Drug research and translational bioinformatics.

摘要: Setting the stage Drug research relies on classical scienti!c methods and statistical inferences across spectrum of preclinical discovery to clinical practice: formulate a hypothesis, test hypothesis experimentally, analyze data, make informed decisions accept, reject, or re!ne hypothesis. development is iterative, collaborative, multidisciplinary, culminating in pivotal trials that provide evidence e"cacy safety support market access. Through mid-1990s, this process worked remarkably well some disease areas with rapid identi!cation validated drug targets, such as antiretroviral drugs for treating HIV statins managing high cholesterol cardiovascular diseases, leading launch many new medicines reduced morbidity mortality increased life expectancy. But other cancer, progress has been more modest. Over past 15 years, success story threatened by expiring patents, poorly understood mechanisms, rate attrition, burgeoning costs. As result, pace coming out pharmaceutical industry pipelines slowed considerably. Translational bioinformatics (TBI) recently emerged an important technology address these challenges. At risk being oversold, TBI expected help bridge gap between pathogenic pathways phenotypes guide molecular measurements can improve target identi!cation, selection, trial design. #e quotation Einstein above emphasizes importance “thinking about thinking” need better understand human cognition. In context thinking, cognition thought describes how data acquired from are transformed into information stored knowledge future decision making. today’s world technological computational advances, it easy get lost ubiquitous di"cult problem cognitive overload workload timelines. novel approach solving problems designed avoid getting “lost data.” It makers answer questions integrating pertinent beyond which could be achieved memory, intuition, pattern thinking alone. Today, companies, academia, others involved have access far sophisticated understanding biological networks decode complex phenotypes. #is changed way conducted. also led recent breakthroughs targeted therapies cancer vemurafenib, B-Raf enzyme inhibitor treatment late-stage melanoma, crizotinib, anaplastic lymphoma kinase types non–small cell lung carcinomas. Federal agencies become part solution development. US Food Administration (FDA) had taken notice trend toward lower productivity when launched Critical Path Initiative 2004, was intended frame national strategy driving innovation tools processes would foster turnaround More recently, FDA published strategic plan advancing regulatory science emphasized several priority implementation strategies.1 Obama administration started government center, called National Center Advancing Sciences, partner companies organizations apply advances develop research. Both initiatives acknowledge growth biomedical urgent predictive discovery, development, postmarketing practice. This article provides macroscopic view perspective regulatory, practice continuum.