Addressing Class Imbalance in Bayesian Classification Through Posterior Probability Adjustment.

Class imbalance is a known issue in classification tasks that can lead to predictive bias toward dominant classes. This paper introduces a novel straightforward Bayesian framework that adjusts posterior probabilities to counteract the bias introduced by imbalanced data sets. Instead of relying on the mean posterior distribution of class probabilities, we propose a method that scales the posterior probability of each class according to their representation in the training data.

Improved automated spot counting and modeling with bias correction.

A complete workflow was presented for estimating the concentration of microorganisms in biological samples by automatically counting spots that represent viral plaque forming units (PFU) bacterial colony forming units (CFU), or spot forming units (SFU) in images, and modeling the counts. The workflow was designed for processing images from dilution series but can also be applied to stand-alone images. The accuracy of the methods was greatly improved by adding a newly developed bias correction method.

The influence of resolution on the predictive power of spatial heterogeneity measures as biomarkers of liver fibrosis.

Spatial heterogeneity of cells in liver biopsies can be used as biomarker for disease severity of patients. This heterogeneity can be quantified by non-parametric statistics of point pattern data, which make use of an aggregation of the point locations. The method and scale of aggregation are usually chosen ad hoc, despite values of the aforementioned statistics being heavily dependent on them.

Automated Spot Counting in Microbiology.

Biological samples are routinely analyzed for microbe concentration. The samples are diluted, loaded onto established host cell cultures, and incubated. If infectious agents are present in the samples, they form circular spots that do not contain the host cells.

Measures of spatial heterogeneity in the liver tissue micro-environment as predictive factors for fibrosis score.

The organization and interaction between hepatocytes and other hepatic non-parenchymal cells plays a pivotal role in maintaining normal liver function and structure. Although spatial heterogeneity within the tumor micro-environment has been proven to be a fundamental feature in cancer progression, the role of liver tissue topology and micro-environmental factors in the context of liver damage in chronic infection has not been widely studied yet. We obtained images from 110 core needle biopsies from a cohort of chronic hepatitis B patients with different fibrosis stages according to METAVIR score.

AI/ML Models to Predict the Severity of Drug-Induced Liver Injury for Small Molecules.

Drug-induced liver injury (DILI), believed to be a multifactorial toxicity, has been a leading cause of attrition of small molecules during discovery, clinical development, and postmarketing. Identification of DILI risk early reduces the costs and cycle times associated with drug development. In recent years, several groups have reported predictive models that use physicochemical properties or and assay endpoints; however, these approaches have not accounted for liver-expressed proteins and drug molecules.

The Impact of Experimental and Calculated Error on the Performance of Affinity Predictions.

The accurate prediction of binding affinity between protein and small molecules with free energy methods, particularly the difference in binding affinities via relative binding free energy calculations, has undergone a dramatic increase in use and impact over recent years. The improvements in methodology, hardware, and implementation can deliver results with less than 1 kcal/mol mean unsigned error between calculation and experiment. This is a remarkable achievement and beckons some reflection on the significance of calculation approaching the accuracy of experiment.

A novel statistical test for treatment differences in clinical trials using a response-adaptive forward-looking Gittins Index Rule.

The most common objective for response-adaptive clinical trials is to seek to ensure that patients within a trial have a high chance of receiving the best treatment available by altering the chance of allocation on the basis of accumulating data. Approaches that yield good patient benefit properties suffer from low power from a frequentist perspective when testing for a treatment difference at the end of the study due to the high imbalance in treatment allocations. In this work we develop an alternative pairwise test for treatment difference on the basis of allocation probabilities of the covariate-adjusted response-adaptive randomization with forward-looking Gittins Index (CARA-FLGI) Rule for binary responses.

Bayesian pooling versus sequential integration of small preclinical trials: a comparison within linear and nonlinear modeling frameworks.

Bayesian sequential integration is an appealing approach in drug development, as it allows to recursively update posterior distributions as soon as new data become available, thus considerably reducing the computation time. However, preclinical trials are often characterized by small sample sizes, which may affect the estimation process during the first integration steps, particularly when complex PK-PD models are used. In this case, sequential integration would not be practicable, and trials should be pooled together.

Testing of acetaminophen in support of the international multilaboratory in vivo rat Pig-a assay validation trial.

Acetaminophen, a nonmutagenic compound as previously concluded from bacteria, in vitro mammalian cell, and in vivo transgenic rat assays, presented a good profile as a nonmutagenic reference compound for use in the international multilaboratory Pig-a assay validation. Acetaminophen was administered at 250, 500, 1,000, and 2,000 mg·kg ·day to male Sprague Dawley rats once daily in 3 studies (3 days, 2 weeks, and 1 month with a 1-month recovery group). The 3-Day and 1-Month Studies included assessments of the micronucleus endpoint in peripheral blood erythrocytes and the comet endpoint in liver cells and peripheral blood cells in addition to the Pig-a assay; appropriate positive controls were included for each assay.

Marginalized models for right-truncated and interval-censored time-to-event data.

Analysis of clustered data is often performed using random effects regression models. In such conditional models, a cluster-specific random effect is often introduced into the linear predictor function. Parameter interpretation of the covariate effects is then conditioned on the random effects, leading to a subject-specific interpretation of the regression parameters.

Bayesian sequential integration within a preclinical pharmacokinetic and pharmacodynamic modeling framework: Lessons learned.

The present manuscript aims to discuss the implications of sequential knowledge integration of small preclinical trials in a Bayesian pharmacokinetic and pharmacodynamic (PK-PD) framework. While, at first sight, a Bayesian PK-PD framework seems to be a natural framework to allow for sequential knowledge integration, the scope of this paper is to highlight some often-overlooked challenges while at the same time providing some guidances in the many and overwhelming choices that need to be made. Challenges as well as opportunities will be discussed that are related to the impact of (1) the prior specification, (2) the choice of random effects, (3) the type of sequential integration method.

A Bayesian K-PD model for synergy: A case study.

Coadministration of 2 or more compounds can alter both the pharmacokinetics and pharmacodynamics of individual compounds. While experiments on pharmacodynamic drug-drug interactions are usually performed in an in vitro setting, this experiment focuses on an in vivo setting. The change over time of a safety biomarker is modeled using an indirect response model, in which the virtual pharmacokinetic profile of one compound drives the effect of the other.

Comparing sampling methods for pharmacokinetic studies using model averaged derived parameters.

Pharmacokinetic studies aim to study how a compound is absorbed, distributed, metabolised, and excreted. The concentration of the compound in the blood or plasma is measured at different time points after administration and pharmacokinetic parameters such as the area under the curve (AUC) or maximum concentration (C ) are derived from the resulting concentration time profile. In this paper, we want to compare different methods for collecting concentration measurements (traditional sampling versus microsampling) on the basis of these derived parameters.

Models for zero-inflated, correlated count data with extra heterogeneity: when is it too complex?

Statistical analysis of count data typically starts with a Poisson regression. However, in many real-life applications, it is observed that the variation in the counts is larger than the mean, and one needs to deal with the problem of overdispersion in the counts. Several factors may contribute to overdispersion: (1) unobserved heterogeneity due to missing covariates, (2) correlation between observations (such as in longitudinal studies), and (3) the occurrence of many zeros (more than expected from the Poisson distribution).

Detecting influential observations in a model-based cluster analysis.

Finite mixture models have been used to model population heterogeneity and to relax distributional assumptions. These models are also convenient tools for clustering and classification of complex data such as, for example, repeated-measurements data. The performance of model-based clustering algorithms is sensitive to influential and outlying observations.

Evaluation of p-phenylenediamine, o-phenylphenol sodium salt, and 2,4-diaminotoluene in the rat comet assay as part of the Japanese Center for the Validation of Alternative Methods (JaCVAM)-initiated international validation study of in vivo rat alkaline comet assay.

As part of the Japanese Center for the Validation of Alternative Methods (JaCVAM)-initiated international validation study of in vivo rat alkaline comet assay (comet assay), p-phenylenediamine dihydrochloride (PPD), o-phenylphenol sodium salt (OPP), and 2,4-diaminotoluene (2,4-DAT), were analyzed in this laboratory as coded test chemicals. Male Sprague-Dawley rats (7-9 weeks of age) were given three oral doses of the test compounds, 24 and 21 h apart and liver and stomach were sampled 3h after the final dose administration. Under the conditions of the test, no increases in DNA damage were observed in liver and stomach with PPD and OPP up to 100 and 1000 mg/kg/day, respectively.

A clustering algorithm for multivariate longitudinal data.

Latent growth modeling approaches, such as growth mixture models, are used to identify meaningful groups or classes of individuals in a larger heterogeneous population. But when applied to multivariate repeated measures computational problems are likely, due to the high dimension of the joint distribution of the random effects in these mixed-effects models. This article proposes a cluster algorithm for multivariate repeated data, using pseudo-likelihood and ideas based on k-means clustering, to reveal homogenous subgroups.

Flexible modelling of simultaneously interval censored and truncated time-to-event data.

This paper deals with the analysis of data from a HET-CAM(VT) experiment. From a statistical perspective, such data yield many challenges. First of all, the data are typically time-to-event like data, which are at the same time interval censored and right truncated.

Carcinogenicity in rats of the SGLT2 inhibitor canagliflozin.

The carcinogenicity potential of canagliflozin, an inhibitor of SGLT2, was evaluated in a 2-year rat study (10, 30, and 100 mg/kg). Rats showed an increase in pheochromocytomas, renal tubular tumors, and testicular Leydig cell tumors. Systemic exposure multiples at the highest dose relative to the maximum clinical dose were 12- to 21-fold.

The concordance between nonclinical and phase I clinical cardiovascular assessment from a cross-company data sharing initiative.

It is widely accepted that more needs to be done to bring new, safe, and efficacious drugs to the market. Cardiovascular toxicity detected both in early drug discovery as well as in the clinic, is a major contributor to the high failure rate of new molecules. The growth of translational safety offers a promising approach to improve the probability of success for new molecules.

Abuse liability assessment in preclinical drug development: predictivity of a translational approach for abuse liability testing using methylphenidate in four standardized preclinical study models.

Objectives: Preclinical abuse liability assessment of novel clinical CNS-active candidates involves several tests, addressing different aspects characteristic for abuse potential, which are considered predictive for substance abuse of these candidates, thus ensuring an appropriate translational approach. To demonstrate how such a strategy could work, a known drug of abuse, methylphenidate was evaluated in a full rodent test battery, comprising four test models, and in accordance with the requirements of the FDA, ICH and EMA guidelines.

Methods: Methylphenidate was tested orally at 2.

In vivo longitudinal micro-CT study of bent long limb bones in rat offspring.

Micro-computed X-ray tomography (micro-CT) has been reported as a reliable method to assess ex vivo rat and rabbit fetal skeletons in embryo-fetal developmental toxicity studies. Since micro-CT is a non-invasive imaging modality it has the potential for longitudinal, in vivo investigation of postnatal skeletal development. This is the first paper using micro-CT to assess the reversibility of drug-induced bent long bones in a longitudinal study from birth to early adulthood in rat offspring.

A translational assessment of preclinical versus clinical tools for the measurement of cardiac contractility: comparison of LV dP/dt(max) with echocardiography in telemetry implanted beagle dogs.

Introduction: Regarding evaluation of drug-induced changes in left ventricular contractility in safety pharmacology there is still a gap in knowledge between preclinically and clinically used measurements.

Methods: As a step towards translation of preclinical to clinical outcomes, this study in telemetered dogs was initiated to compare indexes of contractility, such as LV dP/dt(max) (contractility measured as the maximum raise of pressure in the left ventricle) and LV dP/dt(max)/P (contractility measured as the maximum raise of pressure in the left ventricle, corrected for pressure) (telemetry; both commonly preclinically used) and EF (ejection fraction) and FS (fractional shortening) (echocardiography; both commonly clinically used). Different inotropic states were induced by minoxidil, milrinone, isoprenaline, clonidine, atenolol and verapamil.