biotech-ai
(6)
Dimitrios Skaltsas
Dimitrios Skaltsas is the co-founder and CEO of Intelligencia AI, a New York enterprise software company that uses machine learning and curated biomedical data to estimate the probability that a drug candidate will win regulatory approval. Trained as a lawyer in Athens and London, he spent more than a decade at McKinsey, where he built and led New Ventures' big-data and AI work for pharmaceutical R&D before co-founding Intelligencia with Vangelis Vergetis in 2017. Under his leadership the company raised a Series A, was named one of Forbes's Top AI Companies to Watch, secured a U.S. patent for its probability-of-success assessments, and landed on the Inc. 5000. He is also an Executive in Residence at INSEAD.
AppliedXL
AppliedXL is a New York-based event-detection company that builds machine-learning systems - it calls them editorial algorithms - to spot early signals in clinical trials, biotech, and financial data before they become news. Founded in 2020 by former Wall Street Journal computational journalists Francesco Marconi and Erin Riglin out of the Newlab Venture Studio, the company mines public databases like ClinicalTrials.gov to flag trial delays, enrollment shortfalls, and irregular status changes across more than 100 risk categories, feeding real-time intelligence to life-sciences executives and investors. Its work powers STAT Trials Pulse and appears on the Bloomberg Terminal.
Francesco Marconi
Francesco Marconi is a computational journalist turned startup founder who built AppliedXL, a New York company that points the tools of investigative reporting at machine data to detect events before they become news. After serving as the first R&D Chief at The Wall Street Journal and co-leading AI strategy at the Associated Press, he wrote the field-defining book Newsmakers and now applies 'pre-news' event detection to clinical trials and biopharma, surfacing the earliest signals of trial risk for partners including STAT News and the Bloomberg Terminal.
Matterworks
Matterworks is a Somerville, Massachusetts biotech-AI company building foundation models for molecular biology. Its Large Spectral Models (LSMs) are trained on billions of mass spectrometry spectra and read raw molecular signals directly, turning slow, manual mass-spec workflows into automated, untargeted absolute quantitation. Its flagship cloud platform, Pyxis, acts as a predictive omics assistant that converts raw LC-MS data into identified, quantified molecules and biological insight - making mass spectrometry usable by any biologist rather than only specialist analysts.
Jack Geremia
Jack Geremia is the CEO and co-founder of Matterworks, a Somerville, Massachusetts biotech building Large Spectral Models - foundation models that read raw mass spectrometry signals the way a large language model reads text. A Princeton-trained chemist and former Caltech quantum-control postdoc turned serial biotech founder, he has spent 25-plus years moving technologies from lab bench to market, authoring more than 100 patents and publications. After co-founding Matterworks in 2019 as advising CTO, he stepped into the CEO seat to commercialize Pyxis, the company's generative-AI engine for untargeted molecular annotation, and led the company through a 2025 Series A from Lewis & Clark Partners and OMX Ventures.
Edison Scientific
Edison Scientific is a San Francisco AI company building autonomous 'AI scientists' that can run hundreds of research tasks in parallel. Spun out of the nonprofit FutureHouse in 2025, its flagship product Kosmos compresses what researchers call six months of work into a single day, reading 1,500 papers and writing 42,000 lines of analysis code per run. The company raised $70M in seed funding at a $250M valuation in December 2025.