Harnessing the predictive power of preclinical models for oncology drug development
Abstract
Recent progress in understanding the molecular basis of cellular processes, identification of promising therapeutic targets and evolution of the regulatory landscape makes this an exciting and unprecedented time to be in the field of oncology drug development. However, high costs, long development timelines and steep rates of attrition continue to afflict the drug development process. Lack of predictive preclinical models is considered one of the key reasons for the high rate of attrition in oncology. Generating meaningful and predictive results preclinically requires a firm grasp of the relevant biological questions and alignment of the model systems that mirror the patient context. In doing so, the ability to conduct both forward translation, the process of implementing basic research discoveries into practice, as well as reverse translation, the process of elucidating the mechanistic basis of clinical observations, greatly enhances our ability to develop effective anticancer treatments. In this Review, we outline issues in preclinical-to-clinical translatability of molecularly targeted cancer therapies, present concepts and examples of successful reverse translation, and highlight the need to better align tumour biology in patients with preclinical model systems including tracking of strengths and weaknesses of preclinical models throughout programme development.
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Culture conditions can select specific clones, potentially altering or reducing clonality over time.
“In addition to this topographical issue, culture conditions can contribute to selecting specific clones, possibly altering or reducing clonality over time129.”
From Organoids (2022) · cites this paper as [129]
Evidence is mixed on whether molecular characteristics are maintained over long-term culture, with some studies reporting maintenance and others observing tumor evolution after serial passaging.
“While some studies have reported that molecular characteristics can be maintained over long-term culture, others have observed tumor evolution after serial passaging129,132.”
From Organoids (2022) · cites this paper as [129]
RNAseq has shown that organoids have gene expression profiles similar to the tumors from which they were established across many tumor types, including bladder and esophageal cancer.
“This has been shown by RNAseq on many tumor types including bladder cancer128 and esophageal cancer129 amongst others.”
From Organoids (2022) · cites this paper as [129]
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- Authors
- Honkala, A., Malhotra, S. V., Kummar, S., & Junttila, M. R.
- Affiliations
- Oregon Health & Science University (US)
- ORIC Pharmaceuticals, Inc. (United States) (US)
- Corresponding author
- Kummar, Shivaani
- Junttila, Melissa R.
- Venue
- Nature Reviews Drug Discovery
- Published
- 2021-10-26
- Volume
- 21
- Issue
- 2
- Pages
- 99-114
- ISSN
- 1474-1776 (ISSN-L)
- 1474-1784
- OpenAlex
- W3210942885
- Cited by
- 121
- References
- 166
- Citations by year
- 2026: 30 · 2025: 31 · 2024: 20 · 2023: 23 · 2022: 16 · 2021: 1
- FWCI
- 2.97
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Nature Reviews Drug Discovery (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Veterinary › Small Animals › Animal testing and alternatives
- Health Sciences › Medicine › Oncology › Cancer Cells and Metastasis
- Health Sciences › Medicine › Reproductive Medicine › Science, Research, and Medicine
- Keywords
- anticancer drug development, preclinical models, prediction model, translational research, forward translation, reverse translation, molecularly targeted cancer therapy, drug attrition, tumor biology
- MeSH terms
- Drug Development, Animals, Antineoplastic Agents, Drug Evaluation, Preclinical, Humans, Neoplasms, Biomarkers, Tumor, Molecular Targeted Therapy
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 ›
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