Speaker Profile
M.D., Ph.D., Co-Founder and Chief Scientific Officer, Genomenon
Biography
Dr. Mark Kiel completed his M.D., Ph.D., and Molecular Genetic Pathology Fellowship at the University of Michigan, where his research focused on stem cell biology, genomic profiling of hematopoietic malignancies, and clinical bioinformatics. He is the founder and chief scientific officer at Genomenon, a genomic intelligence company, where he oversees the company's scientific direction and product development. Mark founded Genomenon in 2014 to address the challenge of connecting researchers with evidence in the genomic literature to help diagnose and treat patients with genetic diseases and cancer.
Talk
Unlocking the Power of Literature-Derived Real-World Evidence
The biomedical literature reflects decades of global clinical practice and millions of highly detailed patient records. Especially for rare or complex indications, where traditional sources of RWE may lack coverage, this evidence can fill critical gaps. We reveal how literature-derived RWE can complement other sources and optimize precision medicine programs in inherited disease and oncology.
AI and Data Sciences Showcase:
Genomenon
Genomenon is a RWE and genomics intelligence company helping pharmaceutical and clinical
diagnostics companies to inform precision medicine efforts and accelerate patient diagnosis by
unlocking real-world evidence from biomedical literature. Our unique AI, combined with insights from our team of genomic experts empowers precision therapeutic companies to optimize clinical trial design, enhance diagnostic patient yield, and streamline regulatory submissions.
Session Abstract – PMWC 2026 Silicon Valley
The PMWC 2026 AI Company Showcase will provide a 15-30 minute time slot for selected AI companies to present their latest technologies to an audience of leading investors, potential clients, and partners. We will hear from companies building technologies that expedite the pre-clinical and clinical drug discovery and development process, accelerate patient diagnosis and treatment, or develop scalable systems framework to make AI and deep/machine learning a reality.
