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With Pfizer teams highly focused on ongoing technology projects, PACT addresses challenges around the bandwidth needed for prototyping. “With this collaboration, AWS brings in its prototyping teams to work with business and IT teams directly on relevant challenges,” says Bulusu.
Reported impact
From PACT’s initial list of 14 projects, five ideas have moved into production so far. “Even though we are just doing prototyping and there’s no immediate revenue in it for AWS, AWS always brings forward its top teams,” says Bulusu. Key reported metrics include of search time saved annually 16,000 hours; 16,000 hours; in infrastructure costs 55% reduction.
Learn how Pfizer and AWS are collaborating to build generative AI prototypes to help bring innovative therapeutics to market quickly. With a mission to transform healthcare for its 1.3 billion patients, Pfizer is always seeking to innovate using cutting-edge technology. To optimize the development of new medicines through cloud-based solutions, Pfizer and Amazon Web Services (AWS) have created the Pfizer-Amazon Collaboration Team (PACT) initiative. Under PACT, Pfizer has pursued 14 projects, including generative artificial intelligence (AI) and machine learning (ML) to save scientists up to 16,000 hours of search time annually and cut infrastructure costs by 55 percent. Pfizer uses a plethora of tools from AWS to explore new ideas, quickly build prototypes, and drive a passion for innovation in digital drug development. Source data enters the Pfizer workflow through its application services, processed with Amazon SageMaker, Amazon Bedrock, and delivered through Amazon Kendra.
Source data enters the Pfizer workflow through its application services, processed with Amazon SageMaker, Amazon Bedrock, and delivered through Amazon Kendra.
16,000 hours
55% reduction
From PACT’s initial list of 14 projects, five ideas have moved into production so far.
The development of one drug can result in approximately 20,000 documents, and scientists often must look for data manually using a variety of tools to find historical data.
The first use case sought to minimize the time spent in data discovery upto 80 percent for 1,500 PSSM scientists.
“If we were to do this ourselves, assuming we could find the bandwidth and people with appropriate skills, it would take at least 3 months,” says Bulusu.
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