Human Pharmacokinetic and CYP3A Drug-Drug Interaction Prediction of GDC-2394 Using Physiologically Based Pharmacokinetic Modeling and Biomarker Assessment.

Physiologically based pharmacokinetic (PBPK) modeling was used to predict the human pharmacokinetics and drug-drug interaction (DDI) of GDC-2394. PBPK models were developed using in vitro and in vivo data to reflect the oral and intravenous PK profiles of mouse, rat, dog, and monkey. The learnings from preclinical PBPK models were applied to a human PBPK model for prospective human PK predictions. The prospective human PK predictions were within 3-fold of the clinical data from the first-in-human study, which was used to optimize and validate the PBPK model and subsequently used for DDI prediction. Based on the majority of PBPK modeling scenarios using the in vitro CYP3A induction data (mRNA and activity), GDC-2394 was predicted to have no-to-weak induction potential at 900 mg twice daily (BID). Calibration of the induction mRNA and activity data allowed for the convergence of DDI predictions to a narrower range. The plasma concentrations of the 4ß-hydroxycholesterol (4ß-HC) were measured in the multiple ascending dose study to assess the hepatic CYP3A induction risk. There was no change in plasma 4ß-HC concentrations after 7 days of GDC-2394 at 900 mg BID. A dedicated DDI study found that GDC-2394 has no induction effect on midazolam in humans, which was reflected by the totality of predicted DDI scenarios. This work demonstrates the prospective utilization of PBPK for human PK and DDI prediction in early drug development of GDC-2394. PBPK modeling accompanied with CYP3A biomarkers can serve as a strategy to support clinical pharmacology development plans. SIGNIFICANCE STATEMENT: This work presents the application of physiologically based pharmacokinetic modeling for prospective human pharmacokinetic (PK) and drug-drug interaction (DDI) prediction in early drug development. The strategy taken in this report represents a framework to incorporate various approaches including calibration of in vitro induction data and consideration of CYP3A biomarkers to inform on the overall CYP3A-related DDI risk of GDC-2394.

Direct links between resource availability and activity budget better reveal ecological patterns of endangered Coimbra-Filho's titi monkey.

Many primatological studies do not assess direct indexes of food availability to make inferences about behavioral strategies. We related the diet and behavior of a group of Callicebus coimbrai in northeastern Brazil to fruit availability indexes and compared this pattern between seasons (direct and indirect assessment of food availability) to assess whether direct and indirect approaches detect similar ecological patterns. We monitored the study group for 33 months (5 days/month) via scan sampling. The monthly availability of fruits and new leaves was recorded in phenological transects. Fruit availability varied across years based on fruit prevalence, and timing and duration of the abundant seasons. We did not find evidence of a time-minimizing strategy, since C. coimbrai did not change its activity levels according to food availability. However, the negative relationship between foraging and fruit availability indicates that C. coimbrai can compensate for the lower fruit availability by increasing the search for alternative food sources. Monthly fruit consumption was positively correlated to fruit availability and negatively related to the consumption of other food items. However, the behavioral and feeding profiles did not vary between seasons and were not related to rainfall levels. Primate studies should directly relate behavioral and feeding profiles to fruit availability indices, thus avoiding using seasons as proxies of food availability.

Group size and mating system predict sex differences in vocal fundamental frequency in anthropoid primates.

Vocalizations differ substantially between the sexes in many primates, and low-frequency male vocalizations may be favored by sexual selection because they intimidate rivals and/or attract mates. Sexual dimorphism in fundamental frequency may be more pronounced in species with more intense male mating competition and in those with large group size, where social knowledge is limited and efficient judgment of potential mates and competitors is crucial. These non-mutually exclusive explanations have not been tested simultaneously across primate species. In a sample of vocalizations (n = 1914 recordings) across 37 anthropoid species, we investigated whether fundamental frequency dimorphism evolved in association with increased intensity of mating competition (H1), large group size (H2), multilevel social organization (H3), a trade-off against the intensity of sperm competition (H4), and/or poor acoustic habitats (H5), controlling for phylogeny and body size dimorphism. We show that fundamental frequency dimorphism increased in evolutionary transitions towards larger group size and polygyny. Findings suggest that low-frequency male vocalizations in primates may have been driven by selection to win mating opportunities by avoiding costly fights and may be more important in larger groups, where limited social knowledge affords advantages to rapid assessment of status and threat potential via conspicuous secondary sexual characteristics.

Monkeys exhibit human-like gaze biases in economic decisions.

In economic decision-making individuals choose between items based on their perceived value. For both humans and nonhuman primates, these decisions are often carried out while shifting gaze between the available options. Recent studies in humans suggest that these shifts in gaze actively influence choice, manifesting as a bias in favor of the items that are viewed first, viewed last, or viewed for the overall longest duration in a given trial. This suggests a mechanism that links gaze behavior to the neural computations underlying value-based choices. In order to identify this mechanism, it is first necessary to develop and validate a suitable animal model of this behavior. To this end, we have created a novel value-based choice task for macaque monkeys that captures the essential features of the human paradigms in which gaze biases have been observed. Using this task, we identified gaze biases in the monkeys that were both qualitatively and quantitatively similar to those in humans. In addition, the monkeys' gaze biases were well-explained using a sequential sampling model framework previously used to describe gaze biases in humans-the first time this framework has been used to assess value-based decision mechanisms in nonhuman primates. Together, these findings suggest a common mechanism that can explain gaze-related choice biases across species, and open the way for mechanistic studies to identify the neural origins of this behavior.

When we choose between two items, we might expect to spend more time looking at the one we have a pre-existing preference for. For example, at the grocery store, you might assume that someone who likes grapes better than bananas would spend a longer time looking at the grapes. Surprisingly, a series of studies on human decision-making have shown that the opposite relationship is also true: the more time we spend looking at an item, the more likely we are to pick it. This 'gaze bias' occurs in many real-life and laboratory decision settings, and it is especially evident for choices between two equally preferred options. However, examining the brain circuits that underpin this behavior has so far been difficult due to a lack of animal models in which to study them. In response, Lupkin and McGinty proposed that rhesus macaques may be the ideal species in which to study gaze biases, as these animals likely rely on the same brain regions as humans when gazing and making decisions. To test this hypothesis, a computer-based decision game similar to the ones used for humans was designed for the monkeys. It involved the animals having to choose between two icons that were associated with different amounts of a juice reward. Analysing how long the macaques had spent looking at each icon before making their choice revealed that they indeed tended to select the icon they had looked at for longer ­ including when the two icons indicated equal rewards. Other types of gaze biases present in humans were also detected, such as choosing the icon that was viewed first or last in a trial. Additional analyses using computer simulations confirmed that the gaze biases of humans and monkeys were comparable and, critically, that they could be explained by similar underlying brain processes. These strong similarities suggest that rhesus macaques could be used to study the neural basis for decision-making in both humans and nonhuman primates, potentially making it easier to examine the harmful changes in decision-making that occur in conditions like substance abuse or depression.

Dynamic prospect theory: Two core decision theories coexist in the gambling behavior of monkeys and humans.

Research in the multidisciplinary field of neuroeconomics has mainly been driven by two influential theories regarding human economic choice: prospect theory, which describes decision-making under risk, and reinforcement learning theory, which describes learning for decision-making. We hypothesized that these two distinct theories guide decision-making in a comprehensive manner. Here, we propose and test a decision-making theory under uncertainty that combines these highly influential theories. Collecting many gambling decisions from laboratory monkeys allowed for reliable testing of our model and revealed a systematic violation of prospect theory's assumption that probability weighting is static. Using the same experimental paradigm in humans, substantial similarities between these species were uncovered by various econometric analyses of our dynamic prospect theory model, which incorporates decision-by-decision learning dynamics of prediction errors into static prospect theory. Our model provides a unified theoretical framework for exploring a neurobiological model of economic choice in human and nonhuman primates.

A New Assessment of Robust Capuchin Monkey (Sapajus) Evolutionary History Using Genome-Wide SNP Marker Data and a Bayesian Approach to Species Delimitation.

Robust capuchin monkeys, Sapajus genus, are among the most phenotypically diverse and widespread groups of primates in South America, with one of the most confusing and often shifting taxonomies. We used a ddRADseq approach to generate genome-wide SNP markers for 171 individuals from all putative extant species of Sapajus to access their evolutionary history. Using maximum likelihood, multispecies coalescent phylogenetic inference, and a Bayes Factor method to test for alternative hypotheses of species delimitation, we inferred the phylogenetic history of the Sapajus radiation, evaluating the number of discrete species supported. Our results support the recognition of three species from the Atlantic Forest south of the São Francisco River, with these species being the first splits in the robust capuchin radiation. Our results were congruent in recovering the Pantanal and Amazonian Sapajus as structured into three monophyletic clades, though new morphological assessments are necessary, as the Amazonian clades do not agree with previous morphology-based taxonomic distributions. Phylogenetic reconstructions for Sapajus occurring in the Cerrado, Caatinga, and northeastern Atlantic Forest were less congruent with morphology-based phylogenetic reconstructions, as the bearded capuchin was recovered as a paraphyletic clade, with samples from the Caatinga biome being either a monophyletic clade or nested with the blond capuchin monkey.

Non-specific binding of compounds in in vitro metabolism assays: a comparison of microsomal and hepatocyte binding in different species and an assessment of the accuracy of prediction models.

Non-specific binding in in vitro metabolism systems leads to an underestimation of the true intrinsic metabolic clearance of compounds being studied. Therefore in vitro binding needs to be accounted for when extrapolating in vitro data to predict the in vivo metabolic clearance of a compound. While techniques exist for experimentally determining the fraction of a compound unbound in in vitro metabolism systems, early in drug discovery programmes computational approaches are often used to estimate the binding in the in vitro system.Experimental fraction unbound data (n = 60) were generated in liver microsomes (fumic) from five commonly used pre-clinical species (rat, mouse, dog, minipig, monkey) and humans. Unbound fraction in incubations with mouse, rat or human hepatocytes was determined for the same 60 compounds. These data were analysed to determine the relationship between experimentally determined binding in the different matrices and across different species. In hepatocytes there was a good correlation between fraction unbound in human and rat (r2=0.86) or mouse (r2=0.82) hepatocytes. Similar correlations were observed between binding in human liver microsomes and microsomes from rat, mouse, dog, Göttingen minipig or monkey liver microsomes (r2 of >0.89, n = 51 - 52 measurements in different species). Physicochemical parameters (logP, pKa and logD) were predicted for all evaluated compounds. In addition, logP and/or logD were measured for a subset of compounds.Binding to human hepatocytes predicted using 5 different methods was compared to the measured data for a set of 59 compounds. The best methods evaluated used measured microsomal binding in human liver microsomes to predict hepatocyte binding. The collated physicochemical data were used to predict the human fumic using four different in silico models for a set of 53-60 compounds. The correlation (r2) and root mean square error between predicted and observed microsomal binding was 0.69 & 0.20, 0.47 & 0.23, 0.56 & 0.21 and 0.54 & 0.26 for the Turner-Simcyp, Austin, Hallifax-Houston and Poulin models, respectively. These analyses were extended to include measured literature values for binding in human liver microsomes for a larger set of compounds (n=697). For the larger dataset of compounds, microsomal binding was well predicted for neutral compounds (r2=0.67 - 0.70) using the Poulin, Austin, or Turner-Simcyp methods but not for acidic or basic compounds (r2<0.5) using any of the models. While the lipophilicity-based models can be used, the in vitro binding should be measured for compounds where more certainty is needed, using appropriately calibrated assays and possibly established weak, moderate, and strong binders as reference compounds to allow comparison across databases.

Optimization of an Efficient Cell Culture Hepatitis B Infection System for Assessment of Hepatitis B Virus Neutralizing Monoclonal Antibodies.

BACKGROUND: Human polyclonal plasma-derived hepatitis B immunoglobulin (HBIG) is currently used for immunoprophylaxis of HBV infection. The development of virus-neutralizing monoclonal antibodies (MAbs) requires the use of optimized cell culture systems supporting HBV infection. OBJECTIVE: This study aims to optimize the hepatitis B virus infectivity of NTCP-reconstituted HepG2 (HepG2-NTCP) cells to establish an efficient system to evaluate the HBV-neutralizing effect of anti-HBs MAbs. METHODS: Serum-derived HBV (sHBV) and cell culture-derived HBV (ccHBV) were simultaneously used for the optimization of HBV infection in HepG2-NTCP cells by applying different modifications. RESULTS: Our results for the first time showed that in addition to human serum, monkey serum could significantly improve ccHBV infection, while fetal and adult bovine serum as well as duck and sheep serum did not have a promotive effect. In addition, sHBV and ccHBV infectivity are largely similar except that adding 5% of PEG, which is commonly used to improve in vitro infection of ccHBV, significantly reduced sHBV infection. We showed that a combination of spinoculation, trypsinization, and also adding human or monkey serum to HBV inoculum could significantly improve the permissivity of HepG2-NTCP cells to HBV infection compared with individual strategies. All anti-HBs MAbs were able to successfully neutralize both ccHBV and sHBV infection in our optimized in vitro system. CONCLUSION: Our study suggests different strategies for improving ccHBV and sHBV infection in HepG2-NTCP cells. This cell culture-based system allows assessment of HBV neutralizing MAbs and may also prove to be valuable for the analysis of other HBV neutralizing therapeutics.

Utility of preclinical species for uncertainty assessment and correction of prediction of human volume of distribution using the Rodgers-Lukacova model.

Prediction of rat, dog, monkey, and human volume of distribution (VDss) by Rodgers-Lukacova model was evaluated using a data set of more than 100 compounds.The prediction accuracy was best for humans followed by monkeys and dogs with 59, 52, and 41% of compounds within 2-fold, respectively.The accuracy of predictions in preclinical species was indicative of the human situation. This was particularly true for monkeys, where 87% of the compounds that were predicted within 2-fold in monkeys were also predicted within 2-fold in humans.The model's tendency to underestimate VDss was higher in rats and dogs compared to humans and monkeys for all ion classes but zwitterions. Hence, correction of human predictions using prediction errors in rats and dogs resulted in overestimation of VDss.The model had a similar degree of underestimation in humans and monkeys. Correction using monkeys improved the accuracy of the human estimate, especially for basic and zwitterion compounds.A strategy is proposed based on the accuracy of prediction in monkey and monkey scalars for prediction and prospective assessment of the accuracy of human VDss.

China's big brain project is finally gathering steam.

The $746 million program builds on the country's strengths in neuroscience-and its openness to primate research.

Preliminary assessment of gastrointestinal parasites of the sun-tailed monkey (Allochrocebus solatus) in a semi-free-ranging colony.

BACKGROUND: The occurrence of gastrointestinal parasites in the sun-tailed monkey (Allochrocebus solatus) at the CIRMF primatology center is unknown. We, therefore, assessed the presence and richness (number of different parasite taxa) of gastrointestinal parasites in a semi-free-ranging colony of A. solatus. METHODS: A total of 46 fecal samples were screened using a modified McMaster technique for fecal egg counts. RESULTS: In the 46 samples collected, seven taxa of gastrointestinal parasites, including protozoa and nematodes were identified. The most prevalent parasite was strongyles parasites (98%), followed by Trichuris spp. (72%), Strongyloides spp. (67%) and Entamoeba coli (65%). Balantioides coli (33%), Endolimax nana (25%), and Spirurid eggs (26%) were only found in a minority of the animals. CONCLUSIONS: This study contributes new host records of gastrointestinal parasites in semi-free-ranging A. solatus and highlights the need to investigate the health of this species and implement proper precautions in the management of this colony.

Comparative assessment of favipiravir and remdesivir against human coronavirus NL63 in molecular docking and cell culture models.

Human coronavirus NL63 (HCoV-NL63) mainly affects young children and immunocompromised patients, causing morbidity and mortality in a subset of patients. Since no specific treatment is available, this study aims to explore the anti-SARS-CoV-2 agents including favipiravir and remdesivir for treating HCoV-NL63 infection. We first successfully modelled the 3D structure of HCoV-NL63 RNA-dependent RNA polymerase (RdRp) based on the experimentally solved SARS-CoV-2 RdRp structure. Molecular docking indicated that favipiravir has similar binding affinities to SARS-CoV-2 and HCoV-NL63 RdRp with LibDock scores of 75 and 74, respectively. The LibDock scores of remdesivir to SARS-CoV-2 and HCoV-NL63 were 135 and 151, suggesting that remdesivir may have a higher affinity to HCoV-NL63 compared to SARS-CoV-2 RdRp. In cell culture models infected with HCoV-NL63, both favipiravir and remdesivir significantly inhibited viral replication and production of infectious viruses. Overall, remdesivir compared to favipiravir is more potent in inhibiting HCoV-NL63 in cell culture. Importantly, there is no evidence of resistance development upon long-term exposure to remdesivir. Furthermore, combining favipiravir or remdesivir with the clinically used antiviral cytokine interferon-alpha resulted in synergistic effects. These findings provided a proof-of-concept that anti-SARS-CoV-2 drugs, in particular remdesivir, have the potential to be repurposed for treating HCoV-NL63 infection.

Estimating the dimensionality of the manifold underlying multi-electrode neural recordings.

It is generally accepted that the number of neurons in a given brain area far exceeds the number of neurons needed to carry any specific function controlled by that area. For example, motor areas of the human brain contain tens of millions of neurons that control the activation of tens or at most hundreds of muscles. This massive redundancy implies the covariation of many neurons, which constrains the population activity to a low-dimensional manifold within the space of all possible patterns of neural activity. To gain a conceptual understanding of the complexity of the neural activity within a manifold, it is useful to estimate its dimensionality, which quantifies the number of degrees of freedom required to describe the observed population activity without significant information loss. While there are many algorithms for dimensionality estimation, we do not know which are well suited for analyzing neural activity. The objective of this study was to evaluate the efficacy of several representative algorithms for estimating the dimensionality of linearly and nonlinearly embedded data. We generated synthetic neural recordings with known intrinsic dimensionality and used them to test the algorithms' accuracy and robustness. We emulated some of the important challenges associated with experimental data by adding noise, altering the nature of the embedding of the low-dimensional manifold within the high-dimensional recordings, varying the dimensionality of the manifold, and limiting the amount of available data. We demonstrated that linear algorithms overestimate the dimensionality of nonlinear, noise-free data. In cases of high noise, most algorithms overestimated the dimensionality. We thus developed a denoising algorithm based on deep learning, the "Joint Autoencoder", which significantly improved subsequent dimensionality estimation. Critically, we found that all algorithms failed when the intrinsic dimensionality was high (above 20) or when the amount of data used for estimation was low. Based on the challenges we observed, we formulated a pipeline for estimating the dimensionality of experimental neural data.

Immunogenicity Assessment of Inotersen, a 2'-O-(2-Methoxyethyl) Antisense Oligonucleotide in Animals and Humans: Effect on Pharmacokinetics, Pharmacodynamics, and Safety.

Inotersen (TEGSEDI™) is a 2'-O-(2-methoxyethyl)-modified antisense oligonucleotide, intended for treating hereditary transthyretin (TTR) amyloidosis with polyneuropathy. The potential immunogenicity (IM) response to inotersen was evaluated in chronic nonclinical safety studies and the pivotal phase 2/3 clinical study. The evaluation was designed to assess the characteristics of antidrug antibodies (ADAs) and their effects on the pharmacokinetics, pharmacodynamics, clinical efficacy, and safety in animals and humans. No immunogenic response was observed after long-term treatment with inotersen in mice. In monkeys, the incidence rate of IM to inotersen appeared to be dose dependent, with 28.6%-50.0% of animals developing ADAs after 36 weeks of treatment. This was characterized as late onset (median onset of 185 days) with low titers (median titer of 8, or 400 if minimum required dilution of 50 is included). The overall incidence rate of patients who developed ADAs was 30% after 65 weeks of treatment with median onset of 203 days and median peak titer of 300. IM had minimal effect on plasma peak (Cmax) and total exposure (i.e. area under curve, AUC) of inotersen, but showed elevated plasma trough levels in both IM-positive animals and humans. However, ADAs had no effect on tissue exposure, TTR messenger RNA, or plasma TTR levels in the long-term monkey study. Similarly, IM showed no effect on plasma TTR levels in clinical studies. Thus, ADAs antibodies were binding antibodies, but not neutralizing antibodies. Finally, no association was observed between IM and toxicity findings (eg, platelet, complement activation, and histopathology findings) in the inotersen 9-month monkey study. In humans, no difference was observed in hematology, including platelets, kidney function tests, or incidence of adverse events between IM-positive and -negative patients. Overall, IM showed no effect on toxicity or safety of inotersen evaluated in both monkeys and humans. ClinicalTrials.gov Identifier: NCT01737398.

Prefrontal attentional saccades explore space rhythmically.

Recent studies suggest that attention samples space rhythmically through oscillatory interactions in the frontoparietal network. How these attentional fluctuations coincide with spatial exploration/displacement and exploitation/selection by a dynamic attentional spotlight under top-down control is unclear. Here, we show a direct contribution of prefrontal attention selection mechanisms to a continuous space exploration. Specifically, we provide a direct high spatio-temporal resolution prefrontal population decoding of the covert attentional spotlight. We show that it continuously explores space at a 7-12 Hz rhythm. Sensory encoding and behavioral reports are increased at a specific optimal phase w/ to this rhythm. We propose that this prefrontal neuronal rhythm reflects an alpha-clocked sampling of the visual environment in the absence of eye movements. These attentional explorations are highly flexible, how they spatially unfold depending both on within-trial and across-task contingencies. These results are discussed in the context of exploration-exploitation strategies and prefrontal top-down attentional control.

In situ estimation of optical properties of rat and monkey brains using femtosecond time-resolved measurements.

An accurate knowledge of tissue optical properties (absorption coefficients, µa, and reduced scattering coefficients, µs') is critical for precise modeling of light propagation in biological tissue, essential for developing diagnostic and therapeutic optical techniques that utilize diffusive photons. A great number of studies have explored the optical properties of various tissue, and these values are not known in detail due to difficulties in the experimental determination and significant variations in tissue constitution. Especially, in situ estimates of the optical properties of brain tissue, a common measurement target in optical imaging, is a challenge because of its layer structure (where the thin gray matter covers the white matter). Here, we report an approach to in situ estimates of the µa and µs' of the gray and white matter in living rat and monkey brains by using femtosecond time-resolved measurements and Monte Carlo simulation. The results demonstrate that the µa of the gray matter is larger than that of the white matter, while there was no significant difference in the µs' between the gray and white matter. The optical properties of the rat brain were very similar to those of the monkey brain except for the µa of the gray matter here.

Exposure assessments in reproductive and developmental toxicity testing: An IQ-DruSafe industry survey on current practices and experiences in support of exposure-based high dose selection.

The draft ICH S5(R3) guideline includes an exposure-based endpoint as an option for selecting the high dose in developmental and reproductive toxicity (DART) studies. In 2016, IQ DruSafe conducted an anonymous survey to identify industry practices and experiences related to pharmacokinetic assessments in DART studies in order to facilitate a pragmatic data-driven approach to development of an acceptable multiple of the clinical exposure to be proposed for dose selection in the guideline. Questions in the survey were designed to explore pharmacokinetic differences in pregnant versus non-pregnant animals, and to assess exposure levels attained in the absence of maternal toxicity as well as DART outcomes in animal studies associated with those exposures. Small molecule and therapeutic proteins were analyzed separately. The key findings for small molecules were: a) differences in exposures between pregnant and non-pregnant animals were generally ≤3-fold, b) Cmax or AUC exposures ≥25-fold the clinical exposure were achieved in the absence of maternal toxicity for 31% and 23% of rat and rabbit developmental toxicity studies, respectively, and c) only 3.3% (5/153) and 1.6% (2/128) of the developmental toxicity studies were positive for malformations or embryofetal lethality in rats and rabbits, respectively, that were not observed until exposure margins were ≥25-fold.

Bayesian evaluation of a physiologically based pharmacokinetic (PBPK) model for perfluorooctane sulfonate (PFOS) to characterize the interspecies uncertainty between mice, rats, monkeys, and humans: Development and performance verification.

A challenge in the risk assessment of perfluorooctane sulfonate (PFOS) is the large interspecies differences in its toxicokinetics that results in substantial uncertainty in the dosimetry and toxicity extrapolation from animals to humans. To address this challenge, the objective of this study was to develop an open-source physiologically based pharmacokinetic (PBPK) model accounting for species-specific toxicokinetic parameters of PFOS. Considering available knowledge about the toxicokinetic properties of PFOS, a PBPK model for PFOS in mice, rats, monkeys, and humans after intravenous and oral administrations was created. Available species-specific toxicokinetic data were used for model calibration and optimization, and independent datasets were used for model evaluation. Bayesian statistical analysis using Markov chain Monte Carlo (MCMC) simulation was performed to optimize the model and to characterize the uncertainty and interspecies variability of chemical-specific parameters. The model predictions well correlated with the majority of datasets for all four species, and the model was validated with independent data in rats, monkeys, and humans. The model was applied to predict human equivalent doses (HEDs) based on reported points of departure in selected critical toxicity studies in rats and monkeys following U.S. EPA's guidelines. The lower bounds of the model-derived HEDs were overall lower than the HEDs estimated by U.S. EPA (e.g., 0.2 vs. 1.3 µg/kg/day based on the rat plasma data). This integrated and comparative analysis provides an important step towards improving interspecies extrapolation and quantitative risk assessment of PFOS, and this open-source model provides a foundation for developing models for other perfluoroalkyl substances.

A low-cost, automated parasite diagnostic system via a portable, robotic microscope and deep learning.

Manual hand counting of parasites in fecal samples requires costly components and substantial expertise, limiting its use in resource-constrained settings and encouraging overuse of prophylactic medication. To address this issue, a cost-effective, automated parasite diagnostic system that does not require special sample preparation or a trained user was developed. It is composed of an inexpensive (~US$350), portable, robotic microscope that can scan over the size of an entire McMaster chamber (100 mm2 ) and capture high-resolution (~1 µm lateral resolution) bright field images without need for user intervention. Fecal samples prepared using the McMaster flotation method were imaged, with the imaging region comprising the entire McMaster chamber. These images are then automatically segmented and analyzed using a trained convolution neural network (CNN) to robustly separate eggs from background debris. Simple postprocessing of the CNN output yields both egg species and egg counts. The system was validated by comparing accuracy with hand-counts by a trained operator, with excellent performance. As a further demonstration of utility, the system was used to conveniently quantify drug response over time in a single animal, showing residual disease due to Anthelmintic resistance after 2 weeks.

Recent efforts to elucidate the scientific validity of animal-based drug tests by the pharmaceutical industry, pro-testing lobby groups, and animal welfare organisations.

BACKGROUND: Even after several decades of human drug development, there remains an absence of published, substantial, comprehensive data to validate the use of animals in preclinical drug testing, and to point to their predictive nature with regard to human safety/toxicity and efficacy. Two recent papers, authored by pharmaceutical industry scientists, added to the few substantive publications that exist. In this brief article, we discuss both these papers, as well as our own series of three papers on the subject, and also various views and criticisms of lobby groups that advocate the animal testing of new drugs. MAIN TEXT: We argue that there still remains no published evidence to support the current regulatory paradigm of animal testing in supporting safe entry to clinical trials. In fact, the data in these recent studies, as well as in our own studies, support the contention that tests on rodents, dogs and monkeys provide next to no evidential weight to the probability of there being a lack of human toxicity, when there is no apparent toxicity in the animals. CONCLUSION: Based on these data, and in particular on this finding, it must be concluded that animal drug tests are therefore not fit for their stated purpose. At the very least, it is now incumbent on-and we very much encourage-the pharmaceutical industry and its regulators to commission, conduct and/or facilitate further independent studies involving the use of substantial proprietary data.