Ask Mendel AI

Biologists are rapidly acquiring enormous amounts of high-dimensional data, but the lack of computational expertise to make sense of it hinders their ability to capitalize on the data, leading to decreased efficiency in many areas including the drug discovery process.

Mendel provides immunologists, our beachhead, comprehensive and efficient data analysis and visualization capabilities, streamlining the drug target screening and hypothesis testing, and helping them identify higher quality candidates, ultimately reducing R&D costs and time to market.

We will generate revenue through a hybrid SaaS/Pay-as-you-go model, collecting recurring fees and compute/storage fees based on customer usage. The global bioinformatics market is projected to be worth USD 38.15 billion by 2028 and is experiencing rapid growth. Our initial target market includes customers of 10x Genomics, a leading single cell genomics sequencing company. Competitors in the market charge fees ranging from 5k-60k per year. Capturing 15% of the market served by 10x Genomics alone and charging $15k per lab would generate over $100M/year. Expanding to broader consumer segments in biological R&D would further enhance this revenue potential.

Assaf Magen, PhD, is the founder and CEO. Until recently, he was a Computational Biology Assistant Professor with over a decade of experience in genomics and cancer immunology. His most recent work (Nature Medicine), showcases his unique position at the intersection of computer science and cancer immunology. He has successfully bridged the gaps between academia, industry, and various bioinformatics disciplines to produce a highly-impactful publication. Through his involvement in immunology R&D, he has gained an unparalleled first-hand exposure to the deep and recurring pain points in the field. This has allowed him to design innovative AI-enabled solutions that have the potential to revolutionize the drug discovery process. Additionally, his extensive network would allow Mendel AI to engage KOLs and customers from key academic and industry institutions and accelerate the adoption of generative AI tools in biology and medicine.