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VERSION:2.0
CALSCALE:GREGORIAN
METHOD:PUBLISH
BEGIN:VEVENT
DTSTAMP:20260924T134056Z
DTSTART:20261005T130000Z
DTEND:20261005T140000Z
SUMMARY:Frankie Patten-Elliott -- Modelling drug binding to biological io
 n channels [IN PERSON]
UID:{http://www.columbasystems.com/customers/uom/gpp/eventid/}o5y-mufkwxw
 b-310hsz
DESCRIPTION:Join us for this seminar by Frankie Patten-Elliott (Mancheste
 r) as part of the Maths in the Life Sciences seminar series (and the onl
 ine North West Seminar Series in Mathematical Biology and Data Sciences 
 in collaboration with Liverpool Universities). \n\nTitle: Modelling drug
  binding to biological ion channels\n\nAbstract: In a healthy heart\, io
 n channels in cardiac muscle cells ensure the heart pumps in a regular\,
  coordinated manner. Pharmaceutical drug compounds are prone to binding 
 to cardiac ion channels\, disrupting healthy cardiac function and someti
 mes leading to the onset of cardiac arrhythmias. During drug development
 \, significant time and money are spent on cardiac safety testing to avo
 id these potentially fatal side-effects. Much consideration is\, therefo
 re\, given to improving cardiac safety testing methods to reduce uncerta
 inty in risk predictions\, while minimising time and cost.\n\nMathematic
 al models can provide key insights into the underlying mechanisms that d
 efine complex biological systems. In the field of cardiac electrophysiol
 ogy\, models of ion channel gating and drug binding mechanisms can be ef
 fective tools for predicting drug-induced proarrhythmic risk. In this ta
 lk\, I will describe methods to improve models of drug binding mechanism
 s\, with a specific focus on binding in the hERG channel.\n\nRecent tech
 nological advances have enabled the collection of high-frequency electro
 physiology data that can be used to calibrate models of drug-channel bin
 ding. However\, careful consideration must be given to ensure the collec
 ted data are sufficiently information-rich to discriminate between diffe
 rent proposed models of binding mechanisms. I present an approach that p
 roduces optimal experimental designs to aid model discrimination\, there
 by uncovering drug-specific mechanistic insights and assisting in cardia
 c risk assessment. \n\nTime-permitting I will also discuss the potential
  directions of my current research focusing on modelling the neuroendocr
 ine HPA axis.\n\nThe talk will be also be streamed via Teams\, please co
 ntact carl.whitfield@manchester.ac.uk or igor.chernyavsky@manchester.ac.
 uk for the link\, or sign up to the mailing list.\n\nTo subscribe to the
  mailing list for this event series\, please send an e-mail with the phr
 ase “subscribe math-lifesci-seminar” in the message body to listserv@lis
 tserv.manchester.ac.uk
STATUS:TENTATIVE
TRANSP:TRANSPARENT
CLASS:PUBLIC
LOCATION:6.53 (Niels Bohr Common Room)\, Schuster Building\, Manchester
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