Alternative dosing regimens for atezolizumab: an example of model-informed drug development in the postmarketing setting.

PURPOSE: To determine the exposure-response (ER) relationships between atezolizumab exposure and efficacy or safety in patients with advanced non-small cell lung cancer (NSCLC) or urothelial carcinoma (UC) and to identify alternative dosing regimens. METHODS: ER analyses were conducted using pooled NSCLC and UC data from phase 1 and 3 studies (PCD4989g, OAK, IMvigor211; ClinicalTrials.gov IDs, NCT01375842, NCT02008227, and NCT02302807, respectively). Objective response rate, overall survival, and adverse events were evaluated vs pharmacokinetic (PK) metrics. Population PK-simulated exposures for regimens of 840 mg every 2 weeks (q2w) and 1680 mg every 4 weeks (q4w) were compared with the approved regimen of 1200 mg every 3 weeks (q3w) and the maximum assessed dose (MAD; 20 mg/kg q3w). Phase 3 IMpassion130 (NCT02425891) data were used to validate the PK simulations for 840 mg q2w. Observed safety data were evaluated by exposure and body weight subgroups. RESULTS: No significant ER relationships were observed for safety or efficacy. Predicted exposures for 840 mg q2w and 1680 mg q4w were comparable to 1200 mg q3w and the MAD and consistent with observed PK data from IMpassion130. Observed safety was similar between patients with a Cmax above and below the predicted Cmax for 1680 mg q4w and between patients in the lowest and upper 3 body weight quartiles. CONCLUSION: Atezolizumab regimens of 840 mg q2w and 1680 mg q4w are expected to have comparable efficacy and safety as the approved regimen of 1200 mg q3w, supporting their interchangeable use and offering patients greater flexibility.

Safety, Pharmacokinetics, and Pharmacodynamics in Healthy Volunteers Treated With GDC-0853, a Selective Reversible Bruton's Tyrosine Kinase Inhibitor.

GDC-0853 is a small molecule inhibitor of Bruton's tyrosine kinase (BTK) that is highly selective and noncovalent, leading to reversible binding. In double-blind, randomized, and placebo-controlled phase I healthy volunteer studies, GDC-0853 was well tolerated, with no dose-limiting adverse events (AEs) or serious AEs. The maximum tolerated dose was not reached during dose escalation (≤600 mg, single ascending dose (SAD) study; ≤250 mg twice daily (b.i.d.) and ≤500 mg once daily, 14-day multiple ascending dose (MAD) study). Plasma concentrations peaked 1-3 hours after oral administration and declined thereafter, with a steady-state half-life ranging from 4.2-9.9 hours. Independent assays demonstrated dose-dependent BTK target engagement. Based on pharmacokinetic/pharmacodynamic (PK/PD) simulations, a once-daily dosing regimen (e.g., 100 mg, q.d.) is expected to maintain a high level of BTK inhibition over the dosing interval. Taken together, the safety and PK/PD data support GDC-0853 evaluation in rheumatoid arthritis, lupus, and other autoimmune or inflammatory indications.

Understanding the time course of pharmacological effect: a PKPD approach.

The key concepts that underpin the choice of drug and dosing regimen are an understanding of the drugs' effectiveness, the potential for adverse effects, and the expected time course over which both desired and adverse effects are likely to occur. Research in clinical pharmacology should therefore address three fundamental questions: (1) What is the magnitude of drug effects (beneficial or adverse) from a given dose? (2) How quickly will any given effects occur? (3) How long will these effects last? Under steady-state conditions, only the magnitude of drug effects can be examined. This requires researchers to consider non-steady-state conditions, which require more complex models and an understanding of the mechanisms that drive the time course of drug effect. The aim of this review is to provide a conceptual framework for understanding the time course of drug effects using pharmacokinetic-pharmacodynamic models. Key examples will illustrate how this can inform the optimal use of drugs in the clinic.

Interpreting population pharmacokinetic-pharmacodynamic analyses - a clinical viewpoint.

The population analysis approach is an important tool for clinical pharmacology in aiding the dose individualization of medicines. However, due to their statistical complexity the clinical utility of population analyses is often overlooked. One of the key reasons to conduct a population analysis is to investigate the potential benefits of individualization of drug dosing based on patient characteristics (termed covariate identification). The purpose of this review is to provide a tool to interpret and extract information from publications that describe population analysis. The target audience is those readers who are aware of population analyses but have not conducted the technical aspects of an analysis themselves. Initially we introduce the general framework of population analysis and work through a simple example with visual plots. We then follow-up with specific details on how to interpret population analyses for the purpose of identifying covariates and how to interpret their likely importance for dose individualization.

Steady-state pharmacokinetic, safety, and tolerability profiles of quetiapine, norquetiapine, and other quetiapine metabolites in pediatric and adult patients with psychotic disorders.

OBJECTIVE: The aim of this study was to investigate the steady-state pharmacokinetic, safety, and tolerability profiles of immediate-release quetiapine administered by similar dose-escalation regimens in pediatric and adult populations with psychotic or mood disorders. METHODS: Pediatric patients aged 10-17 years were titrated to a quetiapine dose of 200 mg twice daily (b.i.d. on days 5-7, 400 mg b.i.d. on days 11-12, with a final 400-mg dose on day 13. In a separate trial, adult patients aged 18-45 years were titrated to a quetiapine dose of 200 mg b.i.d. on days 4-6, 400 mg b.i.d. on days 10-11, with a final 400-mg dose on day 12. Concentrations of quetiapine and three metabolites (quetiapine sulfoxide, 7-hydroxy quetiapine, and norquetiapine) were quantified in plasma and urine. Adverse events, vital signs, 12-lead electrocardiogram (ECG), and clinical laboratory tests were evaluated throughout the studies. RESULTS: In both pediatric and adult populations, plasma concentrations of quetiapine and norquetiapine increased proportionately as the dose was escalated from 200 mg b.i.d. to 400 mg b.i.d. There were no age-related differences in the dose-normalized quetiapine plasma concentration-time curve (AUC(SS)) and maximum plasma concentration (C(SS,max)). Quetiapine was rapidly absorbed after 200-mg and 400-mg doses in pediatric patients [median t(max) (time to maximum plasma concentration) 1.5 hours, both doses] and adult patients (median t(max) 1.0 hour and 1.2 hours, respectively). The mean quetiapine t(1/2) (terminal elimination half-life) was approximately 6 hours for pediatric and 5 hours for adult patients. Norquetiapine displayed a similar median t(max) and a longer t(1/2) compared with quetiapine. Quetiapine was well tolerated, with no serious adverse events and no unexpected events reported. CONCLUSION: Pediatric and adult populations demonstrated similar pharmacokinetic, safety, and tolerability profiles for quetiapine administered by dose escalation. The predictability in quetiapine concentration profiles for children aged 10 years to adults suggests that no dosage adjustment may be required when treating patients of these ages.

Open-label steady-state pharmacokinetic drug interaction study on co-administered quetiapine fumarate and divalproex sodium in patients with schizophrenia, schizoaffective disorder, or bipolar disorder.

OBJECTIVE: To determine whether there is a pharmacokinetic drug interaction between quetiapine fumarate and divalproex sodium. METHODS: The pharmacokinetics and short-term tolerability and safety of coadministered quetiapine and divalproex were examined in adults with schizophrenia/schizoaffective disorder (Cohort A) or bipolar disorder (Cohort B) in an open-label, parallel, 2-cohort drug-interaction study conducted at three centers in the United States. Cohort A was administered quetiapine (150 mg bid) prospectively for 13 days, with divalproex (500 mg bid) added on days 6-13. Cohort B was administered divalproex (500 mg bid) for 16 days, with quetiapine (150 mg bid) added on days 9-16. Quetiapine and valproic acid plasma concentration-time data over a 12-h steady-state dosing interval were used to determine C(max), T(max), C(min), area under the plasma concentration-time curve (AUC(tau)), and oral clearance (CL/F). RESULTS: In Cohort A (n = 18), addition of divalproex did increase the C(max) of quetiapine by 17% but did not change AUC(tau). In Cohort B (n = 15), addition of quetiapine decreased both total valproic acid C(max) and AUC(tau) by 11%. No differences were observed in adverse events (AEs) with either quetiapine or divalproex monotherapy or their combination. CONCLUSION: Combination therapy with quetiapine (150 mg bid) and divalproex (500 mg bid) resulted in small and statistically non-significant pharmacokinetic changes.

Effects of cytochrome P450 3A modulators ketoconazole and carbamazepine on quetiapine pharmacokinetics.

AIMS: To explore the potential for drug interactions on quetiapine pharmacokinetics using in vitro and in vivo assessments. METHODS: The CYP enzymes responsible for quetiapine metabolite formation were assessed using recombinant expressed CYPs and CYP-selective inhibitors. P-glycoprotein (Pgp) transport was tested in MDCK cells expressing the human MDR1 gene. The effects of CYP3A4 inhibition were evaluated clinically in 12 healthy volunteers that received 25 mg quetiapine before and after 4 days of treatment with ketoconazole 200 mg daily. To assess CYP3A4 induction in vivo, 18 patients with psychiatric disorders were titrated to steady-state quetiapine levels (300 mg twice daily), then titrated to 600 mg daily carbamazepine for 2 weeks. RESULTS: CYP3A4 was found to be responsible for formation of quetiapine sulfoxide and N- and O-desalkylquetiapine and not a Pgp substrate. In the clinical studies, ketoconazole increased mean quetiapine plasma C(max) by 3.35-fold, from 45 to 150 ng ml(-1) (mean C(max) ratio 90% CI 2.51, 4.47) and decreased its clearance (Cl/F) by 84%, from 138 to 22 l h(-1) (mean ratio 90% CI 0.13, 0.20). Carbamazepine decreased quetiapine plasma C(max) by 80%, from 1042 to 205 ng ml(-1) (mean C(max) ratio 90% CI 0.14, 0.28) and increased its clearance 7.5-fold, from 65 to 483 l h(-1) (mean ratio 90% CI 6.04, 9.28). CONCLUSIONS: Cytochrome P450 3A4 is a primary enzyme responsible for the metabolic clearance of quetiapine. Quetiapine pharmacokinetics were affected by concomitant administration of ketoconazole and carbamazepine, and therefore other drugs and ingested natural products that strongly modulate the activity or expression of CYP3A4 would be predicted to change exposure to quetiapine.

Identification of cytochrome P450 and arylamine N-acetyltransferase isoforms involved in sulfadiazine metabolism.

Sulfadiazine hydroxylamine has been postulated to be the mediator of the greatly increased rates of adverse reactions to sulfadiazine experienced by people with human immunodeficiency virus infection. Therefore, we investigated the in vitro human cytochrome P450 (P450) and N-arylamine acetyltransferase (detoxification) metabolism of sulfadiazine. Formation of both the hydroxylamine and 4-hydroxy sulfadiazine was NADPH-dependent in human liver microsomes (HLM). The average K(m) (+/-S.D.) and V(max) in HLM (n = 3) for hydroxylamine formation was 5.7 +/- 2.2 mM and 185 +/- 142 pmol/min/mg, respectively. Significant (p < 0.05) inhibition by selective P450 isoform inhibitor sulfaphenazole (2.1 microM; CYP2C9) indicated a role for CYP2C9 in the formation of the hydroxylamine. Hydroxylamine formation correlated strongly with tolbutamide 4-hydroxylation (CYP2C8/9) in HLM (r = 0.76, p < or = 0.004, n = 12). Fluconazole (CYP2C9/19 and CYP3A4 inhibitor at clinical concentrations) inhibited hydroxylamine formation, with one-enzyme model K(i) estimates ranging from 9 to 40 microM. Acetylation of sulfadiazine in human liver cytosol (HLC) correlated strongly with NAT2 activity as measured by sulfamethazine N-acetylation (r = 0.92, p < 0.001, n = 12). The average K(m) (+/-S.D.) and V(max) in HLC (n = 3) was 3.1 +/- 1.7 mM and 221.8 +/- 132.3 pmol/min/mg, respectively. The polymorphic acetylation of sulfadiazine may predispose slow acetylator patients to adverse reactions to sulfadiazine. On the basis of our K(i) estimates, clinical fluconazole concentrations of 25 microM would produce decreases of 40 to 70% in hepatic-mediated hydroxylamine production. Therefore, we predict that fluconazole may prove useful in the clinic as an in vivo inhibitor of sulfadiazine hydroxylamine formation to suppress adverse reactions to this drug.

The effect of clarithromycin, fluconazole, and rifabutin on dapsone hydroxylamine formation in individuals with human immunodeficiency virus infection (AACTG 283).

BACKGROUND: Dapsone hydroxylamine formation is thought to be the cause of the high rates of adverse reactions to dapsone in human immunodeficiency virus (HIV)-infected individuals. Therefore we studied the effect of the commonly coadministered drugs fluconazole, clarithromycin, and rifabutin on hydroxylamine formation in individuals with HIV infection. METHODS: HIV-infected subjects (CD4 + > or =200 cells/mm 3 ) were enrolled in a 2-part (A or B) open-label drug interaction study. In part A, subjects (n = 12) received dapsone (100-mg tablet once daily) alone for 2 weeks and then, in a randomly assigned order, received dapsone and either fluconazole (200 mg daily), rifabutin (300 mg daily), or fluconazole plus rifabutin, each for a 2-week period. Part B (n = 11) was identical to part A except that clarithromycin (500 mg twice daily) was substituted for rifabutin. On the last study day of each 2-week period, plasma and urine were collected over ascorbic acid for 24 hours. RESULTS: In part A, fluconazole decreased the area under the plasma concentration-time curve, percent of dose excreted in 24-hour urine, and formation clearance of the hydroxylamine by 49%, 53%, and 55% (n = 12, P < .05), respectively. This inhibition of in vivo hydroxylamine formation was quantitatively consistent with that predicted from human liver microsomal experiments. Rifabutin had no effect on hydroxylamine area under the plasma concentration-time curve or percent excreted in 24-hour urine but increased formation clearance of the hydroxylamine by 92% (n = 12, P < .05). Dapsone clearance was increased by rifabutin or rifabutin plus fluconazole (67% and 38%, respectively) (n = 12, P < .05) but was unaffected by fluconazole or clarithromycin. In part B, hydroxylamine production was unaffected by clarithromycin but was affected by fluconazole in a manner identical to that in part A. CONCLUSIONS: On the basis of these data and with the assumption that the exposure to the hydroxylamine is a determinant of dapsone toxicity, we predict that coadministration of fluconazole should decrease the rate of adverse reactions to dapsone in persons with HIV infection but that rifabutin and clarithromycin will have no effect. When dapsone is given in combination with rifabutin, dapsone dosage adjustment may be necessary in light of the increase in dapsone clearance.

The effect of clarithromycin, fluconazole, and rifabutin on sulfamethoxazole hydroxylamine formation in individuals with human immunodeficiency virus infection (AACTG 283).

BACKGROUND: Sulfamethoxazole hydroxylamine formation, in combination with long-term oxidative stress, is thought to be the cause of high rates of adverse drug reactions to sulfamethoxazole in human immunodeficiency virus (HIV)-infected subjects. Therefore the goal of this study was to determine the effect of fluconazole, clarithromycin, and rifabutin on sulfamethoxazole hydroxylamine formation in individuals with HIV-1 infection. METHODS: HIV-1-infected subjects (CD4 + count >/=200 cells/mm 3 ) were enrolled in a 2-part (A and B), open-label drug interaction study (Adult AIDS Clinical Trial Group [AACTG] 283). In part A (n = 9), subjects received cotrimoxazole (1 tablet of 800 mg sulfamethoxazole/160 mg trimethoprim daily) alone for 2 weeks and then, in a randomly assigned order, cotrimoxazole plus either fluconazole (200 mg daily), rifabutin (300 mg daily), or fluconazole plus rifabutin, each for a 2-week period. Part B (n = 12) was identical to part A except that clarithromycin (500 mg twice daily) was substituted for rifabutin. RESULTS: In part A, fluconazole decreased the area under the plasma concentration-time curve (AUC), percent of dose excreted in 24-hour urine, and formation clearance (CL f ) of the hydroxylamine by 37%, 53%, and 61%, respectively (paired t test, P < .05). Rifabutin increased the AUC, percent excreted, and CL f of the hydroxylamine by 55%, 45%, and 53%, respectively ( P < .05). Fluconazole plus rifabutin decreased the AUC, percent excreted, and CL f of the hydroxylamine by 21%, 37%, and 46%, respectively ( P < .05). In part B the fluconazole data were similar to those of part A. Overall, clarithromycin had no effect on hydroxylamine production. CONCLUSIONS: If the exposure (AUC) to sulfamethoxazole hydroxylamine is predictive of sulfamethoxazole toxicity, then rifabutin will increase and clarithromycin plus fluconazole or rifabutin plus fluconazole will decrease the rates of adverse reactions to sulfamethoxazole in HIV-infected subjects.