New Horizons: Pioneering Pharmaceutical R&D with Generative AI from lab
  to the clinic -- an industry perspective
Guy Doron Sam Genway Mark Roberts Sai Jasti
The rapid advance of generative AI is reshaping the strategic vision for R&D
across industries. The unique challenges of pharmaceutical R&D will see
applications of generative AI deliver value along the entire value chain from
early discovery to regulatory approval. This perspective reviews these
challenges and takes a three-horizon approach to explore the generative AI
applications already delivering impact, the disruptive opportunities which are
just around the corner, and the longer-term transformation which will shape the
future of the industry. Selected applications are reviewed for their potential
to drive increase productivity, accelerate timelines, improve the quality of
research, data and decision making, and support a sustainable future for the
industry. Recommendations are given for Pharma R&D leaders developing a
generative AI strategy today which will lay the groundwork for getting real
value from the technology and safeguarding future growth. Generative AI is
today providing new, efficient routes to accessing and combining organisational
data to drive productivity. Next, this impact will reach clinical development,
enhancing the patient experience, driving operational efficiency, and unlocking
digital innovation to better tackle the future burden of disease. Looking to
the furthest horizon, rapid acquisition of rich multi-omics data, which capture
the 'language of life', in combination with next generation AI technologies
will allow organisations to close the loop around phases of the pipeline
through rapid, automated generation and testing of hypotheses from bench to
bedside. This provides a vision for the future of R&D with sustainability at
the core, with reduced timescales and reduced dependency on resources, while
offering new hope to patients to treat the untreatable and ultimately cure
diseases.