Abstract
Drug-discovery has become a complex discipline in which the amount of knowledge about human biology, physiology, and biochemistry have increased. In order to harness this complex body of knowledge mathematics can play a critical role, and has actually already been doing so. We demonstrate through four case studies, taken from previously published data and analyses, what we can gain from mathematical/analytical techniques when nonlinear concentration-time courses have to be transformed into their equilibrium concentration-response (target or complex) relationships and new structures of drug potency have to be deciphered; when pattern recognition needs to be carried out for an unconventional response-time dataset; when what-if? predictions beyond the observational concentration-time range need to be made; or when the behaviour of a semi-mechanistic model needs to be elucidated or challenged. These four examples are typical situations when standard approaches known to the general community of pharmacokineticists prove to be inadequate.
| Original language | English |
|---|---|
| Pages (from-to) | 3-21 |
| Number of pages | 19 |
| Journal | Journal of Pharmacokinetics and Pharmacodynamics |
| Volume | 45 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2018 |
Keywords
- Receptors
- Drug-disposition
- Dose-responsetime analysis
- Michaelis-menten
- Quasi-steady-state
- Singular perturbations
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