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SUMMARY:Controlling the speed and trajectory of evolution with counterdiab
 atic driving: applications to human disease and expanding populations - Ja
 cob Scott\, Case Western Reserve University and Cleveland Clinic
DTSTART:20200221T160000Z
DTEND:20200221T170000Z
UID:TALK137122@talks.cam.ac.uk
CONTACT:Diana Fusco
DESCRIPTION:Most mature models of disease evolution have had the stated en
 d-goal of predicting evolutionary trajectories\, and have not even approac
 hed the problem of fine grained control. Part of the problem has been a re
 lative lack of formal connections of classical models of population geneti
 cs to systems which permit even a degree of control. To address this\, we 
 have worked to formally transform one of the governing models in populatio
 n genetics -- the multi-type Wright-Fisher Model -- into a Fokker-Planck a
 pproximation: a fully resolved\, time dependent partial differential equat
 ion on a realistic genotype space. This approximation has allowed us to bo
 rrow results originally developed in a completely different context – co
 unterdiabatic driving to control the behavior of quantum states for applic
 ations like quantum computing and manipulating ultra-cold atoms -- and app
 ly them to a cancer or pathogens searching for a fitness optima under ther
 apy. Implementing these ideas for the first time in a biological context\,
  we show how a set of external control parameters (i.e. varying drug conce
 ntrations / types\, temperature\, nutrients) can guide the probability dis
 tribution of genotypes in a population along a specified path and on a fin
 ite\, clinically-relevant timescale. We develop a closed form ‘control p
 rotocol’ from real world data derived from a genetically engineered yeas
 t system under the selective pressure of anti-microbial agents\, and show 
 that in individual based simulations\, and numerical solutions\, the contr
 ol protocol allows us to control the speed and trajectory of evolution in 
 a 4-allele system. \n\nIn order to approach applicability to real-world\, 
 spatially distributed populations\, in the second part of the talk\, I wil
 l describe our efforts to study the changing evolutionary dynamics along t
 he front of an advancing wave of unicellular organisms (or cells) as they 
 expand their population in space. Using stochastic partial differential eq
 uations\, we explore the length scales at which various characteristic evo
 lutionary regimes are concurrently maintained. The ramifications of these 
 changing evolutionary dynamics in spreading populations on evolutionary co
 ntrol will be discussed as well.
LOCATION: Small Lecture Theatre\, Cavendish Laboratory\, J.J. Thomson Aven
 ue
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