Pfizer has been in the news quite a bit lately. The Covid-19 vaccine is what set the company apart from its rivals in the market. Pfizer has reaped a US$900 million profit in the first quarter of 2021 as a result of its vaccine development and distribution programmes. Disruptive technology, on the other hand, played a key role in identifying the right medication and assisting the company in its trials. Artificial intelligence was successfully used by Pfizer to perform vaccine trials and streamline delivery.
Throughout the development of its vaccine, Pfizer took significant decisions in order to remain ahead of the competition and provide people with a successful response to the coronavirus outbreak. Finally, the pharmaceutical industry developed a highly effective vaccine that is 95% effective. Pfizer, on the other hand, used artificial intelligence in the vaccine development process to ensure that the Covid-19 vaccine met the needs of people. Pfizer's vaccine is now overwhelmingly reaching the world's wealthy nations. In addition, the pharmaceutical firm is moving closer to marketing its dosage for children under the age of 18.Pfizer's success has always been owed to the core science and scientist team, who worked around the clock to find a beneficial solution. Fortunately, the company's previous investment in digital infrastructure has contributed to the company's ability to develop the Covid-19 vaccine in less than a year. Pfizer began digitising its research and development activities and incorporating artificial intelligence into its working framework well before the pandemic. The company used artificial intelligence tools to help find signals inside millions of data points in its 44,000-person analysis during the vaccine trials. We'll guide you through the digital strategies that helped Pfizer's vaccine organization profitable in this report.
Pfizer's early drug research partner, IBM Watson
Let's start with Pfizer's long-running partnership with a tech firm. In 2016, the pharmaceutical firm teamed up with IBM Watson to develop new drugs. Pfizer is also using IBM's artificial intelligence technology in its immune-oncology study, which involves using the body's immune system to aid in the battle against cancer. Although human researchers can only read 200 to 300 science papers each year, technology consumed 25 million medicine abstracts, over 1 million full-text medical journal articles, and 4 million patents, all of which helped Pfizer develop new drugs.
Iktos uses artificial intelligence to predict the behavior of small molecules
Pfizer has forged a relationship with Iktos, a virtual drug design software company, in order to use its artificial intelligence for drug discovery. This is the most recent collaboration, which took place in March 2021. Iktos' de nova architecture will be used by Pfizer to "pick Pfizer small-molecule discovery platforms." The partnership would enable the company to use AI in a more equitable manner. It will aid in the discovery, modelling, and prediction of small-molecule activities, allowing Pfizer to determine which goals are more likely to reach the finish line and yield large profits. Pfizer can gain many drug discovery advantages by incorporating Iktos' AI algorithm and data science, which will increase the likelihood of success.
To quickly clean vaccine clinical data, an AI-powered tool has been developed
To fuel its Covid-19 vaccine motives, Pfizer used artificial intelligence as a key technology. The pharmaceutical industry was able to launch its vaccine in less than a year thanks to the revolutionary trend. Pfizer formed a variety of alliances with digital players and even held a hackathon to find the right partner.
Vaccine development and clinical trials are typically lengthy processes that take months, if not years, to complete. However, owing to the urgent need and worsening global situation, Pfizer scientists rushed to produce the Covid-19 vaccine. The pharmaceutical industry used artificial intelligence in several phases of vaccine development and trials during the vaccine rollout period. For example, cleaning up patient data after the trial process takes more than 30 days, allowing scientists to interpret the findings. Data scientists go through datasets manually, looking for coding errors and other anomalies that arise naturally while collecting tens of millions of data points. Fortunately, technology helped to reduce the workload in a smooth manner. After meeting the primary efficacy case counts, a new machine learning platform named "Smart Data Query (SDQ)" performed analysis and made the data accessible in just 22 hours. Throughout the trial, the machine learning tool ensured data accuracy, requiring very little human interference.
But, in order to obtain this fast result, Pfizer held a hackathon to choose its partner. The ‘incubation sandbox' including its pharma industry invited start-ups, large technology companies, individuals, and other institutions to help solve complex research challenges. The aim of the competition was to create an AI-powered tool that could clean medical studies quickly. As a result, Pfizer teamed up with the winner, Saama Technologies, a software firm based in California, to move forward with its accelerated vaccine trials.
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Source: AnalyticsInsight
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