Bernard Munos
Impact in
- Computational Theory and Mathematics top 0.5%
- Computational Drug Discovery Methods
Papers in ⓘ
-
- Pharmaceutical Economics and Policy 10
- Health Systems, Economic Evaluations, Quality of Life 2
- Innovation Policy and R&D 1
-
- Biotechnology and Related Fields 7
- Health and Medical Research Impacts 1
- Co-authors
- Aaron L. Schacht (1 shared paper)Steven M. Paul (1 shared paper)Christopher T. Dunwiddie (1 shared paper)Stacy Lindborg (1 shared paper)Daniel S. Mytelka (1 shared paper)William W. Chin (2 shared papers)John Hixson (1 shared paper)Veena Misra (1 shared paper)
- Journals
- Science Translational Medicine (3 papers)Nature Reviews Drug Discovery (3 papers)Clinical Pharmacology & Therapeutics (2 papers)Science (1 paper)Annals of the New York Academy of Sciences (1 paper)
- Partner nations
- United StatesSwitzerlandIndia
In The Last Decade
Bernard Munos
12 papers receiving 3.3k citations
Hit Papers
Peers
Comparison fields: 5 of 168
- Computational Theory and Mathematics 1.0k
- Management of Technology and Innovation 219
- Pharmacology 275
- Economics and Econometrics 800
- Applied Microbiology and Biotechnology 38
Countries citing papers authored by Bernard Munos
This map shows the geographic impact of Bernard Munos's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Bernard Munos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bernard Munos more than expected).
Fields of papers citing papers by Bernard Munos
This network shows the impact of papers produced by Bernard Munos. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Bernard Munos. The network helps show where Bernard Munos may publish in the future.
Co-authors
The 25 scholars most cited alongside Bernard Munos, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | How to improve R&D productivity: the pharmaceutical industry's grand challenge Hit paper breakdown → | 2010 | 2338 |
| 2 | Lessons from 60 years of pharmaceutical innovation Hit paper breakdown → | 2009 | 795 |
| 3 | 2006 | 69 | |
| 4 | 2016 | 69 | |
| 5 | 2011 | 68 | |
| 6 | 2011 | 49 | |
| 7 | 2010 | 42 | |
| 8 | 2020 | 37 | |
| 9 | 2009 | 29 | |
| 10 | 2013 | 13 | |
| 11 | 2016 | 5 | |
| 12 | 2015 | 2 |
About Bernard Munos
Bernard Munos is a scholar working on Economics and Econometrics, Public Health, Environmental and Occupational Health, Immunology, Reproductive Medicine and Information Systems, having authored 12 papers that have together received 3.5k indexed citations. Recurring topics across this work include Pharmaceutical Economics and Policy (10 papers), Biotechnology and Related Fields (7 papers), Biosimilars and Bioanalytical Methods (3 papers), Health Systems, Economic Evaluations, Quality of Life (2 papers), Science, Research, and Medicine (2 papers), Computational Drug Discovery Methods (1 paper), Innovation Policy and R&D (1 paper) and Health and Medical Research Impacts (1 paper). The work is most often cited by research in Computational Theory and Mathematics (1.0k citations), Management of Technology and Innovation (219 citations), Pharmacology (275 citations), Economics and Econometrics (800 citations) and Applied Microbiology and Biotechnology (38 citations). Bernard Munos has collaborated with scholars based in United States, Switzerland and India. Frequent co-authors include Aaron L. Schacht, Steven M. Paul, Christopher T. Dunwiddie, Stacy Lindborg, Daniel S. Mytelka, William W. Chin, John Hixson, Veena Misra, Ian Ferguson and Michelle Crouthamel. Their work appears in journals such as Science Translational Medicine, Nature Reviews Drug Discovery, Clinical Pharmacology & Therapeutics, Science and Annals of the New York Academy of Sciences.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.