Evidence map›Paper›PMID 33270249›Full record

ArticleClinical pharmacology and therapeutics2021

Physiologically-Based Pharmacokinetic Modeling in Renal and Hepatic Impairment Populations: A Pharmaceutical Industry Perspective.

Tycho Heimbach, Yuan Chen, Jun Chen, Vaishali Dixit, Neil Parrott, Sheila Annie Peters, Italo Poggesi, Pradeep Sharma, Jan Snoeys, Mohamad Shebley and 9 more

Abstract read
In one paragraph

Article in Clinical pharmacology and therapeutics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
73citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

73 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Trial
  4. Article
  5. Article
  6. Best Practices in Physiologically Based Pharmacokinetic (PBPK) Modeling.CPT: pharmacometrics & systems pharmacology · 2026
    Review
  7. Article
  8. Review
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
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  16. Article
  17. Advances in Cytotoxicity Testing: From In Vitro Assays to In Silico Models.International journal of molecular sciences · 2025
    Review
  18. Article
  19. Article
  20. Article

13 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors.

Tycho HeimbachPharmaceutical Sciences, Merck & Co., Inc, Rahway, New Jersey, USA.
Yuan ChenDepartment of Drug Metabolism and Pharmacokinetics, Genentech, Inc, South San Francisco, California, USA.
Jun ChenClinical Pharmacology, Alkermes Inc, Waltham, Massachusetts, USA.
Vaishali DixitDrug Metabolism and Pharmacokinetics, Kymera Therapeutics, Watertown, Massachusetts, USA.
Neil ParrottPharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Basel, Switzerland.
Sheila Annie PetersTranslational Medicine, Merck Healthcare KGaA, Darmstadt, Germany.
Italo PoggesiClinical Pharmacology and Pharmacometrics, Janssen, Milan, Italy.
Pradeep SharmaClinical Pharmacology & Quantitative Pharmacology, Clinical Pharmacology & Safety Sciences, R&D, AstraZeneca, Cambridge, UK.
Jan SnoeysDepartment of Drug Metabolism and Pharmacokinetics, Janssen R&D, Beerse, Belgium.
Mohamad ShebleyClinical Pharmacology and Pharmacometrics, AbbVie Inc, North Chicago, Illinois, USA.
Guoying TaiDepartment of Drug Metabolism and Pharmacokinetics, GlaxoSmithKline Plc, Collegeville, Pennsylvania, USA.
Susanna TseDepartment of Pharmacokinetics, Dynamics and Metabolism, Pfizer Inc, Groton, Connecticut, USA.
Vijay V UpretiClinical Pharmacology, Modeling & Simulation, Amgen Inc, South San Francisco, California, USA.
Ying-Hong WangDepartment of Pharmacokinetics, Pharmacodynamics, and Drug Metabolism, Merck & Co, Inc, Kenilworth, New Jersey, USA.
Alice TsaiDepartment of Drug Metabolism and Pharmacokinetics, Vertex Pharmaceuticals Inc, Boston, Massachusetts, USA.
Binfeng XiaPK/PD Group, Pharmacokinetics, Dynamics and Metabolism, Sanofi, Bridgewater, New Jersey, USA.
Ming ZhengClinical Pharmacology and Pharmacometrics, Bristol-Myers Squibb, Princeton, New Jersey, USA.
Andy Z X ZhuDrug Metabolism and Pharmacokinetics, Takeda Pharmaceuticals International, Co, Cambridge, Massachusetts, USA.
Stephen HallDepartment of Drug Disposition, Lilly, Indianapolis, Indiana, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The predictive performance of physiologically-based pharmacokinetics (PBPK) models for pharmacokinetics (PK) in renal impairment (RI) and hepatic impairment (HI) populations was evaluated using clinical data from 29 compounds with 106 organ impairment study arms were collected from 19 member companies of the International Consortium for Innovation and Quality in Pharmaceutical Development. Fifty RI and 56 HI study arms with varying degrees of organ insufficiency along with control populations were evaluated. For RI, the area under the curve (AUC) ratios of RI to healthy control were predicted within twofold of the observed ratios for > 90% (N = 47/50 arms). For HI, > 70% (N = 43/56 arms) of the hepatically impaired to healthy control AUC ratios were predicted within twofold. Inaccuracies, typically overestimation of AUC ratios, occurred more in moderate and severe HI. PBPK predictions can help determine the need and timing of organ impairment study. It may be suitable for predicting the impact of RI on PK of drugs predominantly cleared by metabolism with varying contribution of renal clearance. PBPK modeling may be used to support mild impairment study waivers or clinical study design.

Indexed as

Models, BiologicalPharmacokineticsArea Under CurveComputer SimulationDose-Response Relationship, DrugDrug IndustryHumansKidney DiseasesLiver DiseasesSeverity of Illness Index

Identifiers

PMID33270249
PMCPMC8359227

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.