Paradigms in Operation: Pharmaceutical Benefit Assessments in England and Germany

The assessment of the benefits of pharmaceutical products through health technology assessments (HTAs) has become a feature of health care decision-making in numerous OECD countries, including England and Germany. Assessment outcomes vary between countries but, to date, there is a lack of research on the factors that affect those assessments. This thesis addresses this shortcoming by examining what determines the outcome of pharmaceutical benefit assessments in two countries that employ formalised HTA procedures. It takes a novel theoretical approach by employing a framework of policy paradigms to explain an empirical phenomenon other than policy change. The study presents a qualitative analysis that compares the reasoning processes that led to assessment outcomes in ten of the same cases of pharmaceuticals in England and Germany. It finds that benefit assessment outcomes are determined by how a similar set of themes around evidence gets interpreted and framed by a HTA body, e.g. the National Institute for Health and Care Excellence (NICE) in England and the Federal Joint Committee (FJC) in Germany. The study explains the differences in addressing a similar set of themes around evidence by reference to different HTA paradigms that are applied, namely a cost effectiveness paradigm in England and a patient relevance paradigm in Germany. The thesis makes a significant theoretical contribution because it demonstrates that policy paradigms can be used to explain empirical phenomena other than policy change. This requires an analysis of how paradigms are articulated in ‘normal decision-making’, much akin to Kuhn’s analysis on the connection between ‘normal science’ and paradigms. The study calls for an expansion of the current use of policy paradigms to include how they are operationalised in practice as this leads to a better understanding of the crucial elements of a paradigm

Artificial intelligence ethics by design:Evaluating public perception on the importance of ethical design principles of artificial intelligence

Despite the immense societal importance of ethically designing artificial intelligence (AI), little research on the public perceptions of ethical AI principles exists. This becomes even more striking when considering that ethical AI development has the aim to be human-centric and of benefit for the whole society. In this study, we investigate how ethical principles (explainability, fairness, security, accountability, accuracy, privacy, machine autonomy) are weighted in comparison to each other. This is especially important, since simultaneously considering ethical principles is not only costly, but sometimes even impossible, as developers must make specific trade-off decisions. In this paper, we give first answers on the relative importance of ethical principles given a specific use case - the use of AI in tax fraud detection. The results of a large conjoint survey (n=1099) suggest that, by and large, German respondents found the ethical principles equally important. However, subsequent cluster analysis shows that different preference models for ethically designed systems exist among the German population. These clusters substantially differ not only in the preferred attributes, but also in the importance level of the attributes themselves. We further describe how these groups are constituted in terms of sociodemographics as well as opinions on AI. Societal implications as well as design challenges are discussed

Reward-Processing Behavior in Depressed Participants Relative to Healthy Volunteers: A Systematic Review and Meta-analysis

IMPORTANCE: Dysfunctional reward processing is a leading candidate mechanism for the development of certain depressive symptoms, such as anhedonia. However, to our knowledge, there has not yet been a systematic assessment of whether and to what extent depression is associated with impairments on behavioral reward-processing tasks. OBJECTIVE: To determine whether depression is associated with impairments in reward-processing behavior. DATA SOURCES: The MEDLINE/PubMed, Embase, and PsycInfo databases were searched for studies that investigated reward processing using performance on behavioral tasks by individuals with depression and nondepressed control groups, published between January 1, 1946, and August 16, 2019. STUDY SELECTION: Studies that contained data regarding performance by depressed and healthy control groups on reward-processing tasks were included in the systematic review and meta-analysis. DATA EXTRACTION AND SYNTHESIS: Summary statistics comparing performance between depressed and healthy groups on reward-processing tasks were converted to standardized mean difference (SMD) scores, from which summary effect sizes for overall impairment in reward processing and 4 subcomponent categories were calculated. Study quality, heterogeneity, replicability-index, and publication bias were also assessed. MAIN OUTCOME AND MEASURES: Performance on reward-processing tasks. RESULTS: The final data set comprised 48 case-control studies (1387 healthy control individuals and 1767 individuals with major depressive disorder). The mean age was 37.85 years and 58% of the participants were women. These studies used tasks assessing option valuation (n = 9), reward bias (n = 6), reward response vigor (n = 12), reinforcement learning (n = 20), and grip force (n = 1). Across all tasks, depression was associated with small to medium impairments in reward-processing behavior (SMD = 0.345; 95% CI, 0.209-0.480). When examining reward-processing subcomponent categories, impairment was associated with tasks assessing option valuation (SMD = 0.309; 95% CI, 0.147-0.471), reward bias (SMD = 0.644; 95% CI, 0.270-1.017), and reinforcement learning (SMD = 0.352; 95% CI, 0.115-0.588) but not reward response vigor (SMD = 0.083; 95% CI, −0.144 to 0.309). The medication status of the major depressive disorder sample did not explain any of the variance in the overall effect size. There was significant between-study heterogeneity overall and in all subcomponent categories other than option valuation. Significant publication bias was identified overall and in the reinforcement learning category. CONCLUSIONS AND RELEVANCE: Relative to healthy control individuals, individuals with depression exhibit reward-processing impairments, particularly for tests of reward bias, option valuation, and reinforcement learning. Understanding the neural mechanisms driving these associations may assist in designing novel interventions

Microscopic origin of entropy-driven polymorphism in hybrid organic-inorganic perovskite materials

Entropy is a critical, but often overlooked, factor in determining the relative stabilities of crystal phases. The importance of entropy is most pronounced in softer materials, where small changes in free energy can drive phase transitions, which has recently been demonstrated in the case of organic-inorganic hybrid-formate perovskites. In this Rapid Communication we demonstrate the interplay between composition and crystal structure that is responsible for the particularly pronounced role of entropy in determining polymorphism in hybrid organic-inorganic materials. Using ab initio based lattice dynamics, we probe the origins and effects of vibrational entropy of four archetype perovskite (ABX3) structures. We consider an inorganic material (SrTiO3), an A-site hybrid-halide material (CH3NH3)PbI3, a X-site hybrid material KSr(BH4)3, and a mixed A- and X-site hybrid-formate material (N2H5)Zn(HCO2)3, comparing the differences in entropy between two common polymorphs. The results demonstrate the importance of low-frequency intermolecular modes in determining the phase stability in these materials. The understanding gained allows us to propose a general principle for the relative stability of different polymorphs of hybrid materials as temperature is increased.</p

Clustering of HIV-1 Subtypes Based on gp120 V3 Loop electrostatic properties

<p>Abstract</p> <p>Background</p> <p>The V3 loop of the glycoprotein gp120 of HIV-1 plays an important role in viral entry into cells by utilizing as coreceptor CCR5 or CXCR4, and is implicated in the phenotypic tropisms of HIV viruses. It has been hypothesized that the interaction between the V3 loop and CCR5 or CXCR4 is mediated by electrostatics. We have performed hierarchical clustering analysis of the spatial distributions of electrostatic potentials and charges of V3 loop structures containing consensus sequences of HIV-1 subtypes.</p> <p>Results</p> <p>Although the majority of consensus sequences have a net charge of +3, the spatial distribution of their electrostatic potentials and charges may be a discriminating factor for binding and infectivity. This is demonstrated by the formation of several small subclusters, within major clusters, which indicates common origin but distinct spatial details of electrostatic properties. Some of this information may be present, in a coarse manner, in clustering of sequences, but the spatial details are largely lost. We show the effect of ionic strength on clustering of electrostatic potentials, information that is not present in clustering of charges or sequences. We also make correlations between clustering of electrostatic potentials and net charge, coreceptor selectivity, global prevalence, and geographic distribution. Finally, we interpret coreceptor selectivity based on the N⁶X⁷T⁸|S⁸X⁹sequence glycosylation motif, the specific positive charge location according to the 11/24/25 rule, and the overall charge and electrostatic potential distribution.</p> <p>Conclusions</p> <p>We propose that in addition to the sequence and the net charge of the V3 loop of each subtype, the spatial distributions of electrostatic potentials and charges may also be important factors for receptor recognition and binding and subsequent viral entry into cells. This implies that the overall electrostatic potential is responsible for long-range recognition of the V3 loop with coreceptors CCR5/CXCR4, whereas the charge distribution contributes to the specific short-range interactions responsible for the formation of the bound complex. We also propose a scheme for coreceptor selectivity based on the sequence glycosylation motif, the 11/24/25 rule, and net charge.</p

Soluble Receptor for Advanced Glycation End Products (sRAGE) Is a Sensitive Biomarker in Human Pulmonary Arterial Hypertension.

Pulmonary arterial hypertension (PAH) is a progressive condition with an unmet need for early diagnosis, better monitoring, and risk stratification. The receptor for advanced glycation end products (RAGE) is activated in response to hypoxia and vascular injury, and is associated with inflammation, cell proliferation and migration in PAH. For the adult cohort, we recruited 120 patients with PAH, 83 with idiopathic PAH (IPAH) and 37 with connective tissue disease-associated PAH (CTD-PAH), and 48 controls, and determined potential plasma biomarkers by enzyme-linked immunoassay. The established heart failure marker NTproBNP and IL-6 plasma levels were several-fold higher in both adult IPAH and CTD-PAH patients versus controls. Plasma soluble RAGE (sRAGE) was elevated in IPAH patients (3044 ± 215.2 pg/mL) and was even higher in CTD-PAH patients (3332 ± 321.6 pg/mL) versus controls (1766 ± 121.9 pg/mL; p < 0.01). All three markers were increased in WHO functional class II+III PAH versus controls (p < 0.001). Receiver-operating characteristic analysis revealed that sRAGE has diagnostic accuracy comparable to prognostic NTproBNP, and even outperforms NTproBNP in the distinction of PAH FC I from controls. Lung tissue RAGE expression was increased in IPAH versus controls (mRNA) and was located predominantly in the PA intima, media, and inflammatory cells in the perivascular space (immunohistochemistry). In the pediatric cohort, plasma sRAGE concentrations were higher than in adults, but were similar in PH (n = 10) and non-PH controls (n = 10). Taken together, in the largest adult sRAGE PAH study to date, we identify plasma sRAGE as a sensitive and accurate PAH biomarker with better performance than NTproBNP in the distinction of mild PAH from controls

Microscopic origin of entropy-driven polymorphism in hybrid organic-inorganic perovskite materials

Entropy is a critical, but often overlooked, factor in determining the relative stabilities of crystal phases. The importance of entropy is most pronounced in softer materials, where small changes in free energy can drive phase transitions, which has recently been demonstrated in the case of organic-inorganic hybrid-formate perovskites. In this study we demonstrate the interplay between composition and crystal-structure that is responsible for the particularly pronounced role of entropy in determining polymorphism in hybrid organic-inorganic materials. Using ab initio based lattice dynamics we probe the origins and effects of vibrational entropy of four archetype perovskite (ABX$_3$) structures. We consider a fully inorganic material (SrTiO$_3$), an A-site hybrid halide material (CH$_3$NH$_3$PbI$_3$), an X-site hybrid material (KSr(BH$_4$)$_3$) and a mixed A- and X-site hybrid-formate material (N$_2$H$_5$Zn(HCO$_2$)$_3$), comparing the differences in entropy between two common polymorphs. The results demonstrate the importance of low-frequency inter-molecular modes in determining phase stability in these materials. The understanding gained allows us to propose a general principle for the relative stability of different polymorphs of hybrid materials as temperature is increased