Pharmacokinetic and Pharmacodynamic Drug-Drug Interactions: Research Methods and Applications

Because of the high research and development cost of new drugs, the long development process of new drugs, and the high failure rate at later stages, combining past drugs has gradually become a more economical and attractive alternative. However, the ensuing problem of drug-drug interactions (DDIs) urgently need to be solved, and combination has attracted a lot of attention from pharmaceutical researchers. At present, DDI is often evaluated and investigated from two perspectives: pharmacodynamics and pharmacokinetics. However, in some special cases, DDI cannot be accurately evaluated from a single perspective. Therefore, this review describes and compares the current DDI evaluation methods based on two aspects: pharmacokinetic interaction and pharmacodynamic interaction. The methods summarized in this paper mainly include probe drug cocktail methods, liver microsome and hepatocyte models, static models, physiologically based pharmacokinetic models, machine learning models, in vivo comparative efficacy studies, and in vitro static and dynamic tests. This review aims to serve as a useful guide for interested researchers to promote more scientific accuracy and clinical practical use of DDI studies.

Mechanisms of respiratory depression induced by the combination of buprenorphine and diazepam in rats

BACKGROUND

The safety profile of buprenorphine has encouraged its widespread use. However, fatalities have been attributed to benzodiazepine/buprenorphine combinations, by poorly understood mechanisms of toxicity. Mechanistic hypotheses include (i) benzodiazepine-mediated increase in brain buprenorphine (pharmacokinetic hypothesis); (ii) benzodiazepine-mediated potentiation of buprenorphine interaction with opioid receptors (receptor hypothesis); and (iii) combined effects of buprenorphine and benzodiazepine on respiratory parameters (pharmacodynamic hypothesis).

METHODS

We studied the neuro-respiratory effects of buprenorphine (30 mg kg-1, i.p.), diazepam (20 mg kg-1, s.c.), and diazepam/buprenorphine combination in rats using arterial blood gas analysis, plethysmography, and diaphragm electromyography. Pretreatments with various opioid and gamma-aminobutyric acid receptor antagonists were tested. Diazepam impact on brain 11C-buprenorphine kinetics and binding to opioid receptors was studied using positron emission tomography imaging.

RESULTS

In contrast to diazepam and buprenorphine alone, diazepam/buprenorphine induced early-onset sedation (P<0.05) and respiratory depression (P<0.001). Diazepam did not alter 11C-buprenorphine brain kinetics or binding to opioid receptors. Diazepam/buprenorphine-induced effects on inspiratory time were additive, driven by buprenorphine (P<0.0001) and were blocked by naloxonazine (P<0.01). Diazepam/buprenorphine-induced effects on expiratory time were non-additive (P<0.001), different from buprenorphine-induced effects (P<0.05) and were blocked by flumazenil (P<0.01). Diazepam/buprenorphine-induced effects on tidal volume were non-additive (P<0.01), different from diazepam- (P<0.05) and buprenorphine-induced effects (P<0.0001) and were blocked by naloxonazine (P<0.05) and flumazenil (P<0.05). Compared with buprenorphine, diazepam/buprenorphine decreased diaphragm contraction amplitude (P<0.01).

CONCLUSIONS

Pharmacodynamic parameters and antagonist pretreatments indicate that diazepam/buprenorphine-induced respiratory depression results from a pharmacodynamic interaction between both drugs on ventilatory parameters.

Relative prevalence of 10 types of pharmacodynamic interactions in psychiatric treatment

OBJECTIVE

To assess the relative prevalence and factors affecting the prescription of medication combinations with a theoretical efficacy limiting pharmacodynamic interaction, defined as two medications with opposing indications and side effects or antagonistic action at the primary receptor of mechanism of action.

METHOD

One hundred sixteen combinations were identified for 10 types of pharmacodynamic interactions. PubMed was searched for each combination to assess the quality of evidence either supporting clinical use or verifying reduced efficacy. Micromedex was searched to determine the presence of warnings to prescribers of reduced efficacy. The prevalence in clinical practice was determined by computer review of the Genoa Healthcare database for all prescribers at 10 participating community mental health centers. The expected prevalence was calculated as the product of the probability of each medication prescribed alone and was compared with the actual prevalence of the combination using the test of proportions.

RESULTS

The frequency of prescription of eight combinations met the Bonferroni corrected level of significance of p < 0.001. Four were combinations of amphetamine and D2 antagonists and each were prescribed less often than chance, p = 0.0001 consistent with epidemiological studies and multiple animal studies verifying an efficacy limiting interaction. Despite epidemiological studies indicating increased risk of accidents, alprazolam and amphetamine were prescribed more often than chance, p = 0.0001. Micromedex generated warnings for efficacy limiting interactions for five other combinations, but with no subsequent change in prescription frequency.

CONCLUSIONS

Neither presence of medical evidence nor warnings from Micromedex consistently affect the prescription of combinations with pharmacodynamic efficacy limiting interactions.

Assessment of Three-Drug Combination Pharmacodynamic Interactions in Pancreatic Cancer Cells

The pharmacodynamic interactions among trifluoperazine (TFP), gemcitabine (GEM), and paclitaxel (PTX) were assessed in pancreatic cancer cells (PANC-1). The phenothiazine TFP was chosen for its potential activity on cancer stem cells, while GEM and PTX cause apoptosis. Effects of each drug alone and in various combinations on cell growth inhibition of PANC-1 cells were studied in vitro to determine the drug-specific parameters and assess the nature of drug interactions. Joint inhibition (JI) and competitive inhibition (CI) equations were applied with a ψ interaction term. TFP fully inhibited growth of cells (I_max = 1) with an IC₅₀ = 9887 nM. Near-maximum inhibition was achieved for GEM (I_max = 0.825) and PTX (I_max= 0.844) with an IC₅₀ = 17.4 nM for GEM and IC₅₀ = 7.08 nM for PTX. Estimates of an interaction term ψ revealed that the combination of TFP-GEM was apparently synergistic; close to additivity, the combination TFP-PTX was antagonistic. The interaction of GEM-PTX was additive, and TFP-GEM-PTX was synergistic but close to additive. The combination of TFP IC₆₀-GEM IC₆₀-PTX IC₆₀ seemed optimal in producing inhibition of PANC-1 cells with an inhibitory effect of 82.1-90.2%. The addition of ψ terms to traditional interaction equations allows assessment of the degree of perturbation of assumed mechanisms.

The interaction between ethanol and pregnanolone at induction of anaesthesia investigated with a threshold method in male rats

1. An anaesthesia threshold was used to investigate the pharmacodynamic and pharmacokinetic interactions between ethanol and pregnanolone in male rats. 2. The criterion to determine threshold doses of pregnanolone was the first burst suppression of 1 s in the EEG. 3. Ethanol (0.5, 1.0, 1.5 and 2.0 g kg(-1)) was injected i.p. 15 min before pregnanolone infusion. Trunk blood, serum, cortex, cerebellum, hippocampus, striatum, brain stem, fat and muscle tissues obtained at criterion were used to determine ethanol (blood) and pregnanolone. Ethanol reduced threshold doses in a dose dependent linear manner. A similar reduction of pregnanolone tissue concentrations was only found in brain stem and striatum. Deviations consisted of larger decreases in serum, cerebellum and hippocampus after 0.5 g kg(-1) ethanol and in cerebellum, cortex and hippocampus after 2.0 g kg(-1) of ethanol. Positive correlations between dose and concentration of pregnanolone was recorded in brain stem, hippocampus, cerebellum and cortex. A kinetic component influenced the concentration in cortex. There was a correlation between dose and serum concentration of pregnanolone only after ethanol. In the muscle 0.5 g kg(-1) ethanol had no influence on pregnanolone concentration. 4. The linear, additive pharmacodynamic interaction could involve the GABA ionophore. A pharmacokinetic interaction was found in cortex. The retained high uptake of pregnanolone in muscle (after 0.5 g kg(-1)) corresponded to losses in other tissues (including serum). The reduced uptake of pregnanolone in cerebellum, cortex and hippocampus (after 2.0 g kg(-1)) was not due to a corresponding change in serum concentration. It was probably due to a reduced blood flow.