Osteopathology and insect traces in the Australopithecus africanus skeleton StW 431

We present the first application of high-resolution micro computed tomography in an analysis of both the internal and external morphology of the lumbar region of StW 431 – a hominin skeleton recovered from Member 4 infill of the Sterkfontein Caves (South Africa) in 1987. The lumbar vertebrae of the individual present a number of proliferative and erosive bony processes, which were investigated in this study. Investigations suggest a complex history of taphonomic alteration to pre-existing spinal degenerative joint disease (SDJD) as well as post-mortem modification by an unknown insect. This study is in agreement with previous pathological diagnoses of SDJD which affected StW 431 and is the first time insect traces on this hominin are described. The results of this analysis attest to the complex series of post-mortem processes affecting the Sterkfontein site and its fossil assemblages

Graphic Mining of High-Order Drug Interactions and Their Directional Effects on Myopathy Using Electronic Medical Records

We propose to study a novel pharmacovigilance problem for mining directional effects of high-order drug interactions on an adverse drug event (ADE). Our goal is to estimate each individual risk of adding a new drug to an existing drug combination. In this proof-of-concept study, we analyzed a large electronic medical records database and extracted myopathy-relevant case control drug co-occurrence data. We applied frequent itemset mining to discover frequent drug combinations within the extracted data, evaluated directional drug interactions related to these combinations, and identified directional drug interactions with large effect sizes. Furthermore, we developed a novel visualization method to organize multiple directional drug interaction effects depicted as a tree, to generate an intuitive graphical and visual representation of our data-mining results. This translational bioinformatics approach yields promising results, adds valuable and complementary information to the existing pharmacovigilance literature, and has the potential to impact clinical practice

STOP-AD portal: Selecting the optimal pharmaceutical for preclinical drug testing in Alzheimer\u27s disease.

We propose an unbiased methodology to rank compounds for advancement into comprehensive preclinical testing for Alzheimer\u27s disease (AD). Translation of compounds to the clinic in AD has been hampered by poor predictive validity of models, compounds with limited pharmaceutical properties, and studies that lack rigor. To overcome this, MODEL-AD\u27s Preclinical Testing Core developed a standardized pipeline for assessing efficacy in AD mouse models. We hypothesize that rank-ordering compounds based upon pharmacokinetic, efficacy, and toxicity properties in preclinical models will enhance successful translation to the clinic. Previously compound selection was based solely on physiochemical properties, with arbitrary cutoff limits, making ranking challenging. Since no gold standard exists for systematic prioritization, validating a selection criteria has remained elusive. The STOP-AD framework evaluates the drug-like properties to rank compounds for in vivo studies, and uses an unbiased approach that overcomes the validation limitation by performing Monte-Carlo simulations. HIGHLIGHTS: Promising preclinical studies for AD drugs have not translated to clinical success. Systematic assessment of AD drug candidates may increase clinical translatability. We describe a well-defined framework for compound selection with clear selection metrics

Restoration of R117H CFTR folding and function in human airway cells through combination treatment with VX-809 and VX-770

Cystic fibrosis (CF) is a lethal recessive genetic disease caused primarily by the F508del mutation in the CF transmembrane conductance regulator (CFTR). The potentiator VX-770 was the first CFTR modulator approved by the FDA for treatment of CF patients with the gating mutation G551D. Orkambi is a drug containing VX-770 and corrector VX809 and is approved for treatment of CF patients homozygous for F508del, which has folding and gating defects. At least 30% of CF patients are heterozygous for the F508del mutation with the other allele encoding for one of many different rare CFTR mutations. Treatment of heterozygous F508del patients with VX-809 and VX-770 has had limited success, so it is important to identify heterozygous patients that respond to CFTR modulator therapy. R117H is a more prevalent rare mutation found in over 2,000 CF patients. In this study we investigated the effectiveness of VX-809/VX-770 therapy on restoring CFTR function in human bronchial epithelial (HBE) cells from R117H/F508del CF patients. We found that VX-809 stimulated more CFTR activity in R117H/F508del HBEs than in F508del/F508del HBEs. R117H expressed exclusively in immortalized HBEs exhibited a folding defect, was retained in the ER, and degraded prematurely. VX-809 corrected the R117H folding defect and restored channel function. Because R117 is involved in ion conductance, VX-770 acted additively with VX-809 to restore CFTR function in chronically treated R117H/F508del cells. Although treatment of R117H patients with VX-770 has been approved, our studies indicate that Orkambi may be more beneficial for rescue of CFTR function in these patients

Pharmacological rescue of conditionally reprogrammed cystic fibrosis bronchial epithelial cells

Well-differentiated primary human bronchial epithelial (HBE) cell cultures are vital for cystic fibrosis (CF) research, particularly for the development of cystic fibrosis transmembrane conductance regulator (CFTR) modulator drugs. Culturing of epithelial cells with irradiated 3T3 fibroblast feeder cells plus the RhoA kinase inhibitor Y-27632 (Y), termed conditionally reprogrammed cell (CRC) technology, enhances cell growth and lifespan while preserving cell-of-origin functionality. We initially determined the electrophysiological and morphological characteristics of conventional versus CRC-expanded non-CF HBE cells. On the basis of these findings, we then created six CF cell CRC populations, three from sequentially obtained CF lungs and three from F508 del homozygous donors previously obtained and cryopreserved using conventional culture methods. Growth curves were plotted, and cells were subcultured, without irradiated feeders plus Y, into air-liquid interface conditions in nonproprietary and proprietary Ultroser G-containing media and were allowed to differentiate. Ussing chamber studies were performed after treatment of F508 del homozygous CF cells with the CFTR modulator VX-809. Bronchial epithelial cells grew exponentially in feeders plus Y, dramatically surpassing the numbers of conventionally grown cells. Passage 5 and 10 CRC HBE cells formed confluent mucociliary air-liquid interface cultures. There were differences in cell morphology and current magnitude as a function of extended passage, but the effect of VX-809 in increasing CFTR function was significant in CRC-expanded F508 del HBE cells. Thus, CRC technology expands the supply of functional primary CF HBE cells for testing CFTR modulators in Ussing chambers

Mixture drug-count response model for the high-dimensional drug combinatory effect on myopathy

Drug-drug interactions (DDIs) are a common cause of adverse drug events (ADEs). The electronic medical record (EMR) database and the FDA's adverse event reporting system (FAERS) database are the major data sources for mining and testing the ADE associated DDI signals. Most DDI data mining methods focus on pair-wise drug interactions, and methods to detect high-dimensional DDIs in medical databases are lacking. In this paper, we propose 2 novel mixture drug-count response models for detecting high-dimensional drug combinations that induce myopathy. The “count” indicates the number of drugs in a combination. One model is called fixed probability mixture drug-count response model with a maximum risk threshold (FMDRM-MRT). The other model is called count-dependent probability mixture drug-count response model with a maximum risk threshold (CMDRM-MRT), in which the mixture probability is count dependent. Compared with the previous mixture drug-count response model (MDRM) developed by our group, these 2 new models show a better likelihood in detecting high-dimensional drug combinatory effects on myopathy. CMDRM-MRT identified and validated (54; 374; 637; 442; 131) 2-way to 6-way drug interactions, respectively, which induce myopathy in both EMR and FAERS databases. We further demonstrate FAERS data capture much higher maximum myopathy risk than EMR data do. The consistency of 2 mixture models' parameters and local false discovery rate estimates are evaluated through statistical simulation studies

Potentiator ivacaftor abrogates pharmacological correction of F508 CFTR in cystic fibrosis

Cystic Fibrosis (CF) is caused by mutations in the CF transmembrane conductance regulator (CFTR). Newly developed “correctors” such as lumacaftor (VX-809) that improve CFTR maturation and trafficking and “potentiators” such as ivacaftor (VX-770) that enhance channel activity may provide important advances in CF therapy. Although VX-770 has demonstrated substantial clinical efficacy in the small subset of patients with a mutation (G551D) that affects only channel activity, a single compound is not sufficient to treat patients with the more common CFTR mutation, ΔF508. Thus, patients with ΔF508 will likely require treatment with both correctors and potentiators to achieve clinical benefit. However, whereas the effectiveness of acute treatment with this drug combination has been demonstrated in vitro, the impact of chronic therapy has not been established. In studies of human primary airway epithelial cells, we found that both acute and chronic treatment with VX-770 improved CFTR function in cells with the G551D mutation, consistent with clinical studies. In contrast, chronic VX-770 administration caused a dose-dependent reversal of VX-809-mediated CFTR correction in ΔF508 homozygous cultures. This result reflected the destabilization of corrected ΔF508 CFTR by VX-770, dramatically increasing its turnover rate. Chronic VX-770 treatment also reduced mature wild-type CFTR levels and function. These findings demonstrate that chronic treatment with CFTR potentiators and correctors may have unexpected effects that cannot be predicted from short-term studies. Combining of these drugs to maximize rescue of ΔF508 CFTR may require changes in dosing and/or development of new potentiator compounds that do not interfere with CFTR stability

Three-Component Mixture Model-Based Adverse Drug Event Signal Detection for the Adverse Event Reporting System

The US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) is an important source for detecting adverse drug event (ADE) signals. In this article, we propose a three-component mixture model (3CMM) for FAERS signal detection. In 3CMM, a drug-ADE pair is assumed to have either a zero relative risk (RR), or a background RR (mean RR = 1), or an increased RR (mean RR >1). By clearly defining the second component (mean RR = 1) as the null distribution, 3CMM estimates local false discovery rates (FDRs) for ADE signals under the empirical Bayes framework. Compared with existing approaches, the local FDR's top signals have noninferior or better sensitivities to detect true signals in both FAERS analysis and simulation studies. Additionally, we identify that the top signals of different approaches have different patterns, and they are complementary to each other

Non-compartment model to compartment model pharmacokinetics transformation meta-analysis – a multivariate nonlinear mixed model

Background To fulfill the model based drug development, the very first step is usually a model establishment from published literatures. Pharmacokinetics model is the central piece of model based drug development. This paper proposed an important approach to transform published non-compartment model pharmacokinetics (PK) parameters into compartment model PK parameters. This meta-analysis was performed with a multivariate nonlinear mixed model. A conditional first-order linearization approach was developed for statistical estimation and inference. Results Using MDZ as an example, we showed that this approach successfully transformed 6 non-compartment model PK parameters from 10 publications into 5 compartment model PK parameters. In simulation studies, we showed that this multivariate nonlinear mixed model had little relative bias (<1%) in estimating compartment model PK parameters if all non-compartment PK parameters were reported in every study. If there missing non-compartment PK parameters existed in some published literatures, the relative bias of compartment model PK parameter was still small (<3%). The 95% coverage probabilities of these PK parameter estimates were above 85%. Conclusions This non-compartment model PK parameter transformation into compartment model meta-analysis approach possesses valid statistical inference. It can be routinely used for model based drug development