A Mechanistic Systems Pharmacology Model for Prediction of LDL Cholesterol Lowering by PCSK9 Antagonism in Human Dyslipidemic Populations
Open accessAbstract
PCSK9 is a promising target for the treatment of hyperlipidemia and cardiovascular disease. A Quantitative Systems Pharmacology model of the mechanisms of action of statin and anti‐PCSK9 therapies was developed to predict low density lipoprotein (LDL) changes in response to anti‐PCSK9 mAb for different treatment protocols and patient subpopulations. Mechanistic interactions and cross‐regulation of LDL, LDL receptor, and PCSK9 were modeled, and numerous virtual subjects were developed and validated against clinical data. Simulations predict a slightly greater maximum percent reduction in LDL cholesterol (LDLc) when anti‐PCSK9 is administered on statin background therapy compared to as a monotherapy. The difference results primarily from higher PCSK9 levels in patients on statin background. However, higher PCSK9 levels are also predicted to increase clearance of anti‐PCSK9, resulting in a faster rebound of LDLc. Simulations of subjects with impaired LDL receptor (LDLR) function predict compromised anti‐PCSK9 responses in patients such as homozygous familial hypercholesterolemics, whose functional LDLR is below 10% of normal. CPT Pharmacometrics Syst. Pharmacol. (2014) 3, e149; doi:10.1038/psp.2014.47; published online 26 November 2014
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Nissen, S. E., Tuzcu, E. M., Schoenhagen, P., Brown, B. G., Ganz, P., Vogel, R. A., Crowe, T., Howard, G., Cooper, C. J., Brodie, B. R., et al. (2004) · JAMA · doi:10.1001/jama.291.9.1071 · Cited by 2,358 · see citing works
Horton, J. D., Shah, N. A., Warrington, J. A., Anderson, N. N., Park, S. W., Brown, M. S., & Goldstein, J. L. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1534923100 · Cited by 1,427 · see citing works
Cohen, J., Pertsemlidis, A., Kotowski, I. K., Graham, R., Garcia, C. K., & Hobbs, H. H. (2005) · Nature Genetics · doi:10.1038/ng1509 · Cited by 1,381 · see citing works
Universally Sloppy Parameter Sensitivities in Systems Biology Models
Gutenkunst, R. N., Waterfall, J. J., Casey, F. P., Brown, K. S., Myers, C. R., & Sethna, J. P. (2007) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0030189 · Cited by 1,261 · see citing works
Effect of a Monoclonal Antibody to PCSK9 on LDL Cholesterol
Stein, E. A., Mellis, S., Yancopoulos, G. D., Stahl, N., Logan, D., Smith, W. B., Lisbon, E., Gutierrez, M., Webb, C., Wu, R., et al. (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1105803 · Cited by 664 · see citing works
Molecular biology of PCSK9: its role in LDL metabolism
HORTON, J., COHEN, J., & HOBBS, H. (2007) · Trends in Biochemical Sciences · doi:10.1016/j.tibs.2006.12.008 · Cited by 621 · see citing works
Dubuc, G., Chamberland, A., Wassef, H., Davignon, J., Seidah, N. G., Bernier, L., & Prat, A. (2004) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/01.atv.0000134621.14315.43 · Cited by 614 · see citing works
General Pharmacokinetic Model for Drugs Exhibiting Target-Mediated Drug Disposition
Mager, D. E., & Jusko, W. J. (2001) · Journal of Pharmacokinetics and Pharmacodynamics · doi:10.1023/a:1014414520282 · Cited by 605 · see citing works
Stein, E. A., Gipe, D., Bergeron, J., Gaudet, D., Weiss, R., Dufour, R., Wu, R., & Pordy, R. C. (2012) · The Lancet · doi:10.1016/s0140-6736(12)60771-5 · Cited by 575 · see citing works
McKenney, J. M., Koren, M. J., Kereiakes, D. J., Hanotin, C., Ferrand, A.-C., & Stein, E. A. (2012) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2012.03.007 · Cited by 507 · see citing works
Raal, F. J., Scott, R. C., Somaratne, R. M., Bridges, I. M., Li, G., Wasserman, S. M., & Stein, E. A. (2012) · Circulation · doi:10.1161/circulationaha.112.144055 · Cited by 502 · see citing works
Atorvastatin with or without an Antibody to PCSK9 in Primary Hypercholesterolemia
Roth, E. M., McKenney, J. M., Hanotin, C., Asset, G., & Stein, E. A. (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1201832 · Cited by 459 · see citing works
Cromwell, W. C., Otvos, J. D., Keyes, M. J., Pencina, M. J., SULLIVAN, L. M., Vasan, R. S., Wilson, P. W. F., & D’Agostino, R. B. (2007) · Journal of clinical lipidology · doi:10.1016/j.jacl.2007.10.001 · Cited by 428 · see citing works
Giugliano, R. P., Desai, N. R., Kohli, P., Rogers, W. J., Somaratne, R. M., Huang, F., Liu, T., Mohanavelu, S., Hoffman, E. B., McDonald, S. T., et al. (2012) · The Lancet · doi:10.1016/s0140-6736(12)61770-x · Cited by 425 · see citing works
Atorvastatin increases human serum levels of proprotein convertase subtilisin/kexin type 9
Careskey, H. E., Davis, R., Alborn, W. E., Troutt, J. S., Cao, G., & Konrad, R. J. (2007) · Journal of Lipid Research · doi:10.1194/jlr.m700437-jlr200 · Cited by 313 · see citing works
Bosner, M. S., Lange, L. G., Stenson, W. F., & Ostlund, R. E. (1999) · Journal of Lipid Research · doi:10.1016/s0022-2275(20)33370-8 · Cited by 310 · see citing works
van der Graaf, P. H., & Benson, N. (2011) · Pharmaceutical Research · doi:10.1007/s11095-011-0467-9 · Cited by 248 · see citing works
Low-Density Lipoprotein Size and Cardiovascular Disease: A Reappraisal
Sacks, F. M., & Campos, H. (2003) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2003-030636 · Cited by 241 · see citing works
Leigh, S. E. A., Foster, A. H., Whittall, R., Hubbart, C., & Humphries, S. E. (2008) · Annals of Human Genetics · doi:10.1111/j.1469-1809.2008.00436.x · Cited by 236 · see citing works
Effects of AMG 145 on Low-Density Lipoprotein Cholesterol Levels
Dias, C. S., Shaywitz, A. J., Wasserman, S. M., Smith, B. P., Gao, B., Stolman, D., Crispino, C., Smirnakis, K. V., Emery, M. G., Colbert, A., et al. (2012) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2012.08.986 · Cited by 230 · see citing works
Plasma PCSK9 levels are significantly modified by statins and fibrates in humans
Mayne, J., Dewpura, T., Raymond, A., Cousins, M., Chaplin, A., Lahey, K. A., LaHaye, S. A., Mbikay, M., Ooi, T. C., & Chrétien, M. (2008) · Lipids in Health and Disease · doi:10.1186/1476-511x-7-22 · Cited by 216 · see citing works
A physiologically based mathematical model of integrated calcium homeostasis and bone remodeling
Peterson, M. C., & Riggs, M. M. (2010) · Bone · doi:10.1016/j.bone.2009.08.053 · Cited by 198 · see citing works
Osono, Y., Woollett, L. A., Herz, J., & Dietschy, J. M. (1995) · Journal of Clinical Investigation · doi:10.1172/jci117760 · Cited by 188 · see citing works
Statins as Potent Antiinflammatory Drugs
Lefer, D. J. (2002) · Circulation · doi:10.1161/01.cir.0000033635.42612.88 · Cited by 182 · see citing works
The formation of LDL: mechanisms and regulation
Havel, R. J. (1984) · Journal of Lipid Research · doi:10.1016/s0022-2275(20)34434-5 · Cited by 146 · see citing works
Raal, F. J., Panz, V. R., Immelman, A., & Pilcher, G. J. (2013) · Journal of the American Heart Association · doi:10.1161/jaha.112.000028 · Cited by 132 · see citing works
Kirouac, D. C., Du, J. Y., Lahdenranta, J., Overland, R. P., Yarar, D., Paragas, V. B., Pace, E. A., McDonagh, C. F., Nielsen, U. B., & Onsum, M. D. (2013) · Science Signaling · doi:10.1126/scisignal.2004008 · Cited by 105 · see citing works
A whole-body mathematical model of cholesterol metabolism and its age-associated dysregulation
Auley, M. T. M., Wilkinson, D. J., Jones, J. J., & Kirkwood, T. B. L. (2012) · BMC Systems Biology · doi:10.1186/1752-0509-6-130 · Cited by 102 · see citing works
Zhang, L., McCabe, T. J. D., Condra, J. H., Ni, Y. G., Peterson, L. B., Wang, W., Strack, A. M., Wang, F., Pandit, S., Hammond, H. A., et al. (2012) · International Journal of Biological Sciences · doi:10.7150/ijbs.3524 · Cited by 101 · see citing works
Stern, R. H., Yang, B., Hounslow, N. J., MacMahon, M., Abel, R. B., & Olson, S. C. (2000) · The Journal of Clinical Pharmacology · doi:10.1002/j.1552-4604.2000.tb05987.x · Cited by 82 · see citing works
Schmidt, B. J., Casey, F., Paterson, T. S., & Chan, J. R. (2013) · BMC Bioinformatics · doi:10.1186/1471-2105-14-221 · Cited by 73 · see citing works
Future of Cholesteryl Ester Transfer Protein (CETP) Inhibitors: A Pharmacological Perspective
Mohammadpour, A. H., & Akhlaghi, F. (2013) · Clinical Pharmacokinetics · doi:10.1007/s40262-013-0071-8 · Cited by 69 · see citing works
Sudhop, T., Reber, M., Tribble, D. L., Sapre, A., Taggart, W. V., Gibbons, P. H., Musliner, T., von Bergmann, K., & Lütjohann, D. (2009) · Journal of Lipid Research · doi:10.1194/jlr.p900004-jlr200 · Cited by 68 · see citing works
Chan, D. C., Lambert, G. C., Barrett, P. H. R., Rye, K., Ooi, E. M. M., & Watts, G. F. (2009) · Clinical Chemistry · doi:10.1373/clinchem.2009.128645 · Cited by 62 · see citing works
Shoda, L. K. M., Kreuwel, H. T. C., Gadkar, K. G., Zheng, Y., Whiting, C. C., Atkinson, M. A., Bluestone, J. A., Mathis, D. J., Young, D. L., & Ramanujan, S. (2010) · Clinical & Experimental Immunology · doi:10.1111/j.1365-2249.2010.04166.x · Cited by 56 · see citing works
Self-citationSystems biology for battling rheumatoid arthritis: Application of the Entelos PhysioLab platform
Rullmann, J. A. C., Struemper, H., Defranoux, N. A., Ramanujan, S., Meeuwisse, C. M., & van Elsas, A. (2005) · Systems Biology · doi:10.1049/ip-syb:20050053 · Cited by 56 · see citing works
Self-citationPCSK9: an emerging target for treatment of hypercholesterolemia
Duff, C. J., & Hooper, N. M. (2011) · Expert Opinion on Therapeutic Targets · doi:10.1517/14728222.2011.547480 · Cited by 50 · see citing works
Anti-PCSK9 therapies for the treatment of hypercholesterolemia
Hooper, A. J., & Burnett, J. R. (2012) · Expert Opinion on Biological Therapy · doi:10.1517/14712598.2012.748743 · Cited by 46 · see citing works
Cholesteryl ester transfer protein inhibition to reduce cardiovascular risk: where are we now?
Barter, P. J., & Rye, K. (2011) · Trends in Pharmacological Sciences · doi:10.1016/j.tips.2011.07.004 · Cited by 27 · see citing works
Tingley, W. G., Luca, D., Leabman, M. K., Budha, N. R., Kahn, R., Baruch, A., Cowan, K. J., & Davis, J. C. (2013) · European Heart Journal · doi:10.1093/eurheartj/eht309.p4183 · Cited by 8 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Clinical pharmacology considerations for the development of immune checkpoint inhibitors
Sheng, J., Srivastava, S., Sanghavi, K., Lu, Z., Schmidt, B. J., Bello, A., & Gupta, M. (2017) · The Journal of Clinical Pharmacology · doi:10.1002/jcph.990 · Cited by 124 · see citing works
Rieger, T. R., Allen, R. J., Bystricky, L., Chen, Y., Colopy, G. W., Cui, Y., Gonzalez, A., Liu, Y., White, R. D., Everett, R. A., et al. (2018) · Progress in Biophysics and Molecular Biology · doi:10.1016/j.pbiomolbio.2018.06.002 · Cited by 94 · see citing works
A Six‐Stage Workflow for Robust Application of Systems Pharmacology
Gadkar, K., Kirouac, D., Mager, D., van der Graaf, P., & Ramanujan, S. (2016) · CPT: Pharmacometrics & Systems Pharmacology · doi:10.1002/psp4.12071 · Cited by 93 · see citing works
Self-citationCheng, Y., Thalhauser, C. J., Smithline, S., Pagidala, J., Miladinov, M., Vezina, H. E., Gupta, M., Leil, T. A., & Schmidt, B. J. (2017) · The AAPS Journal · doi:10.1208/s12248-017-0100-x · Cited by 54 · see citing works
Kirouac, D. C., Cicali, B., & Schmidt, S. (2019) · CPT: Pharmacometrics & Systems Pharmacology · doi:10.1002/psp4.12390 · Cited by 46 · see citing works
“Of the 10 MATLAB-based models, the packages provided by Hasegawa and Duffull , 13 Kadidi et al. , 14 and Gadkar et al. 15 all contained “readme” text files describing the code and a single “run” script that loaded multiple files, executed simulations, and generated pharmacokinetic/pharmacodynamic time course figures f…”
Method
- Authors
- Gadkar, K., Budha, N., Baruch, A., Davis, J. D., Fielder, P., & Ramanujan, S.
- Affiliations
- Genentech (US)
- Corresponding author
- Ramanujan, S
- Venue
- CPT: Pharmacometrics & Systems Pharmacology
- Publisher
- Wiley
- Published
- 2014-11
- Volume
- 3
- Issue
- 11
- Pages
- 1-9
- ISSN
- 2163-8306 (ISSN-L)
- PMC
- PMC4260002
- OpenAlex
- W2068201983
- Cited by
- 48
- References
- 40
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 6 · 2023: 3 · 2022: 6 · 2021: 3 · 2020: 3 · 2019: 5 · 2018: 4 · 2017: 6 · 2016: 7 · 2015: 1
- FWCI
- 4.62
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- CPT Pharmacometrics & Systems Pharmacology (publishedVersion, cc-by-nc-nd)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Health Sciences › Medicine › Surgery › Lipoproteins and Cardiovascular Health
- Health Sciences › Medicine › Surgery › Cholesterol and Lipid Metabolism
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Lipid metabolism and disorders
- Keywords
- LDL cholesterol lowering, quantitative systems pharmacology, hyperlipidemia, statin combination therapy, anti-PCSK9 monoclonal antibodies, virtual subjects, familial hypercholesterolemia, dyslipidemia, cardiovascular disease
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review