Molecules to market: A probabilistic artificial intelligence framework for predicting managed care adoption at the level of drug discovery.
- DOI
- 10.18553/jmcp.2026.32.9.1122
- Published
- 2026 Sep
- Container
- Journal of managed care & specialty pharmacy
- Publisher
- Not recorded
- Open access
- unknown
Credibility signals
limited evidence Score 43/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.18553/jmcp.2026.32.9.1122,
title = {Molecules to market: A probabilistic artificial intelligence framework for predicting managed care adoption at the level of drug discovery.},
author = {Sharma R},
year = {2026},
journal = {Journal of managed care \& specialty pharmacy},
doi = {10.18553/jmcp.2026.32.9.1122},
url = {https://doi.org/10.18553/jmcp.2026.32.9.1122}
}RIS
TY - JOUR TI - Molecules to market: A probabilistic artificial intelligence framework for predicting managed care adoption at the level of drug discovery. AU - Sharma R PY - 2026 JO - Journal of managed care & specialty pharmacy DO - 10.18553/jmcp.2026.32.9.1122 UR - https://doi.org/10.18553/jmcp.2026.32.9.1122 ER -
APA
R, S. (2026). Molecules to market: A probabilistic artificial intelligence framework for predicting managed care adoption at the level of drug discovery.. Journal of managed care & specialty pharmacy. https://doi.org/10.18553/jmcp.2026.32.9.1122
Source records
- pubmed · retrieved 2026-09-25T20:26:32.317Z