Partner at Khosla Ventures
Check size: No personal check range is published. Khosla's Seed Fund supports science and business-model experiments, historically often with roughly $1M–$2M according to a 2020 firm interview, while its Main Fund covers early through later stages. These are firm-level references, not Alex's authority.
Alex invests where computation, biology, and healthcare converge. His scientific and clinical background supports a systems view of biomarker discovery, therapeutics, diagnostics, personalized medicine, neurotechnology, connected devices, and AI-enabled care. He favors important health outcomes and technologies that can automate expensive or inconsistent processes, increase access, and create reproducible, lower-cost care—not science detached from delivery and economics.
State the clinical or biological outcome and why the proposed mechanism can change it. Bring mechanistic evidence, dataset provenance, model validation, reproducibility, failure modes, experimental controls, regulatory path, trial design, workflow integration, reimbursement, manufacturing or delivery constraints, and cost per improved outcome. Show the cheapest milestone that removes the next binary risk and how success expands access rather than only producing a premium intervention.
Interdisciplinary and outsider teams applying advances from computation, physics, engineering, or biology to hard health problems; technologies that improve consistency while lowering cost; founders in control of critical scientific and operational dependencies; and companies with an explicit path from proof through clinical evidence, reimbursement, and broad access.
His public discussions imply caution toward overfunded pre-revenue organizations, capital spent on optics rather than experiments, companies dependent on fragile vendors for existential execution, science without reproducibility or delivery economics, and health products that cannot show how clinical outcomes, patient burden, and cost improve together.
Test whether computational methods improve a specific biological measurement, prediction, intervention, or workflow—and whether the resulting evidence remains clinically meaningful outside the training environment.
A healthcare advance should improve clinical outcome or consistency, lower total delivery cost, and broaden practical access; identify tradeoffs when it only optimizes one corner.
List every lab, CRO, device, data source, regulatory step, clinician workflow, manufacturer, and reimbursement dependency; determine which external failure could block the program and bring critical paths under control.
Validate that passive or remote measurements reliably capture a clinically useful state, can alter a treatment decision, improve adherence or trial completion, and generate evidence acceptable to clinicians and regulators.
“New technology and the real revolutions in fields come from outside.”
— https://www.khoslaventures.com/posts/how-a-tough-2022-could-reshape-biotech
“All of this is about reducing cost.”
— https://www.khoslaventures.com/posts/how-a-tough-2022-could-reshape-biotech
+ 142 more investments. View fund →