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Liu Q, Nair R, Huang R, Zhu H, Anderson A, Belen O, Tran V, Chiu R, Higgins K, Chen J, He L, Doddapaneni S, Huang SM, Nikolov NP, Zineh I. Using Machine Learning to Determine a Suitable Patient Population for Anakinra for the Treatment of COVID-19 Under the Emergency Use Authorization. Clin Pharmacol Ther 2024; 115:890-895. [PMID: 38348530 DOI: 10.1002/cpt.3191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 01/11/2024] [Indexed: 03/21/2024]
Abstract
A randomized, double-blind, placebo-controlled study (SAVEMORE trial) provided data to support an Emergency Use Authorization (EUA) of anakinra in hospitalized adults with positive results of direct severe acute respiratory syndrome-coronavirus 2 viral testing with pneumonia requiring supplemental oxygen (low- or high-flow oxygen) who are at risk of progressing to severe respiratory failure and likely to have an elevated plasma soluble urokinase plasminogen activator receptor (suPAR). Currently, the suPAR assay is not commercially available in the United States. An alternative method was needed to identify patients that best reflect the population in the clinical trial selected based on suPAR level ≥ 6 ng/mL at baseline. A machine learning approach based on data from the SAVEMORE trial was used to develop a scoring rule to identify patients who are likely to have a suPAR level ≥ 6 ng/mL at baseline. External validation of the scoring rule was conducted with data from a different trial (SAVE). This clinical scoring rule with high positive predictive value, high specificity, reasonable sensitivity, and biological relevance is expected to identify patients who are likely to have an elevated suPAR level ≥ 6 ng/mL at baseline. As such, it is included in the EUA to identify patients that fall within the authorized population for whom the known and potential benefits outweigh the known and potential risks of anakinra.
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Affiliation(s)
- Qi Liu
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Raj Nair
- Office of New Drugs, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Ruihao Huang
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Hao Zhu
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Austin Anderson
- Office of New Drugs, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Ozlem Belen
- Office of New Drugs, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Van Tran
- Office of Biostatistics, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Rebecca Chiu
- Office of Biostatistics, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Karen Higgins
- Office of Biostatistics, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Jianmeng Chen
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Lei He
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Suresh Doddapaneni
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Shiew-Mei Huang
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Nikolay P Nikolov
- Office of New Drugs, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Issam Zineh
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
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Wen YF, Ji P, Schrieber SJ, Rathi S, McGuirt D, Liu J, Chen J, Wang YM, Doddapaneni S, Sahajwalla C. Evaluation of Truncated AUC as an Alternative Measure to Assess Pharmacokinetic Comparability in Bridging Biologic-Device Using Prefilled Syringes and Autoinjectors. J Clin Pharmacol 2023; 63:1417-1429. [PMID: 37507728 DOI: 10.1002/jcph.2322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Accepted: 07/24/2023] [Indexed: 07/30/2023]
Abstract
Pharmacokinetic (PK) comparisons between therapeutic biologics have largely been based on the total area under the concentration-time curve (AUC) and the maximum concentration (Cmax ). For biologics with a long half-life, a PK comparability study may be long in duration and costly to conduct. The goal of this study was to evaluate whether a truncated AUC (tAUC) can be used to assess PK comparability when bridging prefilled syringe (PFS) and autoinjector (AI) treatment options for biologics with a long half-life. Fifteen biologics license applications (BLAs) were included to determine the concordance and geometric percent coefficient of variation (%CV) between tAUCs evaluated on days 7, 14, 21, and 28 and AUC evaluated to infinity (AUC0-inf ). Concordance is established if the tAUCs are comparable with AUC0-inf . Trial simulation was performed to examine the effect of the absorption rate constant (ka ) and sample size on the concordance of tAUCs. The tAUCs evaluated on day 14, 21, and 28 had 100% concordance with AUC0-inf for all 15 BLAs. The concordance of tAUC evaluated at day 7 was 87.5%. Based on the trial simulation, tAUC evaluated to day 28 post-dose can achieve high concordance (≥85%) for biologics exhibiting linear or nonlinear elimination with a ka of ≥0.1/day and with a sample size of 70 subjects per arm. tAUC appears to be a promising alternative PK measure, relative to AUC0-inf , for PK comparability assessments.
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Affiliation(s)
- Ya-Feng Wen
- Division of Inflammation and Immune Pharmacology, Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Ping Ji
- Division of Inflammation and Immune Pharmacology, Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Sarah J Schrieber
- Office of Therapeutic Biologics and Biosimilars, Office of New Drugs, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Sneha Rathi
- Division of Inflammation and Immune Pharmacology, Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Delaney McGuirt
- Division of Inflammation and Immune Pharmacology, Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Jiang Liu
- Division of Pharmacometrics, Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Jianmeng Chen
- Division of Inflammation and Immune Pharmacology, Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Yow-Ming Wang
- Therapeutic Biologics Program, Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Suresh Doddapaneni
- Division of Inflammation and Immune Pharmacology, Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Chandrahas Sahajwalla
- Division of Inflammation and Immune Pharmacology, Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
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3
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Ramamoorthy A, Bende G, Chow ECY, Dimova H, Hartman N, Jean D, Pahwa S, Ren Y, Shukla C, Yang Y, Doddapaneni S, Danielsen ZY. Human radiolabeled mass balance studies supporting the FDA approval of new drugs. Clin Transl Sci 2022; 15:2567-2575. [PMID: 36066467 PMCID: PMC9652429 DOI: 10.1111/cts.13403] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Revised: 07/19/2022] [Accepted: 08/16/2022] [Indexed: 01/25/2023] Open
Abstract
Human radiolabeled mass balance studies are an important component of the clinical pharmacology programs supporting the development of new investigational drugs. These studies allow for understanding of the absorption, distribution, metabolism, and excretion of the parent drug and metabolite(s) in the human body. Understanding the drug's disposition as well as metabolite profiling and abundance via mass balance studies can help inform the overall drug development program. A survey of the US Food and Drug Administration (FDA)-approved new drug applications (NDAs) indicated that about 66% of the drugs had relied on findings from the mass balance studies to help understand the pharmacokinetic characteristics of the drug and to inform the overall drug development program. When such studies were not available in the original NDA, adequate justifications were routinely provided. Of the 104 mass balance studies included in this survey, most of the studies were conducted in healthy volunteers (90%) who were mostly men (>86%). The studies had at least six evaluable participants (66%) and were performed using the final route(s) of administration (98%). Eighty-five percent of the studies utilized a dose within the pharmacokinetic linearity range with 54% of the studies using a dose the same as the approved dose. Nearly all studies were performed as a single-dose (97%) study using a fit-for-purpose radiolabeled formulation. In this analysis, we summarized the current practices for conducting mass balance studies and highlighted the importance of conducting appropriately designed human radiolabeled mass balance studies and the challenges associated with inadequately designed or untimely studies.
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Affiliation(s)
- Anuradha Ramamoorthy
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research (CDER)US Food and Drug Administration (FDA)Silver SpringMarylandUSA
| | - Girish Bende
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research (CDER)US Food and Drug Administration (FDA)Silver SpringMarylandUSA
| | - Edwin Chiu Yuen Chow
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research (CDER)US Food and Drug Administration (FDA)Silver SpringMarylandUSA
| | - Hristina Dimova
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research (CDER)US Food and Drug Administration (FDA)Silver SpringMarylandUSA,Present address:
Office of ScienceCenter for Tobacco Products, FDASilver SpringMarylandUSA
| | - Neil Hartman
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research (CDER)US Food and Drug Administration (FDA)Silver SpringMarylandUSA
| | - Daphney Jean
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research (CDER)US Food and Drug Administration (FDA)Silver SpringMarylandUSA
| | - Sonia Pahwa
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research (CDER)US Food and Drug Administration (FDA)Silver SpringMarylandUSA
| | - Yunzhao Ren
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research (CDER)US Food and Drug Administration (FDA)Silver SpringMarylandUSA
| | - Chinmay Shukla
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research (CDER)US Food and Drug Administration (FDA)Silver SpringMarylandUSA
| | - Yuching Yang
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research (CDER)US Food and Drug Administration (FDA)Silver SpringMarylandUSA
| | - Suresh Doddapaneni
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research (CDER)US Food and Drug Administration (FDA)Silver SpringMarylandUSA
| | - Zhixia Yan Danielsen
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research (CDER)US Food and Drug Administration (FDA)Silver SpringMarylandUSA
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4
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Liu T, Neuner R, Thompson A, Pottackal G, Petullo D, Liu J, Nikolov N, Sahajwalla C, Doddapaneni S, Chen J. Clinical pharmacology considerations for the approval of belimumab for the treatment of adult patients with active lupus nephritis: A regulatory perspective. Lupus 2022; 31:424-432. [PMID: 35238725 DOI: 10.1177/09612033221079771] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
On 16 December 2020, FDA approved Benlysta® (belimumab) for both the intravenous (IV) and subcutaneous (SC) administration routes for the treatment of adult patients with active lupus nephritis (LN) who are receiving standard therapy. This approval represents the first FDA approved treatment of patients with active LN.The approved IV dosing regimen (10 mg/kg dose Q2W for three doses, then 10 mg/kg Q4W thereafter) was based on a randomized double-blind placebo controlled clinical trial in adult patients with LN. For the approval of the SC dosing regimen (400 mg dose QW for four doses, then 200 mg QW thereafter), efficacy was supported solely by pharmacokinetics (PK) modeling and simulation which estimated a matched steady state average concentration and higher trough concentrations for the SC administration route, for bridging to the efficacy of IV belimumab in adults with LN. The safety and immunogenicity profile of the SC administration route has been assessed in the SLE studies.In a population PK analysis, higher proteinuria was associated with greater belimumab clearance and lower belimumab exposure. In an exposure response analysis, the efficacy of belimumab as evaluated by renal response was mainly driven by patients with lower proteinuria at baseline regardless of other baseline characteristics (e.g. baseline renal function, renal biopsy classification), induction therapies, or belimumab exposure levels (within 10 mg/kg dosing regimen), etc. However, post hoc analyses showed that belimumab had activity in LN patients with higher proteinuria at baseline. There is no adequate information to suggest that a higher dose would provide additional benefit for patients with lower exposure (e.g. higher proteinuria).
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Affiliation(s)
- Tao Liu
- Division of Inflammation and Immune Pharmacology, Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, 4137Food and Drug Administration, Silver Spring, MD, USA
| | - Rosemarie Neuner
- Division of Rheumatology and Transplant Medicine, Office of Immunology and Inflammation, Office of New Drug, Center for Drug Evaluation and Research, 4137Food and Drug Administration, Silver Spring, MD, USA
| | - Aliza Thompson
- Division of Cardiology and Nephrology, Office of Cardiology, Hematology, Endocrinology and Nephrology, Office of New Drug, Center for Drug Evaluation and Research, 4137Food and Drug Administration, Silver Spring, MD, USA
| | - Ginto Pottackal
- Division of Biometrics III, Office of Biostatistics, Office of Translational Sciences, Center for Drug Evaluation and Research, 4137Food and Drug Administration, Silver Spring, MD, USA
| | - David Petullo
- Division of Biometrics III, Office of Biostatistics, Office of Translational Sciences, Center for Drug Evaluation and Research, 4137Food and Drug Administration, Silver Spring, MD, USA
| | - Jiang Liu
- Division of Pharmacometrics, Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, 4137Food and Drug Administration, Silver Spring, MD, USA
| | - Nikolay Nikolov
- Division of Rheumatology and Transplant Medicine, Office of Immunology and Inflammation, Office of New Drug, Center for Drug Evaluation and Research, 4137Food and Drug Administration, Silver Spring, MD, USA
| | - Chandrahas Sahajwalla
- Division of Inflammation and Immune Pharmacology, Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, 4137Food and Drug Administration, Silver Spring, MD, USA
| | - Suresh Doddapaneni
- Division of Inflammation and Immune Pharmacology, Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, 4137Food and Drug Administration, Silver Spring, MD, USA
| | - Jianmeng Chen
- Division of Inflammation and Immune Pharmacology, Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, 4137Food and Drug Administration, Silver Spring, MD, USA
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5
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Li L, Zhang Y, Ma L, Ji P, Yim S, Chowdhury BA, Doddapaneni S, Liu J, Wang Y, Sahajwalla C. Exposure-Response Modeling and Power Analysis of Components of ACR Response Criteria in Rheumatoid Arthritis (Part 2: Continuous Model). J Clin Pharmacol 2017; 57:1107-1125. [PMID: 28817201 DOI: 10.1002/jcph.967] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2017] [Accepted: 05/19/2017] [Indexed: 11/06/2022]
Abstract
Population pharmacokinetic/pharmacodynamic (PK/PD) models were developed to quantitate the exposure-response relationships using continuous longitudinal data on American College of Rheumatology (ACR) subcomponents, that is, tender-joint count (TJC), swollen-joint count (SJC), C-reactive protein, patient's assessment of pain, patient's global assessment of disease activity, physician's global assessment of disease activity, and patient's assessment of physical function for 5 biologics approved for use in rheumatoid arthritis. The models were then used to simulate the time courses of clinical outcomes following different treatment regimens. The relative sensitivity of the 7 subcomponents was assessed using Monte Carlo simulation-based power analysis. The developed population PK/PD models adequately described the relationship between serum concentrations and changes in ACR subcomponents. The trial simulation and subsequent power analysis showed that SJC and TJC appeared to be more sensitive than the other 5 ACR subcomponents to detect treatment effect over placebo/methotrexate. These 7 ACR subcomponents had similar power in detecting the treatment difference between different doses. In addition, the continuous measures of ACR subcomponents did not appear to be more sensitive than binary measures.
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Affiliation(s)
- Liang Li
- Division of Clinical Pharmacology II, Office of Clinical Pharmacology, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Yi Zhang
- Division of Clinical Pharmacology II, Office of Clinical Pharmacology, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA.,Division of Bioequivalence III, Office of Generic Drugs, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Lian Ma
- Division of Pharmacometrics, Office of Clinical Pharmacology, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Ping Ji
- Division of Clinical Pharmacology II, Office of Clinical Pharmacology, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Sarah Yim
- Division of Pulmonary, Allergy, and Rheumatology Products, Office of New Drugs, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Badrul A Chowdhury
- Division of Pulmonary, Allergy, and Rheumatology Products, Office of New Drugs, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Suresh Doddapaneni
- Division of Clinical Pharmacology II, Office of Clinical Pharmacology, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Jiang Liu
- Division of Pharmacometrics, Office of Clinical Pharmacology, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Yaning Wang
- Division of Pharmacometrics, Office of Clinical Pharmacology, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Chandrahas Sahajwalla
- Division of Clinical Pharmacology II, Office of Clinical Pharmacology, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
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Li L, Zhang Y, Ma L, Ji P, Yim S, Chowdhury B, Doddapaneni S, Liu J, Wang Y, Sahajwalla C. Exposure-Response Modeling and Power Analysis of Components of ACR Response Criteria in Rheumatoid Arthritis (Part 1: Binary Model). J Clin Pharmacol 2017; 57:1097-1106. [DOI: 10.1002/jcph.891] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2016] [Accepted: 02/20/2017] [Indexed: 11/06/2022]
Affiliation(s)
- Liang Li
- Division of Clinical Pharmacology II; Office of Clinical Pharmacology; Center for Drug Evaluation and Research; Food and Drug Administration; Silver Spring MD USA
| | - Yi Zhang
- Division of Clinical Pharmacology II; Office of Clinical Pharmacology; Center for Drug Evaluation and Research; Food and Drug Administration; Silver Spring MD USA
- Division of Bioequivalence III; Office of Generic Drugs; Center for Drug Evaluation and Research; Food and Drug Administration; Silver Spring MD USA
| | - Lian Ma
- Division of Pharmacometrics; Office of Clinical Pharmacology; Center for Drug Evaluation and Research; Food and Drug Administration; Silver Spring MD USA
| | - Ping Ji
- Division of Clinical Pharmacology II; Office of Clinical Pharmacology; Center for Drug Evaluation and Research; Food and Drug Administration; Silver Spring MD USA
| | - Sarah Yim
- Division of Pulmonary; Allergy, and Rheumatology Products; Office of New Drugs; Center for Drug Evaluation and Research; Food and Drug Administration; Silver Spring MD USA
| | - Badrul Chowdhury
- Division of Pulmonary; Allergy, and Rheumatology Products; Office of New Drugs; Center for Drug Evaluation and Research; Food and Drug Administration; Silver Spring MD USA
| | - Suresh Doddapaneni
- Division of Clinical Pharmacology II; Office of Clinical Pharmacology; Center for Drug Evaluation and Research; Food and Drug Administration; Silver Spring MD USA
| | - Jiang Liu
- Division of Pharmacometrics; Office of Clinical Pharmacology; Center for Drug Evaluation and Research; Food and Drug Administration; Silver Spring MD USA
| | - Yaning Wang
- Division of Pharmacometrics; Office of Clinical Pharmacology; Center for Drug Evaluation and Research; Food and Drug Administration; Silver Spring MD USA
| | - Chandrahas Sahajwalla
- Division of Clinical Pharmacology II; Office of Clinical Pharmacology; Center for Drug Evaluation and Research; Food and Drug Administration; Silver Spring MD USA
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Doddapaneni S, Shetty R, Sabih I, Maddali K, Khera K. Assessment of Medication Adherence in Rheumatoid Arthritis Patients in a Tertiary Care Hospital. Value Health 2014; 17:A774. [PMID: 27202860 DOI: 10.1016/j.jval.2014.08.336] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Affiliation(s)
- S Doddapaneni
- Manipal College of Pharmaceutical Sciences, Manipal, India
| | - R Shetty
- Manipal College of Pharmaceutical Sciences, Manipal, India
| | - I Sabih
- Manipal College of Pharmaceutical Sciences, Manipal, India
| | - K Maddali
- Manipal College of Pharmaceutical Sciences, Manipal, India
| | - K Khera
- Manipal College of Pharmaceutical Sciences, Manipal, India
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Ma L, Zhao L, Xu Y, Yim S, Doddapaneni S, Sahajwalla CG, Wang Y, Ji P. Clinical endpoint sensitivity in rheumatoid arthritis: modeling and simulation. J Pharmacokinet Pharmacodyn 2014; 41:537-43. [PMID: 25283268 DOI: 10.1007/s10928-014-9385-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2014] [Accepted: 09/16/2014] [Indexed: 11/25/2022]
Abstract
The commonly used efficacy endpoints in Rheumatoid Arthritis (RA) clinical trials are American College of Rheumatology 20 % improvement criteria (ACR20), ACR50, and ACR70 response rates, and the 28-joint disease activity score (DAS28). Longitudinal models to quantitate the exposure-response relationships for ACRs and DAS28 score were developed for four biologics used for the management of RA. The models were then used to simulate the clinical outcome at various time points following different treatment regimens. Discriminative sensitivity of these endpoints was assessed using a power analysis. The trial simulation and subsequent power analysis showed that both ACR20 and DAS28 exhibit much lower power in distinguishing between two doses investigated compared with distinguishing treatment effect over placebo/Methotrexate (MTX) control. ACR20 response rate is generally more powerful in detecting treatment effect over placebo/MTX control as compared to DAS28. The findings of current study provide useful information which will help future clinical trial design for the treatment of patients with RA.
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Affiliation(s)
- Lian Ma
- Division of Pharmacometrics, Office of Clinical Pharmacology, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
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9
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Ji P, Wang Y, Li Z, Doddapaneni S, Hertz S, Furness S, Sahajwalla CG. Regulatory review of acetaminophen clinical pharmacology in young pediatric patients. J Pharm Sci 2012; 101:4383-9. [PMID: 23073837 DOI: 10.1002/jps.23331] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2012] [Revised: 08/25/2012] [Accepted: 09/11/2012] [Indexed: 11/11/2022]
Abstract
The acetaminophen dosage schedule in pediatric patients below 12 years of age for the over-the-counter (OTC) monograph is one of the many issues being evaluated and discussed in the development of the Proposed Rule for Internal Analgesic, Antipyretic, and Anti-rheumatic drug products. The dosage regimen based on age and weight, with instructions that weight-based dosage should be used if a child's weight is known, is currently being assessed by the agency. This review summarizes the available pharmacokinetic and pharmacodynamic (fever reduction) data of oral acetaminophen in pediatric patients of 6 months to 12 years of age. Acetaminophen is metabolized in the liver mainly through glucuronidation, sulfation, and to a lesser extent oxidation. Because of the difference in the ontogeny of various metabolizing pathways, the relative contribution of each pathway to the overall acetaminophen metabolism in children changes with age. The sulfation pathway plays a more important role in metabolizing acetaminophen than the glucuronidation pathway in younger children as compared with older children and adults. The pharmacokinetic exposure of acetaminophen in pediatric patients of 6 months to 12 years of age given oral administration of 10-15 mg/kg is within the adult exposure range given the OTC monograph dose. The antipyretic effect of acetaminophen is dose dependent and appears to be better than placebo at the dose range of 10-15 mg/kg in pediatric patients of 6 months to 12 years of age.
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Affiliation(s)
- Ping Ji
- Division of Clinical Pharmacology II, Office of Clinical Pharmacology, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland, USA
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10
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Schultheis LW, Nikhar BM, Mellon RD, Doddapaneni S, Christodoulo DD, Roca R, Rappaport BA. Clinical Investigation of Neuraxially Administered Drugs: A Regulatory Perspective. Anesth Analg 2009; 109:299-300. [DOI: 10.1213/ane.0b013e3181a801b9] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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11
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Volpe DA, Asafu-Adjaye EB, Ellison CD, Doddapaneni S, Uppoor RS, Khan MA. Effect of ethanol on opioid drug permeability through caco-2 cell monolayers. AAPS J 2008; 10:360-2. [PMID: 18592381 DOI: 10.1208/s12248-008-9046-3] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/29/2008] [Accepted: 05/30/2008] [Indexed: 11/30/2022]
Affiliation(s)
- Donna A Volpe
- Division of Product Quality Research, Food and Drug Administration, 10903 New Hampshire Ave., Silver Spring, Maryland 20993-0002, USA.
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12
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Abbas R, Schultz IR, Doddapaneni S, Hayton WL. Toxicokinetics of parathion and paraoxon in rainbow trout after intravascular administration and water exposure. Toxicol Appl Pharmacol 1996; 136:194-9. [PMID: 8560474 DOI: 10.1006/taap.1996.0024] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
Fish are less sensitive than mammals to organophosphate insecticide toxicity. The species differences have been mainly investigated by biochemical studies of AChE and organophosphate interaction. To examine whether species differences in the toxicokinetics of the organophosphate insecticides were also involved in their differential toxicity, rainbow trout were fitted with a dorsal aorta cannula and administered parathion and its active metabolite paraoxon intraarterially (ia) and via water exposure. Serial blood samples were removed and the plasma concentrations of parathion and paraoxon were determined by capillary GC with EC detection. Plasma protein binding was determined by equilibrium dialysis and ultrafiltration. After ia injection the plasma concentration-time profiles of parathion and paraoxon were multiexponential, with a terminal t1/2 of 56.1 and 0.528 hr. The steady-state volumes of distribution and total body clearances (CLb) for parathion and paraoxon were 1370 and 1080 ml kg-1 and 21.4 and 3020 ml hr-1 kg-1; the plasma unbound fractions were 1.23 and 52.5%. The large difference in CLb between parathion and paraoxon appeared to result primarily from differences in plasma protein binding. Parathion had greater persistence in trout than rat, suggesting that sensitivity difference were unrelated to toxicokinetic differences.
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Affiliation(s)
- R Abbas
- Division of Pharmaceutics and Pharmaceutical Chemistry, College of Pharmacy, Ohio State University, Columbus 43210, USA
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