Towards a 21st-century roadmap for biomedical research and drug discovery: consensus report and recommendations

Abstract

Decades of costly failures in translating drug candidates from preclinical disease models to human therapeutic use warrant reconsideration of the priority placed on animal models in biomedical research. Following an international workshop attended by experts from academia, government institutions, research funding bodies, and the corporate and non-governmental organisation (NGO) sectors, in this consensus report, we analyse, as case studies, five disease areas with major unmet needs for new treatments. In view of the scientifically driven transition towards a human pathways-based paradigm in toxicology, a similar paradigm shift appears to be justified in biomedical research. There is a pressing need for an approach that strategically implements advanced, human biology-based models and tools to understand disease pathways at multiple biological scales. We present recommendations to help achieve this.

Sobre uma política de ciência e tecnologia para a saúde

“…No campo da pesquisa biomédica, um dos grandes desafios tem sido a dificuldade de decifrar a complexidade de enfermidades que cada vez mais se colocam como responsáveis por grande parte da carga de doenças em todo o mundo. E uma das propostas apresentadas para superar essa dificuldade é a da substituição dos modelos animais por modelos humanos de experimentação em pesquisa pré-clínica 45 . O desenvolvimento desse tema, muito provavelmente, crescerá de importância nos próximos anos e será indispensável o balanceamento dos impactos éticos envolvidos.…”

Hurdles in Basic Science Translation

“…Indeed, there are many new and exciting models being developed, for example human pluripotent stem cells, 3D culture systems, genome editing in vitro , and good quality normal and diseased human tissue, derived from post-mortem or live biopsies (Langley et al, 2017). Importantly, however, there is as yet no good behavioral component in alternative (non-animal) models, and behavior is a vital component of many diseases.…”

“…This is an issue that is relevant to researcher scientists, practitioners, government bodies and the general public alike. The cost of research and development for a successful drug is high, with estimates varying from $US 1 billion (Collins, 2011; Davidson, 2011) to United States $2.6 billion (DiMasi et al, 2016; Langley et al, 2017). Furthermore, it typically takes 10–20 years to bring a new treatment from initial discovery to final approval.…”

NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions

“…Identifying drug-target interactions (DTIs) through computational approaches can greatly narrow down the large search space of drug candidates for downstream experimental validation, and thus significantly reduce the high cost and the long period of developing a new drug (Langley et al, 2017). Currently, the structure based (Morris et al, 2009), ligand-similarity based (Keiser et al, 2007) and machine learning based methods (Yuan et al, 2016;Luo et al, 2017) are three main classes of prediction approaches in computational aided drug screening.…”