Pharmacokinetics Of Individual Drugs Research Articles

Active Targeting Nanoparticle Self‐Assembled from Cisplatin‐Palbociclib Amphiphiles Ensures Optimal Drug Ratio for Combinatorial Chemotherapy

AbstractTriple negative breast cancer (TNBC) not only exhibits aggressive progression and metastasis, but also responds to neither hormone therapy nor checkpoint blockade therapy. Thus, combinatorial chemotherapy is indispensable for TNBC treatment. However, due to the different pharmacokinetics of individual drugs and weak synergistic effects caused by random drug molar ratio in tumor, direct coadministration is far from satisfactory. Constructing a nanoscale drug delivery system with fixed drug molar ratios and maximum drug content is an urgent problem. Herein, an active targeting nanoparticle self‐assembled from cisplatin‐palbociclib amphiphiles with optimal drug ratio is reported. The combination of cisplatin and palbociclib at a molar ratio of 1:2 is found to have the best synergistic effect and is selected for follow‐up studies. After conjugating two palbociclib molecules to one cisplatin molecule, a fixed cisplatin/palbociclib (1:2) molar ratio is enabled and this amphiphilic conjugate can self‐assemble into nanoparticles. A small amount of iRGD coupled 1,2‐distearoyl‐sn‐glycero‐3‐phosphoethanolamine‐N‐polyethylene glycol‐2000 (DSPE‐PEG‐iRGD) that further stabilizes the nanoparticle is introduced to fabricate the desired nanoparticle (iRGD‐PCN) and endow active tumor‐targeting ability. On an orthotopic TNBC mouse model, iRGD‐PCN efficiently accumulates in tumors and inhibits tumor growth. Additionally, the formation of lung metastasis nodes is also significantly suppressed. In general, the active targeting nanoparticles self‐assembled from cisplatin‐palbociclib amphiphiles provide options for combinatorial chemotherapy.

Ratiometric delivery of two therapeutic candidates with inherently dissimilar physicochemical property through pH-sensitive core–shell nanoparticles targeting the heterogeneous tumor cells of glioma

Currently, combination drug therapy is one of the most effective approaches to glioma treatment. However, due to the inherent dissimilar pharmacokinetics of individual drugs and blood brain barriers, it was difficult for the concomitant drugs to simultaneously be delivered to glioma in an optimal dose ratio manner. Herein, a cationic micellar core (Cur-M) was first prepared from d-α-tocopherol-grafted-ε-polylysine polymer to encapsulate the hydrophobic curcumin, followed by dopamine-modified-poly-γ-glutamic acid polymer further deposited on its surface as a anion shell through pH-sensitive linkage to encapsulate the hydrophilic doxorubicin (DOX) hydrochloride. By controlling the combinational Cur/DOX molar ratio at 3:1, a pH-sensitive core–shell nanoparticle (PDCP-NP) was constructed to simultaneously target the cancer stem cells (CSCs) and the differentiated tumor cells. PDCP-NP exhibited a dynamic diameter of 160.8 nm and a zeta-potential of –30.5 mV, while its core–shell structure was further confirmed by XPS and TEM. The ratiometric delivery capability of PDCP-NP was confirmed by in vitro and in vivo studies, in comparison with the cocktail Cur/DOX solution. Meanwhile, the percentage of CSCs in tumors was significantly decreased from 4.16% to 0.95% after treatment with PDCP-NP. Overall, PDCP-NP may be a promising carrier for the combination therapy with drug candidates having dissimilar physicochemical properties.

A pilot study on pharmacokinetic/pharmacodynamic target attainment in critically ill patients receiving piperacillin/tazobactam.

In critically ill patients, multi-trauma and intensive therapy can influence the pharmacokinetics (PK) and pharmacodynamics (PD) of antibiotics with time-dependent bacterial killing. Consequently, PK/PD targets (%fT>MIC) - crucial for antimicrobial effects -may not be attained. Two patients admitted to the surgical ICU of the University Hospital in Hradec Králove for multiple-trauma were given piperacillin/tazobactam by 1-hour IV infusion 4/0.5 g every 8h. PK variables: total and renal clearance (CLtot, CLR), volume of distribution (Vd), and elimination half-life (T1/2) were calculated, followed by glomerular filtration rate (MDRD) and cumulative fluid balance (CFB-total fluid volume based on 24-h registered fluid intake minus output). The PK/PD target attainment (100%fT>MIC) was defined as free (f) piperacillin plasma concentrations that remain, during the entire dosing interval (T), above the minimum inhibitory concentration (100%fT>MIC) within days 4-8 (when CFB culminates and disappears). Piperacillin concentrations were determined by liquid chromatography-tandem mass spectrometry (LC-MS/MS) and corrected for unbound fraction (22%). CFB culminated over days 2-5 reaching 15-30 L and was associated with a large Vd (29-42 L). While MDRD in patient 1 was low (0.3-0.4 mL s⁻¹ 1.7 m⁻²), that of patient 2 was increasing (> 3.1 mL s⁻¹ 1.7 m⁻²), which was associated with augmented CLR. In patient 2, the fT reached only 62, 52, and 44% on days 4, 6, and 8, respectively. In patient 1, the %fT was much higher, attaining values four to fivefold greater than that targeted. Critically ill patients are at risk of drug under- or overdosing without dose up-titration with regard to covariate effects and individual drug pharmacokinetics.

Nonalcoholic steatohepatitis in precision medicine: Unraveling the factors that contribute to individual variability.

There are numerous factors in individual variability that make the development and implementation of precision medicine a challenge in the clinic. One of the main goals of precision medicine is to identify the correct dose for each individual in order to maximize therapeutic effect and minimize the occurrence of adverse drug reactions. Many promising advances have been made in identifying and understanding how factors such as genetic polymorphisms can influence drug pharmacokinetics (PK) and contribute to variable drug response (VDR), but it is clear that there remain many unidentified variables. Underlying liver diseases such as nonalcoholic steatohepatitis (NASH) alter absorption, distribution, metabolism, and excretion (ADME) processes and must be considered in the implementation of precision medicine. There is still a profound need for clinical investigation into how NASH-associated changes in ADME mediators, such as metabolism enzymes and transporters, affect the pharmacokinetics of individual drugs known to rely on these pathways for elimination. This review summarizes the key PK factors in individual variability and VDR and highlights NASH as an essential underlying factor that must be considered as the development of precision medicine advances. A multifactorial approach to precision medicine that considers the combination of two or more risk factors (e.g. genetics and NASH) will be required in our effort to provide a new era of benefit for patients.

A phase I open-label study of the safety, tolerability, and pharmacokinetics of pazopanib in combination with irinotecan and cetuximab for relapsed or refractory metastatic colorectal cancer

Pazopanib is a multi-targeted tyrosine kinase inhibitor shown to be clinically active in the treatment of various cancer types. This study aimed to evaluate the maximum tolerated regimen (MTR), safety, and pharmacokinetics of pazopanib in combination with irinotecan and cetuximab in adult patients with relapsed or refractory metastatic colorectal cancer (mCRC). This was a Phase I, 3 + 3 design, open-label, dose-escalation study (NCT0050943; VEG108925) conducted in sequential cohorts to determine the MTR of pazopanib and irinotecan administered with cetuximab. Twenty-five patients received treatment in three dosing cohorts and were evaluated for safety and tolerability of the combination and pharmacokinetics of individual drugs. The MTR was determined to be 400 mg pazopanib per day orally in combination with 150 mg/m(2) irinotecan biweekly and 250 mg/m(2) cetuximab weekly by infusion. Neutropenia was the main dose-limiting toxicity. Pharmacokinetic results suggested that the overall systemic exposure to SN-38, the active metabolite of irinotecan, was affected by pazopanib to a greater extent than was the systemic exposure to irinotecan itself. This study provided evidence for the manageable safety profile and feasibility of using the novel triplet combination of pazopanib, irinotecan, and cetuximab in patients with refractory mCRC. Further large-scale Phase II studies are warranted.

Transporting pharmacogenomics into clinical practice

A very interesting and concise study by Clarke et al. in this month’s issue of the Journal highlights important principles about the genetic determinants of drug disposition and toxicity, and the impact of underlying liver disease on adverse events from medications. The findings provide an opportunity to consider the current state of our knowledge about how genetic variations affect drug metabolism (i.e., pharmacogenomics), and to highlight efforts being developed to integrate genetic information into the clinical care of patients. The Clarke study is the most recent work in a series of publications by the authors examining the behavior of the hepatic uptake transporter organic ion transporting polypeptide-1B1 (OATP1B1) in drug disposition. This well-characterized membrane transporter regulates the uptake of organic compounds from the circulation into the hepatocyte where they can be metabolized. OATP1B1 has a large number of genetic variants, or single nucleotide polymorphisms (SNPs), that confer widely variable uptake activity by the transporter [1]; variants that confer reduced uptake lead to slower clearance of substrates, and therefore higher blood levels. That is exactly the case with several single nucleotide polymorphisms (SNPs) that have been linked to increased risk of myopathy associated with statin drugs used to treat hypercholesterolemia [1–3]. While statins are remarkably safe in general, individuals with these variants can be at up to 20 times greater risk of myopathy. Moreover, because these transporters have hundreds of substrates, altered activity can also lead to many adverse drug-drug interactions, in addition to altering the pharmacokinetics of individual drugs [1]. As hepatologists know well, many patients with hypercholesterolemia who are treated with statins are also obese and have metabolic syndrome complicated by non-alcoholic fatty liver disease (NAFLD) or non-alcoholic steatohepatitis (NASH). These conditions introduce the confounding effect of underlying fatty liver disease, which may further alter hepatic drug metabolism [4–6]. Additionally, the increased adiposemass in these patients can lead to accumulation of lipophilic drugs in fat cells and hepatocytes. The Clarke study examines how these two important variables, namely the genetic regulation of OATP1B1 activity and

Phase 1 study of lenvatinib combined with carboplatin and paclitaxel in patients with non-small-cell lung cancer

Background:This dose-finding study evaluated lenvatinib, an oral multitargeted receptor tyrosine kinase inhibitor, in combination with carboplatin/paclitaxel in chemotherapy-naïve non-small-cell lung cancer (NSCLC) patients.Patients and Methods:Patients received lenvatinib twice daily (BID) with carboplatin (area under the curve 6 mg ml−1 min−1, day 1)/paclitaxel (200 mg m−2, day 1) every 3 weeks. The initial dose of lenvatinib was 6 mg BID. The primary end point was maximum tolerated dose (MTD) of lenvatinib. At the MTD, the cohort was expanded by 16 patients. Safety, pharmacokinetics, pharmacodynamics, and antitumor effects were evaluated.Results:Twenty-eight patients were treated. At 6 mg BID, dose-limiting toxicities (DLTs) included febrile neutropenia/gingival infection (n=2). No DLTs occurred with 4 mg BID, the recommended MTD for the expansion. Common grade 3/4 toxicities included neutropenia, leukopenia, hypertension, and thrombocytopenia. The combination had no significant impact on individual drug pharmacokinetics. Response rate and median progression-free survival were 68% and 9.0 months, respectively, with 4 mg BID. In the plasma biomarker analysis, stromal cell-derived factor 1α, stem cell factor, and granulocyte colony-stimulating factor correlated with antitumor activity.Conclusion:The MTD for lenvatinib with carboplatin/paclitaxel is 4 mg BID in advanced NSCLC patients. This regimen demonstrated manageable tolerability and encouraging antitumor activity.

The Effect of Critical Illness on Drug Distribution

The complexity of managing critically ill patients has increased since the early establishment of intensive care units in the 1950s. Despite of the fact that the number of drugs available to clinicians has increased, the understanding of the pharmacokinetics of individual drugs in specific disease states is still a matter of concern. Among the pharmacokinetic processes which may be affected in this patient population, drug distribution is a very important one. Changes in drug distribution may cause inadequate drug exposure at the infection site and consequently influence clinical outcome. Since drug distribution is dependent on a plethora of factors, including the physicochemical characteristics of the drug, we will focus on the most common mechanisms responsible for altered tissue distribution. These include changes in protein binding, fluid shifts, and pH changes. Although less common, alterations in organ perfusion may also play a role, particularly in heart failure patients. Despite great advances in understanding the distribution of antibacterial drugs, further studies are needed to define the consequences of changed drug distribution in critically ill patients on dosing regimens and clinical outcome.

A Bayesian Meta-Analysis on Published Sample Mean and Variance Pharmacokinetic Data with Application to Drug–Drug Interaction Prediction

In drug-drug interaction (DDI) research, a two-drug interaction is usually predicted by individual drug pharmacokinetics (PK). Although subject-specific drug concentration data from clinical PK studies on inhibitor or inducer and substrate PK are not usually published, sample mean plasma drug concentrations and their standard deviations have been routinely reported. Hence there is a great need for meta-analysis and DDI prediction using such summarized PK data. In this study, an innovative DDI prediction method based on a three-level hierarchical Bayesian meta-analysis model is developed. The three levels model sample means and variances, between-study variances, and prior distributions. Through a ketoconazle-midazolam example and simulations, we demonstrate that our meta-analysis model can not only estimate PK parameters with small bias but also recover their between-study and between-subject variances well. More importantly, the posterior distributions of PK parameters and their variance components allow us to predict DDI at both population-average and study-specific levels. We are also able to predict the DDI between-subject/study variance. These statistical predictions have never been investigated in DDI research. Our simulation studies show that our meta-analysis approach has small bias in PK parameter estimates and DDI predictions. Sensitivity analysis was conducted to investigate the influences of interaction PK parameters, such as the inhibition constant Ki, on the DDI prediction.

Drug–drug interaction prediction: a Bayesian meta‐analysis approach

In drug-drug interaction (DDI) research, a two drug interaction is usually predicted by individual drug pharmacokinetics (PK). Although subject-specific drug concentration data from clinical PK studies on inhibitor/inducer or substrate's PK are not usually published, sample mean plasma drug concentrations and their standard deviations have been routinely reported. In this paper, an innovative DDI prediction method based on a three-level hierarchical Bayesian meta-analysis model is developed. The first level model is a study-specific sample mean model; the second level model is a random effect model connecting different PK studies; and all priors of PK parameters are specified in the third level model. A Monte Carlo Markov chain (MCMC) PK parameter estimation procedure is developed, and DDI prediction for a future study is conducted based on the PK models of two drugs and posterior distributions of the PK parameters. The performance of Bayesian meta-analysis in DDI prediction is demonstrated through a ketoconazole-midazolam example. The biases of DDI prediction are evaluated through statistical simulation studies. The DDI marker, ratio of area under the concentration curves, is predicted with little bias (less than 5 per cent), and its 90 per cent credible interval coverage rate is close to the nominal level. Sensitivity analysis is conducted to justify prior distribution selections.

Ratiometric dosing of anticancer drug combinations: Controlling drug ratios after systemic administration regulates therapeutic activity in tumor-bearing mice

Anticancer drug combinations can act synergistically or antagonistically against tumor cells in vitro depending on the ratios of the individual agents comprising the combination. The importance of drug ratios in vivo, however, has heretofore not been investigated, and combination chemotherapy treatment regimens continue to be developed based on the maximum tolerated dose of the individual agents. We systematically examined three different drug combinations representing a range of anticancer drug classes with distinct molecular mechanisms (irinotecan/floxuridine, cytarabine/daunorubicin, and cisplatin/daunorubicin) for drug ratio-dependent synergy. In each case, synergistic interactions were observed in vitro at certain drug/drug molar ratio ranges (1:1, 5:1, and 10:1, respectively), whereas other ratios were additive or antagonistic. We were able to maintain fixed drug ratios in plasma of mice for 24 hours after i.v. injection for all three combinations by controlling and overcoming the inherent dissimilar pharmacokinetics of individual drugs through encapsulation in liposomal carrier systems. The liposomes not only maintained drug ratios in the plasma after injection, but also delivered the formulated drug ratio directly to tumor tissue. In vivo maintenance of drug ratios shown to be synergistic in vitro provided increased efficacy in preclinical tumor models, whereas attenuated antitumor activity was observed when antagonistic drug ratios were maintained. Fixing synergistic drug ratios in pharmaceutical carriers provides an avenue by which anticancer drug combinations can be optimized prospectively for maximum therapeutic activity during preclinical development and differs from current practice in which dosing regimens are developed empirically in late-stage clinical trials based on tolerability.

Failure of Modified Directly Observed Therapy Combined with Therapeutic Drug Monitoring to Enhance Antiretroviral Adherence in a Patient with Major Depression

Improving medication nonadherence in HIV-infected patients with concomitant psychiatric issues remains a challenging therapeutic dilemma. One strategy may be to use a short course of modified directly observed therapy combined with therapeutic drug monitoring as an adherence intervention. Individual drug pharmacokinetics could be evaluated while the increased visit frequency is an opportunity to provide additional patient training and psychosocial support. We report our experience with a 43-year-old woman with severe depressive symptoms and persistent virologic failure despite appropriate therapy. Although the intervention was well-received by the patient, improvements in medication adherence behaviors waned over time. It should be recognized that not all patients are capable of achieving lifelong medication adherence and may benefit from continued supervised therapy.

Pharmacokinetics and therapeutic drug monitoring of immunosuppressants.

Immunosuppressive drug treatment has developed considerably in recent years with new methods describing pharmacokinetic-pharmacodynamic relationships. Using in vitro models it is possible to predict the success of clinical immunosuppressive drug combinations. Furthermore, with the advances of analytical methodology it is now possible to measure minute amounts of potent immunosuppressants and to adjust dosing based on concentration measurements. Concentration control, which first was required for cyclosporine A, is being investigated for most immunosuppressive drugs in development. Characterisation of individual drug pharmacokinetics form the basis for successful immunosuppression. Among possible therapeutic drug monitoring methodologies, trough level monitoring is currently the method of choice.

Models for assessing the relationship between drug concentration and drug effect in performance horses

The actions of most drugs are dependent upon achieving adequate plasma concentrations. Plasma concentrations are influenced by the degree to which a drug is absorbed, distributed, metabolized and excreted. Pharmacokinetic assessment reflects changes in these variables as a function of time. Pharmacodynamics refers to specific drug effects or mechanisms of drug action. Individual drug pharmacokinetics provides information on which to base a therapeutic dose, route of administration and dosing interval. However, not all drug actions temporally correlate with plasma kinetics. To resolve this discrepancy, pharmacodynamic models of drug action have been developed. In this review several pharmacodynamic models of anti-inflammatory and central nervous system effects are discussed in relationship to individual drug pharmacokinetics in the horse. The use of appropriate statistical models can minimize error and maximize the detection of drug effects over time. Data are presented showing the value of pharmacodynamic models in assessing and predicting the onset, peak and duration of drug action. Penetration of drugs into inflamed tissue or the brain may not temporally correlate with plasma kinetics. Therefore, drug kinetics in tissues or compartments associated with a particular effect may be a better predictor of efficacy than plasma concentrations. Recent studies have shown that exercise can affect drug disposition and influence both pharmacokinetics and pharmacodynamics. In competitive athletes, plasma or urine concentrations of drugs are determined to regulate use. Some jurisdictions are advocating the establishment of specific drug thresholds based upon plasma or urine concentrations. However, drug effects may occur during low or undetectable plasma concentrations. Urine concentrations are often dissociated in time from those in plasma. Therefore, the use of appropriate pharmacodynamic models, and the exercising horse, can complement plasma pharmacokinetics in determining drug efficacy and drug thresholds.