Hierarchical cluster analysis and nonlinear mixed-effects modelling for candidate biomarker detection in preclinical models of cancer.

BACKGROUND: Preclinical models of cancer can be of translational benefit when assessing how different biomarkers are regulated in response to particular treatments. Detection of molecular biomarkers in preclinical models of cancer is difficult due inter-animal variability in responses, combined with limited accessibility of longitudinal data. METHODS: Nonlinear mixed-effects modelling (NLME) was used to analyse tumour growth data based on expected tumour growth rates observed 7 days after initial doses (DD7) of Radiotherapy (RT) and Combination of RT with DNA Damage Response Inhibitors (DDRi). Cox regression was performed to confirm an association between DD7 and survival. Hierarchical Cluster Analysis (HCA) was then used to identify candidate biomarkers impacting responses to RT and RT/DDRi and these were validated using NLME. RESULTS: Cox regression confirmed significant associations between DD7 and survival. HCA of RT treated samples, combined with NLME confirmed significant associations between DD7 and Cluster specific CD8+ Ki67 MFI, as well as DD7 and cluster specific Natural Killer cell density in RT treated mice. CONCLUSION: Application of NLME, as well as HCA of candidate biomarkers may provide additional avenues to assess the effect of RT in MC38 syngeneic tumour models. Additional studies would need to be conducted to confirm association between DD7 and biomarkers in RT/DDRi treated mice.

Manchester Intermittent Diet in Gestational Diabetes Acceptability Study (MIDDAS-GDM): a two-arm randomised feasibility protocol trial of an intermittent low-energy diet (ILED) in women with gestational diabetes and obesity in Greater Manchester.

INTRODUCTION: The prevalence of gestational diabetes mellitus (GDM) is rising in the UK and is associated with maternal and neonatal complications. National Institute for Health and Care Excellence guidance advises first-line management with healthy eating and physical activity which is only moderately effective for achieving glycaemic targets. Approximately 30% of women require medication with metformin and/or insulin. There is currently no strong evidence base for any particular dietary regimen to improve outcomes in GDM. Intermittent low-energy diets (ILEDs) are associated with improved glycaemic control and reduced insulin resistance in type 2 diabetes and could be a viable option in the management of GDM. This study aims to test the safety, feasibility and acceptability of an ILED intervention among women with GDM compared with best National Health Service (NHS) care. METHOD AND ANALYSIS: We aim to recruit 48 women with GDM diagnosed between 24 and 30 weeks gestation from antenatal clinics at Wythenshawe and St Mary's hospitals, Manchester Foundation Trust, over 13 months starting in November 2022. Participants will be randomised (1:1) to ILED (2 low-energy diet days/week of 1000 kcal and 5 days/week of the best NHS care healthy diet and physical activity advice) or best NHS care 7 days/week until delivery of their baby. Primary outcomes include uptake and retention of participants to the trial and adherence to both dietary interventions. Safety outcomes will include birth weight, gestational age at delivery, neonatal hypoglycaemic episodes requiring intervention, neonatal hyperbilirubinaemia, admission to special care baby unit or neonatal intensive care unit, stillbirths, the percentage of women with hypoglycaemic episodes requiring third-party assistance, and significant maternal ketonaemia (defined as ≥1.0 mmol/L). Secondary outcomes will assess the fidelity of delivery of the interventions, and qualitative analysis of participant and healthcare professionals' experiences of the diet. Exploratory outcomes include the number of women requiring metformin and/or insulin. ETHICS AND DISSEMINATION: Ethical approval has been granted by the Cambridge East Research Ethics Committee (22/EE/0119). Findings will be disseminated via publication in peer-reviewed journals, conference presentations and shared with diabetes charitable bodies and organisations in the UK, such as Diabetes UK and the Association of British Clinical Diabetologists. TRIAL REGISTRATION NUMBER: NCT05344066.

Wearable Technology: A Wellbeing Option for Serving Police Officers and Staff? A Comparison of Results of a Pilot Study with Firearms Officers and a Group of Mixed Officers and Staff.

The high-stress nature of policing contributes to deterioration of officer health and wellbeing as well as high levels of absenteeism and attrition. Wearable technology (WT) has been identified as a potential tool that can help in improving officer health and wellbeing. This pilot study aimed to give initial insight into acceptability and engagement with WT amongst officers. The study also aimed to uncover any notable areas for exploration in future research within the domain of officer health and wellbeing. Two groups were observed, firearms officers and a mixed group of officers. Participants wore the WT for an extended period, completed a variety of health and wellbeing questionnaires and discussed their experience in focus groups. Firearms officers and mixed group officers displayed similar sleep efficiency, but firearms officers have worse sleep consistency and sleep performance. Firearms officers appear to have higher HRV and a slightly lower resting heart rate. Both groups display reasonable acceptance of the use of WT, speaking favorably during the focus groups of how monitoring the data had improved their quality of life in terms of their understanding of sleep, wellbeing and how they had consequently completed lifestyle modification. WT offers some promise in managing officer health and wellbeing; studies with larger sample sizes are needed to confirm this.

Long COVID quality of life and healthcare experiences in the UK: a mixed method online survey.

PURPOSE: The complexity of long COVID and its diverse symptom profile contributes to unprecedented challenges for patients, clinicians, and healthcare services. The threat of long COVID remains ignored by Governments, the media and public health messaging, and patients' experiences must be heard through understanding of the lived experience. This study aimed to understand the lived experience of those living with long COVID. METHODS: An online web-based survey was designed using Patient and Public Involvement and Engagement (PPIE) to increase understanding of the lived experiences of long COVID, and was distributed through PPIE groups, social media, and word of mouth. The survey used closed and open questions relating to demographics, pre- and post-COVID-19 health quality of life, daily activities and long COVID experiences. RESULTS: Within our sample of 132 people living with long COVID, the findings highlight that individuals are being severely impacted by their symptoms and are unable to or limited in participating in their daily activities, reducing quality of life. Long COVID places strain on relationships, the ability to live life fully and is detrimental to mental health. Varying health care experiences are described by participants, with reports of medical gaslighting and inadequate support received. CONCLUSIONS: Long COVID has a severe impact on the ability to live life fully, and strains mental health. The appropriate mechanisms and support services are needed to support those living with long COVID and manage symptoms.

Skipping a pillar does not make for strong foundations: Pharmacokinetic-pharmacodynamic reasoning behind the shape of dose-response relationships in oncology.

Dose-response analysis is often applied to the quantification of drug-effect especially for slowly responding disease end points where a comparison is made across dose levels after a particular period of treatment. It has long been recognized that exposure - response is more appropriate than dose-response. However, trials necessarily are designed as dose-response experiments. Second, a wide range of functional forms are used to express relationships between dose and response. These considerations are also important for clinical development because pharmacokinetic (PK; and variability) plus pharmacokinetic-pharmacodynamic modeling may allow one to anticipate the shape of the dose-response curve and so the trial design. Here, we describe how the location and steepness of the dose response is determined by the PKs of the compound being tested and its exposure-response relationship in terms of potency (location), efficacy (maximum effect) and Hill coefficient (steepness). Thus, the location (50% effective dose [ED50 ]) is dependent not only on the potency (half-maximal effective concentration) but also the compound's PKs. Similarly, the steepness of the dose response is shown to be a function of the half-life of the drug. It is also shown that the shape of relationship varies dependent on the assumed time course of the disease. This is important in the context of drug-discovery where the in vivo potencies of compounds are compared as well as when considering an analysis of summary data (for example, model-based meta-analysis) for clinical decision making.

Protocol for a cluster randomised waitlist-controlled trial of a goal-based behaviour change intervention for employees in workplaces enrolled in health and wellbeing initiatives.

Many workplaces offer health and wellbeing initiatives to their staff as recommended by international and national health organisations. Despite their potential, the influence of these initiatives on health behaviour appears limited and evaluations of their effectiveness are rare. In this research, we propose evaluating the effectiveness of an established behaviour change intervention in a new workplace context. The intervention, 'mental contrasting plus implementation intentions', supports staff in achieving their health and wellbeing goals by encouraging them to compare the future with the present and to develop a plan for overcoming anticipated obstacles. We conducted a systematic review that identified only three trials of this intervention in workplaces and all of them were conducted within healthcare organisations. Our research will be the first to evaluate the effectiveness of mental contrasting outside a solely healthcare context. We propose including staff from 60 organisations, 30 in the intervention and 30 in a waitlisted control group. The findings will contribute to a better understanding of how to empower and support staff to improve their health and wellbeing. Trial registration: ISRCTN17828539.

Mixed effects modeling of radiotherapy in combination with immune checkpoint blockade or inhibitors of the DNA damage response pathway.

Dosage optimization to maximize efficacy and minimize toxicity is a potential issue when administering radiotherapy (RT) in combination with immune checkpoint blockade (ICB) or inhibitors of the DNA Damage Response Pathway (DDRi) in the clinic. Preclinical models and mathematical modeling can help identify ideal dosage schedules to observe beneficial effects of a tri-therapy. The aim of this study is to describe a mathematical model to capture the impact of RT in combination with inhibitors of the DNA Damage Response Pathway or blockade of the immune checkpoint protein - programmed death ligand 1 (PD-L1). This model describes how RT mediated activation of antigen presenting cells can induce an increase in cytolytic T cells capable of targeting tumor cells, and how combination drugs can potentiate the immune response by inhibiting the rate of T cell exhaustion. The model was fitted using preclinical data, where MC38 tumors were treated in vivo with RT alone or in combination with anti-PD-L1 as well as with either olaparib or the ataxia telangiectasia mutated (ATM) inhibitor-AZD0156. The model successfully described the observed data and goodness-of-fit, using visual predictive checks also confirmed a successful internal model validation for each treatment modality. The results demonstrated that the anti-PD-L1 effect in combination with RT was maximal in vivo and any additional benefit of DDRi at the given dosage and schedule used was undetectable. Model fit results indicated AZD0156 to be a more potent DDRi than olaparib. Simulations of alternative doses indicated that reducing efficacy of anti-PD-L1 by 68% would potentially provide evidence for a benefit of ATM inhibition in combination with ICB and increase the relative efficacy of tri-therapy.

Quantitative Systems Pharmacology and Machine Learning: A Match Made in Heaven or Hell?

As pharmaceutical development moves from early-stage in vitro experimentation to later in vivo and subsequent clinical trials, data and knowledge are acquired across multiple time and length scales, from the subcellular to whole patient cohort scale. Realizing the potential of this data for informing decision making in pharmaceutical development requires the individual and combined application of machine learning (ML) and mechanistic multiscale mathematical modeling approaches. Here we outline how these two approaches, both individually and in tandem, can be applied at different stages of the drug discovery and development pipeline to inform decision making compound development. The importance of discerning between knowledge and data are highlighted in informing the initial use of ML or mechanistic quantitative systems pharmacology (QSP) models. We discuss the application of sensitivity and structural identifiability analyses of QSP models in informing future experimental studies to which ML may be applied, as well as how ML approaches can be used to inform mechanistic model development. Relevant literature studies are highlighted and we close by discussing caveats regarding the application of each approach in an age of constant data acquisition. SIGNIFICANCE STATEMENT: We consider when best to apply machine learning (ML) and mechanistic quantitative systems pharmacology (QSP) approaches in the context of the drug discovery and development pipeline. We discuss the importance of prior knowledge and data available for the system of interest and how this informs the individual and combined application of ML and QSP approaches at each stage of the pipeline.

Manchester Intermittent and Daily diet Type 1 Diabetes App Study (MIDDAS-Type 1): protocol for a randomised feasibility trial of an intermittent and continuous low-energy diet in patients with type 1 diabetes and overweight and obesity.

INTRODUCTION: Rising levels of overweight and obesity among people with type 1 diabetes (T1D) contribute to insulin resistance, dyslipidaemia, retinopathy, cardiometabolic complications and psychological morbidity. Continuous low-energy diets (CLED) providing approximately 800 kcal (3347 kJ)/day can produce significant weight loss in type 2 diabetes, and intermittent low-energy diets (ILED) may be an alternative. The Manchester Intermittent and Daily diet Type 1 Diabetes App Study (MIDDAS-Type 1) aims to assess the safety, acceptability and feasibility of remotely delivered ILED and CLED programmes for people with T1D and overweight and obesity. METHODS AND ANALYSIS: Twelve participants with T1D and body mass index ≥27.5 kg/m2 (≥25 kg/m2 in high-risk ethnic minorities) recruited from an National Health Service (NHS) trust and research register in England will be randomised to a remotely delivered CLED (n=6) or ILED (n=6) for 12 weeks. The CLED includes a daily Optifast 850 kcal (3556 kJ) 75 g carbohydrate formula diet. The ILED includes 2 days/week of Optifast and 5 days of a portion-controlled Mediterranean diet (170-250 g carbohydrate/day). Both groups will receive matched high-frequency remote support from a dietitian, nurse and psychologist via telephone and/or the Oviva app. The primary outcome will assess safety (occurrence of severe hypoglycaemia, ketonaemia, ketoacidosis and time above and below target blood glucose). Secondary outcomes include study uptake, retention, dietary adherence, acceptability, intervention delivery fidelity and potential efficacy in relation to change in weight, insulin requirements, glycated haemoglobin, lipids, insulin resistance (estimated glucose disposal rate) and quality of life. Participants will be invited for optional repeat measurements at 52 weeks. ETHICS AND DISSEMINATION: The trial protocol (V4.0/08.06.2022) was granted ethical approval by Cambridge East Research Ethics Committee (Ref: 21/EE/0014). The study will inform progression to a full-scale randomised controlled trial to test the efficacy of these programmes for patients with T1D and overweight and obesity. TRIAL REGISTRATION NUMBER: NCT04674384; Pre-results.

Radiation in Combination with Immune Checkpoint Blockade and DNA Damage Response Inhibitors in Mice: Dosage Optimization in MC38 Syngeneic Tumors via Modelling and Simulation.

Clinical trials assessing the impact of radiotherapy (RT) in combination with DNA damage response pathway inhibitors (DDRis) and/or immune checkpoint blockade are currently ongoing. However, current methods for optimizing dosage and schedule are limited. A mathematical model was developed to capture the impacts of RT in combination with DDRi and/or anti-PD-L1 [immune checkpoint inhibitor (ICI)] on tumor immune interactions in the MC38 syngeneic tumor model. The model was fitted to datasets that assessed the impact of RT in combination with the DNA protein kinase inhibitor (DNAPKi) AZD7648. The model was further fitted to datasets from studies that were used to assess both RT/ICI combinations as well as RT/ICI combinations followed by concurrent administration of the poly ADP ribose polymerase inhibitor (PARPi) olaparib. Nonlinear mixed-effects modeling was performed followed by internal validation with visual predictive checks (VPC). Simulations of alternative dosage regimens and scheduling were performed to identify optimal candidate dosage regimens of RT/DNAPKi and RT/PARPi/ICI. Model fits and VPCs confirmed a successful internal validation for both datasets and demonstrated very small differences in the median, lower, and upper percentile values of tumor diameters between RT/ICI and RT/PARPi/ICI, which indicated that the triple combination of RT/PARPi/ICI at the given dosage and schedule does not provide additional benefit compared with ICI in combination with RT. Simulation of alternative dosage regimens indicated that lowering the dosage of ICI to between 2 and 4 mg/kg could induce similar benefits to the full dosage regimen, which could be of translational benefit. SIGNIFICANCE STATEMENT: This work provides a mixed-effects model framework to quantify the effects of combination radiotherapy/DNA damage response pathway inhibitors/immune checkpoint inhibitors in preclinical tumor models and identify optimal dosage regimens, which could be of translational benefit.

Lived experience of patients with Long COVID: a qualitative study in the UK.

BACKGROUND: Long COVID is a rapidly evolving global health crisis requiring interdisciplinary support strategies that incorporate the lived experience of patients. Currently, there is a paucity of research documenting the day-to-day experiences of patients living with Long COVID. OBJECTIVE: To explore the lived experience of Long COVID patients. STUDY DESIGN: Longitudinal, observation study. SETTING: An inductive, data-driven, qualitative approach was used to evaluate hand-written diaries obtained from individuals who had been referred to a Derbyshire Long COVID clinic. PARTICIPANTS: 12 participants (11 females, age 49±10 years, 11 Caucasians) were recruited. Participants were included if they had a previous confirmed or suspected COVID-19 infection with ongoing recovery, >18 years old, understood the study requirements and provided informed consent. METHOD: Participants were directed to complete self-report diaries over 16 weeks. Responses were transcribed verbatim and analysed using thematic analysis. RESULTS: Three key themes were highlighted: (1) understanding who helps patients manage symptoms, (2) daily activities and the impact on quality of life and health status and (3) the effect of turbulent and episodic symptom profiles on personal identity and recovery. CONCLUSIONS: The novel challenges presented by Long COVID are complex with varying inter-related factors that are broadly impacting functional status and quality of life. Support mechanisms must incorporate the lived experiences and foster true collaborations between health professionals, patients and researchers to improve patient outcomes. TRIAL REGISTRATION NUMBER: NCT04649957.

Natural products from reconstructed bacterial genomes of the Middle and Upper Paleolithic.

Major advances over the past decade in the field of ancient DNA are providing access to past paleogenomic diversity, but the diverse functions and biosynthetic capabilities of this growing paleome remain largely elusive. We investigated the dental calculus of 12 Neanderthals and 52 anatomically modern humans ranging from 100,000 years ago to the present and reconstructed 459 bacterial metagenome-assembled genomes. We identified a biosynthetic gene cluster shared by seven Middle and Upper Paleolithic individuals that allows for the heterologous production of a class of previously unknown metabolites that we name "paleofurans." This paleobiotechnological approach demonstrates that viable biosynthetic machinery can be produced from the preserved genetic material of ancient organisms, allowing access to natural products from the Pleistocene and providing a promising area for natural product exploration.

Cardiovascular disease prevention and management in the COVID-19 era and beyond: An international perspective.

Despite some indicators of a localized curtailing of cardiovascular disease (CVD) prevalence, CVD remains one of the largest contributors to global morbidity and mortality. While the magnitude and impact of the coronavirus disease 2019 (COVID-19) pandemic have yet to be realized in its entirety, an unquestionable impact on global health and well-being is already clear. At a time when the global state of CVD is perilous, we provide a continental overview of prevalence data and initiatives that have positively influenced CVD outcomes. What is clear is that despite attempts to address the global burden of CVD, there remains a lack of collective thinking and approaches. Moving forward, a coordinated global infrastructure that, if developed with appropriate and relevant key stakeholders, could provide significant and longstanding benefits to public health and yield prominent and consistent policy resulting in impactful change. To achieve global impact, research priorities that address multi-disciplinary social, environmental, and clinical perspectives must be underpinned by unified approaches that maximize public health.

The response to the COVID-19 pandemic: With hindsight what lessons can we learn?

The purpose of this paper is to put forward some evidence-based lessons that can be learned from how to respond to a Pandemic that relate to healthy living behaviours (HLB). A 4-step methodology was followed to conduct a narrative review of the literature and to present a professional practice vignette. The narrative review identified 8 lessons: 1) peer review; 2) historical perspectives; 3) investing in resilience and protection; 4) unintended consequences; 5) protecting physical activity; 6) school closures; 7) mental health; and 8) obesity. As in all probability there will be another Pandemic, it is important that the lessons learned over the last three years in relation to HLB are acted upon. Whilst there will not always be a consensus on what to emphasise, it is important that many evidence-based positions are presented. The authors of this paper recognise that this work is a starting point and that the lessons presented here will need to be revisited as new evidence becomes available.

Ecology, Not Host Phylogeny, Shapes the Oral Microbiome in Closely Related Species.

Host-associated microbiomes are essential for a multitude of biological processes. Placed at the contact zone between external and internal environments, the little-studied oral microbiome has important roles in host physiology and health. Here, we investigate the roles of host evolutionary relationships and ecology in shaping the oral microbiome in three closely related gorilla subspecies (mountain, Grauer's, and western lowland gorillas) using shotgun metagenomics of 46 museum-preserved dental calculus samples. We find that the oral microbiomes of mountain gorillas are functionally and taxonomically distinct from the other two subspecies, despite close evolutionary relationships and geographic proximity with Grauer's gorillas. Grauer's gorillas show intermediate bacterial taxonomic and functional, and dietary profiles. Altitudinal differences in gorilla subspecies ranges appear to explain these patterns, suggesting a close connection between dental calculus microbiomes and the environment, likely mediated through diet. This is further supported by the presence of gorilla subspecies-specific phyllosphere/rhizosphere taxa in the oral microbiome. Mountain gorillas show a high abundance of nitrate-reducing oral taxa, which may promote adaptation to a high-altitude lifestyle by modulating blood pressure. Our results suggest that ecology, rather than evolutionary relationships and geographic distribution, shape the oral microbiome in these closely related species.

Synthesis, crystal structure and Hirshfeld analysis of triphenylphosphine-(4-bromophenyl)borane.

The title compound, alternatively called (4-bromophenyl)dihydrido(triphenylphosphanyl)boron, C24H21BBrP, crystallizes in the space group P-1 with one symmetry-independent molecule in the asymmetric unit. The B and P atoms both adopt the expected tetrahedral geometry. A possible intramolecular B-Hδ-...δ+H-C dihydrogen bond exists between an arene group on phosphorus and the borane center. In the solid state, the title molecule is connected to its neighbors by intermolecular C-H...π interactions, with the arene rings on the P atom acting as hydrogen-bond donors and the arene ring of the borane acting as the acceptor. Hirshfeld analysis supports the existence of these interactions, as well as weak Br...Br interactions between neighboring molecules.

Preclinical Characterization of AZD5305, A Next-Generation, Highly Selective PARP1 Inhibitor and Trapper.

PURPOSE: We hypothesized that inhibition and trapping of PARP1 alone would be sufficient to achieve antitumor activity. In particular, we aimed to achieve selectivity over PARP2, which has been shown to play a role in the survival of hematopoietic/stem progenitor cells in animal models. We developed AZD5305 with the aim of achieving improved clinical efficacy and wider therapeutic window. This next-generation PARP inhibitor (PARPi) could provide a paradigm shift in clinical outcomes achieved by first-generation PARPi, particularly in combination. EXPERIMENTAL DESIGN: AZD5305 was tested in vitro for PARylation inhibition, PARP-DNA trapping, and antiproliferative abilities. In vivo efficacy was determined in mouse xenograft and PDX models. The potential for hematologic toxicity was evaluated in rat models, as monotherapy and combination. RESULTS: AZD5305 is a highly potent and selective inhibitor of PARP1 with 500-fold selectivity for PARP1 over PARP2. AZD5305 inhibits growth in cells with deficiencies in DNA repair, with minimal/no effects in other cells. Unlike first-generation PARPi, AZD5305 has minimal effects on hematologic parameters in a rat pre-clinical model at predicted clinically efficacious exposures. Animal models treated with AZD5305 at doses ≥0.1 mg/kg once daily achieved greater depth of tumor regression compared to olaparib 100 mg/kg once daily, and longer duration of response. CONCLUSIONS: AZD5305 potently and selectively inhibits PARP1 resulting in excellent antiproliferative activity and unprecedented selectivity for DNA repair deficient versus proficient cells. These data confirm the hypothesis that targeting only PARP1 can retain the therapeutic benefit of nonselective PARPi, while reducing potential for hematotoxicity. AZD5305 is currently in phase I trials (NCT04644068).

Epstein-Barr Virus Reactivation After Paediatric Haematopoietic Stem Cell Transplantation: Risk Factors and Sensitivity Analysis of Mathematical Model.

Epstein-Barr virus (EBV) establishes a lifelong latent infection in healthy humans, kept under immune control by cytotoxic T cells (CTLs). Following paediatric haematopoetic stem cell transplantation (HSCT), a loss of immune surveillance leads to opportunistic outgrowth of EBV-infected cells, resulting in EBV reactivation, which can ultimately progress to post-transplant lymphoproliferative disorder (PTLD). The aims of this study were to identify risk factors for EBV reactivation in children in the first 100 days post-HSCT and to assess the suitability of a previously reported mathematical model to mechanistically model EBV reactivation kinetics in this cohort. Retrospective electronic data were collected from 56 children who underwent HSCT at Great Ormond Street Hospital (GOSH) between 2005 and 2016. Using EBV viral load (VL) measurements from weekly quantitative PCR (qPCR) monitoring post-HSCT, a multivariable Cox proportional hazards (Cox-PH) model was developed to assess time to first EBV reactivation event in the first 100 days post-HSCT. Sensitivity analysis of a previously reported mathematical model was performed to identify key parameters affecting EBV VL. Cox-PH modelling revealed EBV seropositivity of the HSCT recipient and administration of anti-thymocyte globulin (ATG) pre-HSCT to be significantly associated with an increased risk of EBV reactivation in the first 100 days post-HSCT (adjusted hazard ratio (AHR) = 2.32, P = 0.02; AHR = 2.55, P = 0.04). Five parameters were found to affect EBV VL in sensitivity analysis of the previously reported mathematical model. In conclusion, we have assessed the effect of multiple covariates on EBV reactivation in the first 100 days post-HSCT in children and have identified key parameters in a previously reported mechanistic mathematical model that affect EBV VL. Future work will aim to fit this model to patient EBV VLs, develop the model to account for interindividual variability and model the effect of clinically relevant covariates such as rituximab therapy and ATG on EBV VL.

The ingredients for an antimicrobial mathematical modelling broth.

Mathematical modelling has made significant contributions to the optimization of the use of antimicrobial treatments. This article discusses the key processes that such mathematical modelling should attempt to capture. In particular, this article highlights that the response of the host immune system requires quantification, and this is illustrated with a novel model structure.