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Showing 1 to 12 of 489 entries
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Disease Progression/Clinical Outcome Model for Castration-Resistant Prostate Cancer in Patients Treated With Eribulin.

CPT: pharmacometrics & systems pharmacology

van Hasselt JG, Gupta A, Hussein Z, Beijnen JH, Schellens JH, Huitema AD.
PMID: 26312162
CPT Pharmacometrics Syst Pharmacol. 2015 Jul;4(7):386-95. doi: 10.1002/psp4.49. Epub 2015 Jun 30.

Frameworks that associate cancer dynamic disease progression models with parametric survival models for clinical outcome have recently been proposed to support decision making in early clinical development. Here we developed such a disease progression clinical outcome model for castration-resistant...

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van Hasselt JG, Gupta A, Hussein Z, et al. Disease Progression/Clinical Outcome Model for Castration-Resistant Prostate Cancer in Patients Treated With Eribulin. CPT Pharmacometrics Syst Pharmacol. 2015;4(7):386-95doi: 10.1002/psp4.49.
van Hasselt, J. G., Gupta, A., Hussein, Z., Beijnen, J. H., Schellens, J. H., & Huitema, A. D. (2015). Disease Progression/Clinical Outcome Model for Castration-Resistant Prostate Cancer in Patients Treated With Eribulin. CPT: pharmacometrics & systems pharmacology, 4(7), 386-95. https://doi.org/10.1002/psp4.49
van Hasselt, J G C, et al. "Disease Progression/Clinical Outcome Model for Castration-Resistant Prostate Cancer in Patients Treated With Eribulin." CPT: pharmacometrics & systems pharmacology vol. 4,7 (2015): 386-95. doi: https://doi.org/10.1002/psp4.49
van Hasselt JG, Gupta A, Hussein Z, Beijnen JH, Schellens JH, Huitema AD. Disease Progression/Clinical Outcome Model for Castration-Resistant Prostate Cancer in Patients Treated With Eribulin. CPT Pharmacometrics Syst Pharmacol. 2015 Jul;4(7):386-95. doi: 10.1002/psp4.49. Epub 2015 Jun 30. PMID: 26312162; PMCID: PMC4544052.
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CORRIGENDUM: Commentary on Pharmacometrics for Immunotherapy.

CPT: pharmacometrics & systems pharmacology

Garrido MJ, Berraondo P, Trocóniz IF.
PMID: 28425210
CPT Pharmacometrics Syst Pharmacol. 2017 Apr;6(4):277. doi: 10.1002/psp4.12186. Epub 2017 Apr 06.

No abstract available.

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Garrido MJ, Berraondo P, Trocóniz IF. CORRIGENDUM: Commentary on Pharmacometrics for Immunotherapy. CPT Pharmacometrics Syst Pharmacol. 2017;6(4):277doi: 10.1002/psp4.12186.
Garrido, M. J., Berraondo, P., & Trocóniz, I. F. (2017). CORRIGENDUM: Commentary on Pharmacometrics for Immunotherapy. CPT: pharmacometrics & systems pharmacology, 6(4), 277. https://doi.org/10.1002/psp4.12186
Garrido, M J, et al. "CORRIGENDUM: Commentary on Pharmacometrics for Immunotherapy." CPT: pharmacometrics & systems pharmacology vol. 6,4 (2017): 277. doi: https://doi.org/10.1002/psp4.12186
Garrido MJ, Berraondo P, Trocóniz IF. CORRIGENDUM: Commentary on Pharmacometrics for Immunotherapy. CPT Pharmacometrics Syst Pharmacol. 2017 Apr;6(4):277. doi: 10.1002/psp4.12186. Epub 2017 Apr 06. PMID: 28425210; PMCID: PMC5397560.
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Preclinical Modeling of Tumor Growth and Angiogenesis Inhibition to Describe Pazopanib Clinical Effects in Renal Cell Carcinoma.

CPT: pharmacometrics & systems pharmacology

Ouerdani A, Struemper H, Suttle AB, Ouellet D, Ribba B.
PMID: 26783502
CPT Pharmacometrics Syst Pharmacol. 2015 Nov;4(11):660-8. doi: 10.1002/psp4.12001. Epub 2015 Nov 03.

The objective was to leverage tumor size data from preclinical experiments to propose a model of tumor growth and angiogenesis inhibition for the analysis of pazopanib efficacy in renal cell carcinoma (RCC) patients. We analyzed tumor data in mice...

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Ouerdani A, Struemper H, Suttle AB, et al. Preclinical Modeling of Tumor Growth and Angiogenesis Inhibition to Describe Pazopanib Clinical Effects in Renal Cell Carcinoma. CPT Pharmacometrics Syst Pharmacol. 2015;4(11):660-8doi: 10.1002/psp4.12001.
Ouerdani, A., Struemper, H., Suttle, A. B., Ouellet, D., & Ribba, B. (2015). Preclinical Modeling of Tumor Growth and Angiogenesis Inhibition to Describe Pazopanib Clinical Effects in Renal Cell Carcinoma. CPT: pharmacometrics & systems pharmacology, 4(11), 660-8. https://doi.org/10.1002/psp4.12001
Ouerdani, A, et al. "Preclinical Modeling of Tumor Growth and Angiogenesis Inhibition to Describe Pazopanib Clinical Effects in Renal Cell Carcinoma." CPT: pharmacometrics & systems pharmacology vol. 4,11 (2015): 660-8. doi: https://doi.org/10.1002/psp4.12001
Ouerdani A, Struemper H, Suttle AB, Ouellet D, Ribba B. Preclinical Modeling of Tumor Growth and Angiogenesis Inhibition to Describe Pazopanib Clinical Effects in Renal Cell Carcinoma. CPT Pharmacometrics Syst Pharmacol. 2015 Nov;4(11):660-8. doi: 10.1002/psp4.12001. Epub 2015 Nov 03. PMID: 26783502; PMCID: PMC4716582.
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Scale reduction of a systems coagulation model with an application to modeling pharmacokinetic-pharmacodynamic data.

CPT: pharmacometrics & systems pharmacology

Gulati A, Isbister GK, Duffull SB.
PMID: 24402117
CPT Pharmacometrics Syst Pharmacol. 2014 Jan 08;3:e90. doi: 10.1038/psp.2013.67.

Bridging systems biology and pharmacokinetics-pharmacodynamics has resulted in models that are highly complex and complicated. They usually contain large numbers of states and parameters and describe multiple input-output relationships. Based on any given data set relating to a specific...

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Gulati A, Isbister GK, Duffull SB. Scale reduction of a systems coagulation model with an application to modeling pharmacokinetic-pharmacodynamic data. CPT Pharmacometrics Syst Pharmacol. 2014;3:e90doi: 10.1038/psp.2013.67.
Gulati, A., Isbister, G. K., & Duffull, S. B. (2014). Scale reduction of a systems coagulation model with an application to modeling pharmacokinetic-pharmacodynamic data. CPT: pharmacometrics & systems pharmacology, 3e90. https://doi.org/10.1038/psp.2013.67
Gulati, A, et al. "Scale reduction of a systems coagulation model with an application to modeling pharmacokinetic-pharmacodynamic data." CPT: pharmacometrics & systems pharmacology vol. 3 (2014): e90. doi: https://doi.org/10.1038/psp.2013.67
Gulati A, Isbister GK, Duffull SB. Scale reduction of a systems coagulation model with an application to modeling pharmacokinetic-pharmacodynamic data. CPT Pharmacometrics Syst Pharmacol. 2014 Jan 08;3:e90. doi: 10.1038/psp.2013.67. PMID: 24402117; PMCID: PMC3910010.
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Evaluation of 4β-Hydroxycholesterol as a Clinical Biomarker of CYP3A4 Drug Interactions Using a Bayesian Mechanism-Based Pharmacometric Model.

CPT: pharmacometrics & systems pharmacology

Leil TA, Kasichayanula S, Boulton DW, LaCreta F.
PMID: 24964282
CPT Pharmacometrics Syst Pharmacol. 2014 Jun 25;3:e120. doi: 10.1038/psp.2014.18.

A Bayesian mechanism-based pharmacokinetic/pharmacodynamic model of cytochrome P450 3A4 (CYP3A4) activity was developed based on a clinical study of the effects of ketoconazole and rifampin on midazolam exposure and plasma 4β-hydroxycholesterol (4βHC) concentrations. Simulations from the model demonstrated that...

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Leil TA, Kasichayanula S, Boulton DW, et al. Evaluation of 4β-Hydroxycholesterol as a Clinical Biomarker of CYP3A4 Drug Interactions Using a Bayesian Mechanism-Based Pharmacometric Model. CPT Pharmacometrics Syst Pharmacol. 2014;3:e120doi: 10.1038/psp.2014.18.
Leil, T. A., Kasichayanula, S., Boulton, D. W., & LaCreta, F. (2014). Evaluation of 4β-Hydroxycholesterol as a Clinical Biomarker of CYP3A4 Drug Interactions Using a Bayesian Mechanism-Based Pharmacometric Model. CPT: pharmacometrics & systems pharmacology, 3e120. https://doi.org/10.1038/psp.2014.18
Leil, T A, et al. "Evaluation of 4β-Hydroxycholesterol as a Clinical Biomarker of CYP3A4 Drug Interactions Using a Bayesian Mechanism-Based Pharmacometric Model." CPT: pharmacometrics & systems pharmacology vol. 3 (2014): e120. doi: https://doi.org/10.1038/psp.2014.18
Leil TA, Kasichayanula S, Boulton DW, LaCreta F. Evaluation of 4β-Hydroxycholesterol as a Clinical Biomarker of CYP3A4 Drug Interactions Using a Bayesian Mechanism-Based Pharmacometric Model. CPT Pharmacometrics Syst Pharmacol. 2014 Jun 25;3:e120. doi: 10.1038/psp.2014.18. PMID: 24964282; PMCID: PMC4076805.
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Mechanistic Modeling Reveals the Critical Knowledge Gaps in Bile Acid-Mediated DILI.

CPT: pharmacometrics & systems pharmacology

Woodhead JL, Yang K, Brouwer KL, Siler SQ, Stahl SH, Ambroso JL, Baker D, Watkins PB, Howell BA.
PMID: 25006780
CPT Pharmacometrics Syst Pharmacol. 2014 Jul 09;3:e123. doi: 10.1038/psp.2014.21.

Bile salt export pump (BSEP) inhibition has been proposed to be an important mechanism for drug-induced liver injury (DILI). Modeling can prioritize knowledge gaps concerning bile acid (BA) homeostasis and thus help guide experimentation. A submodel of BA homeostasis...

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Woodhead JL, Yang K, Brouwer KL, et al. Mechanistic Modeling Reveals the Critical Knowledge Gaps in Bile Acid-Mediated DILI. CPT Pharmacometrics Syst Pharmacol. 2014;3:e123doi: 10.1038/psp.2014.21.
Woodhead, J. L., Yang, K., Brouwer, K. L., Siler, S. Q., Stahl, S. H., Ambroso, J. L., Baker, D., Watkins, P. B., & Howell, B. A. (2014). Mechanistic Modeling Reveals the Critical Knowledge Gaps in Bile Acid-Mediated DILI. CPT: pharmacometrics & systems pharmacology, 3e123. https://doi.org/10.1038/psp.2014.21
Woodhead, J L, et al. "Mechanistic Modeling Reveals the Critical Knowledge Gaps in Bile Acid-Mediated DILI." CPT: pharmacometrics & systems pharmacology vol. 3 (2014): e123. doi: https://doi.org/10.1038/psp.2014.21
Woodhead JL, Yang K, Brouwer KL, Siler SQ, Stahl SH, Ambroso JL, Baker D, Watkins PB, Howell BA. Mechanistic Modeling Reveals the Critical Knowledge Gaps in Bile Acid-Mediated DILI. CPT Pharmacometrics Syst Pharmacol. 2014 Jul 09;3:e123. doi: 10.1038/psp.2014.21. PMID: 25006780; PMCID: PMC4120015.
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Commentary on the MID3 Good Practices Paper.

CPT: pharmacometrics & systems pharmacology

Manolis E, Brogren J, Cole S, Hay JL, Nordmark A, Karlsson KE, Lentz F, Benda N, Wangorsch G, Pons G, Zhao W, Gigante V, Serone F, Standing JF, Dokoumetzidis A, Vakkilainen J, van den Heuvel M, Mangas Sanjuan V, Taminiau J, Kerwash E, Khan D, Musuamba FT, Skottheim Rusten I.
PMID: 28653481
CPT Pharmacometrics Syst Pharmacol. 2017 Jul;6(7):416-417. doi: 10.1002/psp4.12223. Epub 2017 Jul 22.

During the last 10 years the European Medicines Agency (EMA) organized a number of workshops on modeling and simulation, working towards greater integration of modeling and simulation (M&S) in the development and regulatory assessment of medicines. In the 2011...

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Manolis E, Brogren J, Cole S, et al. Commentary on the MID3 Good Practices Paper. CPT Pharmacometrics Syst Pharmacol. 2017;6(7):416-417doi: 10.1002/psp4.12223.
Manolis, E., Brogren, J., Cole, S., Hay, J. L., Nordmark, A., Karlsson, K. E., Lentz, F., Benda, N., Wangorsch, G., Pons, G., Zhao, W., Gigante, V., Serone, F., Standing, J. F., Dokoumetzidis, A., Vakkilainen, J., van den Heuvel, M., Mangas Sanjuan, V., Taminiau, J., Kerwash, E., Khan, D., Musuamba, F. T., Skottheim Rusten, I. (2017). Commentary on the MID3 Good Practices Paper. CPT: pharmacometrics & systems pharmacology, 6(7), 416-417. https://doi.org/10.1002/psp4.12223
Manolis, Efthymios, et al. "Commentary on the MID3 Good Practices Paper." CPT: pharmacometrics & systems pharmacology vol. 6,7 (2017): 416-417. doi: https://doi.org/10.1002/psp4.12223
Manolis E, Brogren J, Cole S, Hay JL, Nordmark A, Karlsson KE, Lentz F, Benda N, Wangorsch G, Pons G, Zhao W, Gigante V, Serone F, Standing JF, Dokoumetzidis A, Vakkilainen J, van den Heuvel M, Mangas Sanjuan V, Taminiau J, Kerwash E, Khan D, Musuamba FT, Skottheim Rusten I. Commentary on the MID3 Good Practices Paper. CPT Pharmacometrics Syst Pharmacol. 2017 Jul;6(7):416-417. doi: 10.1002/psp4.12223. Epub 2017 Jul 22. PMID: 28653481; PMCID: PMC5529732.
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Connecting the Dots: Linking Osteocyte Activity and Therapeutic Modulation of Sclerostin by Extending a Multiscale Systems Model.

CPT: pharmacometrics & systems pharmacology

Eudy RJ, Gastonguay MR, Baron KT, Riggs MM.
PMID: 26451332
CPT Pharmacometrics Syst Pharmacol. 2015 Sep;4(9):527-36. doi: 10.1002/psp4.12013. Epub 2015 Sep 11.

The goal of this work was to extend a mathematical, multiscale systems model of bone function, remodeling, and health in order to explore hypotheses related to therapeutic modulation of sclerostin and quantitatively describe purported osteocyte activity within bone remodeling...

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Eudy RJ, Gastonguay MR, Baron KT, et al. Connecting the Dots: Linking Osteocyte Activity and Therapeutic Modulation of Sclerostin by Extending a Multiscale Systems Model. CPT Pharmacometrics Syst Pharmacol. 2015;4(9):527-36doi: 10.1002/psp4.12013.
Eudy, R. J., Gastonguay, M. R., Baron, K. T., & Riggs, M. M. (2015). Connecting the Dots: Linking Osteocyte Activity and Therapeutic Modulation of Sclerostin by Extending a Multiscale Systems Model. CPT: pharmacometrics & systems pharmacology, 4(9), 527-36. https://doi.org/10.1002/psp4.12013
Eudy, R J, et al. "Connecting the Dots: Linking Osteocyte Activity and Therapeutic Modulation of Sclerostin by Extending a Multiscale Systems Model." CPT: pharmacometrics & systems pharmacology vol. 4,9 (2015): 527-36. doi: https://doi.org/10.1002/psp4.12013
Eudy RJ, Gastonguay MR, Baron KT, Riggs MM. Connecting the Dots: Linking Osteocyte Activity and Therapeutic Modulation of Sclerostin by Extending a Multiscale Systems Model. CPT Pharmacometrics Syst Pharmacol. 2015 Sep;4(9):527-36. doi: 10.1002/psp4.12013. Epub 2015 Sep 11. PMID: 26451332; PMCID: PMC4592532.
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Using a Systems Pharmacology Approach to Study the Effect of Statins on the Early Stage of Atherosclerosis in Humans.

CPT: pharmacometrics & systems pharmacology

Pichardo-Almarza C, Metcalf L, Finkelstein A, Diaz-Zuccarini V.
PMID: 26225221
CPT Pharmacometrics Syst Pharmacol. 2015 Jan;4(1):e00007. doi: 10.1002/psp4.7. Epub 2014 Dec 30.

More than 100,000 people have participated in controlled trials of statins (lowering cholesterol drugs) since the introduction of lovastatin in the 1980s. Meta-analyses of this data have shown that statins have a beneficial effect on treated groups compared to...

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Pichardo-Almarza C, Metcalf L, Finkelstein A, et al. Using a Systems Pharmacology Approach to Study the Effect of Statins on the Early Stage of Atherosclerosis in Humans. CPT Pharmacometrics Syst Pharmacol. 2014;4(1):e00007doi: 10.1002/psp4.7.
Pichardo-Almarza, C., Metcalf, L., Finkelstein, A., & Diaz-Zuccarini, V. (2015). Using a Systems Pharmacology Approach to Study the Effect of Statins on the Early Stage of Atherosclerosis in Humans. CPT: pharmacometrics & systems pharmacology, 4(1), e00007. https://doi.org/10.1002/psp4.7
Pichardo-Almarza, C, et al. "Using a Systems Pharmacology Approach to Study the Effect of Statins on the Early Stage of Atherosclerosis in Humans." CPT: pharmacometrics & systems pharmacology vol. 4,1 (2015): e00007. doi: https://doi.org/10.1002/psp4.7
Pichardo-Almarza C, Metcalf L, Finkelstein A, Diaz-Zuccarini V. Using a Systems Pharmacology Approach to Study the Effect of Statins on the Early Stage of Atherosclerosis in Humans. CPT Pharmacometrics Syst Pharmacol. 2015 Jan;4(1):e00007. doi: 10.1002/psp4.7. Epub 2014 Dec 30. PMID: 26225221; PMCID: PMC4337252.
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Evaluating the Use of Linear Mixed-Effect Models for Inference of the Concentration-QTc Slope Estimate as a Surrogate for a Biological QTc Model.

CPT: pharmacometrics & systems pharmacology

Huh Y, Hutmacher MM.
PMID: 26225224
CPT Pharmacometrics Syst Pharmacol. 2015 Jan;4(1):e00014. doi: 10.1002/psp4.14. Epub 2015 Jan 28.

In concentration-QTc modeling, oscillatory functions have been used to characterize biological rhythms in QTc profiles. Fitting such functions is not always feasible because it requires sufficient electrocardiograph sampling. In this study, drug concentration and QTc data were simulated using...

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Huh Y, Hutmacher MM. Evaluating the Use of Linear Mixed-Effect Models for Inference of the Concentration-QTc Slope Estimate as a Surrogate for a Biological QTc Model. CPT Pharmacometrics Syst Pharmacol. 2015;4(1):e00014doi: 10.1002/psp4.14.
Huh, Y., & Hutmacher, M. M. (2015). Evaluating the Use of Linear Mixed-Effect Models for Inference of the Concentration-QTc Slope Estimate as a Surrogate for a Biological QTc Model. CPT: pharmacometrics & systems pharmacology, 4(1), e00014. https://doi.org/10.1002/psp4.14
Huh, Y, and Hutmacher, M M. "Evaluating the Use of Linear Mixed-Effect Models for Inference of the Concentration-QTc Slope Estimate as a Surrogate for a Biological QTc Model." CPT: pharmacometrics & systems pharmacology vol. 4,1 (2015): e00014. doi: https://doi.org/10.1002/psp4.14
Huh Y, Hutmacher MM. Evaluating the Use of Linear Mixed-Effect Models for Inference of the Concentration-QTc Slope Estimate as a Surrogate for a Biological QTc Model. CPT Pharmacometrics Syst Pharmacol. 2015 Jan;4(1):e00014. doi: 10.1002/psp4.14. Epub 2015 Jan 28. PMID: 26225224; PMCID: PMC4337253.
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Target Mediated Drug Disposition Model of CPHPC in Patients with Systemic Amyloidosis.

CPT: pharmacometrics & systems pharmacology

Sahota T, Berges A, Barton S, Cookson L, Zamuner S, Richards D.
PMID: 26225229
CPT Pharmacometrics Syst Pharmacol. 2015 Feb;4(2):e15. doi: 10.1002/psp4.15. Epub 2015 Feb 04.

The amyloid deposits that cause disease in systemic amyloidosis always contain the normal plasma protein, serum amyloid P (SAP) component. SAP is the target of a novel immunotherapy approach now being developed to eliminate amyloid deposits. The treatment is...

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Sahota T, Berges A, Barton S, et al. Target Mediated Drug Disposition Model of CPHPC in Patients with Systemic Amyloidosis. CPT Pharmacometrics Syst Pharmacol. 2015;4(2):e15doi: 10.1002/psp4.15.
Sahota, T., Berges, A., Barton, S., Cookson, L., Zamuner, S., & Richards, D. (2015). Target Mediated Drug Disposition Model of CPHPC in Patients with Systemic Amyloidosis. CPT: pharmacometrics & systems pharmacology, 4(2), e15. https://doi.org/10.1002/psp4.15
Sahota, T, et al. "Target Mediated Drug Disposition Model of CPHPC in Patients with Systemic Amyloidosis." CPT: pharmacometrics & systems pharmacology vol. 4,2 (2015): e15. doi: https://doi.org/10.1002/psp4.15
Sahota T, Berges A, Barton S, Cookson L, Zamuner S, Richards D. Target Mediated Drug Disposition Model of CPHPC in Patients with Systemic Amyloidosis. CPT Pharmacometrics Syst Pharmacol. 2015 Feb;4(2):e15. doi: 10.1002/psp4.15. Epub 2015 Feb 04. PMID: 26225229; PMCID: PMC4360666.
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Quantification of the Forgiveness of Drugs to Imperfect Adherence.

CPT: pharmacometrics & systems pharmacology

Assawasuwannakit P, Braund R, Duffull SB.
PMID: 26225235
CPT Pharmacometrics Syst Pharmacol. 2015 Mar;4(3):e00004. doi: 10.1002/psp4.4. Epub 2015 Mar 04.

The circumstance of how sensitive therapeutic success is under imperfect adherence is driven by the property known as forgiveness. To date, no studies have considered variability in the pharmacokinetic-pharmacodynamic process in conjunction with imperfect adherence patterns in order to...

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Assawasuwannakit P, Braund R, Duffull SB. Quantification of the Forgiveness of Drugs to Imperfect Adherence. CPT Pharmacometrics Syst Pharmacol. 2015;4(3):e00004doi: 10.1002/psp4.4.
Assawasuwannakit, P., Braund, R., & Duffull, S. B. (2015). Quantification of the Forgiveness of Drugs to Imperfect Adherence. CPT: pharmacometrics & systems pharmacology, 4(3), e00004. https://doi.org/10.1002/psp4.4
Assawasuwannakit, P, et al. "Quantification of the Forgiveness of Drugs to Imperfect Adherence." CPT: pharmacometrics & systems pharmacology vol. 4,3 (2015): e00004. doi: https://doi.org/10.1002/psp4.4
Assawasuwannakit P, Braund R, Duffull SB. Quantification of the Forgiveness of Drugs to Imperfect Adherence. CPT Pharmacometrics Syst Pharmacol. 2015 Mar;4(3):e00004. doi: 10.1002/psp4.4. Epub 2015 Mar 04. PMID: 26225235; PMCID: PMC4394614.
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Showing 1 to 12 of 489 entries