Definition and research guide
This page combines a MeSH definition, publication statistics and selected research abstracts. It is a starting point for reading the literature, not a medical textbook or a systematic evidence review.
Content available: 4 complete abstracts (648 words), 10 references. Full article text is not stored or reproduced here; follow the PMID, DOI or PMC links to read the original sources and their access terms.
Definition
Any process by which toxicity, metabolism, absorption, elimination, preferred route of administration, safe dosage range, etc., for a drug or group of drugs is determined through clinical assessment in humans or veterinary animals.
Definition: NLM Medical Subject Headings (MeSH) scope note (Public domain (U.S. National Library of Medicine); attribution requested). View the MeSH record.
Also known as: Drug Evaluations; Evaluation, Drug; Evaluations, Drug; Drug Evaluation Studies; Drug Evaluation Study; Evaluation Study, Drug; Studies, Drug Evaluation; Study, Drug Evaluation.
Where it fits in the MeSH classification
- Broader topics
- Drug Development; Evaluation Studies as Topic
- See also
- Clinical Trials as Topic
Research landscape
PubMed indexes 42,092 records tagged with the MeSH heading “Drug Evaluation” (counts retrieved 2026-10-29). 207 of them (0.5%) were published from 2020 onward, and the busiest period so far is through 1999 with 37,420 records.
Reviews account for 3,122 records (7.4%) and meta-analyses for 64. Randomized controlled trials number 3,388 (8.0%) as a share of all records on the topic. Randomized trials make up a comparatively large share of this literature, which means many treatment questions have been tested directly.
Show the data
| Period | Records |
|---|---|
| through 1999 | 37,420 |
| 2000-2009 | 3,082 |
| 2010-2019 | 1,383 |
| 2020 onward | 207 |
Publication-type chart data
| Type | Records | Share |
|---|---|---|
| Reviews | 3,122 | 7.4% |
| Meta-analyses | 64 | 0.2% |
| Randomized controlled trials | 3,388 | 8.0% |
Method: PubMed query "Drug Evaluation"[MeSH Terms] with publication-type and date filters, retrieved 2026-10-29.
Reading the evidence in clinical research
Research methods determine how much a result can be trusted. Randomized trials guard against confounding, systematic reviews and meta-analyses combine many studies, and observational designs are valuable but can show only association. Reporting standards, trial registration and pre-specified outcomes reduce bias. When reading about a method, ask what problem it is designed to solve and which problems it does not solve.
Evidence from open-access studies
These open-access studies come from PubMed’s best-match results for this heading (papers whose main topic it is), ranked here by citation count, with one recent addition. Each abstract is reproduced in full under its recorded open licence so that you can read the authors’ own words. They illustrate the literature; they are not a systematic summary of it. Citation counts measure attention, not reliability or clinical benefit.
| Study / authors | Year | Source label / design | Europe PMC citations | Licence / source |
|---|---|---|---|---|
| Design and analysis of randomized clinical trials requiring prolonged observation of each patient. II. analysis and examples | 1977 | Research article Design not recorded in structured metadata | 5,605 | cc by PMID 831755 · DOI · PMC2025310 |
| Advances in establishment and analysis of three-dimensional tumor spheroid-based functional assays for target validation and drug evaluation | 2012 | Research article Design not recorded in structured metadata | 783 | cc by PMID 22439642 · DOI · PMC3349530 |
| The value of plants used in traditional medicine for drug discovery | 2001 | Review article Design not recorded in structured metadata | 668 | cc by PMID 11250806 · DOI · PMC1240543 |
| Evaluating the performance of drug-repurposing technologies | 2022 | Review article Design not recorded in structured metadata | 43 | cc by PMID 34400352 · DOI · PMC10014214 |
Design and analysis of randomized clinical trials requiring prolonged observation of each patient. II. analysis and examples [1]
Abstract reading summary — source excerpts
- Opening excerpt
- Part I of this report appeared in the previous issue (Br.
- Closing excerpt
- It is intended to enable physicians without statistical training either to analyse such data themselves using life tables, the logrank test and retrospective stratification, or, when such analyses are presented, to appreciate them more critically, but the discussion may also be of interest to statisticians who have not yet specialized in clinical trial analyses.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (114 words)
Part I of this report appeared in the previous issue (Br. J. Cancer (1976) 34,585), and discussed the design of randomized clinical trials. Part II now describes efficient methods of analysis of randomized clinical trials in which we wish to compare the duration of survival (or the time until some other untoward event first occurs) among different groups of patients. It is intended to enable physicians without statistical training either to analyse such data themselves using life tables, the logrank test and retrospective stratification, or, when such analyses are presented, to appreciate them more critically, but the discussion may also be of interest to statisticians who have not yet specialized in clinical trial analyses.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 831755 · DOI · PMC2025310
Advances in establishment and analysis of three-dimensional tumor spheroid-based functional assays for target validation and drug evaluation [2]
Abstract reading summary — source excerpts
- Opening excerpt
- BackgroundThere is overwhelming evidence that in vitro three-dimensional tumor cell cultures more accurately reflect the complex in vivo microenvironment than simple two-dimensional cell monolayers, not least with respect to gene expression profiles, signaling pathway activity and drug sensitivity.
- Closing excerpt
- We believe these assays will increase the translational predictive value of in vitro drug evaluation studies and reduce the need for in vivo studies by more effective triaging of compounds.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (301 words)
BackgroundThere is overwhelming evidence that in vitro three-dimensional tumor cell cultures more accurately reflect the complex in vivo microenvironment than simple two-dimensional cell monolayers, not least with respect to gene expression profiles, signaling pathway activity and drug sensitivity. However, most currently available three-dimensional techniques are time consuming and/or lack reproducibility; thus standardized and rapid protocols are urgently needed.ResultsTo address this requirement, we have developed a versatile toolkit of reproducible three-dimensional tumor spheroid models for dynamic, automated, quantitative imaging and analysis that are compatible with routine high-throughput preclinical studies. Not only do these microplate methods measure three-dimensional tumor growth, but they have also been significantly enhanced to facilitate a range of functional assays exemplifying additional key hallmarks of cancer, namely cell motility and matrix invasion. Moreover, mutual tissue invasion and angiogenesis is accommodated by coculturing tumor spheroids with murine embryoid bodies within which angiogenic differentiation occurs. Highly malignant human tumor cells were selected to exemplify therapeutic effects of three specific molecularly-targeted agents: PI-103 (phosphatidylinositol-3-kinase (PI3K)-mammalian target of rapamycin (mTOR) inhibitor), 17-N-allylamino-17-demethoxygeldanamycin (17-AAG) (heat shock protein 90 (HSP90) inhibitor) and CCT130234 (in-house phospholipase C (PLC)γ inhibitor). Fully automated analysis using a Celigo cytometer was validated for tumor spheroid growth and invasion against standard image analysis techniques, with excellent reproducibility and significantly increased throughput. In addition, we discovered key differential sensitivities to targeted agents between two-dimensional and three-dimensional cultures, and also demonstrated enhanced potency of some agents against cell migration/invasion compared with proliferation, suggesting their preferential utility in metastatic disease.ConclusionsWe have established and validated a suite of highly reproducible tumor microplate three-dimensional functional assays to enhance the biological relevance of early preclinical cancer studies. We believe these assays will increase the translational predictive value of in vitro drug evaluation studies and reduce the need for in vivo studies by more effective triaging of compounds.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 22439642 · DOI · PMC3349530
The value of plants used in traditional medicine for drug discovery [3]
Abstract reading summary — source excerpts
- Opening excerpt
- In this review we describe and discuss several approaches to selecting higher plants as candidates for drug development with the greatest possibility of success.
- Closing excerpt
- We identify and discuss advantages and disadvantages of using plants as starting points for drug development, specifically those used in traditional medicine.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (113 words)
In this review we describe and discuss several approaches to selecting higher plants as candidates for drug development with the greatest possibility of success. We emphasize the role of information derived from various systems of traditional medicine (ethnomedicine) and its utility for drug discovery purposes. We have identified 122 compounds of defined structure, obtained from only 94 species of plants, that are used globally as drugs and demonstrate that 80% of these have had an ethnomedical use identical or related to the current use of the active elements of the plant. We identify and discuss advantages and disadvantages of using plants as starting points for drug development, specifically those used in traditional medicine.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 11250806 · DOI · PMC1240543
Evaluating the performance of drug-repurposing technologies [4]
Abstract reading summary — source excerpts
- Opening excerpt
- Drug-repurposing technologies are growing in number and maturing.
- Closing excerpt
- Understanding and using different performance evaluation metrics ensures robust cross-platform comparability, enabling us to continue to strive toward optimal repurposing by decreasing the time and cost of drug discovery and development.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (120 words)
Drug-repurposing technologies are growing in number and maturing. However, comparisons to each other and to reality are hindered because of a lack of consensus with respect to performance evaluation. Such comparability is necessary to determine scientific merit and to ensure that only meaningful predictions from repurposing technologies carry through to further validation and eventual patient use. Here, we review and compare performance evaluation measures for these technologies using version 2 of our shotgun repurposing Computational Analysis of Novel Drug Opportunities (CANDO) platform to illustrate their benefits, drawbacks, and limitations. Understanding and using different performance evaluation metrics ensures robust cross-platform comparability, enabling us to continue to strive toward optimal repurposing by decreasing the time and cost of drug discovery and development.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 34400352 · DOI · PMC10014214
Key reviews and meta-analyses
The most cited review-type papers among PubMed’s best-match results for this heading, listed with bibliographic details only. Follow the links for the full text and access terms.
- Research article Opioids in chronic non-cancer pain: systematic review of efficacy and safety [5]
- Research article Assessment of health-related quality of life in children: a review of conceptual, methodological, and regulatory issues [6]
- Research article Three-dimensional in vitro tumor models for cancer research and drug evaluation [7]
- Research article Neurotrophins: from enthusiastic expectations through sobering experiences to rational therapeutic approaches [8]
- Research article Investigational nanomedicines in 2016: a review of nanotherapeutics currently undergoing clinical trials [9]
- Research article Clinical trial designs for cytostatic agents: are new approaches needed? [10]
References
- Peto R, Pike MC, Armitage P, Breslow NE, Cox DR, Howard SV, et al.. Design and analysis of randomized clinical trials requiring prolonged observation of each patient. II. analysis and examples. . 1977. PMID 831755 · DOI · PMC2025310
- Vinci M, Gowan S, Boxall F, Patterson L, Zimmermann M, Court W, et al.. Advances in establishment and analysis of three-dimensional tumor spheroid-based functional assays for target validation and drug evaluation. . 2012. PMID 22439642 · DOI · PMC3349530
- Fabricant DS, Farnsworth NR. The value of plants used in traditional medicine for drug discovery. . 2001. PMID 11250806 · DOI · PMC1240543
- Schuler J, Falls Z, Mangione W, Hudson ML, Bruggemann L, Samudrala R. Evaluating the performance of drug-repurposing technologies. . 2022. PMID 34400352 · DOI · PMC10014214
- Kalso E, Edwards JE, Moore AR, McQuay HJ. Opioids in chronic non-cancer pain: systematic review of efficacy and safety. Pain. 2004. PMID 15561393 · DOI
- Matza LS, Swensen AR, Flood EM, Secnik K, Leidy NK. Assessment of health-related quality of life in children: a review of conceptual, methodological, and regulatory issues. Value Health. 2004. PMID 14720133 · DOI
- Xu X, Farach-Carson MC, Jia X. Three-dimensional in vitro tumor models for cancer research and drug evaluation. Biotechnol Adv. 2014. PMID 25116894 · DOI · PMC4171250
- Thoenen H, Sendtner M. Neurotrophins: from enthusiastic expectations through sobering experiences to rational therapeutic approaches. Nat Neurosci. 2002. PMID 12403983 · DOI
- Caster JM, Patel AN, Zhang T, Wang A. Investigational nanomedicines in 2016: a review of nanotherapeutics currently undergoing clinical trials. Wiley Interdiscip Rev Nanomed Nanobiotechnol. 2017. PMID 27312983 · DOI
- Korn EL, Arbuck SG, Pluda JM, Simon R, Kaplan RS, Christian MC. Clinical trial designs for cytostatic agents: are new approaches needed?. J Clin Oncol. 2001. PMID 11134222 · DOI
About this article
- Sources
- NLM Medical Subject Headings (definition, synonyms); NCBI PubMed (counts, identifiers); Europe PMC (open-access abstracts and citation counts).
- Verification
- Every reference was resolved against PubMed on 2026-10-31; title, year and DOI matched.
- Review state
- automated source verified; no human expert review has been recorded yet.
- Version
- 1, last updated 2026-10-29.
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Evidence strength
EvidenceHelix's computed view of the study designs behind this topic: how common meta-analyses, randomized trials and reviews are, how recent the literature is, and a plain-language reading. It describes the design mix of the literature. It is not a quality appraisal of any study, and it is not medical advice.