Academic Journal
View in EDS

Bridging the translational gap: an operational classification and quantitative framework for accelerating enteric vaccine research using animal models.

Bibliographic Details
Title: Bridging the translational gap: an operational classification and quantitative framework for accelerating enteric vaccine research using animal models.
Authors: Koley H; Division of Bacteriology, ICMR-National Institute for Research in Bacterial Infections, P-33 CIT Road, Scheme -XM, Beliaghata, Kolkata 700010, India. Electronic address: hemantakoley@hotmail.com., Mukherjee A; Division of Bacteriology, ICMR-National Institute for Research in Bacterial Infections, P-33 CIT Road, Scheme -XM, Beliaghata, Kolkata 700010, India., Mukhopadhyay AK; Division of Bacteriology, ICMR-National Institute for Research in Bacterial Infections, P-33 CIT Road, Scheme -XM, Beliaghata, Kolkata 700010, India., Das S; Division of Bacteriology, ICMR-National Institute for Research in Bacterial Infections, P-33 CIT Road, Scheme -XM, Beliaghata, Kolkata 700010, India., Howlader DR; Division of Bacteriology, ICMR-National Institute for Research in Bacterial Infections, P-33 CIT Road, Scheme -XM, Beliaghata, Kolkata 700010, India. Electronic address: debaki.r.howlader@gmail.com.
Source: Vaccine [Vaccine] 2026 Oct 24; Vol. 92, pp. 129167. Date of Electronic Publication: 2026 Sep 23.
Publication Type: Journal Article; Review
Language: English
Journal Info: Publisher: Elsevier Science Country of Publication: Netherlands NLM ID: 8406899 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-2518 (Electronic) Linking ISSN: 0264410X NLM ISO Abbreviation: Vaccine Subsets: MEDLINE
Imprint Name(s): Publication: Amsterdam, The Netherlands : Elsevier Science
Original Publication: [Guildford, Surrey, UK] : Butterworths, [c1983-
MeSH Terms: Vaccine Development*/methods , Disease Models, Animal* , Translational Research, Biomedical*, Dysentery, Bacillary/prevention & control ; Salmonella Infections/prevention & control ; Animals ; Humans ; Guinea Pigs ; Mice ; Rabbits ; Zebrafish
Abstract: Enteric bacterial infections, notably shigellosis and salmonellosis, represent a staggering global health burden. Vaccine development is severely hampered by host-restriction, creating a persistent "translational gap" where preclinical data fails to correlate with human outcomes. Traditionally, model selection has been largely qualitative. This review provides a comprehensive analysis of the research landscape, evaluating the physiological fidelity of non-human primates, the surgical precision of rabbit and guinea pig models, and specialized induced rodent systems, including the streptomycin‑iron-overload mouse model. We further discuss emerging alternatives, including translucent zebrafish for real-time imaging and Human Intestinal Enteroids (HIE) for human-specific mechanistic insights. Crucially, we move beyond qualitative descriptions by introducing the Model Utility Index (MUI), a novel quantitative framework designed to objectively balance Normalized Clinical Fidelity (F) against the Geometric Efficiency Quotient (E). By applying constrained optimization logic, we propose the Context-Specific Model Optimization (CSMO) selection matrix to simplify the logistical burden of model choice, focusing on the unique translational hurdles of host-restricted invasive pathogens such as Shigella and typhoidal Salmonella. This strategy aligns specific research bottlenecks - from high-throughput screening to final regulatory validation, with mathematically optimized research systems. In light of the FDA Modernization Act 2.0, this integrated approach provides a robust roadmap for utilizing New Approach Methodologies (NAMs) to de-risk clinical transitions and accelerate the licensure of next-generation enteric vaccines.
(Copyright © 2026 Elsevier Ltd. All rights reserved.)
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Contributed Indexing: Keywords: Animal models; Bacterial pathogenesis; Disease models; Enteric pathogens; Model utility index (MUI); Vaccine development
Entry Date(s): Date Created: 20260924 Date Completed: 20260927 Latest Revision: 20260927
Update Code: 20260928
DOI: 10.1016/j.vaccine.2026.129167
PMID: 42784864
Database: MEDLINE
FullText Text:
  Availability: 0
CustomLinks:
  – Url: https://www.doi.org/10.1016/j.vaccine.2026.129167?
    Name: ScienceDirect (all content) (s7799221)
    Category: fullText
    Text: View record from ScienceDirect
    MouseOverText: View record from ScienceDirect
  – Url: https://resolver.ebsco.com/c/fiv2js/result?sid=EBSCO:cmedm&genre=article&issn=18732518&ISBN=&volume=92&issue=&date=20261024&spage=129167&pages=129167&title=Vaccine&atitle=Bridging%20the%20translational%20gap%3A%20an%20operational%20classification%20and%20quantitative%20framework%20for%20accelerating%20enteric%20vaccine%20research%20using%20animal%20models.&aulast=Koley%20H&id=DOI:10.1016/j.vaccine.2026.129167
    Name: Full Text Finder (for New FTF UI) (ns324271)
    Category: fullText
    Text: Full Text Finder
    MouseOverText: Full Text Finder
Header DbId: cmedm
DbLabel: MEDLINE
An: 42784864
AccessLevel: 3
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Bridging the translational gap: an operational classification and quantitative framework for accelerating enteric vaccine research using animal models.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AU" term="%22Koley+H%22">Koley H</searchLink>; Division of Bacteriology, ICMR-National Institute for Research in Bacterial Infections, P-33 CIT Road, Scheme -XM, Beliaghata, Kolkata 700010, India. Electronic address: hemantakoley@hotmail.com.<br /><searchLink fieldCode="AU" term="%22Mukherjee+A%22">Mukherjee A</searchLink>; Division of Bacteriology, ICMR-National Institute for Research in Bacterial Infections, P-33 CIT Road, Scheme -XM, Beliaghata, Kolkata 700010, India.<br /><searchLink fieldCode="AU" term="%22Mukhopadhyay+AK%22">Mukhopadhyay AK</searchLink>; Division of Bacteriology, ICMR-National Institute for Research in Bacterial Infections, P-33 CIT Road, Scheme -XM, Beliaghata, Kolkata 700010, India.<br /><searchLink fieldCode="AU" term="%22Das+S%22">Das S</searchLink>; Division of Bacteriology, ICMR-National Institute for Research in Bacterial Infections, P-33 CIT Road, Scheme -XM, Beliaghata, Kolkata 700010, India.<br /><searchLink fieldCode="AU" term="%22Howlader+DR%22">Howlader DR</searchLink>; Division of Bacteriology, ICMR-National Institute for Research in Bacterial Infections, P-33 CIT Road, Scheme -XM, Beliaghata, Kolkata 700010, India. Electronic address: debaki.r.howlader@gmail.com.
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%228406899%22">Vaccine</searchLink> [Vaccine] 2026 Oct 24; Vol. 92, pp. 129167. <i>Date of Electronic Publication: </i>2026 Sep 23.
– Name: TypePub
  Label: Publication Type
  Group: TypPub
  Data: Journal Article; Review
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: TitleSource
  Label: Journal Info
  Group: Src
  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Elsevier+Science%22">Elsevier Science </searchLink><i>Country of Publication: </i>Netherlands <i>NLM ID: </i>8406899 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1873-2518 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%220264410X%22">0264410X </searchLink><i>NLM ISO Abbreviation: </i>Vaccine <i>Subsets: </i>MEDLINE
– Name: PublisherInfo
  Label: Imprint Name(s)
  Group: PubInfo
  Data: <i>Publication</i>: Amsterdam, The Netherlands : Elsevier Science<br /><i>Original Publication</i>: [Guildford, Surrey, UK] : Butterworths, [c1983-
– Name: SubjectMESH
  Label: MeSH Terms
  Group: Su
  Data: <searchLink fieldCode="MM" term="%22Vaccine+Development%22">Vaccine Development*</searchLink>/<searchLink fieldCode="MM" term="%22Vaccine+Development+methods%22">methods</searchLink> <br /><searchLink fieldCode="MM" term="%22Disease+Models%2C+Animal%22">Disease Models, Animal*</searchLink> <br /><searchLink fieldCode="MM" term="%22Translational+Research%2C+Biomedical%22">Translational Research, Biomedical*</searchLink><br /><searchLink fieldCode="MH" term="%22Dysentery%2C+Bacillary%22">Dysentery, Bacillary</searchLink>/<searchLink fieldCode="MH" term="%22Dysentery%2C+Bacillary+prevention+%26+control%22">prevention & control</searchLink> ; <searchLink fieldCode="MH" term="%22Salmonella+Infections%22">Salmonella Infections</searchLink>/<searchLink fieldCode="MH" term="%22Salmonella+Infections+prevention+%26+control%22">prevention & control</searchLink> ; <searchLink fieldCode="MH" term="%22Animals%22">Animals</searchLink> ; <searchLink fieldCode="MH" term="%22Humans%22">Humans</searchLink> ; <searchLink fieldCode="MH" term="%22Guinea+Pigs%22">Guinea Pigs</searchLink> ; <searchLink fieldCode="MH" term="%22Mice%22">Mice</searchLink> ; <searchLink fieldCode="MH" term="%22Rabbits%22">Rabbits</searchLink> ; <searchLink fieldCode="MH" term="%22Zebrafish%22">Zebrafish</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Enteric bacterial infections, notably shigellosis and salmonellosis, represent a staggering global health burden. Vaccine development is severely hampered by host-restriction, creating a persistent "translational gap" where preclinical data fails to correlate with human outcomes. Traditionally, model selection has been largely qualitative. This review provides a comprehensive analysis of the research landscape, evaluating the physiological fidelity of non-human primates, the surgical precision of rabbit and guinea pig models, and specialized induced rodent systems, including the streptomycin‑iron-overload mouse model. We further discuss emerging alternatives, including translucent zebrafish for real-time imaging and Human Intestinal Enteroids (HIE) for human-specific mechanistic insights. Crucially, we move beyond qualitative descriptions by introducing the Model Utility Index (MUI), a novel quantitative framework designed to objectively balance Normalized Clinical Fidelity (F) against the Geometric Efficiency Quotient (E). By applying constrained optimization logic, we propose the Context-Specific Model Optimization (CSMO) selection matrix to simplify the logistical burden of model choice, focusing on the unique translational hurdles of host-restricted invasive pathogens such as Shigella and typhoidal Salmonella. This strategy aligns specific research bottlenecks - from high-throughput screening to final regulatory validation, with mathematically optimized research systems. In light of the FDA Modernization Act 2.0, this integrated approach provides a robust roadmap for utilizing New Approach Methodologies (NAMs) to de-risk clinical transitions and accelerate the licensure of next-generation enteric vaccines.<br /> (Copyright © 2026 Elsevier Ltd. All rights reserved.)
– Name: Abstract
  Label: Competing Interests
  Group: Ab
  Data: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
– Name: SubjectMinor
  Label: Contributed Indexing
  Group:
  Data: <i>Keywords: </i>Animal models; Bacterial pathogenesis; Disease models; Enteric pathogens; Model utility index (MUI); Vaccine development
– Name: DateEntry
  Label: Entry Date(s)
  Group: Date
  Data: <i>Date Created: </i>20260924 <i>Date Completed: </i>20260927 <i>Latest Revision: </i>20260927
– Name: DateUpdate
  Label: Update Code
  Group: Date
  Data: 20260928
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1016/j.vaccine.2026.129167
– Name: AN
  Label: PMID
  Group: ID
  Data: 42784864
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=cmedm&AN=42784864
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.vaccine.2026.129167
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        StartPage: 129167
    Subjects:
      – SubjectFull: Dysentery, Bacillary prevention & control
        Type: general
      – SubjectFull: Salmonella Infections prevention & control
        Type: general
      – SubjectFull: Animals
        Type: general
      – SubjectFull: Humans
        Type: general
      – SubjectFull: Guinea Pigs
        Type: general
      – SubjectFull: Mice
        Type: general
      – SubjectFull: Rabbits
        Type: general
      – SubjectFull: Zebrafish
        Type: general
      – SubjectFull: Vaccine Development methods
        Type: general
      – SubjectFull: Disease Models, Animal
        Type: general
      – SubjectFull: Translational Research, Biomedical
        Type: general
    Titles:
      – TitleFull: Bridging the translational gap: an operational classification and quantitative framework for accelerating enteric vaccine research using animal models.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Koley H
      – PersonEntity:
          Name:
            NameFull: Mukherjee A
      – PersonEntity:
          Name:
            NameFull: Mukhopadhyay AK
      – PersonEntity:
          Name:
            NameFull: Das S
      – PersonEntity:
          Name:
            NameFull: Howlader DR
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 24
              M: 10
              Text: 2026 Oct 24
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-electronic
              Value: 1873-2518
          Numbering:
            – Type: volume
              Value: 92
          Titles:
            – TitleFull: Vaccine
              Type: main
ResultId 1