Adaptive Biomedical Innovation.

Adaptive Biomedical Innovation (ABI) is a multistakeholder approach to product and process innovation aimed at accelerating the delivery of clinical value to patients and society. ABI offers the opportunity to transcend the fragmentation and linearity of decision-making in our current model and create a common collaborative framework that optimizes the benefit and access of new medicines for patients as well as creating a more sustainable innovation ecosystem.

Pharmacotherapy for Neurodegenerative Diseases: Are We Approaching the Tipping Point?

Neurodegenerative diseases continue to represent major unmet medical and public health needs and will increasingly strain the healthcare system as people live longer due to medical advances in other diseases. Hopefully the emergence of increased understanding of the biology of these conditions coupled with novel clinical pharmacology tools, clinical trial designs, and regulatory innovation will allow the emergence of highly effective symptomatic and disease modifying pharmacotherapies.

Recent trends and success factors in reducing the lag time to approval of new drugs in Japan.

For many years, approvals of new drugs in Japan have lagged behind those in the United States and Europe. As a result of simultaneous global development strategies, more widespread inclusion of Japan in multiregional clinical trials, and significant reforms and investment in Japan's Pharmaceuticals and Medical Devices Agency reviewer capacity and capability, the drug lag appears to be diminishing. This is allowing new medicines to be approved sooner in Japan, improving the efficiency of drug development and benefiting patients.

A proposal for integrated efficacy-to-effectiveness (E2E) clinical trials.

We propose an "efficacy-to-effectiveness" (E2E) clinical trial design, in which an effectiveness trial would commence seamlessly upon completion of the efficacy trial. Efficacy trials use inclusion/exclusion criteria to produce relatively homogeneous samples of participants with the target condition, conducted in settings that foster adherence to rigorous clinical protocols. Effectiveness trials use inclusion/exclusion criteria that generate heterogeneous samples that are more similar to the general patient spectrum, conducted in more varied settings, with protocols that approximate typical clinical care. In E2E trials, results from the efficacy trial component would be used to design the effectiveness trial component, to confirm and/or discern associations between clinical characteristics and treatment effects in typical care, and potentially to test new hypotheses. An E2E approach may improve the evidentiary basis for selecting treatments, expand understanding of the effectiveness of treatments in subgroups with particular clinical features, and foster incorporation of effectiveness information into regulatory processes.

Reinventing bioinnovation.

The landscape for bioinnovation is undergoing a seismic shift as drug developers, regulators, academic institutions, and government research organizations adapt to the formidable challenge of bringing new medicines to market. The inability to translate current advances in the scientific understanding of disease into new therapeutics is forcing all sectors to replace traditional drug development paradigms with newer and more efficient models. This issue of Clinical Pharmacology & Therapeutics explores these changes to the bioinnovation ecosystem.

Advancing the science of pharmacovigilance.

The importance of detecting postmarketing safety signals earlier and with a high degree of fidelity is increasingly important and of great interest to industry, regulators, and the public. This issue of Clinical Pharmacology & Therapeutics contains two companion articles that represent exciting new advances in the field of pharmacovigilance and postmarketing safety signal detection. Given that drug safety evaluation and pharmacovigilance science are core competencies in the discipline of clinical pharmacology, these articles should be of interest to clinical pharmacologists as well as drug safety professionals.

Systematic reviews and meta-analyses in the new age of transparency.

Systematic reviews and meta-analyses are useful in integrating large amounts of data to inform medical practice, and it is likely that the already large number of published meta-analyses will increase further as the provisions in the Food and Drug Administration Amendments Act and other forces result in dramatically increased transparency about the design and results of clinical trials. It is critical for readers of these analyses to be capable of assessing the quality of this research.

An evaluation of computer-aided disproportionality analysis for post-marketing signal detection.

To understand the value of computer-aided disproportionality analysis (DA) in relation to current pharmacovigilance signal detection methods, four products were retrospectively evaluated by applying an empirical Bayes method to Merck's post-marketing safety database. Findings were compared with the prior detection of labeled post-marketing adverse events. Disproportionality ratios (empirical Bayes geometric mean lower 95% bounds for the posterior distribution (EBGM05)) were generated for product-event pairs. Overall (1993-2004 data, EBGM05> or =2, individual terms) results of signal detection using DA compared to standard methods were sensitivity, 31.1%; specificity, 95.3%; and positive predictive value, 19.9%. Using groupings of synonymous labeled terms, sensitivity improved (40.9%). More of the adverse events detected by both methods were detected earlier using DA and grouped (versus individual) terms. With 1939-2004 data, diagnostic properties were similar to those from 1993 to 2004. DA methods using Merck's safety database demonstrate sufficient sensitivity and specificity to be considered for use as an adjunct to conventional signal detection methods.