The Team

Our Team

Clinical pharmacologists and software engineers with deep roots in oncology research and clinical trial data systems.

Dr. Lena Hartmann

Dr. Lena Hartmann

CEO, Co-Founder

Former clinical pharmacologist at Dana-Farber Cancer Institute and HMS, where she ran PK/PD modeling for Phase I/II oncology studies for six years. Holds a PhD in pharmaceutical sciences from ETH Zurich and authored 14 peer-reviewed publications on population pharmacokinetic modeling in oncology.

Dr. Marcus Reyes

Dr. Marcus Reyes

CTO, Co-Founder

Previously led clinical data engineering at Medidata Solutions, where he architected the FHIR R4 migration for Rave EDC integrations. PhD in biomedical engineering from MIT. Built the Bayesian inference engine underpinning the DoseMind platform and holds two patents related to real-time PK estimation in constrained computation environments.

Priya Nair

Priya Nair

VP Clinical Operations

Eight years in clinical operations at AstraZeneca and Genentech, focused on oncology Phase I/II trial execution across North America and Europe. Led the implementation of TDM programs for three carboplatin re-dosing protocols. Joined DoseMind in early 2024 to lead site onboarding and protocol validation.

How We Work

A small team solving a specific problem

8

Full-time team members

3

Nationalities represented

14

Peer-reviewed PK publications among founders

Boston

Headquartered in the Longwood Medical Area

Joining DoseMind

What we look for

Domain depth over breadth

We hire people who have spent time at the intersection of clinical pharmacology and software. You do not need to be a PhD, but you do need to understand why the difference between MAP Bayesian and empirical Bayesian estimation matters in a sparse-sampling context.

Clinician communication

Everything we ship has to be understood and trusted by an oncologist or CRC under time pressure. We look for people who can explain a model assumption in plain language - not because clinicians cannot handle complexity, but because they should not have to decode jargon to make a decision.

Work With Us