Kinetics & PK

Rate laws fitted to reactor data and a compartment model fitted to plasma and metabolite concentrations share the same core structure: a nonlinear model with several parameters, multiple responses that may be correlated, and data that may or may not identify every parameter individually. Pharmacokinetics adds a population layer, because parameters vary from subject to subject, but the toolkit underneath is common to both: maximum-likelihood estimation across responses, the parameter Jacobian and the information matrix built from it, identifiability analysis, and experimental design that chooses runs to maximize information about the parameters. The worked examples use Wolfram Language throughout.

• Arrhenius Reparameterization: Same Data, Better-Posed Parameters

  Why A and Ea come out almost perfectly correlated in the standard Arrhenius fit, and how a reference temperature, chosen with the Jacobian's help, removes the correlation without adding a single run.