ArticleDaru : journal of Faculty of Pharmacy, Tehran University of Medical Sciences2021
Stock price reaction to the drug development setbacks in the pharmaceutical industry.
Article in Daru : journal of Faculty of Pharmacy, Tehran University of Medical Sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundInvestments in pharmaceutical companies remain challenging due to the inherent uncertainties of risk assessment.
objectivesOur paper aims to assess the impact of the drug development setbacks (DDS) on the stock price of pharmaceutical companies while taking into account the company's financial situation, pipeline size and trend of the stock price before the DDS.
methodsThe model-based clustering based on finite Gaussian mixture modeling was employed to identify the clusters of pharmaceutical companies with homogenous parameters. An artificial neural network was constructed to aid the prediction of the positive mean rate of return 120 days after the DDS.
resultsOur results reveal that a higher pipeline size and a lower rate of return before the DDS, as well as a lower ratio of the market value of the equity and the book value of the total liabilities, are associated with a positive mean rate of return 120 days after the DDS.
conclusionIn general, the DDS have a negative impact on the company's stock price, but this risk can be minimized by investors choosing the companies that satisfy certain criteria. Graphical abstract The higher pipeline size(spip) and lower rate of return before (srr) the drug development setback (DDS) and the Market Value of Equity/Book Value of Total Liabilities ratio (sx4) are associated with a positive mean rate of return 120 days after the DDS.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.