Elarekibep (PRS-060/AZD1402), a new class of inhaled Anticalin medicine targeting IL-4Ra for type 2 endotype asthma.

BACKGROUND: Type 2 endotype asthma is driven by IL-4 and IL-13 signaling via IL-4Ra, which is highly expressed on airway epithelium, airway smooth muscle, and immunocytes in the respiratory mucosa, suggesting potential advantages of an inhalable antagonist. Lipocalin 1 (Lcn1), a 16 kDa protein abundant in human periciliary fluid, has a robust drug-like structure well suited to protein engineering, but it has never been used to make an inhaled Anticalin protein therapeutic. OBJECTIVES: We sought to reengineer Lcn1 into an inhalable IL-4Ra antagonist and assess its pharmacodynamic/kinetic profile. METHODS: Lcn1 was systematically modified by directed protein mutagenesis yielding a high-affinity, slowly dissociating, long-acting full antagonist of IL-4Ra designated PRS-060 with properties analogous to dupilumab, competitively antagonizing IL-4Ra-dependent cell proliferation, mucus induction, and eotaxin expression in vitro. Because PRS-060 displayed exquisite specificity for human IL-4Ra, with no cross-reactivity to rodents or higher primates, we created a new triple-humanized mouse model substituting human IL-4Ra, IL-4, and IL-13 at their correct syntenic murine loci to model clinical dosing. RESULTS: Inhaled PRS-060 strongly suppressed acute allergic inflammation indexes in triple-humanized mice with a duration of action longer than its bulk clearance, suggesting that it may act locally in the lung. CONCLUSION: Lcn1 can be reengineered into the Anticalin antagonist PRS-060 (elarekibep), exemplifying a new class of inhaled topical, long-acting therapeutic drugs with the potential to treat type 2 endotype asthma.

Improvements to in silico skin sensitisation predictions through privacy-preserving data sharing.

In silico models are often built solely on publicly available data which may mean that they are less predictive for proprietary chemical space. Data sharing initiatives can improve the performance of such models, but organisations are often unable to share their data due to the need to protect their business interests and maintain the confidentiality of the chemicals in their research and development programmes. In silico models like Derek Nexus, which use expert knowledge to develop structural alerts based on chemical toxicity, can use proprietary data to identify new areas of chemical space and/or refine existing alerts whilst still preserving the privacy of the confidential data. Five hundred and thirty seven proprietary chemicals with skin sensitisation data were shared which led to the implementation of 7 new alerts and 5 modified alerts, with a concomitant 19% increase in sensitivity and 3% increase in specificity of the model.

An Evaluation of the Occupational Health Hazards of Peptide Couplers.

Peptide couplers (also known as amide bond-forming reagents or coupling reagents) are broadly used in organic chemical syntheses, especially in the pharmaceutical industry. Yet, occupational health hazards associated with this chemical class are largely unexplored, which is disconcerting given the intrinsic reactivity of these compounds. Several case studies involving occupational exposures reported adverse respiratory and dermal health effects, providing initial evidence of chemical sensitization. To address the paucity of toxicological data, a pharmaceutical cross-industry task force was formed to evaluate and assess the potential of these compounds to cause eye and dermal irritation as well as corrosivity and dermal sensitization. The goal of our work was to inform health and safety professionals as well as pharmaceutical and organic chemists of the occupational health hazards associated with this chemical class. To that end, 25 of the most commonly used peptide couplers and five hydrolysis products were selected for in vivo, in vitro, and in silico testing. Our findings confirmed that dermal sensitization is a concern for this chemical class with 21/25 peptide couplers testing positive for dermal sensitization and 15 of these being strong/extreme sensitizers. We also found that dermal corrosion and irritation (8/25) as well as eye irritation (9/25) were health hazards associated with peptide couplers and their hydrolysis products (4/5 were dermal irritants or corrosive and 4/5 were eye irritants). Resulting outcomes were synthesized to inform decision making in peptide coupler selection and enable data-driven hazard communication to workers. The latter includes harmonized hazard classifications, appropriate handling recommendations, and accurate safety data sheets, which support the industrial hygiene hierarchy of control strategies and risk assessment. Our study demonstrates the merits of an integrated, in vivo -in silico analysis, applied here to the skin sensitization endpoint using the Computer-Aided Discovery and REdesign (CADRE) and Derek Nexus programs. We show that experimental data can improve predictive models by filling existing data gaps while, concurrently, providing computational insights into key initiating events and elucidating the chemical structural features contributing to adverse health effects. This interactive, interdisciplinary approach is consistent with Green Chemistry principles that seek to improve the selection and design of less hazardous reagents in industrial processes and applications.

How to resolve inconclusive predictions from defined approaches for skin sensitisation in OECD Guideline No. 497.

In June 2021 the Organisation for Economic Co-operation and Development published Guideline No. 497 on Defined Approaches for Skin Sensitisation (DASS GL). There are two DAs published, known as the 2o3 and the ITS. The 2o3 uses two concordant results from either the DPRA, KeratinoSens™, or the h-CLAT assays to predict hazard (sensitiser/non-sensitiser). The ITS applies a score to results from the DPRA, the h-CLAT and an in silico model to predict United Nations Globally Harmonized System (GHS) sub-categories (1A/1B/Not Classified). The ITS can use Derek Nexus as the in silico model (known as ITSv1) or use OECD QSAR Toolbox (known as ITSv2). As limitations of the individual in chemico/in vitro assays and in silico predictions are carried through to the DAs, inconclusive predictions are possible for chemicals with results in the borderline range, and chemicals with out of domain results. However, these inconclusive predictions can be resolved by applying a weight of evidence approach. Herein, four case studies are presented, each 'inconclusive' for skin sensitisation potential according to both DAs. A weight of evidence approach was applied to each using a robust scientific approach to provide a conclusive prediction, where possible, based on several additional, non-animal lines of evidence.

Updating the Dermal Sensitisation Thresholds using an expanded dataset and an in silico expert system.

The Dermal Sensitisation Thresholds (DST) are Thresholds of Toxicological Concern, which can be used to justify exposure-based waiving when conducting a skin sensitisation risk assessment. This study aimed to update the published DST values by expanding the size of the Local Lymph Node Assay dataset upon which they are based, whilst assigning chemical reactivity using an in silico expert system (Derek Nexus). The potency values within the expanded dataset fitted a similar gamma distribution to that observed for the original dataset. Derek Nexus was used to classify the sensitisation activity of the 1152 chemicals in the expanded dataset and to predict which chemicals belonged to a High Potency Category (HPC). This two-step classification led to three updated thresholds: a non-reactive DST of 710 µg/cm2 (based on 79 sensitisers), a reactive (non-HPC) DST of 73 µg/cm2 (based on 331 sensitisers) and an HPC DST of 1.0 µg/cm2 (based on 146 sensitisers). Despite the dataset containing twice as many sensitisers, these values are similar to the previously published thresholds, highlighting their robustness and increasing confidence in their use. By classifying reactivity in silico the updated DSTs can be applied within a skin sensitisation risk assessment in a reproducible, scalable and accessible manner.

Gut hormones profile after an Ivor Lewis gastro-esophagectomy and its relationship to delayed gastric emptying.

Delayed gastric emptying (DGE) is common after an Ivor Lewis gastro-esophagectomy (ILGO). The risk of a dilated conduit is the much-feared anastomotic leak. Therefore, prompt management of DGE is required. However, the pathophysiology of DGE is unclear. We proposed that post-ILGO patients with/without DGE have different gut hormone profiles (GHP). Consecutive patients undergoing an ILGO from 1 December 2017 to 31 November 2019 were recruited. Blood sampling was conducted on either day 4, 5, or 6 with baseline sample taken prior to a 193-kcal meal and after every 30 minutes for 2 hours. If patients received pyloric dilatation, a repeat profile was performed post-dilatation and were designated as had DGE. Analyses were conducted on the following groups: patient without dilatation (non-dilated) versus dilatation (dilated); and pre-dilatation versus post-dilatation. Gut hormone profiles analyzed were glucagon-like peptide-1 (GLP-1) and peptide tyrosine tyrosine (PYY) using radioimmunoassay. Of 65 patients, 24 (36.9%) had dilatation and 41 (63.1%) did not. For the non-dilated and dilated groups, there were no differences in day 4, 5, or 6 GLP-1 (P = 0.499) (95% confidence interval for non-dilated [2822.64, 4416.40] and dilated [2519.91, 3162.32]). However, PYY levels were raised in the non-dilated group (P = 0.021) (95% confidence interval for non-dilated [1620.38, 3005.75] and dilated [821.53, 1606.18]). Additionally, after pyloric dilatation, paired analysis showed no differences in GLP-1, but PYY levels were different at all time points and had an exaggerated post-prandial response. We conclude that DGE is associated with an obtunded PYY response. However, the exact nature of the association is not yet established.

Fractured Femoral Stems in Primary and Revision Hip Arthroplasties Revisited: Wrightington Experience.

BACKGROUND: The aim of this study is to present our experience in managing fractured femoral stems over the last 10 years for both primary and revision stems at our tertiary unit focusing on modes of failure and operative techniques. METHODS: This is a retrospective consecutive study of all patients with fractured femoral stems that were operatively managed in our unit between 2008 and 2018. Detailed radiographic evaluation (Paprosky classification) was undertaken and data collected on operative techniques used to extract distal fractured stem fragments. RESULTS: Thirty-five patients (35 hips) were included (25 men/10 women) with average age at time of presentation of 68 years (range, 29-93). Average body mass index was 30 (standard deviation, 3.8; range, 22.5-39). There were variety of stems both contemporary and historical, primary and revision cases (15 hips polished tapered cemented stems, 10 hips composite beam and miscellaneous stems, and 10 revision hip stems). The predominant mechanism of failure was fatigue due to cantilever bending in distally fixed stems. Surgical techniques used to extract distal fragment were drilling technique in 2 hips, cortical window in 13 hips, extended trochanteric osteotomy (ETO) in 5 hips, and proximal extraction in 15 hips. CONCLUSION: When faced with a contemporary fractured stem, drilling techniques into the distal fragment are unlikely to succeed. If a trochanteric osteotomy had been used at time of index surgery, this could be used again to aid proximal extraction with conventional revision instrumentations. The cortical window technique is useful but surgically demanding technique that is most successful in extracting polished tapered fractured stems particularly when an ETO is not planned for femoral reconstruction. Use of trephines can be useful for removal of longer, uncemented stems. Finally, an ETO might be necessary when other techniques have failed.

Hip replacement.

Total hip replacement is a frequently done and highly successful surgical intervention. The procedure is undertaken to relieve pain and improve function in individuals with advanced arthritis of the hip joint. Symptomatic osteoarthritis is the most common indication for surgery. In paper 1 of this Series, we focus on how patient factors should inform the surgical decision-making process. Substantial demands are placed upon modern implants, because patients expect to remain active for longer. We discuss the advances made in implant performance and the developments in perioperative practice that have reduced complications. Assessment of surgery outcomes should include patient-reported outcome measures and implant survival rates that are based on data from joint replacement registries. The high-profile failure of some widely used metal-on-metal prostheses has shown the shortcomings of the existing regulatory framework. We consider how proposed changes to the regulatory framework could influence safety.

A defined approach for predicting skin sensitisation hazard and potency based on the guided integration of in silico, in chemico and in vitro data using exclusion criteria.

A decision tree-based defined approach (DA) has been designed using exclusion criteria based on applicability domain knowledge of in chemico/in vitro information sources covering key events 1-3 in the skin sensitisation adverse outcome pathway and an in silico tool predicting the adverse outcome (Derek Nexus). The hypothesis is that using exclusion criteria to de-prioritise less applicable assays and/or in silico outcomes produces a rational, transparent, and reliable DA for the prediction of skin sensitisation potential. Five exclusion criteria have been established: Derek Nexus reasoning level, Derek Nexus negative prediction, metabolism, lipophilicity, and lysine-reactivity. These are used to prioritise the most suitable information sources for a given chemical and results from which are used in a '2 out of 3' approach to provide a prediction of hazard. A potency category (and corresponding GHS classification) is then assigned using a k-Nearest Neighbours model containing human and LLNA data. The DA correctly identified the hazard (sensitiser/non-sensitiser) for 85% and 86% of a dataset with reference LLNA and human data. The correct potency category was identified for 59% and 68% of chemicals, and the GHS classification accurately predicted for 73% and 76% with reference LLNA and human data, respectively.

Is patient satisfaction related to patient reported sounds from ceramic on ceramic total hip arthroplasty? A study of 265 hips.

INTRODUCTION: The ideal method and implant to perform total hip arthroplasty (THA) is still a debated topic. Ceramic on ceramic (CoC) bearings have favourable wear properties, but squeaking has been reported as an unwanted side effect. We aimed to determine the rate of noise generation from CoC hips and investigate whether there is a relationship with patient satisfaction. METHODS: A total of 246 consecutive CoC bearing uncemented THA were retrospectively identified in a single institution. Post-operatively patients were sent a postal questionnaire to evaluate their reported sounds and satisfaction with their THA. Uni- and multi-variate analyses were performed to identify potential predictor variables for reported post-operative sounds. RESULTS: Questionnaires were returned by 172 patients (70% return rate). 24% reported sounds from their hips with 11% reporting a squeak. Median satisfaction levels were minimally, but significantly less for "noisy" (9/10) than "quiet" hips (10/10) (median difference = - 1, 95% CI - 2 to 0, p < 0.001). Compared to those with "noisy" hips, patients with "quiet" hips were 1.7 times (95% CI 1.3-2.5, p = 0.0002) more likely to report a "forgotten" hip. Younger age (p < 0.043) and increased anteversion (p < 0.021) were predictors for reported sounds. CONCLUSION: We have identified a high rate of "noisy" hips in this series of CoC THA with a significant inverse relationship between "noisy" hips and patient satisfaction levels. In our unit, we are moving towards the use of ceramic on cross-linked polyethylene bearings as a result of these findings and the excellent survivorship of this bearing combination.

Does oversizing an uncemented cup increase post-operative pain in primary total hip arthroplasty?

INTRODUCTION: It has been suggested that one of the factors related to persistent post-operative pain following total hip arthroplasty (THA) is to over sizing of the acetabular component. In order to investigate this potential issue, we retrospectively analysed a series of consecutive uncemented THA. We assessed the incidence of persistent post-operative pain and the size difference between the implanted acetabular component and the native femoral head. METHODS: A total of 265 consecutive THAs were retrospectively identified. Standardised pre-operative radiographs were analysed using validated techniques to determine the native femoral head diameter. Post-operative standardised radiographs were reviewed and the acetabular orientation determined. Patients were sent postal questionnaires regarding their outcome and level of pain. RESULTS: Questionnaires were returned by 169 patients (189 hips, 71% response rate). A total of 17 were excluded due to inadequate radiographs., leaving 172 THA in the study group. The mean native femoral head (NFH) size was 47 mm. The most common implanted acetabular component size was 52 mm. The mean difference in cup to NFH diameter (delta) was 5.7 mm (range - 6.1 to 15.4 mm; 95% CI 5.3-6.2 mm). A delta of > 6 mm was found to be significant for predicting persistent post-operative pain (RR = 1.81; 95% CI 1.1-3.1; P = 0.027). CONCLUSION: Our study confirms that a delta of > 6 mm is associated with an increased risk of persistent post-operative pain following THA. We recommend pre-operative templating in all uncemented THA to ensure the planned acetabular component is no more than 6 mm larger than the NFH diameter.

Assessment and Reproducibility of Quantitative Structure-Activity Relationship Models by the Nonexpert.

Model reliability is generally assessed and reported as an intrinsic component of quantitative structure-activity relationship (QSAR) publications; it can be evaluated using defined quality criteria such as the Organisation for Economic Cooperation and Development (OECD) principles for the validation of QSARs. However, less emphasis is afforded to the assessment of model reproducibility, particularly by users who may wish to use model outcomes for decision making, but who are not QSAR experts. In this study we identified a range of QSARs in the area of absorption, distribution, metabolism, and elimination (ADME) prediction and assessed their adherence to the OECD principles, as well as investigating their reproducibility by scientists without expertise in QSAR. Here, 85 papers were reviewed, reporting over 80 models for 31 ADME-related endpoints. Of these, 12 models were identified that fulfilled at least 4 of the 5 OECD principles and 3 of these 12 could be readily reproduced. Published QSAR models should aim to meet a standard level of quality and be clearly communicated, ensuring their reproducibility, to progress the uptake of the models in both research and regulatory landscapes. A pragmatic workflow for implementing published QSAR models and recommendations to modellers, for publishing models with greater usability, are presented herein.

Making reliable negative predictions of human skin sensitisation using an in silico fragmentation approach.

A previously published fragmentation method for making reliable negative in silico predictions has been applied to the problem of predicting skin sensitisation in humans, making use of a dataset of over 2750 chemicals with publicly available skin sensitisation data from 18 in vivo assays. An assay hierarchy was designed to enable the classification of chemicals within this dataset as either sensitisers or non-sensitisers where data from more than one in vivo test was available. The negative prediction approach was validated internally, using a 5-fold cross-validation, and externally, against a proprietary dataset of approximately 1000 chemicals with in vivo reference data shared by members of the pharmaceutical, nutritional, and personal care industries. The negative predictivity for this proprietary dataset was high in all cases (>75%), and the model was also able to identify structural features that resulted in a lower accuracy or a higher uncertainty in the negative prediction, termed misclassified and unclassified features respectively. These features could serve as an aid for further expert assessment of the negative in silico prediction.

A quantitative in silico model for predicting skin sensitization using a nearest neighbours approach within expert-derived structure-activity alert spaces.

Dermal contact with chemicals may lead to an inflammatory reaction known as allergic contact dermatitis. Consequently, it is important to assess new and existing chemicals for their skin sensitizing potential and to mitigate exposure accordingly. There is an urgent need to develop quantitative non-animal methods to better predict the potency of potential sensitizers, driven largely by European Union (EU) Regulation 1223/2009, which forbids the use of animal tests for cosmetic ingredients sold in the EU. A Nearest Neighbours in silico model was developed using an in-house dataset of 1096 murine local lymph node (LLNA) studies. The EC3 value (the effective concentration of the test substance producing a threefold increase in the stimulation index compared to controls) of a given chemical was predicted using the weighted average of EC3 values of up to 10 most similar compounds within the same mechanistic space (as defined by activating the same Derek skin sensitization alert). The model was validated using previously unseen internal (n = 45) and external (n = 103) data and accuracy of predictions assessed using a threefold error, fivefold error, European Centre for Ecotoxicology and Toxicology of Chemicals (ECETOC) and Globally Harmonized System of Classification and Labelling of Chemicals (GHS) classifications. In particular, the model predicts the GHS skin sensitization category of compounds well, predicting 64% of chemicals in an external test set within the correct category. Of the remaining chemicals in the previously unseen dataset, 25% were over-predicted (GHS 1A predicted: GHS 1B experimentally) and 11% were under-predicted (GHS 1B predicted: GHS 1A experimentally). Copyright © 2017 John Wiley & Sons, Ltd.

Predicting skin sensitisation using a decision tree integrated testing strategy with an in silico model and in chemico/in vitro assays.

There is a pressing need for non-animal methods to predict skin sensitisation potential and a number of in chemico and in vitro assays have been designed with this in mind. However, some compounds can fall outside the applicability domain of these in chemico/in vitro assays and may not be predicted accurately. Rule-based in silico models such as Derek Nexus are expert-derived from animal and/or human data and the mechanism-based alert domain can take a number of factors into account (e.g. abiotic/biotic activation). Therefore, Derek Nexus may be able to predict for compounds outside the applicability domain of in chemico/in vitro assays. To this end, an integrated testing strategy (ITS) decision tree using Derek Nexus and a maximum of two assays (from DPRA, KeratinoSens, LuSens, h-CLAT and U-SENS) was developed. Generally, the decision tree improved upon other ITS evaluated in this study with positive and negative predictivity calculated as 86% and 81%, respectively. Our results demonstrate that an ITS using an in silico model such as Derek Nexus with a maximum of two in chemico/in vitro assays can predict the sensitising potential of a number of chemicals, including those outside the applicability domain of existing non-animal assays.

Neutrophil-derived Activin-A moderates their pro-NETotic activity and attenuates collateral tissue damage caused by Influenza A virus infection.

Background: Pre-neutrophils, while developing in the bone marrow, transcribe the Inhba gene and synthesize Activin-A protein, which they store and release at the earliest stage of their activation in the periphery. However, the role of neutrophil-derived Activin-A is not completely understood. Methods: To address this issue, we developed a neutrophil-specific Activin-A-deficient animal model (S100a8-Cre/Inhba fl/fl mice) and analyzed the immune response to Influenza A virus (IAV) infection. More specifically, evaluation of body weight and lung mechanics, molecular and cellular analyses of bronchoalveolar lavage fluids, flow cytometry and cell sorting of lung cells, as well as histopathological analysis of lung tissues, were performed in PBS-treated and IAV-infected transgenic animals. Results: We found that neutrophil-specific Activin-A deficiency led to exacerbated pulmonary inflammation and widespread hemorrhagic histopathology in the lungs of IAV-infected animals that was associated with an exuberant production of neutrophil extracellular traps (NETs). Moreover, deletion of the Activin-A receptor ALK4/ACVR1B in neutrophils exacerbated IAV-induced pathology as well, suggesting that neutrophils themselves are potential targets of Activin-A-mediated signaling. The pro-NETotic tendency of Activin-A-deficient neutrophils was further verified in the context of thioglycollate-induced peritonitis, a model characterized by robust peritoneal neutrophilia. Of importance, transcriptome analysis of Activin-A-deficient neutrophils revealed alterations consistent with a predisposition for NET release. Conclusion: Collectively, our data demonstrate that Activin-A, secreted by neutrophils upon their activation in the periphery, acts as a feedback mechanism to moderate their pro-NETotic tendency and limit the collateral tissue damage caused by neutrophil excess activation during the inflammatory response.

Sensitization Assessment of Extractables and Leachables in Pharmaceuticals: ELSIE Database Analysis.

Quality by design is the foundation of the risk management framework for extractables and leachables (E&Ls) recommended by the Extractables and Leachables Safety Information Exchange (ELSIE). Following these principles during the selection of materials for pharmaceutical product development minimizes the presence of highly toxic substances and decreases the health risk of potential leachables in the drug product. Therefore, in the context of the broad arena of chemicals, it is important to distinguish E&Ls as a subset of chemicals and evaluate this relevant chemical space to derive appropriate analytical and safety thresholds. When considering the health hazards posed by E&Ls, one area presenting a challenge is understanding the sensitization potential and whether it poses a risk to patients. A dataset of E&Ls compiled by ELSIE (n=466) was analysed to determine the prevalence and potency of skin sensitizers in this chemical subset and explore a scientifically justified approach to the sensitization assessment of potential leachables in parenteral drug products. Approximately half of the compounds (56%, 259/466) had sensitization data recorded in the ELSIE database and of these, 20% (52/259) are potential skin sensitizers. Only 3% (8/259) of the E&L dataset with sensitization data were considered potent (strong or extreme) sensitizers following in silico analysis and expert review, illustrating that potent sensitizers are not routinely observed as leachables in pharmaceutical products. Our analysis highlights that in silico potency prediction and expert review are key tools during the sensitization assessment process for E&Ls. The results confirm where material selection is anticipated to mitigate the risk of presence of strong and/or extreme sensitizers (e.g., extractable testing via ISO 10993-10), and that implementing thresholds per ICH M7 and/or Masuda-Herrera et al. provides a reasonably conservative approach for establishing the analytical testing and safety thresholds.

Metal allergy in primary and revision total knee arthroplasty : a scoping review and evidence-based practical approach.

AIMS: Metal allergy in knee arthroplasty patients is a controversial topic. We aimed to conduct a scoping review to clarify the management of metal allergy in primary and revision total knee arthroplasty (TKA). METHODS: Studies were identified by searching electronic databases: Cochrane Central Register of Controlled Trials, Ovid MEDLINE, and Embase, from their inception to November 2020, for studies evaluating TKA patients with metal hypersensitivity/allergy. All studies reporting on diagnosing or managing metal hypersensitivity in TKA were included. Data were extracted and summarized based on study design, study population, interventions and outcomes. A practical guide is then formulated based on the available evidence. RESULTS: We included 38 heterogeneous studies (two randomized controlled trials, six comparative studies, 19 case series, and 11 case reports). The evidence indicates that metal hypersensitivity is a rare complication with some histopathological features leading to pain and dissatisfaction with no reliable screening tests preoperatively. Hypoallergenic implants are viable alternatives for patients with self-reported/confirmed metal hypersensitivity if declared preoperatively; however, concerns remain over their long-term outcomes with ceramic implants outperforming titanium nitride-coated implants and informed consent is paramount. For patients presenting with painful TKA, metal hypersensitivity is a diagnosis of exclusion where patch skin testing, lymphocyte transformation test, and synovial biopsies are useful adjuncts before revision surgery is undertaken to hypoallergenic implants with shared decision-making and informed consent. CONCLUSION: Using the limited available evidence in the literature, we provide a practical approach to metal hypersensitivity in TKA patients. Future national/registry-based studies are needed to identify the scale of metal hypersensitivity, agreed diagnostic criteria, and management strategies. Cite this article: Bone Jt Open 2021;2(10):785-795.

Beyond adverse outcome pathways: making toxicity predictions from event networks, SAR models, data and knowledge.

Adverse outcome pathways have shown themselves to be useful ways of understanding and expressing knowledge about sequences of events that lead to adverse outcomes (AOs) such as toxicity. In this paper we use the building blocks of adverse outcome pathways-namely key events (KEs) and key event relationships-to construct networks which can be used to make predictions of the likelihood of AOs. The networks of KEs are augmented by data from and knowledge about assays as well as by structure activity relationship predictions linking chemical classes to the observation of KEs. These inputs are combined within a reasoning framework to produce an information-rich display of the relevant knowledge and data and predictions of AOs both in the abstract case and for individual chemicals. Illustrative examples are given for skin sensitization, reprotoxicity and non-genotoxic carcinogenicity.