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“Human genetics can provide compelling evidence of causation through approaches such as Mendelian randomization (MR).”
From Integrating genomics with biomarkers and therapeutic targets to invigorate cardiovascular drug development (2021) · cites this paper as [9]
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“Human genetics can provide a tool by which the causal role of an exposure (such as a complex phenotype and/or a drug target) can be characterized 9 .”
From Integrating genomics with biomarkers and therapeutic targets to invigorate cardiovascular drug development (2021) · cites this paper as [9]
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“Performed well, such studies called Mendelian randomization (MR) analyses, can provide rigorous evidence of causation 9,10 .”
From Integrating genomics with biomarkers and therapeutic targets to invigorate cardiovascular drug development (2021) · cites this paper as [9]
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“didates from phase I clinical trials to the initiation of late-stage development is below 10%, and the main reason for their failure is inadequate safety or efficacy.(179) Therefore, the establishment of”
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Peng, Y., Wang, M., Xu, Y., et al. (2020) · Briefings in Bioinformatics · doi:10.1093/bib/bbaa027 · Cited by 43
Microfluidic Liver-on-a-Chip for Preclinical Drug Discovery
Fu, J., Qiu, H., & Tan, C. S. (2023) · Pharmaceutics · doi:10.3390/pharmaceutics15041300 · Cited by 42
nach0: multimodal natural and chemical languages foundation model
Livne, M., Miftahutdinov, Z., Tutubalina, E. V., Kuznetsov, M., Polykovskiy, D. A., Brundyn, A., Jhunjhunwala, A., Costa, A. B., Aliper, A., Aspuru‐Guzik, A., et al. (2024) · Chemical Science · doi:10.1039/d4sc00966e · Cited by 61
“…for the biomedical domain, utilizing a variety of model families: for instance, researchers have developed BioBERT 17 , based on BERT with 110 million parameters, and SciFive, based on T5-base and T5-large with 220 and 770 million parameters respectively, using biomedical literature from PubMed.”
MethodSchuhmacher, A., Hinder, M., Brief, E., Gassmann, O., & Hartl, D. (2025) · Drug Discovery Today · doi:10.1016/j.drudis.2025.104291 · Cited by 47
Applications of Artificial Intelligence in Drug Design: Opportunities and Challenges
Thomas, M. C., Boardman, A., García-Ortegón, M., Yang, H., de Graaf, C., & Bender, A. (2021) · Methods in molecular biology · doi:10.1007/978-1-0716-1787-8_1 · Cited by 43
Cohen, B. M., Lehnherr, D., Sezen-Edmonds, M., et al. (2023) · Process Safety and Environmental Protection · doi:10.1016/j.cherd.2023.02.050 · Cited by 42
Creemers, J. H. A., Ankan, A., Roes, K. C. B., Schröder, G., Mehra, N., Figdor, C. G., de Vries, I. J. M., & Textor, J. C. (2023) · Nature Communications · doi:10.1038/s41467-023-37933-8 · Cited by 39
“%) ultimately obtain market approval 2 – 4 .”
Prodrug Approach as a Strategy to Enhance Drug Permeability
de Souza, M. M., Gini, A. L. R., Moura, J. A., Scarim, C. B., Chin, C. M., & dos Santos, J. L. (2025) · Pharmaceuticals · doi:10.3390/ph18030297 · Cited by 47
“Studies indicate that 9 out of 10 approved drugs fail in demonstrating efficacy and safety during various stages of development [2].”
Cell-Type-Specific High Throughput Toxicity Testing in Human Midbrain Organoids
Renner, H., Becker, K., Kagermeier, T., Grabos, M., Eliat, F., Günther, P. S., Schöler, H. R., & Bruder, J. M. (2021) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2021.715054 · Cited by 41
The rat as an animal model in chronic wound research: An update
Ghanbari, M., Salkovskiy, Y., & Carlson, M. A. (2024) · Life Sciences · doi:10.1016/j.lfs.2024.122783 · Cited by 52
Yıldırım, Z., Swanson, K., Wu, X., Zou, J., & Wu, J. C. (2024) · The Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev-pharmtox-022724-095035 · Cited by 40
Shamul, J. G., Wang, Z., Gong, H., Ou, W., White, A. M., Garcia, D. P. M., Gu, S., Clyne, A. M., Quiñones‐Hinojosa, A., & He, X. (2024) · Nature Biomedical Engineering · doi:10.1038/s41551-024-01250-2 · Cited by 43
“Animal models are currently used widely for preclinical testing of drug transport across the BBB and efficacy in the brain; however, better models are needed since ~92% of drug candidates that show success in animal models fail in clinical trials 98–100 .”
Meta-MolNet: A Cross-Domain Benchmark for Few Examples Drug Discovery
Lv, Q., Chen, G., Yang, Z., Zhong, W., & Chen, C. Y. (2024) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2024.3359657 · Cited by 42
“T HE discovery of new drugs is a system engineering with high investment, long cycle, and high risk [1], [2].”
Clinical trials in-a-dish for cardiovascular medicine
Wu, X., Swanson, K., Yıldırım, Z., Liu, W., Liao, R., & Wu, J. C. (2024) · European Heart Journal · doi:10.1093/eurheartj/ehae519 · Cited by 42
Metadata
- Authors
- Dowden, H., & Munro, J.
- Corresponding author
- Munro, Jamie
- Venue
- Nature Reviews Drug Discovery
- Published
- 2019-05-08
- Volume
- 18
- Issue
- 7
- Pages
- 495-496
- ISSN
- 1474-1776 (ISSN-L)
- 1474-1784
- OpenAlex
- W2944466104
- Cited by
- 649
- References
- 0
- Citations by year
- 2026: 101 · 2025: 129 · 2024: 140 · 2023: 114 · 2022: 57 · 2021: 57 · 2020: 43 · 2019: 7
- FWCI
- 39.38
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Nature Reviews Drug Discovery (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Science, Research, and Medicine
- Health Sciences › Medicine › Pharmacology (medical) › Historical Medical Research and Treatments
- Health Sciences › Medicine › Internal Medicine › General Medicine and Therapeutics
- Keywords
- clinical success rate, therapeutic focus, drug development, clinical trial results, therapeutic areas
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.
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