How Data Analytics Impacts Drug Discovery and Development
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How Data Analytics Impacts Drug Discovery and Development

Skye Fitzgerald, Data Analytics Manager, Jazz Pharmaceuticals

Skye Fitzgerald, Data Analytics Manager, Jazz Pharmaceuticals

Drug discovery and research are a time and resource-intensive process, and data analytics can help companies maximize their return on investment and reduce development time. 

Drug development focuses on identifying treatments for known disease targets or improving the management of diseases, conditions, and viruses. Significant advancements in computing power, robotics, and biological technology are driving drug R&D processes.

The drug discovery process, on the other hand, can be expensive and time-consuming in most circumstances. In addition, before a drug can be commercialized, it must first be evaluated through clinical trials to determine its efficacy, safety, and proper dosage.

Drug R&D is based on correct data, research, patient and peer-reviewed trials to ensure continued advancements because data is critical in identifying areas where additional work is needed to achieve the desired results.

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The future of big data in drug development

Data-driven drug development resources and procedures contribute to the ever-increasing amount of data generated by large-scale biological research, and they aid biotech companies.

Several biotech and pharmaceutical businesses are hesitant to invest extensively in increasing big data's analytical capabilities, primarily because there are few examples of colleagues extracting more value from it. But the investments will increase.

Artificial intelligence, deep learning, and PM are all difficult to achieve. Companies must understand that the benefits of big data in industry R&D are genuine, and those who succeed will be richly rewarded. But the entire business must first go through many digital transformation procedures in order to accomplish this.

Major benefits of data analytics in drug discovery software

Drug discovery and research is a time and resource-intensive process. Pharmaceutical companies need every benefit they can get to maximize their return on investment and shorten development time. Organizations must employ professional analytics and reporting software to get better results and give all necessary data for a more convenient and effective work process. Here are a few examples of basic ones. 

Ensures reproducibility of results

The extensive use of data collection, pre-processing, analysis, and inference offers immense opportunities in drug development.

Saves image analysis time

Image analysis components in drug discovery software automate and exploit breakthrough technologies to drastically reduce disease image analysis time, testing, and time to market.

Improves the quality, relevance, and impact of aggregated data

Pharmaceutical companies benefit from drug discovery software because it allows them to develop new drugs to solve severe problems for patients, analyze calculations that generate data, detect potential targets, and recognize potential flaws in developing drugs, all of which help speed up the drug discovery process. 

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