is achievable in advanced-stage disease. These findings underpin the need for a further enhanced-precision medicine paradigm in the treatment of breast cancer.

Histology independent drug development - Is this the future for cancer drugs?

The Cancer Drug Development Forum (CDDF)'s 'Histology independent drug development - is this the future for cancer drugs?' workshop was set up to explore the current landscape of histology independent drug development, review the current regulatory landscape and propose recommendations for improving the conduct of future trials. The first session considered lessons learnt from previous trials, including innovative solutions for reimbursement. The session explored why overall survival represents the most valuable endpoint, and the importance of duration of response, which can be captured with swimmer and spider plots. The second session on biomarker development and treatment optimisation considered current regulations for companion diagnostics, FDA guidance on histology independent drug development in oncology, and the need to establish cut-offs for the biomarker of tumour mutational burden to identify the patients most likely to benefit from PDL1 treatment. The third session reviewed novel trial designs, including basket, umbrella and platform trials, and statistical approaches of hierarchical modelling where homogeneity between study cohorts enables information to be borrowed between cohorts. The discussion highlighted the need to agree 'common assessment standards' to facilitate pooling of data across studies. In the fourth session, the sharing of data sets was recognised as a key step for improving equity of access to precision medicines across Europe. The session considered how the European Health Data Space (EHDS) could streamline access to medical records, emphasizing the importance of introducing greater accountability into the digital space. In conclusion the workshop proposed 11 recommendations to facilitate histology agnostic drug development.

A dynamic model of circadian rhythms in rodent tail skin temperature for comparison of drug effects.

Menopause-associated thermoregulatory dysfunction can lead to symptoms such as hot flushes severely impairing quality of life of affected women. Treatment effects are often assessed by the ovariectomized rat model providing time series of tail skin temperature measurements in which circadian rhythms are a fundamental ingredient. In this work, a new statistical strategy is presented for analyzing such stochastic-dynamic data with the aim of detecting successful drugs in hot flush treatment. The circadian component is represented by a nonlinear dynamical system which is defined by the van der Pol equation and provides well-interpretable model parameters. Results regarding the statistical evaluation of these parameters are presented.

Shortened treatment duration of glucocorticoid-induced skin atrophy in rats.

Glucocorticoids (GCs) belong to the most widely used anti-inflammatory drugs at all. However, their topical use is limited by their side effect potential, with skin atrophy being the most prominent one. Thus, determining the atrophogenic potential of novel compounds is of importance for drug development. Currently, the most frequently performed model in the base and pharmaceutical research is the hr/hr rat model of GC-induced skin atrophy that lasts for 19 days. In this study, we analysed statistically skin atrophy experiments retrospectively to ascertain (i) the earliest time-point, at which skin atrophy is significantly induced; and (ii) whether the differences between the GC treatment groups change until the end of the experiment. We show here that the treatment duration of rat skin atrophy models might be reduced to 5 days for economical and ethical reasons.

Recommendations on the statistical analysis of the Comet assay.

In 2010, the Statisticians in the Pharmaceutical Industry (PSI) Toxicology Special Interest Group met to discuss the design and analysis of the Comet assay. The Comet assay is one potential component of the package of safety studies required by regulatory bodies. As these studies usually involve a three-way nested experimental design and as the distribution of the measured response is usually either lognormal or lognormal plus a point mass at zero, the analysis is not straightforward. This has led to many different types of analysis being proposed in the literature, with several different methods applied within the pharmaceutical industry itself. This article summarises the PSI Toxicology Group's discussions and recommendations around these issues.

Effects of synthetic gestagens on fish reproduction.

Although it is well known that estrogenic steroidal hormones are able to affect the sexual development and reproduction of fish at low concentrations, no data on environmental effects of the class of progestogenic hormones are available yet. Synthetic gestagens (progestins) are a component in oral contraceptives. Upon their use, a fraction of the progestins will be excreted via urine into the aquatic environment. On the basis of their pharmacological action in mammals, it is supposed that fish reproduction is the most sensitive endpoint for the progestin treatment. In order to test this assumption, the effects of two progestins currently marketed in contraceptive formulations, levonorgestrel (LNG) and drospirenone (DRSP), were investigated in adult fathead minnows (Pimephales promelas) following an Organization for Economic Cooperation and Development 21-d fish reproduction screening assay draft protocol with additional end points. Levonorgestrel was tested at measured concentrations of 0.8, 3.3, and 29.6 ng/L, and DRSP at concentrations of 0.66, 6.5, and 70 microg/L. Both tested progestins caused an inhibition of reproduction. For LNG, this occurred at concentrations of >or=0.8 ng/L, no no-observed-effect concentration (NOEC) could be defined. Higher concentrations resulted in masculinization of females with de novo synthesis of nuptial tubercles. Drospirenone treatment, however, affected the reproductive success of fathead minnow at concentrations of 6.5 microg/L and higher with a clear dose-response relationship and a NOEC of 0.66 microg/L, which is above environmentally relevant concentrations.

A Bayesian model to estimate the cutoff and the clinical utility of a biomarker assay.

To enable targeted therapies and enhance medical decision-making, biomarkers are increasingly used as screening and diagnostic tests. When using quantitative biomarkers for classification purposes, this often implies that an appropriate cutoff for the biomarker has to be determined and its clinical utility must be assessed. In the context of drug development, it is of interest how the probability of response changes with increasing values of the biomarker. Unlike sensitivity and specificity, predictive values are functions of the accuracy of the test, depend on the prevalence of the disease and therefore are a useful tool in this setting. In this paper, we propose a Bayesian method to not only estimate the cutoff value using the negative and positive predictive values, but also estimate the uncertainty around this estimate. Using Bayesian inference allows us to incorporate prior information, and obtain posterior estimates and credible intervals for the cut-off and associated predictive values. The performance of the Bayesian approach is compared with alternative methods via simulation studies of bias, interval coverage and width and illustrations on real data with binary and time-to-event outcomes are provided.

Comparative analysis of the uterine and mammary gland effects of drospirenone and medroxyprogesterone acetate.

The role of progestins in combined hormone therapy is the inhibition of uterine epithelial cell proliferation. The Women's Health Initiative study provided evidence for an increased risk of breast cancer in women treated with conjugated equine estrogens plus the synthetic progestin medroxyprogesterone acetate (MPA), compared with conjugated equine estrogens-only treatment. These findings continue to be discussed, and it remains to be clarified whether the results obtained for MPA in the Women's Health Initiative study are directly applicable to other progestins used in hormone therapy. In this study we compared in a mouse model the effects of the synthetic progestins, MPA, and drospirenone in two major target organs: the uterus and mammary gland. As quantitative measures of progestin activity, we analyzed maintenance of pregnancy, ductal side branching in the mammary gland, and proliferation of mammary and uterine epithelial cells as well as target gene induction in both organs. The outcome of this study is that not all synthetic progestins exhibit the same effects. MPA demonstrated uterine activity and mitogenic activity in the mammary gland at the same doses. In contrast, drospirenone behaved similarly to the natural hormone, progesterone, and exhibited uterine activity at doses lower than those leading to considerable proliferative effects in the mammary gland. We hypothesize that the safety of combined hormone therapy in postmenopausal women may be associated with a dissociation between the uterine and mammary gland activities of the progestin component.

In vivo characterization of estrogen receptor modulators with reduced genomic versus nongenomic activity in vitro.

Estrogen receptor (ER) ligands that are able to prevent postmenopausal bone loss, but have reduced activity in the uterus and the mammary gland might be of great value for hormone therapy. It is well established that the classical ER can activate genomic as well as nongenomic signal transduction pathways. In this study, we analyse the in vivo behaviour of ER ligands that stimulate nongenomic ER effects to the same extent as estradiol, but show clearly reduced activation of genomic ER effects in vitro. Using different readout parameters such as morphological changes, cellular proliferation, and target gene induction, we are able to demonstrate that ER ligands with reduced genomic activity in vitro show a better dissociation of bone versus uterine and mammary gland effects than estradiol that stimulates genomic and nongenomic effects to the same extent. We conclude that pathway-selective ER ligands may represent an interesting option for hormone therapy.

A statistical approach for analyzing data from the in vivo Pig-a gene mutation assay.

The in vivo Pig-a gene mutation assay serves to evaluate the genotoxic potential of chemicals. In the rat blood-based assay, the lack of CD59 on the surface of erythrocytes is quantified via fluorophore-labeled antibodies in conjunction with flow cytometric analysis to determine the frequency of Pig-a mutant phenotype cells. The assay has achieved regulatory relevance as it is suggested as an in vivo follow-up test for Ames mutagens in the recent ICH M7 [25] step 4 document. However, very little work exists regarding suitable statistical approaches for analyzing Pig-a data. In the current report, we present a statistical strategy based on a two factor model involving 'treatment' and 'time' incl. their interaction and a baseline covariate for log proportions to compare treatment and vehicle data per time point as well as in time. In doing so, multiple contrast tests allow us to discover time-related changes within and between treatment groups in addition to multiple treatment comparisons to a control group per single time point. We compare our proposed strategy with the results of classical Dunnett and Wilcoxon-Mann-Whitney tests using two data sets describing the mode of action of Chlorambucil and Glycidyl methacrylate both analyzed in a 28-day treatment schedule.

Increasing the efficiency of oncology basket trials using a Bayesian approach.

With the rapid growth of targeted and immune-oncology therapies, novel statistical design approaches are needed to increase the flexibility and efficiency of early phase oncology trials. Basket trials enroll patients with defined biological deficiencies, but with multiple histologic tumor types (or indications), to discover in which indications the drug is active. In such designs different indications are typically analyzed independently. This, however, ignores potential biological similarities among the indications. Our research provides a statistical methodology to enhance such basket trials by assessing the homogeneity of the response rates among indications at an interim analysis, and applying a Bayesian hierarchical modeling approach in the second stage if the efficacy is deemed reasonably homogenous across indications. This increases the power of the study by allowing indications with similar response rates to borrow information from each other. Via simulations, we quantify the efficiency gain of our proposed approach relative to the conventional parallel approach. The operating characteristics of our method depend on the similarity of the response rates between the different indications. If the response rates are comparable in most or all indications after treatment with the investigational drug, a substantial increase in efficiency as compared to the conventional approach can be obtained as fewer patients are required or a higher power is attained. We also demonstrate that efficacy again decreases if the response rates vary considerably among tumor types but it is still better than the conventional approach.

A Neutralizing Prolactin Receptor Antibody Whose In Vivo Application Mimics the Phenotype of Female Prolactin Receptor-Deficient Mice.

The prolactin receptor (PRLR) has been implicated in a variety of physiological processes (lactation, reproduction) and diseases (breast cancer, autoimmune diseases). Prolactin synthesis in the pituitary and extrapituitary sites is regulated by different promoters. Dopamine receptor agonists such as bromocriptine can only interfere with pituitary prolactin synthesis and thus do not induce a complete blockade of PRLR signaling. Here we describe the identification of a human monoclonal antibody 005-C04 that blocks PRLR-mediated signaling at nanomolar concentrations in vitro. In contrast to a negative control antibody, the neutralizing PRLR antibody 005-C04 inhibits signal transducer and activator of transcription 5 phosphorylation in T47D cells and proliferation of BaF3 cells stably expressing murine or human PRLRs in a dose-dependent manner. In vivo application of this new function-blocking PRLR antibody reflects the phenotype of PRLR-deficient mice. After antibody administration female mice become infertile in a reversible manner. In lactating dams, the antibody induces mammary gland involution and negatively interferes with lactation capacity as evidenced by reduced milk protein expression in mammary glands and impaired litter weight gain. Antibody-mediated blockade of the PRLR in vivo stimulates hair regrowth in female mice. Compared with peptide-derived PRLR antagonists, the PRLR antibody 005-C04 exhibits several advantages such as higher potency, noncompetitive inhibition of PRLR signaling, and a longer half-life, which allows its use as a tool compound also in long-term in vivo studies. Therefore, we suggest that this antibody will help to further our understanding of the role of auto- and paracrine PRLR signaling in health and disease.

Estradiol release kinetics determine tissue response in ovariectomized rats.

Estrogen replacement is an effective therapy of postmenopausal symptoms such as hot flushes, bone loss, and vaginal dryness. Undesired estrogen effects are the stimulation of uterine and mammary gland epithelial cell proliferation as well as hepatic estrogenicity. In this study, we examined the influence of different estradiol release kinetics on tissue responsivity in ovariectomized (OVX) rats. Pulsed release kinetics was achieved by ip or sc administration of estradiol dissolved in physiological saline containing 10% ethanol (EtOH/NaCl) whereas continuous release kinetics was achieved by sc injection of estradiol dissolved in benzylbenzoate/ricinus oil (1+4, vol/vol). Initial 3-d experiments in OVX rats showed that pulsed ip estradiol administration had profoundly reduced stimulatory effects on the uterus and the liver compared with continuous release kinetics. On the other hand, both administration forms prevented severe vaginal atrophy. Based on these results, we compared the effects of pulsed (sc in EtOH/NaCl) vs. continuous (sc in benzylbenzoate/ricinus oil) estradiol release kinetics on bone, uterus, mammary gland, and liver in a 4-month study in OVX rats. Ovariectomy-induced bone loss was prevented by both administration regimes. However, pulsed estradiol resulted in lower uterine weight, reduced induction of hepatic gene expression, and reduced mammary epithelial hyperplasia relative to continuous estradiol exposure. We conclude that organ responsivity is influenced by different hormone release kinetics, a fact that might be exploited to reduce undesired estradiol effects in postmenopausal women.

Impaired left-ventricular cardiac function in male GPR30-deficient mice.

G-protein-coupled receptor 30 (GPR30) has been reported to act as a membrane-bound estrogen receptor that is involved in the mediation of non-genomic estradiol signalling. In this study, we demonstrated that male, but not female, GPR30-deficient mice suffer from impaired left­ventricular cardiac function. Left ventricles from male mutant mice were enlarged. There were no malformations in the valves or outflow tract of the heart. Both the contractility and relaxation capacity of the left ventricle were reduced, leading to increased left­ventricular end-diastolic pressure in GPR30-deficient mice. In conclusion, our data support a role for GPR30 in the gender-specific aspects of heart failure.

Willingness to Donate Human Samples for Establishing a Dermatology Research Biobank: Results of a Survey.

There is a rising need for biomaterial in dermatological research with regard to both quality and quantity. Research biobanks as organized collections of biological material with associated personal and clinical data are of increasing importance. Besides technological/methodological and legal aspects, the willingness to donate samples by patients and healthy volunteers is a key success factor. To analyze the theoretical willingness to donate blood and skin samples, we developed and distributed a questionnaire. Six hundred nineteen questionnaires were returned and analyzed. The willingness to donate samples of blood (82.5%) and skin (58.7%) is high among the population analyzed and seems to be largely independent of any expense allowance. People working in the healthcare system, dermatological patients, and higher qualified individuals seem to be in particular willing to donate material. An adequate patient insurance as well as an extensive education about risks and benefits is requested. In summary, there is a high willingness to donate biological samples for dermatological research. This theoretical awareness fits well with our own experiences in establishing such a biobank.