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The Role of Pharmacological Predictors in Drug Development. Prof. Hartmut Derendorf University of Florida. Resistance Development. Approved Antibacterial Agents 1983-2004. Pharmacodynamics conc. vs effect. Pharmacokinetics conc. vs time. 0.4. Conc. Effect. 0.0. Time. 0. 25.
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The Role of Pharmacological Predictors in Drug Development Prof. Hartmut Derendorf University of Florida
Pharmacodynamics conc. vs effect Pharmacokinetics conc. vs time 0.4 Conc. Effect 0.0 Time 0 25 Conc. (log) 10 -3 PK/PD effect vs time 1 Effect 0 Time 0
PD PK MIC Serum
Problems: Protein Binding Tissue Distribution Pharmacokinetics
vascular space extravascular space binding to extracellular biological material plasma protein binding blood cell binding, diffusion into blood cells, binding to intracellular biological material tissue cell binding, diffusion into tissue cells, binding to intracellular biological material
Azithromycin Tissue Concentrations tonsil (t) prostate (P) lung (L) serum (S) 500 mg p.o. from Foulds et al. (1990)
Tissue Concentrations Tissue can be looked at as an aqueous dispersed system of biological material. It is the concentration in the water of the tissue that is responsible for pharmacological activity. Total tissue concentrations need to be interpreted with great care since they reflect hybrid values of total amount of drug (free + bound) in a given tissue ‘Tissue-partition-coefficients’ are not appropriate since they imply homogenous tissue distribution
The free (unbound)concentration of the drug at the receptor site should be used in PK/PD correlations to make prediction for pharmacological activity
Blister Fluid • Blister fluid is a ‘homogenous tissue fluid’ • Protein binding in blister fluid needs to be considered
Ampicillin Cloxacillin Serum Free blister fluid
Microdialysis Perfusate Dialysate Interstitium Capillary Cell
Cefpodoxime (Protein binding 17-30%) Cefixime (Protein binding 65%)
iv dose of 20 mg/kg of cefpodoxime (n=6) plasma lung muscle
To compare the soft tissue distribution of these two antibiotics after 400mg oral dose in healthy male volunteers by microdialysis Two way cross-over, single oral dose study Clinical study Cefpodoxime and Cefixime
Clinical Microdialysis Cefixime 400 mg po Cefpodoxime 400 mg po Liu & Derendorf, JAC 50, 19 (2002)
PD PK MIC Serum
Ceftazidime K. pneumoniae in neutropenic mice Craig 2002
Temafloxacin S. pneumoniae in neutropenic mice Craig 2002
Problems: MIC is imprecise MIC is monodimensional MIC is used as a threshold When MIC does not explain the data, patches are used(post-antibiotic effect, sub-MIC effect) Pharmacodynamics
Kill Curves flask reservoir tubing connector pump waste Auto-dilution system
Kill Curves of Ceftriaxone S. pneumoniae ATCC6303 MIC: 20 ng/mL H. influenzae ATCC10211 MIC: 5 ng/mL
Kill Curves of Ceftriaxone S. pneumoniae ATCC6303 MIC: 20 ng/mL H. influenzae ATCC10211 MIC: 5 ng/mL
PK-PD Model Maximum Growth Rate Constant k Maximum Killing Rate Constant k-kmax Initially, bacteria are in log growth phase
Single Dose Piperacillin vs. E. coli
Dosing Interval Piperacillin (2g and 4g) vs. E. coli q24h q8h q4h
PK-PD Model In animals Bacterial survival fraction of P. aeruginosa in a neutropenic mouse model at different doses (mg/kg) of piperacillin (Zhi et al., 1988)
FDA Draft-Guidance for Industry (1997) Providing Clinical Evidence of Effectiveness for Human Drug and Biological Products New Dosage Form of a Previously Studied Drug In some cases, modified release dosage forms may be approved on the basis of pharmacokinetic data linking the new dosage form from a previously studied immediate-release dosage form. Because the pharmacokinetic patterns of controlled-release and immediate release dosage forms are not identical, it is generally important to have some understanding of the relationship of blood concentration to response to extrapolate to the new dosage form.
500 mg IR Plasma and free tissue levels n = 12 (means +/- S.D.) total plasma concentrations free tissue concentrations
Plasma and free tissue levels 500 mg MR 750 mg MR n = 12 (means +/- S.D.) total plasma concentrations free tissue concentrations
Pre-existing subpopulations Emerging subpopulations Adaptive resistance (transporters) Resistance Modeling
Drug (C) Killing fs(C) Bacteria (S) Growth ( k0) Bacteria (R) fr(C) Bacteria pool Two sub-population model OBS: same growth rate for sensitive (S) and resistant (R)
Modified Emax Model: Dose ka Cp ke kill (-) Cr k0 kecr Bacteria Comparing to Emax model:
Model Comparison – E. coli Two sub-population model (simultaneous fit) Modified Emax model (simultaneous fit)
Summary • A simple comparison of serum concentration and MIC is usually not sufficient to evaluate the PK/PD-relationships af anti-infective agents. • Protein binding and tissue distribution are important pharmacokinetic parameters that need to be considered. Microdialysis can provide information on local exposure. • PK-PD analysis based on MIC alone can be misleading. • Microbiological kill curves provide more detailed information about the PK/PD-relationships than simple MIC values.
Wild Card Patent Extension Proposal A company that receives approval for a new antibiotic, or a new indication for an existing antibiotic, that treats a targeted pathogen would be permitted to extend the market exclusivity period for another of the company’s FDA-approved drugs.
Workshops at ECCMID and ICAAC Symposia at ECCMID and ICAAC Joint Symposium with FDAand IDSA Website with slides, presentations and tons of information ISAPInternational Society of Anti-Infective Pharmacology www.isap.org
Acknowledgements Edgar Schuck Qi Liu Ping Liu Teresa Dalla Costa Amparo de la Peña Ariya Khunvichai Arno Nolting Wanchai Treeyaprasert Stephan Schmidt Elizabeth Potocka Martin Brunner Markus Müller Kenneth Rand Alistair Webb Maria Grant Andreas Kovar Olaf Burkhardt Vipul Kumar Yanjun Li Oliver Ghobrial April Barbour