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Healthcare innovations often represent important improvements in population welfare, but at what cost, and to whom? Health technology assessment (HTA) is a multidisciplinary process to inform resource allocation. HTA is conventionally anchored on health maximization as the only relevant output of health services. If we accept the proposition that health technologies can generate value outside the healthcare system, resource allocation decisions could be suboptimal from a societal perspective. Incorporating “broader value” in HTA as derived from social values and patient experience could provide a richer evaluative space for informing resource allocation decisions. This article considers how HTA is practiced and what its current context implies for adopting “broader value” to evaluating health technologies. Methodological challenges are highlighted, as is a future research agenda. Ireland serves as an example of a healthcare system that both has an explicit role for HTA and is evolving under a current program of reform to offer universal, single-tier access to public services. There are various ways in which HTA processes could move beyond health, including considering the processes of care delivery and/or expanding the evaluative space to some broader concept of well-being. Methods to facilitate the latter exist, but their adaptation to HTA is still emerging. We recommend a multi-stakeholder working group to develop and advance an international agenda for HTA that captures welfare/benefit beyond health.

Background Mandatory co-payments attached to prescription medicines on the Irish public health insurance [General Medical Services (GMS)] scheme have undergone multiple iterations since their introduction in October 2010. To date, whilst patients’ opinions on said co-payments have been evaluated, the perspectives of community pharmacists and general practitioners (GPs) have not. Objective To explore the involvement and perceptions of community pharmacists and GPs on this pharmaceutical policy change. Methods A qualitative study using purposive sampling alongside snowballing recruitment was used. Nineteen interviews were conducted in a Southern region of Ireland. Data were analysed using the Framework Approach. Results Three major themes emerged: 1) the withered tax-collecting pharmacist; 2) concerns and prescribing patterns of physicians; and 3) the co-payment system – impact and sustainability. Both community pharmacists and GPs accepted the theoretical concept of a co-payment on the GMS scheme as it prevents moral hazard. However, there were multiple references to the burden that the current method of co-payment collection places on community pharmacists in terms of direct financial loss and reductions in workplace productivity. GPs independently suggested that a co-payment system may inhibit moral hazard by GMS patients in the utilisation of GP services. It was unclear to participants what evidence is guiding the GMS co-payment fee changes. Conclusion Interviewees accepted the rationale for the co-payment system, but reform is warranted.

Background Two large acute Irish University teaching hospitals changed the manner in which they treated human epidermal growth factor receptor (HER)2-positive breast cancer patients by implementing the administration of trastuzumab via the subcutaneous (SC) route into their clinical practice. The study objective is to compare the trastuzumab SC and trastuzuamb intravenous (IV) treatment pathways in both hospitals and assess which route is more cost-effective and time saving in relation to active health care professional (HCP) time. Materials and Methods A prospective observational study in the form of cost minimization analysis constituted the study design. Active HCP time for trastuzumab SC- and IV-related tasks were recorded. Staff costs were calculated using fully loaded salary costs. Loss of productivity costs for patients were calculated using the human capital method. Results On average, the total HCP time saved per trastuzumab SC treatment cycle relative to trastuzumab IV treatment cycle was 59.21 minutes. Time savings in favor of trastuzumab SC resulted from quicker drug reconstitution, no IV catheter installation/removal, and less HCP monitoring. Over a full treatment course of 17 cycles, average HCP time saved accumulates to 16.78 hours, with an estimated direct cost saving of €1609.99. Loss of productivity for patients receiving trastuzumab IV (2.15 days) was greater than that of trastuzumab SC (0.60 days) for a full treatment course. Conclusion Trastuzumab SC treatment has proven to be a more cost-effective option than trastuzumab IV treatment that generated greater HCP time savings in both study sites. Healthcare policymakers should consider replacing trastuzumab IV with trastuzumab SC treatment in all eligible patients.

Background and aim: Biosimilar medicines are not considered exact replicas of originator biological medicines. As a result, prescribers can be hesitant to introduce such medicines into the clinical setting until evidence surfaces confirming their safety and effectiveness. In Ireland, a national biosimilar medicines policy is currently in development but the decision to prescribe biosimilar medicines remains at the discretion of the physician. The aim of this descriptive review is to tell the story of the evidence used by a large acute Irish teaching hospital to introduce biosimilar infliximab CT-P13 for the treatment of inflammatory bowel disease (IBD) in a safe and timely manner into routine care. Methods: To explore the evidence supporting the effective introduction of biosimilar infliximab in a large acute Irish teaching hospital, a literature review was conducted. Evidence consisted of published studies, reviews, reports, position statements, articles, clinical guidelines, and recommendations from national bodies, regulatory authorities and professional organizations. All evidence was published in English. Results and discussion: In September 2014, the accumulated evidence base provided physicians with reassurance to prescribe biosimilar infliximab CT-P13 for new patients suffering from IBD in this large acute Irish teaching hospital. In September 2016, as the evidence base grew, physicians began to safely and confidently switch patients from the originator infliximab product to the biosimilar product. Conclusion: There was a significant time lag between regulatory approval and clinical acceptance given that the European Medicines Agency had granted market authorization for biosimilar infliximab CT-P13 three years prior to the initiation of this hospital's switching process. Although conservative in their execution, the authors conclude that with the existential concern and uncertainty still surrounding biosimilar medicines, a distinct and individualized approach for biosimilar medicine implementation is required. It is with hope that the Irish biosimilar medicines policy will improve upon biosimilar medicine clinical acceptance once published.

Background Developed in the late 20th century, the health policy triangle (HPT) is a policy analysis framework used and applied ubiquitously in the literature to analyse a large number of health-related issues. Objective To explore and summarise the application of the HPT framework to health-related (public) policy decisions in the recent literature. Methods This narrative review consisted of a systematic search and summary of included articles from January 2015 January 2020. Six electronic databases were searched. Included studies were required to use the HPT framework as part of their policy analysis. Data were analysed using principles of thematic analysis. Results Of the 2217 studies which were screened for inclusion, the final review comprised of 54 studies, mostly qualitative in nature. Five descriptive categorised themes emerged (i) health human resources, services and systems, (ii) communicable and non-communicable diseases, (iii) physical and mental health, (iv) antenatal and postnatal care and (v) miscellaneous. Most studies were conducted in lower to upper-middle income countries. Conclusion This review identified that the types of health policies analysed were almost all positioned at national or international level and primarily concerned public health issues. Given its generalisable nature, future research that applies the HPT framework to smaller scale health policy decisions investigated at local and regional levels, could be beneficial.

Background: A recent randomised controlled trial conducted in an Irish University teaching hospital that evaluated a physician-implemented medication screening tool, demonstrated positive outcomes in terms of a reduction in incident adverse drug reactions. Objective: The present study objective was to evaluate the cost effectiveness of physicians applying this screening tool to older hospitalised patients compared with usual hospital care in the context of the earlier randomised controlled trial. Method: We used a cost-effectiveness analysis alongside a conventional outcome analysis in a cluster randomised controlled trial. Patients in the intervention arm (n = 360) received a multifactorial intervention consisting of medicines reconciliation, communication with patients’ senior medical team, and generation of a pharmaceutical care plan in addition to usual medical and pharmaceutical care. Control arm patients (n = 372) received usual medical and pharmaceutical care only. Incremental cost effectiveness was examined in terms of costs to the healthcare system and an outcome measure of adverse drug reactions during inpatient hospital stay. Uncertainty in the analysis was explored using a cost-effectiveness acceptability curve. Results: On average, the intervention arm was more costly but was also more effective. Compared with usual care (control), the intervention was associated with a non-statistically significant increase of €877 (95% confidence interval − €1807, €3561) in the mean healthcare cost, and a statistically significant decrease of − 0.164 (95% confidence interval − 0.257, − 0.070) in the mean number of adverse drug reaction events per patient. The associated incremental cost-effectiveness ratio per adverse drug reaction averted was €5358. The probability of the intervention being cost effective at threshold values of €0, €5000 and €10,000 was 0.236, 0.455 and 0.680, respectively. Conclusion: Based on the evidence presented, this physician-led intervention is not likely to be cost effective compared with usual hospital care. To inform future healthcare policy decisions in this field, more economic analyses of structured medication reviews by other healthcare professionals and by computerised clinical decision support software need to be conducted.

The financial crisis that enveloped Europe in 2009 created financial pressure for governments and required a number of countries to obtain a financial bailout from the IMF. The purpose of this paper is to examine the effect of the financial crisis on public health expenditure in bailout countries and if bailouts shift the burden of paying for healthcare from the state onto individuals. Quantitative health expenditure data were collected from the WHO and OECD for the period 2004–2015 and evaluated using a comparison of means Welch’s t test. The majority of bailout countries recorded a decrease in public health expenditure as a percentage of total government expenditure, with Ireland recording the largest decrease with government health expenditure as a percentage of total government expenditure, falling by 22% (P

T-cell epitopes form the basis of many vaccines, diagnostics, and reagents. Current methods for the in silico identification of T-cell epitopes rely, in the main, on the accurate quantitative prediction of peptide-Major Histocompatibility Complex (pMHC) affinity using data-driven computational approaches. Here, we describe a dataset of experimentally determined pMHC binding affinities for the problematic human class I allele HLA-B*2705. Using an in-house, FACS-based, MHC stabilization assay, we measured binding of 223 peptides. This dataset includes both nonbinding and binding peptides, with measured affinities (expressed as −log10 of the half-maximal binding level) ranging from 1.2 to 7.4. This dataset should provide a useful independent benchmark for new and existing methods for predicting peptide binding to HLA-B*2705.

Immunoinformatics is facilitating important change within immunology and is helping it to engage more completely with the dynamic post-genomic revolution sweeping through bioscience. Historically, predicting the specificity of peptide Major Histocompatibility Complex (MHC) interactions has been the major contribution made by bioinformatics disciplines to research in immunology and the vaccinology. This will be the focus of the current chapter. Initially, we will review some background to this problem, such as the thermodynamics of peptide binding and the known constraints on peptide selectivity by the MHC. We will then review artificial intelligence and machine learning approaches to the prediction problem. Finally, we will outline our own contribution to this field: the application of QSAR techniques to the prediction of peptide-MHC binding.

Perhaps the most exciting sub-discipline within Bioinformatics is the application of informatic methods to immunology. Immunoinformatics, which combines informatics with computational chemistry, is facilitating important change within immunology. As it frees itself from the empirical straight jacket that has characterised its development, immunoinformatics is helping immunology to engage fully with the dynamic post-genomic revolution sweeping through bioscience. Focussing on quantitative aspects, we will review recent developments within immunoinformatics, paying particular attention to the following: the development of functional immunological databases; prediction of the antigen presentation pathway; predicting the specificity of peptide Major Histocompatibility Complex (MHC) interactions, using statistical techniques and atomistic molecular dynamics; and the grouping of MHC molecules into supertypes.

Throughout time functional immunology has accumulated vast amounts of quantitative and qualitative data relevant to the design and discovery of vaccines. Such data includes, but is not limited to, components of the host and pathogen genome (including antigens and virulence factors), T- and B-cell epitopes and other components of the antigen presentation pathway and allergens. In this review the authors discuss a range of databases that archive such data. Built on such information, increasingly sophisticated data mining techniques have developed that create predictive models of utilitarian value. With special reference to epitope data, the authors discuss the strengths and weaknesses of the available techniques and how they can aid computer-aided vaccine design deliver added value for vaccinology.

Objective Our objective is to review and assess the main pharmaceutical cost-containment policies used in Ireland in recent years, and to highlight how a policy that improved fiscal sustainability but worsened economic sustainability could have improved both if an option-based approach was implemented. Method The main public pharmaceutical cost-containment policy measures including reducing the ex-factory price of drugs, pharmacy dispensing fees and community drug scheme coverage, and increasing patient copayments are outlined along with the resulting savings. We quantify the cost implications of a new policy that restricts the entitlement to free prescription drugs of persons older than 70 years and propose an alternative option-based policy that reduces the total cost to both the state and the patient. Results This set of policy measures reduced public spending on community drugs by an estimated €380m in 2011. The policy restricting free prescription drugs for persons older than 70 years, though effective in reducing public cost, increased the total cost of the drugs supplied. The policy-induced cost increase stems from a fees anomaly between the two main community drugs schemes which is circumvented by our alternative option-based policy. Conclusions Our findings highlight the need for policymakers, even when absorbed with reducing cost, to design cost-containment policies that are both fiscally and economically sustainable.

BACKGROUND: Predictive models of peptide-Major Histocompatibility Complex (MHC) binding affinity are important components of modern computational immunovaccinology. Here, we describe the development and deployment of a reliable peptide-binding prediction method for a previously poorly-characterized human MHC class I allele, HLA-Cw*0102. METHODOLOGY/FINDINGS: Using an in-house, flow cytometry-based MHC stabilization assay we generated novel peptide binding data, from which we derived a precise two-dimensional quantitative structure-activity relationship (2D-QSAR) binding model. This allowed us to explore the peptide specificity of HLA-Cw*0102 molecule in detail. We used this model to design peptides optimized for HLA-Cw*0102-binding. Experimental analysis showed these peptides to have high binding affinities for the HLA-Cw*0102 molecule. As a functional validation of our approach, we also predicted HLA-Cw*0102-binding peptides within the HIV-1 genome, identifying a set of potent binding peptides. The most affine of these binding peptides was subsequently determined to be an epitope recognized in a subset of HLA-Cw*0102-positive individuals chronically infected with HIV-1. CONCLUSIONS/SIGNIFICANCE: A functionally-validated in silico-in vitro approach to the reliable and efficient prediction of peptide binding to a previously uncharacterized human MHC allele HLA-Cw*0102 was developed. This technique is generally applicable to all T cell epitope identification problems in immunology and vaccinology.

The affinities of 177 nonameric peptides binding to the HLA-A*0201 molecule were measured using a FACS-based MHC stabilisation assay and analysed using chemometrics. Their structures were described by global and local descriptors, QSAR models were derived by genetic algorithm, stepwise regression and PLS. The global molecular descriptors included molecular connectivity chi indices, kappa shape indices, E-state indices, molecular properties like molecular weight and log P, and three-dimensional descriptors like polarizability, surface area and volume. The local descriptors were of two types. The first used a binary string to indicate the presence of each amino acid type at each position of the peptide. The second was also position-dependent but used five z-scales to describe the main physicochemical properties of the amino acids forming the peptides. The models were developed using a representative training set of 131 peptides and validated using an independent test set of 46 peptides. It was found that the global descriptors could not explain the variance in the training set nor predict the affinities of the test set accurately. Both types of local descriptors gave QSAR models with better explained variance and predictive ability. The results suggest that, in their interactions with the MHC molecule, the peptide acts as a complicated ensemble of multiple amino acids mutually potentiating each other.

The ability to define and manipulate the interaction of peptides with MHC molecules has immense immunological utility, with applications in epitope identification, vaccine design, and immunomodulation. However, the methods currently available for prediction of peptide-MHC binding are far from ideal. We recently described the application of a bioinformatic prediction method based on quantitative structure-affinity relationship methods to peptide-MHC binding. In this study we demonstrate the predictivity and utility of this approach. We determined the binding affinities of a set of 90 nonamer peptides for the MHC class I allele HLA-A*0201 using an in-house, FACS-based, MHC stabilization assay, and from these data we derived an additive quantitative structure-affinity relationship model for peptide interaction with the HLA-A*0201 molecule. Using this model we then designed a series of high affinity HLA-A2-binding peptides. Experimental analysis revealed that all these peptides showed high binding affinities to the HLA-A*0201 molecule, significantly higher than the highest previously recorded. In addition, by the use of systematic substitution at principal anchor positions 2 and 9, we showed that high binding peptides are tolerant to a wide range of nonpreferred amino acids. Our results support a model in which the affinity of peptide binding to MHC is determined by the interactions of amino acids at multiple positions with the MHC molecule and may be enhanced by enthalpic cooperativity between these component interactions.

The immune system is hierarchical and has many levels, exhibiting much emergent behaviour. However, at its heart are molecular recognition events that are indistinguishable from other types of biomacromolecular interaction. These can be addressed well by quantitative experimental and theoretical biophysical techniques, and particularly by methods from drug design. We review here our approach to computational immunovaccinology. In particular, we describe the JenPep database and two new techniques for T cell epitope prediction. One is based on quantitative structure-activity relationships (a 3D-QSAR method based on CoMSIA and another 2D method based on the Free-Wilson approach) and the other on atomistic molecular dynamic simulations using high performance computing. JenPep (http://www.jenner.ar.uk/ JenPep) is a relational database system supporting quantitative data on peptide binding to major histocompatibility complexes, TAP transporters, TCR-pMHC complexes, and an annotated list of B cell and T cell epitopes. Our 2D-QSAR method factors the contribution to peptide binding from individual amino acids as well as 1-2 and 1-3 residue interactions. In the 3D-QSAR approach, the influence of five physicochemical properties (volume, electrostatic potential, hydrophobicity, hydrogen-bond donor and acceptor abilities) on peptide affinity were considered. Both methods are exemplified through their application to the well-studied problem of peptide binding to the human class I MHC molecule HLA-A*0201.

The immune system is hierarchical and has many levels, exhibiting much emergent behaviour. However, at its heart are molecular recognition events that are indistinguishable from other types of biomacromolecular interaction. These can be addressed well by quantitative experimental and theoretical biophysical techniques, and particularly by methods from drug design. We review here our approach to computational immunovaccinology. In particular, we describe the JenPep database and two new techniques for T cell epitope prediction. One is based on quantitative structure-activity relationships (a 3D-QSAR method based on CoMSIA and another 2D method based on the Free-Wilson approach) and the other on atomistic molecular dynamic simulations using high performance computing. JenPep (http://www.jenner.ar.uk/ JenPep) is a relational database system supporting quantitative data on peptide binding to major histocompatibility complexes, TAP transporters, TCR-pMHC complexes, and an annotated list of B cell and T cell epitopes. Our 2D-QSAR method factors the contribution to peptide binding from individual amino acids as well as 1-2 and 1-3 residue interactions. In the 3D-QSAR approach, the influence of five physicochemical properties (volume, electrostatic potential, hydrophobicity, hydrogen-bond donor and acceptor abilities) on peptide affinity were considered. Both methods are exemplified through their application to the well-studied problem of peptide binding to the human class I MHC molecule HLA-A*0201.

Linkage of atopy and associated traits to a locus on chromosome 13q14 has been identified by several studies in diverse populations. We have previously shown the putative atopy gene to be contained within an interval of approximately 5 Mb flanked by D13S328 and D13S1269 and centred on D13S273. We have now extended this work using a top-down approach to physical mapping. A YAC contig was constructed covering the D13S328 and D13S1269 interval. Thirty-one ESTs were mapped to the contig. We constructed a BAC and PAC contig flanking D13S273 by approximately 750 kb in either direction. The interval contained 27 of the 31 ESTS from the YAC contig. Seven previously unknown microsatellites were recovered and then typed in two subject panels. A positive association between the total serum Immunoglobulin E concentration and the novel USAT24G1 microsatellite was discovered (P(corrected)