Axial Podcast

→ WHAT IT COVERS Corin Wagen, founder of Rowan, explains how his cloud-based quantum chemistry platform democratizes high-accuracy molecular modeling for drug designers and chemists. The platform replaces legacy Fortran-based tools requiring SSH access with a web-native interface, incorporating machine learning potentials that run 100–1,000x faster than traditional density functional theory calculations.

→ WHAT IT COVERS Jeremy Agresti, founder and CTO of Triplebar Bio, explains how microfluidic droplet screening at picoliter scale enables testing hundreds of millions of biological variants per day, unlocking a horizontal platform business model for biologics discovery across antibody therapeutics, cultivated meat cell lines, and precision fermentation proteins.

→ WHAT IT COVERS Alex Telford, founder of six-month-old Convoke, explains how LLMs now make it feasible to automate biopharma commercial assessments — competitive intelligence, revenue forecasting, and indication selection — tasks previously requiring $300/hour consultants and months of manual Excel and PowerPoint work. → KEY INSIGHTS - **Early Commercial Analysis:** Biopharma companies routinely delay commercial assessments until Phase 2 or later, then discover they selected the wrong...

→ WHAT IT COVERS Scott Stevenson, co-founder of Spellbook, describes building an AI contract review and drafting tool for commercial lawyers. Starting as Rally in 2019, the company ran nearly 100 product experiments before launching its LLM-based copilot in 2022, now serving close to 2,000 paying law firms. → KEY INSIGHTS - **Product-Market Fit Testing:** Run experiments in three sequential stages before scaling: first test whether a landing page captures email signups, then whether users pay,...

→ WHAT IT COVERS Milad Dagher, cofounder and CEO of Nomic Bio, explains how the Analyzer platform scales multiplexed ELISA-based proteomics to 200 proteins per sample using pre-assembled antibody pairs on color-coded beads, enabling drug discovery teams to run high-throughput protein measurements at costs low enough for routine daily use across large sample cohorts.

→ WHAT IT COVERS Peter Cimermančič, cofounder of Tesserai and former seven-year Verily researcher, explains how AI-powered preprocessing of mass spectrometry proteomics data can recover up to 80% of currently unidentified spectra, unlocking drug targets and biological insights that conventional search algorithms systematically miss. → KEY INSIGHTS - **The 80% Dark Matter Problem:** Current mass spectrometry search algorithms leave up to 80% of measured spectra unidentified, meaning most...

→ WHAT IT COVERS Penn State chemical engineering professor Costas Maranas discusses how computational methods — specifically optimization algorithms, biophysical force fields, and emerging transformer models — can engineer proteins, enzymes, and microbial strains to perform functions nature never evolved them to do, and why data quality remains the central bottleneck.

→ WHAT IT COVERS Simeon Graupe, cofounder of PatentPlus, explains how his platform indexes 540,000 technologies from 1,000 research organizations globally, using AI-powered search and use case generation to connect R&D-intensive companies with licensable patents, contract research partnerships, and startup solutions to accelerate product development.

→ WHAT IT COVERS Kevin Leland, founder and CEO of Halo.science, explains how his AI-powered platform connects academic researchers and science-led startups with corporate R&D teams. Starting from a failed crowdfunding concept, Halo evolved into a sector-agnostic marketplace modeled on LinkedIn, now partnering with Bayer, Pepsi, and Baxter. → KEY INSIGHTS - **Bootstrapping a two-sided marketplace:** Solve the chicken-and-egg problem by identifying "power nodes" — university tech transfer...

→ WHAT IT COVERS Spencer Hey, cofounder of Prism, a metascience software company, describes how his philosophy-of-science background led him to build data visualization and LLM-powered tools that help biopharma organizations extract strategic knowledge from clinical trial data, reducing analysis turnaround from several weeks to days, with a goal of reaching hours.