Preliminary list of Hamming problems in biology

  • Next generation small molecule bioengineering

    Innovations in the design, manipulation, and production of small molecules have significant implications for many fields, including drug discovery, by increasing the number of possible targets.

  • Genetic therapies

    CRISPR gene editing promises to cure any human genetic disease — at least theoretically. Every obstacle for the delivery, distribution, and safety of genetic therapies is a problem worth solving on its own.

  • Continuous monitoring for phenotypic discovery

    Wearable biosensors could track phenotypic data in real time and move the needle in drug discovery, anti-aging, and reproductive research. This is a largely unexplored area of collaboration between biomedical engineers, biologists, and clinicians.

  • Translational modeling

    90-95% of drugs that are tested in humans fail to move to the next step. Prior to phase I trials, a lot of resources are invested in preclinical trials. Lowering the cost-to-clinical trials is a high impact intervention that might involve more regulatory changes and incentives alignment than previously thought.

How did we select these problems?

The Hamming problems listed here are preliminary selections and we are hungry for feedback!

  • We interviewed founders, funders, and academics in biotech in different fields, from longevity to metascience and bioengineering, in order to unearth the Hamming problems of their fields. This process included rating different problems in importance, tractability, and neglectedness.

  • Due to the large scope of fields in bio x AI and our desire to go in depth, we took efforts to limit the number of problems. We updated the final selection after every interview.

  • We are actively recruiting an expert advisory panel in order to prepare a pre-unconference study guide for attendees to wish to make the most out of the event.

    If you’d like to get invovled as an expert, please click here.