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The integration of generative AI is transforming the pharmaceutical industry by changing the approach to drug discovery. Exscientia, a technology-driven drug design and development company based in the UK, is dedicated to creating more effective medicines for patients in a faster timeframe. The company has partnered with Amazon Web Services (AWS) to develop an innovative platform that accelerates the design-make-test-learn (DMTL) cycle, setting new standards for cost efficiency and innovation in medicine.
Drug discovery is a lengthy and costly process, often taking up to 15 years and exceeding $2 billion in development costs. Compounding this challenge is the high failure rate, which ranges from 90% to 96%. This significant attrition is primarily due to the daunting task of screening 10^60 bioavailable small molecules to identify viable candidates. In light of these challenges, Exscientia needed to address the following issues:
1. Accelerating drug discovery timelines.
2. Cut the cost of chemical synthesis and experimental testing
3. Improve the success rate of identifying effective drug candidates.
Exscientia collaborated with AWS to put generative AI and robotics in the company's design-make-test-learn (DMTL) cycle. The solution covered:
1. In Silico Design: Applying generative AI algorithms with AWS powers, Exscientia designs the drug candidates in the cloud with predictions of molecular features on safety and efficacy before physical synthesis.
2. Automated Robotics: Exscientia uses cutting-edge robotic systems in its lab, orchestrated by AWS microservices, to synthesize compounds without human intervention, thus allowing it to run 24/7.
3. Active Learning Algorithms: Data from patient tissue samples, genomics, etc are processed to refine compound designs in iterative cycles.
Exscientia's DMTL platform is a generative AI solution based on AWS that establishes a set of Target Product Profiles. This ensures that all drug candidates are defined with precision, meeting the necessary therapeutic requirements. The platform employs a synthesis-aware approach, focusing on designing only compounds that can be physically synthesized, which helps reduce unnecessary experimentation. It integrates cloud-based data analysis for iterative learning and optimization, generative AI for compound design, and automated robotics for rapid synthesis. Together, these elements create an innovative and efficient drug discovery solution.
Exscientia was able to attain high efficiency and cost savings in the following ways:
Time Efficiency: Drug design timelines were accelerated by up to 70%, which allowed faster progression to clinical trials.
Cost Efficiency: The company reduced its capital expenditure by 80% compared to industry standards.
Improved Accuracy: By designing 10x fewer compounds than the industry average, Exscientia optimized resources and minimized chemical liabilities.
Clinical Impact: Six molecules designed by AI have already entered clinical trials, which has benchmarked the speed and innovation and set a benchmark.
Exscientia: Exscientia is a UK-based technology-driven pharmaceutical company that designed and developed drugs, as committed, for patients in much less time. The company works by amalgamating modern AI algorithms with laboratory automation, breaking the DMTL cycle and making drug discoveries efficient yet effective.
Amazon Web Services (AWS): AWS is a leading cloud computing platform offering advanced tools and technologies for innovation. Its AI-powered solutions support Exscientia in achieving operational efficiency and scalability in drug discovery.
Through this cooperation with AWS, Exscientia embodies the transformational promise of generative AI in healthcare. It is successful in terms of cost savings and accelerated timeline and quality of the drug candidate while raising the bar further for the standards of innovation in the pharmaceutical industry.
