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Web End = Naunyn-Schmiedeberg's Arch Pharmacol (2016) 389:353360 DOI 10.1007/s00210-016-1216-8
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Managing risks in drug discovery: reproducibility of published findings
Aimo Kannt1,2 & Thomas Wieland2
Received: 22 December 2015 /Accepted: 5 February 2016 /Published online: 17 February 2016 # The Author(s) 2016. This article is published with open access at Springerlink.com
Abstract In spite of tremendous advances in biopharmaceutical science and technology, the productivity of pharmaceutical research and development has been steadily declining over the last decades. The reasons for this decline are manifold and range from improved standard of care that is more and more difficult to top to inappropriate management of technical and translational risks along the R&D value chain. In this short review, major types of risks in biopharmaceutical R&D and means to address them will be described. A special focus will be on a risk, i.e., the lack of reproducibility of published information, that has so far not been fully appreciated and systematically analyzed. Measures to improve reproducibility and trust in published information will be discussed.
Keywords Risk management . Research and development .
Reproducibility . Technical risk . Translational risk
The decline in pharmaceutical R&D productivity
The last decades have seen major advances and productivity gains in science and technology. The polymerase chain reaction (Saiki et al. 1985), for example, has revolutionized molecular biology and made it possible to amplify and quantify nucleic acids in a short time and at high throughput.
Next-generation sequencing technologies (Ozsolak 2012) have reduced time and cost of whole-genome sequencing by several orders of magnitude from more than 10 years and three billion dollars for the first sequence of the human genome (Lander et al. 2001; Venter et al. 2001) to a few days and a thousand dollars (Hayden 2014), with further time and cost reductions being in sight. Computer power has increased exponentially: With well in excess of 1011 floating point operations per second (100 GFLOPS), modern smartphones are more than ten times more powerful than Deep Blue, the IBM supercomputer that beat chess world champion Garri Kasparow in 1997, that achieved 11.4 GFLOPS. The...