Predictive Preclinical Modeling

Predictive Preclinical Modeling is a formal scientific framework that systematically integrates reverse translation principles to extrapolate clinical outcomes from preclinical data, distinguished by its emphasis on bidirectional validation between therapeutic efficacy in human trials and underlying biological mechanisms observed in animal or in vitro models.

43

Publications

2.8K

Citations

343

Authors

168

Institutions

Publications per year

2017–2026

24

Authors

343

  1. WN
    William Nguyen

    Stanford University, United States

    2 publications · 103 citations

    2

    h-index

  2. AG
    Andre Ghetti

    AnaBios (United States), United States

    2 publications · 103 citations

    2

    h-index

  3. NA
    Najah Abi‐Gerges

    AstraZeneca (United Kingdom), United Kingdom

    2 publications · 103 citations

    2

    h-index

  4. PE
    Paul E. Miller

    AnaBios (United States), United States

    2 publications · 103 citations

    2

    h-index

  5. NN
    Nathalie Nguyen

    San Diego State University, United States

    2 publications · 103 citations

    2

    h-index

1–5 of 343

Venues

  1. Scientific Reports

    3 publications · 181 citations

    3

    h-index

  2. PubMed

    Repository · 3 publications · 170 citations

    3

    h-index

  3. Cancers

    3 publications · 111 citations

    3

    h-index

  4. Frontiers in Pharmacology

    2 publications · 27 citations

    2

    h-index

  5. Clinical Pharmacokinetics

    1 publications · 10 citations

    1

    h-index

1–5