Monday 13th November 2017

Organisers

Michael Chappell (Engineering), Louise Dyson (Mathematics, Life Sciences).

This meeting will consider the techniques for ascertaining whether unknown models or model parameters can be identified uniquely or otherwise from available measurements of the system. The talks will outline basic concepts and state-of-the-art approaches in the field of structural (a priori) identifiability analysis, this being a prerequisite for experimental design, parameter estimation and system identification. Issues regarding practical (a posteriori) identifiability will also be considered alongside discussion of associated statistical inference with respect to the parameter estimation performed. Applications of these techniques to parameterised models across a range of disciplines will also be provided.

Schedule (preliminary)

Talks will be in B3.02 (Mathematics Institute, Zeeman Building)

12:00	lunch (Mathematics Common Room)
13:00	welcome
13:05	Neil Evans (Engineering, Warwick)
	Structural identifiability analysis, with applications in Systems Pharmacology
13:40	Diana Cole (Mathematics, Statistics & Actuarial Science, Kent)
	Inference with non-identifiable models: reparameterisation, constraints and integrated models
14:10	Tom Grandjean (WMG, Warwick)
	Structural Identifiability of Li-ion Models
14:30	James Yates (DMPK, AstraZeneca, Cambridge)
	Model building with animal data: Sparse sampling, heterogeneity and other nuisances
15:00	coffee / tea (Mathematics Common Room)
15:30	David Smith (Mathematics, Birmingham)
	Pharmacokinetic model-based machine learning
16:00	Ben Lambert (Imperial College)
	tbc
16:30	Leon Aarons (Pharmacy, Manchester)
	Identifiability and random effects
17:00	Gary Mirams (Mathematical Sciences, Nottingham)
	Minimising uncertainty in ion channel models with experimental design
17:30	discussion and closing remarks
17:45	drinks / snacks (Mathematics Common Room)

No registration required, everyone interested is invited!