Greater Boston launches more biotech startups than anywhere on earth, and most of them make the same IT decisions in the same order: a founder sets up Google Workspace or Microsoft 365, someone’s cousin configures the Wi-Fi in the incubator space, and eighteen months later the company is signing a pharma partnership whose due-diligence questionnaire asks about security controls nobody has ever thought about. Here’s what growing labs actually need, in the order they need it.
Stage 1: Foundations That Don’t Need Redoing
Even at two people in shared lab space, get these right: company-owned identity (not personal Gmail), multi-factor authentication on everything, centralized file storage with permissions, and laptops that are encrypted and centrally managed. None of this is expensive — but retrofitting it at 30 employees is painful.
Stage 2: When the Instruments Arrive
The first HPLC or sequencer changes your IT profile completely. Instrument-attached PCs often run outdated operating systems the vendor won’t let you patch — they need network segmentation so a compromised office laptop can’t reach them. Plan for scientific data too: instrument output grows faster than anyone budgets for, and “the external drive on the bench” is not a data management strategy.
Stage 3: When Partners Start Asking Questions
Every meaningful milestone — pharma partnership, Series A diligence, first regulated study — comes with a security questionnaire. Suddenly you need documented policies, access controls, audit trails, backup evidence, and often alignment to NIST or similar frameworks. Startups that built on a managed foundation answer these in days; the rest lose weeks of founder time mid-deal.
Stage 4: Scaling Without an IT Department
Hiring an internal IT manager rarely makes sense before 75–100 employees. Until then, managed IT built for life sciences covers onboarding (new scientists productive on day one), 24/7 helpdesk, lab build-out networking, LIMS and ELN support, and the security stack your partners and insurers expect — without the salary, recruiting, or single point of failure.
The Mistake to Avoid
The costliest pattern we see: treating IT as a problem to solve “after the science works.” By then the data, devices, and habits are entrenched, and the cleanup competes with your most important milestones for attention.
Talk to a Team That Knows Lab Environments
Boston Networks supports biotech and life sciences companies across Boston, Cambridge, and the 128/495 corridors. Whether you’re two scientists in an incubator or scaling toward manufacturing, request a consultation and we’ll map your IT roadmap to your scientific one.