BackgroundThe time taken, or ‘time lags’, between biomedical/health research and its translation into health improvements is receiving growing attention. Reducing time lags should increase rates of return to such research. However, ways to measure time lags are under-developed, with little attention on where time lags arise within overall timelines. The process marker model has been proposed as a better way forward than the current focus on an increasingly complex series of translation ‘gaps’. Starting from that model, we aimed to develop better methods to measure and understand time lags and develop ways to identify policy options and produce recommendations for future studies.MethodsFollowing reviews of the literature on time lags and of relevant policy documents, we developed a new approach to conduct case studies of time lags. We built on the process marker model, including developing a matrix with a series of overlapping tracks to allow us to present and measure elements within any overall time lag. We identified a reduced number of key markers or calibration points and tested our new approach in seven case studies of research leading to interventions in cardiovascular disease and mental health. Finally, we analysed the data to address our study’s key aims.ResultsThe literature review illustrated the lack of agreement on starting points for measuring time lags. We mapped points from policy documents onto our matrix and thus highlighted key areas of concern, for example around delays before new therapies become widely available. Our seven completed case studies demonstrate we have made considerable progress in developing methods to measure and understand time lags. The matrix of overlapping tracks of activity in the research and implementation processes facilitated analysis of time lags along each track, and at the cross-over points where the next track started. We identified some factors that speed up translation through the actions of companies, researchers, funders, policymakers, and regulators. Recommendations for further work are built on progress made, limitations identified and revised terminology.ConclusionsOur advances identify complexities, provide a firm basis for further methodological work along and between tracks, and begin to indicate potential ways of reducing lags.Electronic supplementary materialThe online version of this article (doi:10.1186/1478-4505-13-1) contains supplementary material, which is available to authorized users.

The success rate of the pharmaceutical research and development (R&D) for dementia drugs has been abysmally low, in the last two decades. Also low has been the number of pipeline drugs in development, compared to other therapy areas. However, the rationale of early terminations has not been reported in the majority of trials. These are key findings of the recently published pharmaceutical pipeline analysis by the UK-based Office of Health Economics (OHE). Our understanding of main challenges include (1) the significant gaps of knowledge in the nosology and complexity of the underpinning biological mechanisms of the commonest, not familial, forms of late onset dementias; (2) low signal-to-noise ratio, notwithstanding the lack of validated biomarkers as entry and/or end-point criteria; (3) recruitment and retention, particularly in the asymptomatic and early disease stages. A number of current and future strategies aimed at ameliorating drug development are outlined and discussed.

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The term ‘biosimilar’ refers to an alternative similar version of an off-patent innovative originator biotechnology product (the ‘reference product’). Several biosimilars have been approved in Europe, and a number of top-selling biological medicines have lost, or will lose, patent protection over the next 5 years. We look at the experience in Europe so far. The USA has finally implemented a regulatory route for biosimilar approval. We recommend that European and US governments and payers take a strategic approach to get value for money from the use of biosimilars by (1) supporting and incentivising generation of high-quality comprehensive outcomes data on the effectiveness and safety of biosimilars and originator products; and (2) ensuring that incentives are in place for budget holders to benefit from price competition. This may create greater willingness on the part of budget holders and clinicians to use biosimilar and originator products with comparable outcomes interchangeably, and may drive down prices. Other options, such as direct price cuts for originator products or substitution rules without outcomes data, are likely to discourage biosimilar entry. With such approaches, governments may achieve a one-off cut in originator prices but may put at risk the creation of a more competitive market that would, in time, produce much greater savings. It was the creation of competitive markets for chemical generic drugs—notably, in the USA, the UK and Germany—rather than price control, that enabled payers to achieve the high discounts now taken for granted.

Background Debate over the viability of the current commercial research and development (R&D) model is ongoing. A controversial theme is the cost of bringing a new molecular entity (NME) to market. Objective Our aim was to evaluate the range and suitability of published R&D cost estimates as to the degree to which they represent the actual costs of industry. Methods We provided a systematic literature review based on articles found in the Pubmed, Embase and EconLit electronic databases, and in a previously published review. Articles published before March 2020 that estimated the total R&D costs were included (22 articles with 45 unique cost estimates). We included only literature in which the methods used to collect the information and to estimate the R&D costs were clearly described; therefore, three reports were excluded. We extracted average pre-launch R&D costs per NME and converted the values to 2019 US dollars (US$) using the gross domestic product (GDP) price deflator. We appraised the suitability of the R&D estimated costs by using a scoring system that captures three domains: (1) how success rates and development time used for cost estimation were obtained; (2) whether the study considered potential sources contributing to the variation in R&D costs; and (3) what the components of the cost estimation were. Results Estimates of total average capitalized pre-launch R&D costs varied widely, ranging from $161 million to $4.54 billion (2019 US$). Therapeutic area-specific estimates were highest for anticancer drugs (between $944 million and $4.54 billion). Our analysis identified a trend of increasing R&D costs per NME over time but did not reveal a relation between cost estimates and study ranking when the suitability scores were assessed. We found no evidence of an increase in suitability scores over time. Conclusion There is no universally correct answer regarding how much it costs, on average, to research and develop an NME. Future studies should explicitly address previously neglected variables, which likely explain some variability in estimates, and consider the trade-off between the transparency and public accessibility of data and their specificity. Use of our proposed suitability scoring system may assist in addressing such issues.

Healthcare systems depend on the availability of new antibiotics. However, there is a lack of treatments for infections caused by multidrug resistant (MDR) pathogens and a weak development pipeline of new therapies. One core challenge to the development of new antibiotics targeting MDR pathogens is that expected revenues are insufficient to drive long-term investment. In the USA and Europe, financial incentives have focussed on supporting R&D, reducing regulatory burden, and extending market exclusivity. Using resistance data to estimate global revenues, we demonstrate that the combined effects of these incentives are unlikely to rekindle investment in antibiotics. We analyse two supplemental approaches: a commercial incentive (a premium price model) and a new business model (an insurance model). A premium price model is familiar and readily implemented but the required price and local budget impact is highly uncertain and sensitive to cross-sectional and longitudinal variation in prevalence of antibiotic resistance. An insurance model delivering risk mitigation for payers, providers and manufacturers would provide an incentive to drive investment in the development of new antibiotics while also facilitating antibiotic conservation. We suggest significant efforts should be made to test the insurance model as one route to stimulate investment in novel antibiotics.

Objectives The primary objective of this study was to compare the availability and access of orphan medicinal products (OMPs) in the devolved nations in the United Kingdom (UK), France, Germany, Italy and Spain. Availability is defined as the possibility to prescribe OMPs. Access refers to their full or partial reimbursement by the public health service. Methods Data were collated on: marketing authorisations, Health Technology Assessment (HTA) decisions, commissioning, and reimbursement decisions, and respective dates of these events for all the OMPs centrally authorised. Indicators of availability of and access to OMPs were calculated in each country and compared. Results We found that since the implementation of the OMPs Regulation in 2000 to end of May 2016, 143 OMPs obtained a marketing authorisation in the European Union. These OMPs are most widely accessible in Germany and France. In the other countries between 30 and 60% of OMPs are reimbursed. In particular in England, less than 50% of centrally authorised OMPs are routinely funded by the NHS, with one-third of these recommended by NICE. In Germany reimbursement is automatically granted to all medicines which receive a marketing authorisation, immediately after authorisation – but since 2011, there is an evaluation and potentially a pricing negotiation between companies and sickness funds (third party payers). In the other countries, the shortest time from authorisation to a reimbursement decision is observed in Italy and France where it takes 18.6 and 19.5 months respectively on average. Conclusions Marketing authorisation granted to OMPs is only the first step, as medicines reach patients when reimbursement decisions are implemented by national health systems (this applies to non-OMPs too). We found that more than a half of centrally authorised OMPs were available in the five selected countries, but that access to patients was further restricted by different national reimbursement policies, especially in the UK, Italy and Spain. Electronic supplementary material The online version of this article (10.1186/s13023-019-1078-5) contains supplementary material, which is available to authorized users.

This paper analyzes pharmaceutical pricing between and within countries to achieve second best static and dynamic efficiency. We distinguish countries with and without universal insurance, because insurance undermines patients' price sensitivity, potentially leading to prices above second-best efficient levels. In countries with universal insurance, if each payer unilaterally sets an incremental cost effectiveness ratio (ICER) threshold based on its citizens' willingness to pay for health; manufacturers price to that ICER threshold; and payers limit reimbursement to patients for whom a drug is cost-effective at that price and ICER, then the resulting price levels and use within each country and price differentials across countries are roughly consistent with second best static and dynamic efficiency. These value-based prices are expected to differ cross-nationally with per capita income and be broadly consistent with Ramsey Optimal Prices. Countries without comprehensive insurance avoid its distorting effects on prices but also lack financial protection and affordability for the poor. Conditions for efficient pricing in these self-pay countries include that consumers are well-informed about product quality and firms can price discriminate between rich and poor subgroups within and between countries.