Who we are

Vision Statement

  • Who we are

    At Cowell Biodigm, we offer fast and cost-effective targeted drugs to provide service to humanity.
    Our expertise and capabilities are centered around the early phase development of first-in-class small molecule drugs along with targets.
    The developments are inspired by frameworks of integrated, value-added and through-out omics,
    molecular modelling, chemistry, molecular biologic, and medical researches under the excellence in clinical experiences. 

  • Our Inspiration

    Millions of people every year are afflicted with diseases.
    A drug takes about 10-15 years to reach the market.
    This is just unacceptable. This humanitarian crisis therefore instills bits of passion and creativity in our work to innovate future treatments for life-threatening or incurable diseases.
    With this vision in mind, we continue to invest in early-stage discoveries and research capabilities, broadening not only our patent portfolio but also the list of therapeutic applications in which we can deploy our underlying know-how to achieve significant clinical impact. We commit ourselves to scientific integrity, upright ethics, and dedication to medical
    innovations, and ultimately strive to provide a healthy and happy life to humanity.

Our Solution

We push the boundaries of biomedical data and clinical experiences to transform medicine regarding
novel drug discovery to facilitate the transfer of scientific discoveries to patient care.
Cowell Biodigm will revolutionize the early-phase drug discovery process for targeted drug
and precision medicine via three key methods.

  • Solution 01

    Taking advantage of our own AI/data science powered platform, Biodigm AI Screening System (BASS) with cutting edge machine learning algorithm and sophisticatedly curated biomedical and omics data from medical fields.

  • Solution 02

    Utilizing the convergence of advanced molecular modeling techniques that model the behavior of the target compound molecular systems and machine learning models derived from the compound’s activity data.

  • Solution 03

    Using the biomedical verification system based on decades of experience
    in a Yonsei University Health System.