The automation of science

The automation of science

23 Pages · 2017 · 996 KB · English

Powers to Augment Scientists n They flawlessly remember vast numbers of facts n They execute flawless logical reasoning n They execute near optimal probabilistic reasoning n They learn more rationally than humans n They can learn from vast amounts of data n They can 'read' millions of scientific 

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The Automation of Science Ross D King, University of Manchester, [email protected] AI Systems have Superhuman Powers to Augment Scientists n They flawlessly remember vast numbers of facts n They execute flawless logical reasoning n They execute near optimal probabilistic reasoning n They learn more rationally than humans n They can learn from vast amounts of data n They can ‘read’ millions of scientific papers n Etc Scientific Discovery Science is a well suited application area for AI n Scientific problems are abstract, but involve the real world n Scientific problems are restricted in scope – no need to know about “Cabbages and Kings” n Nature is honest – no malicious agents n Nature is a worthy object of our study n The generation of scientific knowledge is a public good Meta Dendral Analysis of mass spectrometry data Joshua Lederburg , Ed Feigenbaum , Bruce Buchanan, Karl Djerassi , et al 1960 70s Bacon Rediscovering physics and chemistry: Langley, Bradshaw, Simon (1979) Robot Scientists The Concept of a Robot Scientist Background Knowledge Analysis Final Theory Experiment selection Robot Results Interpretation C omputer systems capable of originating their own experiments, physically executing them , interpreting the results, and then repeating the cycle Hypothesis Formation Potential Advantages of Robot Scientists n Faster scientific discovery n Cheaper experimentation n They are more easily reproduced and trained than human scientists n They are harder working than human scientists n Improved knowledge/data sharing, and reproducibility Robot Scientist Timeline n 1999 2004 Initial Robot Scientist Project – Limited Hardware: Collaboration with Douglas Kell ( Aber Biology), Steve Oliver (Manchester), Stephen Muggleton (Imperial) King et al (2004) Nature, 427, 247 252 n 2004 2011 Adam – Yeast Functional Genomics – Sophisticated Laboratory Automation: Collaboration with Steve Oliver (Cambridge) King et al (2009) Science, 324, 85 89 n 2008 2015 Eve – Drug Design for Tropical Diseases – Sophisticated Laboratory Automation: Collaboration with Steve Oliver (Cambridge) Williams et al ( 2015) Royal Society Interface, DOI 101098 /rsif20141289 n 2015 2018 Eve – Human cells Cancer, Yeast Aging – DARPA, CHIST ERA Adam Adam n Adam was the first AI system to both explicitly form hypotheses and experiments, and physically do the experiments n Adam generated and confirmed novel functional genomics hypotheses concerning the identify of genes encoding enzymes catalysing orphan reactions in the metabolic network of the yeast S cerevisiae n Adam's conclusions have been manually verified using bioinformatic and biochemical evidence Adam Movie Eve Eve Parasitic Diseases targeted Malaria Shistosomaisis L eishmania Chagas Why Tropical Diseases? n Millions of people die of these diseases, and hundreds of millions of people suffer infection n It is clear how to cure these diseases – kill the parasites n They are “neglected”, so avoid competition from the Pharmaceutical industry The Economics of Intelligent Screening Nm Number of compounds not assayed by Eve Tm Cost of the time to screen a compound using the mass screening assay Cm Cost of the loss of a compound in the mass screening assay Nx Number of hits missed by Eve Tc Cost of the time to screen a compound using a cherry picking (confirmation or intelligent) assay Cc Cost of the loss of a compound in a cherry picking assay Uh Utility of a hit Ne Number of compounds assayed by Eve Ne : Comp ounds assa ye d by Eve Tm : Time per co mp ound, ma ss scre en Tc : Time per co mp ound, ch erryp icki ng assa y Cm : Cost per lost co mp ound, ma ss scre en Cc : Cost per lost co mp ound, ch erryp icki ng assa y Nx : Hits mi sse d by Eve Uh : Utility of a hit Nm : Comp ounds not assa ye d by Eve !" #" $" Triclosan Repositioned for Malaria n Simple compound n Known to be safe – used in toothpaste n Targets both DHFR and FAS II – well established targets n Demonstrated activity using multiple wet

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