Inference and Decision Making for 21st-Century Drug Development and Approval

ABSTRACT

The cost and time of pharmaceutical drug development continue to grow at rates that many say are unsustainable. These trends have enormous impact on what treatments get to patients, when they get them and how they are used. The statistical framework for supporting decisions in regulated clinical development of new medicines has followed a traditional path of frequentist methodology. Trials using hypothesis tests of “no treatment effect” are done routinely, and the p-value < 0.05 is often the determinant of what constitutes a “successful” trial. Many drugs fail in clinical development, adding to the cost of new medicines, and some evidence points blame at the deficiencies of the frequentist paradigm. An unknown number effective medicines may have been abandoned because trials were declared “unsuccessful” due to a p-value exceeding 0.05. Recently, the Bayesian paradigm has shown utility in the clinical drug development process for its probability-based inference. We argue for a Bayesian approach that employs data from other trials as a “prior” for Phase 3 trials so that synthesized evidence across trials can be utilized to compute probability statements that are valuable for understanding the magnitude of treatment effect. Such a Bayesian paradigm provides a promising framework for improving statistical inference and regulatory decision making.     

Bayesian analysis of mixture modelling using the multivariate t distribution

A finite mixture model using the multivariate t distribution has been shown as a robust extension of normal mixtures. In this paper, we present a Bayesian approach for inference about parameters of t-mixture models. The specifications of prior distributions are weakly informative to avoid causing nonintegrable posterior distributions. We present two efficient EM-type algorithms for computing the joint posterior mode with the observed data and an incomplete future vector as the sample. Markov chain Monte Carlo sampling schemes are also developed to obtain the target posterior distribution of parameters. The advantages of Bayesian approach over the maximum likelihood method are demonstrated via a set of real data.     

Youth Allowances: Incentive & Reform

Australia's income support arrangements have come under increasing scrutiny lately reflecting a growing concern about high levels of youth unemployment and about low levels of full-time education participation. This paper aims to explore the relationship between education participation and financial incentives and to assess as a possible direction for future reform, the concept of a single and universal youth allowance. The paper begins by outlining the major forms of income support available to young people and illustrates some of the complexities in the youth income support structure. The evidence on the importance of financial factors conflicts, particularly between economists and non-economists. This is in part explained by the different conceptual frameworks used. Other possible reasons are canvassed as to why studies have so far not thrown much light on the role of financial factors in the education participation decision. The paper also outlines specific directions of distortion contained in current payment relativities. Several difficulties with the proposal for a single youth allowance as a means of increasing education participation are discussed and alternatives briefly outlined. The concluding section of the paper summarises the issues relevant to the future debate on youth income support and identifies areas for further research.     

Maintaining the connection: Parenting as a noncustodial father

The purpose of this study was to identify relevant factors associated with the noncustodial father's frequency of contact with his child following divorce. The findings of the research revealed that a combination of demographic, personal characteristics, and psychosocial factors are related to the father's frequency of contact with the child.     

Book Review: Beyond Earth Day: Fulfilling the Promise. Gaylord Nelson with Susan Campbell and Paul Wozniak. Madison,WI: The University of Wisconsin Press, 2002: 160 pp.

Population and Environment -     

ATSDR Science Panel on the Bioavailability of Mercury in Soils: Lessons Learned

On the basis of discussion and analysis during and following an ATSDR science panel on the bioavailability of mercury in soils, it is apparent that the default assumption of 100% relative bioavailability for mercury-contaminated soils is excessively conservative. However, current knowledge does not allow the development of default assumptions or guidelines for determining relative bioavailability of mercury in soils. Until such default assumptions or guidelines can be developed, site-specific assays of bioavailability, preferably using either animal bioassays or validated in vitro techniques, may provide the best approach for estimating soil-mercury bioavailability.     

The reification of celebrity: global newspaper coverage of the death of David Bowie*

This paper examines global English-language newspaper coverage of the death of David Bowie. Drawing upon the concept of reification, it is argued that the notion of celebrity is discursively (re)produced and configured through a ‘public face’ that is defined, maintained and shaped via media reports and public responses that aim to know and reflect upon celebrity. The findings highlight how Bowie’s reification was supported by discourses that represented him as an observable, reified form. Here, Bowie’s ‘reality’, that is, his authentic/veridical self, was obscured behind a façade of mediation, interpretation and representation that debated and decided his ‘authenticity’ as a cultural icon. Such debates, however, were engagements with a reified image, enveloped in continual (re)interpretation. As a result, Bowie’s reification was grounded in a polysemous process that allowed numerous versions of ‘himself’ to be aesthetically reimagined, reinvented and repeated.     

Response‐adaptive designs for binary responses: How to offer patient benefit while being robust to time trends?

Response‐adaptive randomisation (RAR) can considerably improve the chances of a successful treatment outcome for patients in a clinical trial by skewing the allocation probability towards better performing treatments as data accumulates. There is considerable interest in using RAR designs in drug development for rare diseases, where traditional designs are not either feasible or ethically questionable. In this paper, we discuss and address a major criticism levelled at RAR: namely, type I error inflation due to an unknown time trend over the course of the trial. The most common cause of this phenomenon is changes in the characteristics of recruited patients—referred to as patient drift. This is a realistic concern for clinical trials in rare diseases due to their lengthly accrual rate. We compute the type I error inflation as a function of the time trend magnitude to determine in which contexts the problem is most exacerbated. We then assess the ability of different correction methods to preserve type I error in these contexts and their performance in terms of other operating characteristics, including patient benefit and power. We make recommendations as to which correction methods are most suitable in the rare disease context for several RAR rules, differentiating between the 2‐armed and the multi‐armed case. We further propose a RAR design for multi‐armed clinical trials, which is computationally efficient and robust to several time trends considered.