Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 6

The DOI matches its Crossref record; the references it cites are not checked yet.

An Analytic Investigation of the Drug Formulation-Based Recalls in the USA: See More Beyond the Literal

Yang, Mian, Byrn, Stephen R., Clase, Kari L.·2020·AAPS PharmSciTech
DOI 10.1208/s12249-020-01726-9
Open this paper in CoChat — free account

Overview

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1208/s12249-020-01726-9

Cites

Statistics

Verification

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.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

The citation lists haven’t been fetched yet

Cited by 6

Research works printed but not linked: 35

  1. Food and Drug Administration. Benefit-risk assessment in drug regulatory decision making. Draft PDUFA VI Implementation Plan. FY2018–2022. Washington, DC: Food and Drug Administration; 2018.
  2. Lawrence XY, Woodcock J. FDA pharmaceutical quality oversight. Int J Pharm. 2015;491(1–2):2–7.
  3. Feldmesser M. Fungal disease following contaminated steroid injections: exserohilum is ready for its close-up. Am J Pathol. 2013;183(3):661–4. · doi:10.1016/j.ajpath.2013.06.010
  4. Jarrell G, Peltzman S. The impact of product recalls on the wealth of sellers. J Polit Econ. 1985;93(3):512–36. · DOI · Paper page
  5. Davidson WN III, Worrell DL. Research notes and communications: the effect of product recall announcements on shareholder wealth. Strateg Manag J. 1992;13(6):467–73. · DOI · Paper page
  6. Hörner J. Reputation and competition. Am Econ Rev. 2002 Jun;92(3):644–63. · DOI · Paper page
  7. Ball G, Macher JT, Stern AD. Recalls, innovation, and competitor response: evidence from medical device firms. In:Harvard Business School Working Paper; 2018 Sep. p. 19–028.
  8. Ball GP, Shah R, Donohue K. The decision to recall: a behavioral investigation in the medical device industry. J Oper Manag. 2018;62:1–5. · DOI
  9. Mukherjee UK, Sinha KK. Product recall decisions in medical device supply chains: a big data analytic approach to evaluating judgment bias. Prod Oper Manag. 2018;27(10):1816–33. · DOI
  10. Ball G, Siemsen E, Shah R. Do plant inspections predict future quality? The role of investigator experience. Manuf Serv Oper Manag. 2017;19(4):534–50. · DOI
  11. Yom-Tov E. Predicting drug recalls from internet search engine queries. IEEE J Transl Eng Health Med. 2017;5:1–6. · DOI
  12. Sun D, Hu M, Browning M, Friedman RL, Jiang W, Zhao L, et al. Dissolution failure of solid oral drug products in field alert reports. J Pharm Sci. 2017;106(5):1302–9. · DOI
  13. Škalko-Basnet N. Biologics: the role of delivery systems in improved therapy. Biol Targets Ther. 2014;8:107. · DOI
  14. Shire SJ. Formulation and manufacturability of biologics. Curr Opin Biotechnol. 2009;20(6):708–14. · DOI · Paper page
  15. Morales JO, Fathe KR, Brunaugh A, Ferrati S, Li S, Montenegro-Nicolini M, et al. Challenges and future prospects for the delivery of biologics: oral mucosal, pulmonary, and transdermal routes. AAPS J. 2017;19(3):652–68. · DOI
  16. Snodin DJ, Elder DP. Short commentary on NDMA (N-nitrosodimethylamine) contamination of valsartan products. Regul Toxicol Pharmacol. 2019;103:325–9. · doi:10.1016/j.yrtph.2019.01.007
  17. SAS Institute. SAS user's guide: statistics. Sas Inst; 1985.
  18. Games PA, Howell JF. Pairwise multiple comparison procedures with unequal n’s and/or variances: a Monte Carlo study. J Educ Stat. 1976;1(2):113–25.
  19. Wang X. Firth logistic regression for rare variant association tests. Front Genet. 2014;5:187.
  20. Halsey LG, Curran-Everett D, Vowler SL, Drummond GB. The fickle P value generates irreproducible results. Nat Methods. 2015;12(3):179–85. · DOI · Paper page
  21. McCullagh P. On the asymptotic distribution of Pearson's statistic in linear exponential-family models. Int Stat Rev Revue Internationale de Statistique. 1985;1:61–7.
  22. Hogerzeil HV, Walker GJ. Instability of (methyl) ergometrine in tropical climates: an overview. Eur J Obstet Gynecol Reprod Biol. 1996;69(1):25–9. · doi:10.1016/0301-2115(95)02530-8
  23. Denyer SP, Guy RH, Hadgraft J, Hugo WB. The microbial degradation of topically applied drugs. Int J Pharm. 1985;26(1–2):89–97. · doi:10.1016/0378-5173(85)90202-9
  24. Florence AT, Attwood D. Physicochemical principles of pharmacy: in manufacture, formulation and clinical use. London: Pharmaceutical press; 2015.
  25. Smith BT. Remington education: physical pharmacy. London: Pharmaceutical Press; 2015.
  26. Tadros TF. Physical stability of suspension concentrates. Adv Colloid Interf Sci. 1980;12(2–3):141–261. · doi:10.1016/0001-8686(80)85006-8
  27. Wilson RG, Ecanow B. Powdered particle interactions: suspension flocculation and caking I. J Pharm Sci. 1963;52(8):757–62. · doi:10.1002/jps.2600520810
  28. Wheless JW, Phelps SJ. A Clinician's guide to oral extended-release drug delivery systems in epilepsy. J Pediatr Pharmacol Ther. 2018;23(4):277–92.
  29. Al-Jazairi AS, Blhareth S, Eqtefan IS, Al-Suwayeh SA. Brand and generic medications: are they interchangeable? Ann Saudi Med. 2008;28(1):33–41.
  30. Kleinbaum DG, Dietz K, Gail M, Klein M, Klein M. Logistic regression. New York: Springer-Verlag; 2002.
  31. Jain KK. Investigation and management of loss of efficacy of an antiepileptic medication using carbamazepine as an example. J R Soc Med. 1993;86(3):133. · doi:10.1177/014107689308600305
  32. Al Ameri MN, Nayuni N, Kumar KA, Perrett D, Tucker A, Johnston A. The differences between the branded and generic medicines using solid dosage forms: in-vitro dissolution testing. Results Pharm Sci. 2012;2:1–8. · DOI
  33. Fathima N, Mamatha T, Qureshi HK, Anitha N, Rao JV. Drug-excipient interaction and its importance in dosage form development. J Appl Pharm Sci. 2011;1(06):66–71.
  34. Narang AS, Rao VM, Raghavan KS. Excipient compatibility. In:developing solid oral dosage forms; 2009. p. 125–45. · doi:10.1016/b978-0-444-53242-8.00006-0
  35. Badawy SI. Handbook of Pharmaceutical Wet Granulation; 2019. p. 173–202. · doi:10.1016/b978-0-12-810460-6.00014-2

Metadata

Authors
Yang, M., Byrn, S. R., & Clase, K. L.
Venue
AAPS PharmSciTech
Publisher
Springer Science and Business Media LLC
Published
2020-07
Volume
21
Issue
5
ISSN
1530-9932
DOI
10.1208/s12249-020-01726-9
Cited by
6
Language
en
Licence

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

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: An Analytic Investigation of the Drug Formulation-Based Recalls in the USA: See More Beyond the Literal. https://app.cochat.ai/papers/10.1208/s12249-020-01726-9
The paper
Yang, M., Byrn, S. R., & Clase, K. L. (2020). An Analytic Investigation of the Drug Formulation-Based Recalls in the USA: See More Beyond the Literal. AAPS PharmSciTech. https://doi.org/10.1208/s12249-020-01726-9

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.