iNVERTOX: Rapid intelligent in silico prediction of sub-lethal ecotoxicological effects in invertebrates following pharmaceutical exposure

INVERTOX项目将是第一个发现和预测微量药物残留对生活在英国和国际淡水中的小型生态关键无脊椎动物生物的表型和分子水平影响的项目，这些生物目前受到人类活动的影响。药物被广泛认为是我们环境中的生物活性污染物，在全球范围内被测量到非常低的浓度。它们主要是在消耗的人类和动物药物排出后进入环境的，并已被证明对废水处理具有抵抗力。这导致它们持续和长时间地注入到接受水的集水区。最近，在对三种药物对生物群的毒性进行广泛研究后，三种药物被列入新出现的优先污染物的“观察名单”。然而，环境中药物污染的发生和多样性进一步扩大，在任何时候在河水、沉积物、土壤和最近甚至在环境物种中检测到的化合物都要多得多。因此，考虑到这个问题的规模，衡量它们对我们环境的影响太慢了，也太费力了。需要更多创新和快速的方法来了解和减轻这些可能对我们的环境造成的任何影响。现实地说，这现在必须涉及某种形式的高级计算模型，以利用我们拥有的有限信息来预测额外药物的效果。此外，传统的微污染物生态毒性测试使用致死剂量，而就药物而言，这些剂量往往远远高于测得的环境浓度。这表明，需要研究更微妙的影响，以此作为对风险的更准确评估。在某些情况下，这种微小的变化导致了严重的生态系统失衡，这对野生动物、我们的环境以及潜在的人类健康都有间接影响。这些所谓的“亚致死表型效应”往往更难确定，而确定与药物接触的明确联系是极具挑战性的。这个项目的目的是研究和模拟模式淡水底栖无脊椎动物物种(Gammarus Pulex)的四种亚致死表型效应，包括生长速度、摄食速度、通风和运动，在受控暴露于低剂量的水环境中通常存在的60多种药物后。除此之外，生物体在分子水平上的变化将形成一个新的中心焦点，并使生物群能够在基本水平上对此类暴露做出反应的知识发现。这将通过代谢组学实现，代谢组学是对暴露于环境污染物后存在于生物系统中的数千个小分子进行测量。最后，也是最重要的是，这些信息将被用来建立一套先进的计算模型，使用新的机器学习工具，使用户能够快速筛选药物对硅胶中生物群的潜在表型和分子水平的影响，并最大限度地减少或消除为此目的而延长使用动物进行生态毒性测试的需要。因此，该项目将在方法上具有开创性，并汇集伦敦国王学院、伦敦弗朗西斯·克里克研究所和全球制药领先者阿斯利康的最好的学术和行业专业知识，以迅速和负责任地了解药品对环境生物体的影响。

The iNVERTOX project will be the first of its kind to discover and predict both phenotypic and molecular level effects of trace pharmaceutical residues on small, but ecologically critical invertebrate organisms living in UK and international freshwaters which are now impacted by human activity. Pharmaceuticals are widely recognised as bioactive contaminants in our environment having been measured globally at very low concentrations. They enter the environment predominantly following excretion of consumed human and animal medicines and have been shown to be resistant to wastewater treatment. This leads to their consistent and prolonged infusion into receiving water catchments. Recently, three pharmaceuticals were placed on a "watch-list" of emerging priority pollutants following extensive studies of their toxicity to biota. However, the occurrence and diversity of pharmaceuticals contamination in the environment extends much further, with significantly more compounds detected in river water, sediments, soils and recently even in environmental species at any one time. Therefore given the scale of this problem, measurement of their effects on our environment is far too slow and laborious. More innovative and rapid approaches are required to understand and mitigate any effects these may have on our environment. Realistically, this must now involve some form of advanced computational modelling to use the limited information we have to predict the effects of additional pharmaceuticals. Moreover, traditional ecotoxicity testing for micro-pollutants use lethal doses and in the case of pharmaceuticals, these are often much higher than measured environmental concentrations. This suggests that more subtle effects need to be researched instead as a more accurate assessment of risk. In some cases, such small changes have resulted in a significant ecosystem imbalance which has indirect effects on wildlife, our environment and potentially also on human health. These so called, "sub-lethal phenotypic effects" are often more difficult to determine and establishing defined links to a pharmaceutical exposure is extremely challenging. The aim of this project is to study and model four sub-lethal phenotypic effects on a model freshwater benthic invertebrate species (Gammarus pulex) including growth rate, feeding rate, ventilation and locomotion following controlled exposure to low doses of over 60 pharmaceuticals typically found in the aquatic environment. In addition to this, changes in the organism at a molecular level will form a novel, central focus and enable knowledge discovery of how biota respond to such exposures at a fundamental level. This will be achieved via metabolomics, which is the measurement of thousands of small molecules present in a biological system following exposure to environmental contaminants. Lastly, and most importantly, this information will be used to build an set of advanced computational models using new machine learning tools to rapidly allow a user to screen potential phenotypic and molecular level effects of a pharmaceutical on biota in silico and minimise or remove the need for extended use of animals in ecotoxicity testing for this purpose. This project will therefore be pioneering in its approach and draw together the best academic and industry expertise from King's College London, The Francis Crick Institute, London and a global leader in pharmaceuticals, AstraZeneca, to rapidly and responsibly understand the effects of pharmaceuticals on environmental organisms.