Supplementation of minerals and vitamins influences optimal targeted selective treatment thresholds for the control of gastro-intestinal nematodes in lambs.

Targeted Selective Treatment (TST) is a gastrointestinal nematode (GIN) control strategy where anthelmintic treatment decisions are made at an individual animal level. TST has been proven to reduce anthelmintic use and subsequently slow down anthelmintic resistance development, however questions remain regarding optimal TST methods and their applicability across farms. In this study, the influence of Mineral and Vitamin (MV) supplementation on optimal energy utilisation (EU) TST thresholds was assessed on three Welsh farms. In total, 360 lambs were split into two groups, MV supplemented and control, and were treated with an anthelmintic against GIN at the midway point of the experiment. Lambs that improved their EU efficiency post treatment were deemed to have benefited from anthelmintic treatment. Optimal EU TST thresholds was determined for each treatment group per farm using Youden's J statistic where the treatment threshold retrospectively exhibiting the greatest combined sensitivity and specificity in correctly identifying lambs benefiting from treatment was deemed to be optimal. Results demonstrated that the optimal EU TST threshold was higher in MV supplemented groups at 0.72, 0.71 and 0.56 versus 0.58, 0.67, 0.51 for control groups on each respective farm. Identification of lambs for TST was more effective when using an optimised EU TST threshold, compared to when using the standard EU TST threshold of 0.66. The study highlights that applying standard EU TST thresholds may not be appropriate on all commercial farms with factors including MV status as noted in this study likely to influence optimal EU TST thresholds. Additional refinement of TST systems can further strengthen their applicability across sheep flocks.

Climate Change Mitigation Policies and Co-Impacts on Indigenous Health: A Scoping Review.

Climate change mitigation policies can either facilitate or hinder progress towards health equity, and can have particular implications for Indigenous health. We sought to summarize current knowledge about the potential impacts (co-benefits and co-harms) of climate mitigation policies and interventions on Indigenous health. Using a Kaupapa Maori theoretical positioning, we adapted a validated search strategy to identify studies for this scoping review. Our review included empirical and modeling studies that examined a range of climate change mitigation measures, with health-related outcomes analyzed by ethnicity or socioeconomic status. Data were extracted from published reports and summarized. We identified 36 studies that examined a diverse set of policy instruments, with the majority located in high-income countries. Most studies employed conventional Western research methodologies, and few examined potential impacts of particular relevance to Indigenous peoples. The existing body of knowledge is limited in the extent to which it can provide definitive evidence about co-benefits and co-harms for Indigenous health, with impacts highly dependent on individual policy characteristics and contextual factors. Improving the quality of evidence will require research partnerships with Indigenous communities and study designs that centralize Indigenous knowledges, values, realities and priorities.

A radical revision of the public health response to environmental crisis in a warming world: contributions of Indigenous knowledges and Indigenous feminist perspectives.

Indigenous peoples have long been successful at adapting to climatic and environmental changes. However, anthropogenic climatic crisis represents an epoch of intensified colonialism which poses particular challenges to Indigenous peoples throughout the world, including those in wealthier 'modern' nation states. Indigenous peoples also possess worldviews and traditional knowledge systems that are critical to climate mitigation and adaptation, yet, paradoxically, these are devalued and marginalized and have yet to be recognized as essential foundations of public health. In this article, we provide an overview of how public health policy and discourse fails Indigenous peoples living in the colonial nation states of Canada and Aotearoa New Zealand. We argue that addressing these systemic failures requires the incorporation of Indigenous knowledges and Indigenous feminist perspectives beyond superficial understandings in public health-related climate change policy and practice, and that systems transformation of this nature will in turn require a radical revision of settler understandings of the determinants of health. Further, public health climate change responses that centre Indigenous knowledges and Indigenous feminist perspectives as presented by Indigenous peoples themselves must underpin from local to global levels.

RéSUMé: Les peuples autochtones ont de tout temps réussi à s'adapter aux changements du climat et de leur environnement. La crise climatique anthropogène constitue toutefois une époque de colonialisme intensifié qui pose des difficultés particulières aux peuples autochtones du monde entier, y compris ceux des États-nations riches et « modernes ¼. Les peuples autochtones possèdent aussi des visions du monde et des systèmes de savoir traditionnels indispensables aux efforts d'atténuation et d'adaptation au changement climatique; paradoxalement, ces visions et systèmes sont dévalués et marginalisés et ne sont pas encore reconnus comme étant des bases essentielles de la santé publique. Dans cet article, nous expliquons en général en quoi les politiques et le discours de la santé publique laissent sur le carreau les peuples autochtones vivant dans les États-nations coloniaux du Canada et d'Aotearoa (la Nouvelle-Zélande). Nous faisons valoir que pour aborder ces échecs systémiques, il faut intégrer les savoirs autochtones et les perspectives féministes autochtones au-delà d'une compréhension superficielle des politiques et des pratiques de santé publique relatives au changement climatique, et qu'une telle transformation des systèmes exigera en retour une révision radicale des savoirs coloniaux sur les déterminants de la santé. Plus encore, les ripostes de la santé publique au changement climatique, que ce soit à l'échelle locale ou mondiale, doivent être centrées sur les savoirs autochtones et les perspectives féministes autochtones tels que présentés par les peuples autochtones eux-mêmes.

Further Considerations Towards an Effective and Efficient Oncology Drug Discovery DMPK Strategy.

BACKGROUND: DMPK data and knowledge are critical in maximising the probability of developing successful drugs via the application of in silico, in vitro and in vivo approaches in drug discovery. METHODS: The evaluation, optimisation and prediction of human pharmacokinetics is now a mainstay within drug discovery. These elements are at the heart of the 'right tissue' component of AstraZeneca's '5Rs framework' which, since its adoption, has resulted in increased success of Phase III clinical trials. With the plethora of DMPK related assays and models available, there is a need to continually refine and improve the effectiveness and efficiency of approaches best to facilitate the progression of quality compounds for human clinical testing. RESULTS: This article builds on previously published strategies from our laboratories, highlighting recent discoveries and successes, that brings our AstraZeneca Oncology DMPK strategy up to date. We review the core aspects of DMPK in Oncology drug discovery and highlight data recently generated in our laboratories that have influenced our screening cascade and experimental design. We present data and our experiences of employing cassette animal PK, as well as re-evaluating in vitro assay design for metabolic stability assessments and expanding our use of freshly excised animal and human tissue to best inform first time in human dosing and dose escalation studies. CONCLUSION: Application of our updated drug-drug interaction and central nervous system drug exposure strategies are exemplified, as is the impact of physiologically based pharmacokinetic and pharmacokinetic-pharmacodynamic modelling for human predictions.

Developing PreDICT - a fully integrated data platform for preclinical in vivo data: learning from experience.

In vivo models have been crucial for developing our understanding of key processes associated with human disease and developing novel therapeutics. These in vivo studies are becoming increasingly complex, requiring long-term efficacy data and additional supportive datasets such as pharmacokinetic profiles and analysis of multiple biomarkers of pharmacodynamic response and efficacy. Moreover, a new agent will be investigated in many different models and often in combination with other drugs. Despite advances across the industry integrating and analysing complex datasets, management of in vivo data remains an ongoing challenge across the industry. Here, we describe a project that has successfully delivered a working solution to integrate pharmacokinetic, biomarker and efficacy data, independent of therapy area.

Model-based drug discovery: implementation and impact.

Model-based drug discovery (MBDDx) aims to build and continuously improve the quantitative understanding of the relation between drug exposure (target engagement) efficacy and safety, to support target validation; to define compound property criteria for lead optimization and safety margins; to set the starting dose; and to predict human dose and scheduling for clinical candidates alone, or in combination with other medicines. AstraZeneca has systematically implemented MBDDx within all drug discovery programs, with a focused investment to build a preclinical modeling and simulation capability and an in vivo information platform and architecture, the implementation, impact and learning of which are discussed here.

Design and synthesis of long acting inhaled corticosteroids for the treatment of asthma.

In this Letter we present data for a novel series of ICS for the treatment of asthma. 'Inhalation by design' principles have been applied to a series of highly potent steroidal GR agonists, with a focus on optimising the potential therapeutic index in human. Pharmacokinetic properties were tuned with high intrinsic clearance and low oral bioavailability in mind, to minimise systemic exposure and reduce systemically driven adverse events. High CYP mediated clearance as well as glucuronidation were targeted to achieve high intrinsic clearance coupled with multiple routes of clearance to minimise drug-drug interactions. Furthermore, pharmaceutical properties such as stability, crystallinity and solubility were considered to ensure compatibility with a dry powder inhaler. This work culminated in the identification of the clinical candidate 15, which demonstrates preclinically the desired efficacy and safety profiles confirming its potential as an inhaled agent for the treatment of asthma.

Challenges of drug discovery in novel target space. The discovery and evaluation of PF-3893787: a novel histamine H4 receptor antagonist.

We describe the development of novel benzimidazoles as small molecule histamine H4 receptor (H4R) antagonists and their profiling in rat early toxicity studies. The discovery and optimisation of a second series of pyrimidine based antagonists is then described culminating in the identification of the clinical development candidate 13 (PF-3893787). The pre-clinical profile of 13 (PF-3893787) is presented including the development of a translatable biomarker. Our pragmatic approach to target selection, safety assessment, and testing for efficacy faced numerous challenges and we share a number of lessons which the team learned and which will assist us and others in future drug discovery projects.

PHRMA CPCDC initiative on predictive models of human pharmacokinetics, part 5: prediction of plasma concentration-time profiles in human by using the physiologically-based pharmacokinetic modeling approach.

The objective of this study is to assess the effectiveness of physiologically based pharmacokinetic (PBPK) models for simulating human plasma concentration-time profiles for the unique drug dataset of blinded data that has been assembled as part of a Pharmaceutical Research and Manufacturers of America initiative. Combinations of absorption, distribution, and clearance models were tested with a PBPK approach that has been developed from published equations. An assessment of the quality of the model predictions was made on the basis of the shape of the plasma time courses and related parameters. Up to 69% of the simulations of plasma time courses made in human demonstrated a medium to high degree of accuracy for intravenous pharmacokinetics, whereas this number decreased to 23% after oral administration based on the selected criteria. The simulations resulted in a general underestimation of drug exposure (Cmax and AUC0- t ). The explanations for this underestimation are diverse. Therefore, in general it may be due to underprediction of absorption parameters and/or overprediction of distribution or oral first-pass. The implications of compound properties are demonstrated. The PBPK approach based on in vitro-input data was as accurate as the approach based on in vivo data. Overall, the scientific benefit of this modeling study was to obtain more extensive characterization of predictions of human PK from PBPK methods.

PhRMA CPCDC initiative on predictive models of human pharmacokinetics, part 3: comparative assessement of prediction methods of human clearance.

The objective of this study was to evaluate the performance of various allometric and in vitro-in vivo extrapolation (IVIVE) methodologies with and without plasma protein binding corrections for the prediction of human intravenous (i.v.) clearance (CL). The objective was also to evaluate the IVIVE prediction methods with animal data. Methodologies were selected from the literature. Pharmaceutical Research and Manufacturers of America member companies contributed blinded datasets from preclinical and clinical studies for 108 compounds, among which 19 drugs had i.v. clinical pharmacokinetics data and were used in the analysis. In vivo and in vitro preclinical data were used to predict CL by 29 different methods. For many compounds, in vivo data from only two species (generally rat and dog) were available and/or the required in vitro data were missing, which meant some methods could not be properly evaluated. In addition, 66 methods of predicting oral (p.o.) area under the curve (AUCp.o. ) were evaluated for 107 compounds using rational combinations of i.v. CL and bioavailability (F), and direct scaling of observed p.o. CL from preclinical species. Various statistical and outlier techniques were employed to assess the predictability of each method. Across methods, the maximum success rate in predicting human CL for the 19 drugs was 100%, 94%, and 78% of the compounds with predictions falling within 10-fold, threefold, and twofold error, respectively, of the observed CL. In general, in vivo methods performed slightly better than IVIVE methods (at least in terms of measures of correlation and global concordance), with the fu intercept method and two-species-based allometry (rat-dog) being the best performing methods. IVIVE methods using microsomes (incorporating both plasma and microsomal binding) and hepatocytes (not incorporating binding) resulted in 75% and 78%, respectively, of the predictions falling within twofold error. IVIVE methods using other combinations of binding assumptions were much less accurate. The results for prediction of AUCp.o. were consistent with i.v. CL. However, the greatest challenge to successful prediction of human p.o. CL is the estimate of F in human. Overall, the results of this initiative confirmed predictive performance of common methodologies used to predict human CL.

PhRMA CPCDC initiative on predictive models of human pharmacokinetics, part 1: goals, properties of the PhRMA dataset, and comparison with literature datasets.

This study is part of the Pharmaceutical Research and Manufacturers of America (PhRMA) initiative on predictive models of efficacy, safety, and compound properties. The overall goal of this part was to assess the predictability of human pharmacokinetics (PK) from preclinical data and to provide comparisons of available prediction methods from the literature, as appropriate, using a representative blinded dataset of drug candidates. The key objectives were to (i) appropriately assemble and blind a diverse dataset of in vitro, preclinical in vivo, and clinical data for multiple drug candidates, (ii) evaluate the dataset with empirical and physiological methodologies from the literature used to predict human PK properties and plasma concentration-time profiles, (iii) compare the predicted properties with the observed clinical data to assess the prediction accuracy using routine statistical techniques and to evaluate prediction method(s) based on the degree of accuracy of each prediction method, and (iv) compile and summarize results for publication. Another objective was to provide a mechanistic understanding as to why one methodology provided better predictions than another, after analyzing the poor predictions. A total of 108 clinical lead compounds were collected from 12 PhRMA member companies. This dataset contains intravenous (n = 19) and oral pharmacokinetic data (n = 107) in humans as well as the corresponding preclinical in vitro, in vivo, and physicochemical data. All data were blinded to protect the anonymity of both the data and the company submitting the data. This manuscript, which is the first of a series of manuscripts, summarizes the PhRMA initiative and the 108 compound dataset. More details on the predictability of each method are reported in companion manuscripts.

PhRMA CPCDC initiative on predictive models of human pharmacokinetics, part 2: comparative assessment of prediction methods of human volume of distribution.

The objective of this study was to evaluate the performance of various empirical, semimechanistic and mechanistic methodologies with and without protein binding corrections for the prediction of human volume of distribution at steady state (Vss ). PhRMA member companies contributed a set of blinded data from preclinical and clinical studies, and 18 drugs with intravenous clinical pharmacokinetics (PK) data were available for the analysis. In vivo and in vitro preclinical data were used to predict Vss by 24 different methods. Various statistical and outlier techniques were employed to assess the predictability of each method. There was not simply one method that predicts Vss accurately for all compounds. Across methods, the maximum success rate in predicting human Vss was 100%, 94%, and 78% of the compounds with predictions falling within tenfold, threefold, and twofold error, respectively, of the observed Vss . Generally, the methods that made use of in vivo preclinical data were more predictive than those methods that relied solely on in vitro data. However, for many compounds, in vivo data from only two species (generally rat and dog) were available and/or the required in vitro data were missing, which meant some methods could not be properly evaluated. It is recommended to initially use the in vitro tissue composition-based equations to predict Vss in preclinical species and humans, putting the assumptions and compound properties into context. As in vivo data become available, these predictions should be reassessed and rationalized to indicate the level of confidence (uncertainty) in the human Vss prediction. The top three methods that perform strongly at integrating in vivo data in this way were the Øie-Tozer, the rat -dog-human proportionality equation, and the lumped-PBPK approach. Overall, the scientific benefit of this study was to obtain greater characterization of predictions of human Vss from several methods available in the literature.

PhRMA CPCDC initiative on predictive models of human pharmacokinetics, part 4: prediction of plasma concentration-time profiles in human from in vivo preclinical data by using the Wajima approach.

The objective of this study was to evaluate the performance of the Wajima allometry (Css -MRT) approach published in the literature, which is used to predict the human plasma concentration-time profiles from a scaling of preclinical species data. A diverse and blinded dataset of 108 compounds from PhRMA member companies was used in this evaluation. The human intravenous (i.v.) and oral (p.o.) pharmacokinetics (PK) data were available for 18 and 107 drugs, respectively. Three different scenarios were adopted for prediction of human PK profiles. In the first scenario, human clearance (CL) and steady-state volume of distribution (Vss ) were predicted by unbound fraction corrected intercept method (FCIM) and Øie-Tozer (OT) approaches, respectively. Quantitative structure activity relationship (QSAR)-based approaches (TSrat-dog ) based on compound descriptors together with rat and dog data were utilized in the second scenario. Finally, in the third scenario, CL and Vss were predicted using the FCIM and Jansson approaches, respectively. For the prediction of oral pharmacokinetics, the human bioavailability and absorption rate constant were assumed as the average of preclinical species. Various statistical techniques were used for assessing the accuracy of the simulation scenarios. The human CL and Vss were predicted within a threefold error range for about 75% of the i.v. drugs. However, the accuracy in predicting key p.o. PK parameters appeared to be lower with only 58% of simulations falling within threefold of observed parameters. The overall ability of the Css -MRT approach to predict the curve shape of the profile was in general poor and ranged between low to medium level of confidence for most of the predictions based on the selected criteria.

The discovery of indole-derived long acting beta2-adrenoceptor agonists for the treatment of asthma and COPD.

The design and profile of a series of indole containing long acting beta(2)-adrenoceptor agonists is described. Evaluation of these analogues using an in vitro guinea pig trachea tissue model demonstrates that analogues within this series have salmeterol-like duration of action with potential for long duration of action in humans.