Usage of Web Scraping in the Pharmaceutical Sector




Web scraping, beautiful soup, drug, medicine


INTRODUCTION: Web scraping is a technique that provides organizations with the ability to analyse large amounts of information and gather new information.

OBJECTIVES: Find a group that is a health check, a full body test, a blood test, and so on. In this way, the pharmaceutical industry should consider how to improve information, information storage, information retrieval, and capture. For example, the healthcare system may decide to standardize the assessment of speech and allow information to be shared across organizations to improve treatment outcomes in web scraping applications.

METHODS: Web scraping is based on the pharmaceutical industry. From here, we get information about pharmacies, such as drug names in different categories or drug sales. However, we are dealing with diseases and common medicines. Using this information, we can find the most common viruses. There are many factors to consider when creating a junk website for the pharmaceutical industry, such as drug names, tablet categories, and syrups found in the pharmaceutical industry.

RESULTS: As is clearly visible from the output, there are columns for drug names, manufacturers, drug types, and prices. This is the information we get from a website called Net meds, a pharmacy site. With the help of this information, we learn which drugs are most needed, and then we can find the most common diseases today.

CONCLUSION: The results of this web scraping can be very useful and powerful. However, the industry's success in web scraping and data extraction techniques depends on the availability of clean chemical data.


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B. Zhao, “Web Scraping,” Encyclopedia of Big Data, pp. 1–3, 2017, doi: 10.1007/978-3-319-32001-4_483-1.

A. V. Saurkar, K. G. Pathare, and S. A. Gode, “An Overview on Web Scraping Techniques and Tools,” 2018.

J. Kinne and J. Axenbeck, “Web Mining of Firm Websites: A Framework for Web Scraping and a Pilot Study for Germany,” SSRN Electronic Journal, Sep. 2018, doi: 10.2139/SSRN.3240470.

A. Bradley and R. J. E. James, “Web Scraping Using R,” Adv Methods Pract Psychol Sci, vol. 2, no. 3, pp. 264–270, Sep. 2019, doi: 10.1177/2515245919859535/SUPPL_FILE/BRADLEY_AMPPSOPENPRACTICESDISCLOSURE-V1-0.PDF.

I. T. F. O. T. D. P. I. A. C. T. A. T. M. F. O. S. C. S. A. Engineering and S. Cycle, “Web Scraping using Machine Learning,” 2020, Accessed: Oct. 15, 2023. [Online]. Available:

S. D. S. Sirisuriya, “A Comparative Study on Web Scraping,” 2015.

K. Parmar, R. Yadav, and D. Supekar Associate Professor, “Issue 6 (ISSN-2349-5162),” JETIR2106682 Journal of Emerging Technologies and Innovative Research, vol. 8, 2021, Accessed: Oct. 15, 2023. [Online]. Available:

N. Krishna, A. Nayak, S. Badagan, and C. Jetty, “A study on Web Scraping,” International Journal of Engineering Research in Computer Science and Engineering (IJERCSE), vol. 9, pp. 2394–2320, 2022, Accessed: Oct. 15, 2023. [Online]. Available:

E. Vargiu and M. Urru, “Exploiting web scraping in a collaborative filtering- based approach to web advertising,” Artif. Intell. Res., vol. 2, no. 1, Nov. 2012, doi: 10.5430/AIR.V2N1P44.

S. Han and C. K. Anderson, “Web Scraping for Hospitality Research: Overview, Opportunities, and Implications,” Cornell Hospitality Quarterly, vol. 62, no. 1, pp. 89–104, Feb. 2021, doi: 10.1177/1938965520973587/ASSET/IMAGES/LARGE/10.1177_1938965520973587-FIG9.JPEG.

L. C. Dewi, Meiliana, and A. Chandra, “Social Media Web Scraping using Social Media Developers API and Regex,” Procedia Comput Sci, vol. 157, pp. 444–449, Jan. 2019, doi: 10.1016/J.PROCS.2019.08.237.




How to Cite

Dahiya R, Nidhi, Kumari K, Kumari S, Agarwal N. Usage of Web Scraping in the Pharmaceutical Sector. EAI Endorsed Trans Perv Health Tech [Internet]. 2023 Nov. 6 [cited 2023 Dec. 10];9. Available from: