Minimal Physiologically Based Pharmacokinetic-Pharmacodynamic (mPBPK-PD) Model of N-Acetylgalactosamine-Conjugated Small Interfering RNA Disposition and Gene Silencing in Preclinical Species and Humans.

Conjugation of small interfering RNA (siRNA) to tris N-acetylgalactosamine [(GalNAc)3] can enable highly selective, potent, and durable knockdown of targeted proteins in the liver. However, potential knowledge gaps between in vitro experiments, preclinical species, and clinical scenarios remain. A minimal physiologically based pharmacokinetic-pharmacodynamic model for GalNAc-conjugated siRNA (GalNAc-siRNA) was developed using published data for fitusiran (ALN-AT3), an investigational compound targeting liver antithrombin (AT), to delineate putative determinants governing the whole-body-to-cellular pharmacokinetic (PK) and pharmacodynamic (PD) properties of GalNAc-siRNA and facilitate preclinical-to-clinical translation. The model mathematically linked relevant mechanisms: 1) hepatic biodistribution, 2) tris-GalNAc binding to asialoglycoprotein receptors (ASGPRs) on hepatocytes, 3) ASGPR endocytosis and recycling, 4) endosomal transport and escape of siRNA, 5) cytoplasmic RNA-induced silencing complex (RISC) loading, 6) degradation of target mRNA by bound RISC, and 7) knockdown of protein. Physiologic values for 36 out of 48 model parameters were obtained from the literature. Kinetic parameters governing (GalNAc)3-ASGPR binding and internalization were derived from published studies of uptake in hepatocytes. The proposed model well characterized reported pharmacokinetics, RISC dynamics, and knockdown of AT mRNA and protein by ALN-AT3 in mice. The model bridged multiple PK-PD data sets in preclinical species (mice, rat, monkey) and successfully captured reported plasma pharmacokinetics and AT knockdown in a phase I ascending-dose study. Estimates of in vivo potency were similar (∼2-fold) across species. Subcutaneous absorption and serum AT degradation rate constants scaled across species by body weight with allometric exponents of -0.29 and -0.22. The proposed mechanistic modeling framework characterizes the unique PK-PD properties of GalNAc-siRNA. SIGNIFICANCE STATEMENT: Tris N-acetylgalactosamine (GalNAc)3-conjugated small interfering RNA (siRNA) therapeutics enable liver-targeted gene therapy and precision medicine. Using a translational and systems-based minimal physiologically based pharmacokinetic-pharmacodynamic (mPBPK-PD) modeling approach, putative determinants influencing GalNAc-conjugated siRNA (GalNAc-siRNA) functionality in three preclinical species and humans were investigated. The developed model successfully integrated and characterized relevant published in vitro-derived biomeasures, mechanistic PK-PD profiles in animals, and observed clinical PK-PD responses for an investigational GalNAc-siRNA (fitusiran). This modeling effort delineates the disposition and liver-targeted pharmacodynamics of GalNAc-siRNA.

Bench-to-bedside translation of chimeric antigen receptor (CAR) T cells using a multiscale systems pharmacokinetic-pharmacodynamic model: A case study with anti-BCMA CAR-T.

Despite tremendous success of chimeric antigen receptor (CAR) T cell therapy in clinical oncology, the dose-exposure-response relationship of CAR-T cells in patients is poorly understood. Moreover, the key drug-specific and system-specific determinants leading to favorable clinical outcomes are also unknown. Here we have developed a multiscale mechanistic pharmacokinetic (PK)-pharmacodynamic (PD) model for anti-B-cell maturation antigen (BCMA) CAR-T cell therapy (bb2121) to characterize (i) in vitro target cell killing in multiple BCMA expressing tumor cell lines at varying effector to target cell ratios, (ii) preclinical in vivo tumor growth inhibition and blood CAR-T cell expansion in xenograft mice, and (iii) clinical PK and PD biomarkers in patients with multiple myeloma. Our translational PK-PD relationship was able to effectively describe the commonly observed multiphasic CAR-T cell PK profile in the clinic, consisting of the rapid distribution, expansion, contraction, and persistent phases, and accounted for the categorical individual responses in multiple myeloma to effectively calculate progression-free survival rates. Preclinical and clinical data analysis revealed comparable parameter estimates pertaining to CAR-T cell functionality and suggested that patient baseline tumor burden could be more sensitive than dose levels toward overall extent of exposure after CAR-T cell infusion. Virtual patient simulations also suggested a very steep dose-exposure-response relationship with CAR-T cell therapy and indicated the presence of a "threshold" dose, beyond which a flat dose-response curve could be observed. Our simulations were concordant with multiple clinical observations discussed in this article. Moving forward, this framework could be leveraged a priori to explore multiple infusions and support the preclinical/clinical development of future CAR-T cell therapies.

Model-Based Cellular Kinetic Analysis of Chimeric Antigen Receptor-T Cells in Humans.

Chimeric antigen receptor (CAR)-T cell therapy has achieved considerable success in treating B-cell hematologic malignancies. However, the challenges of extending CAR-T therapy to other tumor types, particularly solid tumors, remain appreciable. There are substantial variabilities in CAR-T cellular kinetics across CAR-designs, CAR-T products, dosing regimens, patient responses, disease types, tumor burdens, and lymphodepletion conditions. As a "living drug," CAR-T cellular kinetics typically exhibit four distinct phases: distribution, expansion, contraction, and persistence. The cellular kinetics of CAR-T may correlate with patient responses, but which factors determine CAR-T cellular kinetics remain poorly defined. Herein, we developed a cellular kinetic model to retrospectively characterize CAR-T kinetics in 217 patients from 7 trials and compared CAR-T kinetics across response status, patient populations, and tumor types. Based on our analysis results, CAR-T cells exhibited a significantly higher cell proliferation rate and capacity but a lower contraction rate in patients who responded to treatment. CAR-T cells proliferate to a higher degree in hematologic malignancies than in solid tumors. Within the assessed dose ranges (107 -109 cells), CAR-T doses were weakly correlated with CAR-T cellular kinetics and patient response status. In conclusion, the developed CAR-T cellular kinetic model adequately characterized the multiphasic CAR-T cellular kinetics and supported systematic evaluations of the potential influencing factors, which can have significant implications for the development of more effective CAR-T therapies.

Development of a quantitative relationship between CAR-affinity, antigen abundance, tumor cell depletion and CAR-T cell expansion using a multiscale systems PK-PD model.

The development of mechanism-based, multiscale pharmacokinetic-pharmacodynamic (PK-PD) models for chimeric antigen receptor (CAR)-T cells is needed to enable investigation of in vitro and in vivo correlation of CAR-T cell responses and to facilitate preclinical-to-clinical translation. Toward this goal, we first developed a cell-level in vitro PD model that quantitatively characterized CAR-T cell-induced target cell depletion, CAR-T cell expansion and cytokine release. The model accounted for key drug-specific (CAR-affinity, CAR-densities) and system-specific (antigen densities, E:T ratios) variables and was able to characterize comprehensive in vitro datasets from multiple affinity variants of anti-EGFR and anti-HER2 CAR-T cells. Next, a physiologically based PK (PBPK) model was developed to simultaneously characterize the biodistribution of untransduced T-cells, anti-EGFR CAR-T and anti-CD19 CAR-T cells in xenograft -mouse models. The proposed model accounted for the engagement of CAR-T cells with tumor cells at the site of action. Finally, an integrated PBPK-PD relationship was established to simultaneously characterize expansion of CAR-T cells and tumor growth inhibition (TGI) in xenograft mouse model, using datasets from anti-BCMA, anti-HER2, anti-CD19 and anti-EGFR CAR-T cells. Model simulations provided potential mechanistic insights toward the commonly observed multiphasic PK profile (i.e., rapid distribution, expansion, contraction and persistence) of CAR-T cells in the clinic. Model simulations suggested that CAR-T cells may have a steep dose-exposure relationship, and the apparent Cmax upon CAR-T cell expansion in blood may be more sensitive to patient tumor-burden than CAR-T dose levels. Global sensitivity analysis described the effect of other drug-specific parameters toward CAR-T cell expansion and TGI. The proposed modeling framework will be further examined with the clinical PK and PD data, and the learnings can be used to inform design and development of future CAR-T therapies.

Development of a Target cell-Biologics-Effector cell (TBE) complex-based cell killing model to characterize target cell depletion by T cell redirecting bispecific agents.

T-cell redirecting bispecific antibodies (bsAbs) or antibody-derived agents that combine tumor antigen recognition with CD3-mediated T cell recruitment are highly potent tumor-killing molecules. Despite the tremendous progress achieved in the last decade, development of such bsAbs still faces many challenges. This work aimed to develop a mechanism-based pharmacokinetic/pharmacodynamic (PK/PD) modeling framework that can be used to assist the development of T-cell redirecting bsAbs. A Target cell-Biologics-Effector cell (TBE) complex-based cell killing model was developed using in vitro and in vivo data, which incorporates information on binding affinities of bsAbs to CD3 and target receptors, expression levels of CD3 and target receptors, concentrations of effector and target cells, as well as respective physiological parameters. This TBE model can simultaneously evaluate the effect of multiple system-specific and drug-specific factors on the T-cell redirecting bsAb exposure-response relationship on a physiological basis; it reasonably captured multiple reported in vitro cytotoxicity data, and successfully predicted the effect of some key factors on in vitro cytotoxicity assays and the efficacious dose of blinatumomab in humans. The mechanistic nature of this model uniquely positions it as a knowledge-based platform that can be readily expanded to guide target selection, drug design, candidate selection and clinical dosing regimen projection, and thus support the overall discovery and development of T-cell redirecting bsAbs.

Best practices for the use of itraconazole as a replacement for ketoconazole in drug-drug interaction studies.

Ketoconazole has been widely used as a strong cytochrome P450 (CYP) 3A (CYP3A) inhibitor in drug-drug interaction (DDI) studies. However, the US Food and Drug Administration has recommended limiting the use of ketoconazole to cases in which no alternative therapies exist, and the European Medicines Agency has recommended the suspension of its marketing authorizations because of the potential for serious safety concerns. In this review, the Innovation and Quality in Pharmaceutical Development's Clinical Pharmacology Leadership Group (CPLG) provides a compelling rationale for the use of itraconazole as a replacement for ketoconazole in clinical DDI studies and provides recommendations on the best practices for the use of itraconazole in such studies. Various factors considered in the recommendations include the choice of itraconazole dosage form, administration in the fasted or fed state, the dose and duration of itraconazole administration, the timing of substrate and itraconazole coadministration, and measurement of itraconazole and metabolite plasma concentrations, among others. The CPLG's recommendations are based on careful review of available literature and internal industry experiences.

Molecular properties determining unbound intracellular and extracellular brain exposure of CNS drug candidates.

In the present work we sought to gain a mechanistic understanding of the physicochemical properties that influence the transport of unbound drug across the blood-brain barrier (BBB) as well as the intra- and extracellular drug exposure in the brain. Interpretable molecular descriptors that significantly contribute to the three key neuropharmacokinetic properties related to BBB drug transport (Kp,uu,brain), intracellular accumulation (Kp,uu,cell), and binding and distribution in the brain (Vu,brain) for a set of 40 compounds were identified using partial least-squares (PLS) analysis. The tailoring of drug properties for improved brain exposure includes decreasing the polarity and/or hydrogen bonding capacity. The design of CNS drug candidates with intracellular targets may benefit from an increase in basicity and/or the number of hydrogen bond donors. Applying this knowledge in drug discovery chemistry programs will allow designing compounds with more desirable CNS pharmacokinetic properties.

Pharmacokinetic interactions between topiramate and pioglitazone and metformin.

OBJECTIVE: To investigate potential drug-drug interactions between topiramate and metformin and pioglitazone at steady state. METHODS: Two open-label studies were performed in healthy adult men and women. In Study 1, eligible participants were given metformin alone for 3 days (500 mg twice daily [BID]) followed by concomitant metformin and topiramate (titrated to 100mg BID) from days 4 to 10. In Study 2, eligible participants were randomly assigned to treatment with pioglitazone 30 mg once daily (QD) alone for 8 days followed by concomitant pioglitazone and topiramate (titrated to 96 mg BID) from days 9 to 22 (Group 1) or to topiramate (titrated to 96 mg BID) alone for 11 days followed by concomitant pioglitazone 30 mg QD and topiramate 96 mg BID from days 12 to 22 (Group 2). An analysis of variance was used to evaluate differences in pharmacokinetics with and without concomitant treatment; 90% confidence intervals (CI) for the ratio of the geometric least squares mean (LSM) estimates for maximum plasma concentration (Cmax), area under concentration-time curve for dosing interval (AUC12 or AUC24), and oral clearance (CL/F) with and without concomitant treatment were used to assess a drug interaction. RESULTS: A comparison to historical data suggested a modest increase in topiramate oral clearance when given concomitantly with metformin. Coadministration with topiramate reduced metformin oral clearance at steady state, resulting in a modest increase in systemic metformin exposure. Geometric LSM ratios and 90% CI for metformin CL/F and AUC12 were 80% (75%, 85%) and 125% (117%, 134%), respectively. Pioglitazone had no effect on topiramate pharmacokinetics at steady state. Concomitant topiramate resulted in decreased systemic exposure to pioglitazone and its active metabolites, with geometric LSM ratios and 90% CI for AUC24 of 85.0% (75.7%, 95.6%) for pioglitazone, 40.5% (36.8%, 44.6%) for M-III, and 83.8% (76.1%, 91.2%) for M-IV, respectively. This effect appeared more pronounced in women than in men. Coadministration of topiramate with metformin or pioglitazone was generally well tolerated by healthy participants in these studies. CONCLUSIONS: A modest increase in metformin exposure and decrease in topiramate exposure was observed at steady state following coadministration of metformin 500 mg BID and topiramate 100mg BID. The clinical significance of the observed interaction is unclear but is not likely to require a dose adjustment of either agent. Pioglitazone 30 mg QD did not affect the pharmacokinetics of topiramate at steady state, while coadministration of topiramate 96 mg BID with pioglitazone decreased steady-state systemic exposure to pioglitazone, M-III, and M-IV. While the clinical consequence of this interaction is unknown, careful attention should be given to the routine monitoring for adequate glycemic control of patients receiving this concomitant therapy. Concomitant administration of topiramate with metformin or pioglitazone was generally well tolerated and no new safety concerns were observed.

Pharmacokinetics of topiramate in patients with renal impairment, end-stage renal disease undergoing hemodialysis, or hepatic impairment.

PURPOSE: Topiramate is primarily renally excreted. Chronic renal and hepatic impairment can affect the clearance of topiramate. Therefore, the objective was to establish dosage guidelines for topiramate in chronic renal impairment, end-stage renal disease (ESRD) undergoing hemodialysis, or chronic hepatic impairment patients. METHODS: In 3 separate open-label, parallel group studies (n=5-7/group), in patients with mild-moderate and severe renal impairment (based on creatinine clearance), ESRD requiring hemodialysis, or moderate-severe hepatic impairment (based on Child-Pugh classification) and matching healthy participants, pharmacokinetics of a single oral 100mg topiramate was determined. RESULTS: Compared with healthy controls, overall exposure (AUC0-∞) for topiramate was higher in mild-moderate (85%) and severe renal impairment (117%), consistent with significantly (p<0.05) lower apparent total body clearance (CL/F) and renal clearance (CLR), leading to longer elimination half-life. Both CLR and CL/F of topiramate correlated well with renal function. CL/F was comparable in ESRD and severe renal impairment. Half of usual starting and maintenance dose is recommended in moderate-severe renal impairment patients, and those with ESRD. Hemodialysis effectively removed plasma topiramate with mean dialysis clearance approximately 12-fold greater than CL/F (123.5 mL/min versus 10.8 mL/min). Compared with healthy matched, patients with moderate-severe hepatic impairment exhibited small increase (29%) in topiramate peak plasma concentrations and AUC0-∞ values, consistent with lower CL/F (26%). Topiramate was generally well tolerated. CONCLUSION: Half of usual dose is recommended for moderate-severe renal impairment and ESRD. Supplemental dose may be required during hemodialysis. Dose adjustments might not be required in moderate-severe hepatic impairments; however, the small sample size limits generalization.

Mechanistic understanding of brain drug disposition to optimize the selection of potential neurotherapeutics in drug discovery.

PURPOSE: The current project was undertaken with the aim to propose and test an in-depth integrative analysis of neuropharmacokinetic (neuroPK) properties of new chemical entities (NCEs), thereby optimizing the routine of evaluation and selection of novel neurotherapeutics. METHODS: Forty compounds covering a wide range of physicochemical properties and various CNS targets were investigated. The combinatory mapping approach was used for the assessment of the extent of blood-brain and cellular barriers transport via estimation of unbound-compound brain (Kp,uu,brain) and cell (Kp,uu,cell) partitioning coefficients. Intra-brain distribution was evaluated using the brain slice method. Intra- and sub-cellular distribution was estimated via calculation of unbound-drug cytosolic and lysosomal partitioning coefficients. RESULTS: Assessment of Kp,uu,brain revealed extensive variability in the brain penetration properties across compounds, with a prevalence of compounds actively effluxed at the blood-brain barrier. Kp,uu,cell was valuable for identification of compounds with a tendency to accumulate intracellularly. Prediction of cytosolic and lysosomal partitioning provided insight into the subcellular accumulation. Integration of the neuroPK parameters with pharmacodynamic readouts demonstrated the value of the proposed approach in the evaluation of target engagement and NCE selection. CONCLUSIONS: With the rather easily-performed combinatory mapping approach, it was possible to provide quantitative information supporting the decision making in the drug discovery setting.

Pharmacokinetic interactions between topiramate and diltiazem, hydrochlorothiazide, or propranolol.

Drug-drug interactions between topiramate and diltiazem, hydrochlorothiazide, or propranolol were evaluated along with safety/tolerability in three open-label studies. Healthy participants (aged 18-45 years) received topiramate 75 mg every 12 hours (q12h) and diltiazem 240 mg/day (study 1); topiramate 96 mg q12h and hydrochlorothiazide 25 mg/day (study 2); topiramate 100 mg q12h and propranolol 40-80 mg q12h (study 3). The pharmacokinetic parameters for topiramate, diltiazem (and active metabolites, desacetyldiltiazem [DEA], N-demethyl diltiazem [DEM]), hydrochlorothiazide, and propranolol (and its active metabolite) were assessed at steady state. Results showed no effect of diltiazem on topiramate pharmacokinetics. However, a modest reduction in systemic exposures of diltiazem and DEA (10-27%) occurred during coadministration with topiramate. Systemic exposure of DEM was unaffected. Furthermore, oral and renal clearance of topiramate decreased (22-30%) significantly (P < 0.05) during coadministration with hydrochlorothiazide, while systemic exposure increased by 27-29%. Topiramate had no effect on hydrochlorothiazide pharmacokinetics. The results demonstrated lack of pharmacokinetic interaction between topiramate and propranolol. Overall, no new safety concerns emerged when topiramate was coadministered with diltiazem, hydrochlorothiazide, or propranolol.

An open-label drug-drug interaction study of the steady-state pharmacokinetics of topiramate and glyburide in patients with type 2 diabetes mellitus.

BACKGROUND: Topiramate is approved for epilepsy and migraine headache management and has potential antidiabetic activity. Because topiramate and antidiabetic drugs may be co-administered, the potential drug-drug interactions between topiramate and glyburide (glibenclamide), a commonly used sulfonylurea antidiabetic agent, was evaluated at steady state in patients with type 2 diabetes mellitus (T2DM). METHODS: This was a single-center, open-label, phase I, drug interaction study of topiramate (150 mg/day) and glyburide (5 mg/day alone and concomitantly) in patients with T2DM. The study consisted of 14-day screening, 48-day open-label treatment, and a 7-day follow-up phase. Serial blood and urine were obtained and analyzed by liquid chromatography coupled mass spectrometry/mass spectrometry for topiramate, glyburide, and its active metabolites M1 (4-trans-hydroxy-glyburide) and M2 (3-cis-hydroxy-glyburide) concentrations. Pharmacokinetic parameters were estimated by model-independent methods. Changes in fasting plasma glucose from baseline and safety parameters were monitored throughout the study. RESULTS: Of 28 enrolled patients, 24 completed the study. Co-administration of topiramate resulted in a significant (p < 0.05) decrease in the glyburide area under the concentration-time curve (25 %) and maximum plasma concentration (22 %), and reduction in systemic exposure of M1 (13 %) and M2 (15 %). Renal clearance of M1 (13 %) and M2 (12 %) increased during treatment with topiramate. Steady-state pharmacokinetics of topiramate were unaffected by co-administration of glyburide. Co-administration of topiramate and glyburide was generally tolerable in patients with T2DM. CONCLUSION: Glyburide did not affect the pharmacokinetics of topiramate. Co-administration of topiramate decreased systemic exposure of glyburide and its active metabolites; combined treatment may require dosing adjustments of glyburide as per clinical judgment and glycemic control.

From preclinical to human--prediction of oral absorption and drug-drug interaction potential using physiologically based pharmacokinetic (PBPK) modeling approach in an industrial setting: a workflow by using case example.

PURPOSE: A case example is presented in which the physiologically based modeling approach has been used to model the absorption of a lipophilic BCS Class II compound predominantly metabolized by CYP3A4, and to assess the interplay of absorption related parameters with the drug-drug interaction (DDI) potential. METHODS: The PBPK model was built in the rat using Gastroplus® to study the absorption characteristics of the compound. Subsequently relevant model parameters were used to predict the non-linear human PK observed during first-in-human study after optimizing the absorption model for colonic absorption, bile micelle solubilization and unbound fraction in gut enterocytes (fu(gut)) using SIMCYP® simulator. The model fitted absorption parameters were then used to assess the drug-drug interaction (DDI) potential of the test compound when administered along with multiple doses of a potent CYP 3A4 inhibitor, ketoconazole. The impact of fu(gut) in the extent of DDI was assessed using parameter sensitivity analysis. RESULTS AND CONCLUSIONS: After optimizing the preclinical model and taking into consideration bile micelle solubilization and colonic absorption, the non-linear pharmacokinetics of the test compound was satisfactorily predicted in man. Sensitivity analysis performed with the absorption parameter fu(gut) indicated that it could be an important parameter in predicting oral absorption. In addition, DDI simulations using SIMCYP® suggest that C(max) and AUC ratios may also be sensitive to the fu(gut) input in the model. Since fu(gut) cannot be measured experimentally, sensitivity analysis may help in assessing the importance of fu(gut) in human PK and DDI prediction using SIMCYP®.

Pharmacokinetics of enoxaparin in patients undergoing percutaneous coronary intervention with and without glycoprotein IIb/IIIa therapy.

The pharmacokinetic profile of enoxaparin was established in a substudy involving 1054 patients undergoing percutaneous coronary intervention. Patients enrolled in the National Investigators Collaborating on Enoxaparin 1 (NICE-1) trial received enoxaparin as a 1.0-mg/kg intravenous bolus. Patients enrolled in the NICE-4 trial received enoxaparin as a 0.75-mg/kg intravenous bolus followed by abciximab as a 0.25-mg/kg bolus and a 0.125-mcg/kg/min 12-hour infusion. Blood samples were collected at six time points over 12 hours and analyzed for plasma anti-Xa, anti-IIa, and Heptest (Haemachem Inc., St. Louis, MO) activity using specific and sensitive assay methods. Data were similar in both trials. Plasma anti-Xa, anti-IIa, and Heptest activity peaked shortly after the enoxaparin bolus and declined in parallel over the ensuing 12 hours. Area under the curve and peak activity were greatest for Heptest activity and least for anti-IIa activity. Values for clearance, volume of distribution, volume of distribution at steady state, and elimination rate constant were on the order of 10 mL/h/kg, 48 mL/kg, 45 mL/kg, and 0.22/h, respectively. These measures suggest that the use of abciximab in combination with enoxaparin during percutaneous coronary intervention is unlikely to affect the pharmacokinetics of enoxaparin.

Comparative Pharmacokinetics and Bioavailability of Dilacor XR and Cardizem CD in Healthy Volunteers.

The objective of this investigation was to compare the single-dose and steady-state pharmacokinetic profiles of Dilacor XR to Cardizem CD. The study enrolled 24 healthy males and was divided into three parts: a single intravenous 25-mg bolus dose of diltiazem HCl (Cardizem Injectable) followed by a two-way crossover comparison of single and multiple once-daily 240-mg oral doses of Dilacor XR and Cardizem CD. Plasma samples were analyzed for diltiazem using a specific and sensitive HPLC assay. Statistical analysis and deconvolution were performed on the data. A 1- and 3-hour lag time in diltiazem absorption was noted following the administration of Dilacor XR and Cardizem CD, respectively. Statistically significant differences were noted in mean single- and multiple-dose t(max) values with Cardizem CD taking approximately twice as long as Dilacor XR to reach C(max). Dilacor XR was equivalent to Cardizem CD with respect to AUC((0--infty infinity)) and C(max). Equivalent minimum and average steady-state plasma diltiazem concentrations were noted after multiple-dose administration. Deconvolution of the single-dose data also showed similar mean bioavailabilities for the respective formulations but revealed dissimilarities in each product's absorption profile that may reflect observed differences in absorption lag time and t(max).

The Pharmacokinetics of Once-Daily Diltiazem SR (Sustained-Release) in Young Versus Elderly Hypertensive Patients.

The objective of this open-label, outpatient, parallel-group investigation was to compare the single-dose and steady-state pharmacokinetic profiles of young (n = 12; x = 41 ± 6 years) and elderly (n = 12; X = 69 ± 4 years) hypertensive patients following administration of a once-daily formulation of diltiazem. The study was comprised of two phases. The first phase was a lead-in phase used to establish hypertensive status. In the second phase, patients were administered a single- and multiple-daily dose regimen of 240 mg of diltiazem SR. Plasma samples were obtained at selected times and analyzed for diltiazem using a specific and sensitive HPLC assay. Biopharmaceutic parameter estimates were determined and analyzed for statistical differences. Qualitatively similar concentration-time profiles were observed between groups, suggesting similar release characteristics of the sustained-release formulation. However, significantly higher overall concentrations of diltiazem were observed following single-dose administration in the elderly, possibly as a result of an age-related decrease in the apparent oral clearance of diltiazem. A further reduction in the apparent oral clearance of diltiazem with multiple-dose administration was observed in the elderly resulting in even higher than projected concentrations of diltiazem. Thus, greater oral systemic availability of diltiazem in the elderly hypertensive patients may warrant closer clinical monitoring and possibly a reduction in dosage.