Comparison and critique of two models for regional drug delivery

Assessing the Benefits of Drug Delivery by Nanocarriers: A Partico/Pharmacokinetic Framework

OBJECTIVE

An in vivo kinetic framework is introduced to analyze and predict the quantitative advantage of using nanocarriers to deliver drugs, especially anticancer agents, compared to administering the same drugs in their free form.

METHODS

This framework recognizes three levels of kinetics. First is the particokinetics associated with deposition of nanocarriers into tissues associated with drug effect and toxicity, their residence inside those tissues, and elimination of the nanocarriers from the body. Second is the release pattern in time of free drug from the nanocarriers. Third is the pharmacokinetics of free drug, as it relates to deposition and elimination processes in the target and toxicity associated tissues, and total body clearance. A figure of merit, the drug targeting index (DTI), is used to quantitate the benefit of nanocarrier-based drug delivery by considering the effects of preferential deposition of nanoparticles into target tissues and relative avoidance of tissues associated with drug toxicity, compared to drug that is administered in its free form.

RESULTS

General methods are derived for calculating DTI when appropriate particokinetic, pharmacokinetic, and drug release rate information is available, and it is shown that relatively simple algebraic forms result when some common assumptions are made.

CONCLUSION

This approach may find use in developing and selecting nanocarrier formulations, either for populations or for individuals.

Bayesian approach to estimate AUC, partition coefficient and drug targeting index for studies with serial sacrifice design

PURPOSE

The current study presents a Bayesian approach to non-compartmental analysis (NCA), which provides the accurate and precise estimate of AUC 0 (∞) and any AUC 0 (∞) -based NCA parameter or derivation.

METHODS

In order to assess the performance of the proposed method, 1,000 simulated datasets were generated in different scenarios. A Bayesian method was used to estimate the tissue and plasma AUC 0 (∞) s and the tissue-to-plasma AUC 0 (∞) ratio. The posterior medians and the coverage of 95% credible intervals for the true parameter values were examined. The method was applied to laboratory data from a mice brain distribution study with serial sacrifice design for illustration.

RESULTS

Bayesian NCA approach is accurate and precise in point estimation of the AUC 0 (∞) and the partition coefficient under a serial sacrifice design. It also provides a consistently good variance estimate, even considering the variability of the data and the physiological structure of the pharmacokinetic model. The application in the case study obtained a physiologically reasonable posterior distribution of AUC, with a posterior median close to the value estimated by classic Bailer-type methods.

CONCLUSIONS

This Bayesian NCA approach for sparse data analysis provides statistical inference on the variability of AUC 0 (∞) -based parameters such as partition coefficient and drug targeting index, so that the comparison of these parameters following destructive sampling becomes statistically feasible.

Pharmacokinetic considerations of regional administration and drug targeting: influence of site of input in target tissue and flux of binding protein

Hunt et al. introduced the concept of the Drug Targeting Index (DTI) to quantify the gain associated with regional drug administration and targeting and showed that for the ideal case of all drug first reaching the target DTI = l + CLs/(QT(l-ET)) where CL, is the total clearance of drug from the body (including the target tissue). QT is the target blood flow and ET is the steady-state extraction ratio of the drug in the target. In the model they portrayed the tissue as a homogeneous organ. A more general pharmacokinetic model has been developed that takes into account the three anatomical spaces (vascular, interstitial, and intracellular) of the target organ or tissue and that, in addition to unbound drug permeating the vascular and cellular membranes, protein-bound drug can also flux between the vascular and interstitial spaces. Elimination of unbound drug can take place from the cellular and interstitial spaces. An important parameter influencing the DTI is shown to be the fraction of targeted dose that is eliminated there before it reaches the systemic circulation, fT. Equations have been developed showing the relationship between fT and ET and for DTI when drug is administered at the various sites within the tissue and under a variety of conditions. Only when drug is administered into the target arterial blood stream or when distribution of drug within the target tissue is perfusion rate-limited, does fT = ET and DTI = 1 + CLs/x (QT (I - ET)). Otherwise consideration needs to be given to the permeabilities of both the unbound and bound drug and site of target administration, interstitial or intracellular. Then fT is greater than ET and DTI is greater than that expected had perfusion-rate limited distribution prevailed. The maximum benefit in DTI is seen for a drug of low cellular permeability but high cellular intrinsic clearance administered intracellularly.

Evaluation of the efficiency of targeting of antitumor drugs: simulation analysis based on pharmacokinetic/pharmacodynamic considerations

Antitumor drugs can be classified into two groups; cell cycle phase nonspecific (type I) and specific (type II) drugs. The cytotoxic activity of type I drugs depends on the time-concentration product (AUC), whereas that of type II drugs is time-dependent. Therefore, not only the AUC in the target organ, but also the exposure time is an important factor for evaluating the efficiency of any delivery system for antitumor drugs. In the present study, we examined the factors governing the cytotoxicity of drugs in tumors based on a hybrid perfusion model. It is suggested that the increase in tumor tissue binding of drug results in an increased unbound drug mean residence time (MRTT,U), leading to the increased activity of type II drugs. In contrast, the cytotoxic activity of type I drugs is unaffected by the alteration in the tissue binding since the intracellular AUC defined for unbound drugs (AUCT,U) is unaffected by the extent of drug binding. We also found that the symmetrical increase in the permeability-surface area products (PS) for drug influx (PSinf) and efflux (PSeff) across the tumor plasma membrane results in the unaltered and reduced antitumor activity for the type I and type II drugs, respectively, due to the unaltered AUCT,U and to the reduced MRTT,U. The kinetic analysis suggests that the increase in PSinf/PSeff ratio results in the increased cytotoxic activity of both type I and type II drugs. Collectively, optimization of the antitumor activity can be attained by increasing the tissue binding for type II drugs and by increasing PSinf and/or by decreasing PSeff type I and type II drugs. The present simulation study was carried out by considering the pharmacodynamic features of antitumor drugs and was a method of predicting how the antitumor activity may change on altering each process (tissue binding and membrane permeability for the influx and efflux processes) which governs the characteristics of drug distribution to tumors.

Experimental determination of a drug targeting index for S(+)ibuprofen using the rat air pouch model of inflammation

We have used the rat air pouch model of inflammation and S(+)ibuprofen as an experimental model system to enable the quantitative assessment of the pharmacokinetic determinants of site specific drug delivery. S(+)ibuprofen (50 & 1mg/kg) was administered directly into six day old air pouches immediately following the injection of the irritant carrageenan. Serial exudate and plasma samples were collected and analysed for ibuprofen by HPLC. The procedure was repeated following administration of S(+)ibuprofen (20 & 5mg/kg) intravenously. The parameters describing events in the air pouch and plasma indicated linear kinetics over the doses employed. The dose normalised AUCs were then used to formulate a quantitative measure of benefit for S(+)ibuprofen delivered directly to the air pouch. A Drug Targeting Index (DTI) was calculated from the ratio of AUC in the air pouch and plasma following direct intrapouch administration divided by the same ratio following intravenous administration and gave a value of 130. This pharmacokinetic measure of benefit represents the maximum advantage afforded by the site specific delivery of S(+)ibuprofen as the whole of the administered dose is delivered directly to the site of action.