Biopharma companies are on a mission: deliver better therapeutics to patients faster to improve human health. Fulfilling this mission today still requires upwards of 10 years, an average cost of $1.1 billion USDÇ, and total cost as high as $4.54 billionÑ for each newly approved drug. How can we accelerate drug discovery, development, and delivery? To achieve these ends, biopharmas have driven digital transformations in earnest. They’ve turned to technologies like artificial intelligence (AI) and machine learning (ML) to build predictive models from existing data sets. Unfortunately, AI/ML outcomes heavily rely on the quality of this underlying data.
The TetraScience 2022 Biopharma Executive Survey of 500 biopharma executives reveals an imperative for success in biopharma digital transformation lies in maximizing the value of scientific data across the value chain [Discovery–> Development –> Manufacturing] to impact three key industry drivers:
1. Speed: Learning from experiments faster, reducing time to market for final molecules
2. Cost: Improving productivity, increasing operational efficiency, increasing return on investment (ROI)
3. Risk: Improving safety, reducing errors, improving compliance with regulatory requirements
