RESUMO
Given the high attrition rates, substantial costs and slow pace of new drug discovery and development, repurposing of 'old' drugs to treat both common and rare diseases is increasingly becoming an attractive proposition because it involves the use of de-risked compounds, with potentially lower overall development costs and shorter development timelines. Various data-driven and experimental approaches have been suggested for the identification of repurposable drug candidates; however, there are also major technological and regulatory challenges that need to be addressed. In this Review, we present approaches used for drug repurposing (also known as drug repositioning), discuss the challenges faced by the repurposing community and recommend innovative ways by which these challenges could be addressed to help realize the full potential of drug repurposing.
Assuntos
Descoberta de Drogas , Indústria Farmacêutica , Reposicionamento de Medicamentos/normas , HumanosAssuntos
Bases de Dados de Produtos Farmacêuticos , Descoberta de Drogas/tendências , Indústria Farmacêutica/tendências , Terapia de Alvo Molecular , Ensaios Clínicos como Assunto , Descoberta de Drogas/economia , Descoberta de Drogas/métodos , Indústria Farmacêutica/economia , Indústria Farmacêutica/métodos , Drogas em Investigação/farmacologia , Drogas em Investigação/uso terapêutico , Competição EconômicaRESUMO
The application of translational approaches (e.g. from bed to bench and back) is gaining momentum in the pharmaceutical industry. By utilizing the rapidly increasing volume of data at all phases of drug discovery, translational bioinformatics is poised to address some of the key challenges faced by the industry. Indeed, computational analysis of clinical data and patient records has informed decision-making in multiple aspects of drug discovery and development. Here, we review key examples of translational bioinformatics approaches to emphasize its potential to enhance the quality of drug discovery pipelines, reduce attrition rates and, ultimately, lead to more effective treatments.
Assuntos
Biologia Computacional/métodos , Descoberta de Drogas/métodos , Animais , Indústria Farmacêutica/métodos , HumanosRESUMO
The 1990s and early years of this century have seen a series of large-scale mergers and acquisitions in the Pharmaceutical and Biotech arena. These activities each required integration at multiple levels. One of the most important activities is the integration of the R&D pipelines of the participants. We outline the combined portfolio and bioinformatic strategy that was used, and detail the lessons learned for the longer term, from the GlaxoWellcome-SmithKline-Beecham merger in 2000. To date, this has been the largest merger of two equally sized Pharma R&D organisations.